Author: "Farrell P" - Searchworks@Jio Institute Digital Library Search Results

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19,324 results on '"Farrell P"'

1. Applying sparse autoencoders to unlearn knowledge in language models

Author: Farrell, Eoin, Lau, Yeu-Tong, and Conmy, Arthur
Subjects: Computer Science - Machine Learning, Computer Science - Artificial Intelligence
Abstract: We investigate whether sparse autoencoders (SAEs) can be used to remove knowledge from language models. We use the biology subset of the Weapons of Mass Destruction Proxy dataset and test on the gemma-2b-it and gemma-2-2b-it language models. We demonstrate that individual interpretable biology-related SAE features can be used to unlearn biology-related knowledge with minimal side-effects. Our results suggest that negative scaling of feature activations is necessary and that zero ablating features is ineffective. We find that intervening using multiple SAE features simultaneously can unlearn multiple different topics, but with similar or larger unwanted side-effects than the existing Representation Misdirection for Unlearning technique. Current SAE quality or intervention techniques would need to improve to make SAE-based unlearning comparable to the existing fine-tuning based techniques.
Published: 2024

2. FAIR Universe HiggsML Uncertainty Challenge Competition

Author: Bhimji, Wahid, Calafiura, Paolo, Chakkappai, Ragansu, Chou, Yuan-Tang, Diefenbacher, Sascha, Dudley, Jordan, Farrell, Steven, Ghosh, Aishik, Guyon, Isabelle, Harris, Chris, Hsu, Shih-Chieh, Khoda, Elham E, Lyscar, Rémy, Michon, Alexandre, Nachman, Benjamin, Nugent, Peter, Reymond, Mathis, Rousseau, David, Sluijter, Benjamin, Thorne, Benjamin, Ullah, Ihsan, and Zhang, Yulei
Subjects: High Energy Physics - Phenomenology, Computer Science - Machine Learning, High Energy Physics - Experiment, Physics - Data Analysis, Statistics and Probability
Abstract: The FAIR Universe -- HiggsML Uncertainty Challenge focuses on measuring the physics properties of elementary particles with imperfect simulators due to differences in modelling systematic errors. Additionally, the challenge is leveraging a large-compute-scale AI platform for sharing datasets, training models, and hosting machine learning competitions. Our challenge brings together the physics and machine learning communities to advance our understanding and methodologies in handling systematic (epistemic) uncertainties within AI techniques., Comment: Whitepaper for the FAIR Universe HiggsML Uncertainty Challenge Competition, available : https://fair-universe.lbl.gov
Published: 2024

3. Comprehensive Performance Modeling and System Design Insights for Foundation Models

Author: Subramanian, Shashank, Rrapaj, Ermal, Harrington, Peter, Chheda, Smeet, Farrell, Steven, Austin, Brian, Williams, Samuel, Wright, Nicholas, and Bhimji, Wahid
Subjects: Computer Science - Machine Learning, Computer Science - Distributed, Parallel, and Cluster Computing
Abstract: Generative AI, in particular large transformer models, are increasingly driving HPC system design in science and industry. We analyze performance characteristics of such transformer models and discuss their sensitivity to the transformer type, parallelization strategy, and HPC system features (accelerators and interconnects). We utilize a performance model that allows us to explore this complex design space and highlight its key components. We find that different transformer types demand different parallelism and system characteristics at different training regimes. Large Language Models are performant with 3D parallelism and amplify network needs only at pre-training scales with reduced dependence on accelerator capacity and bandwidth. On the other hand, long-sequence transformers, representative of scientific foundation models, place a more uniform dependence on network and capacity with necessary 4D parallelism. Our analysis emphasizes the need for closer performance modeling of different transformer types keeping system features in mind and demonstrates a path towards this. Our code is available as open-source., Comment: 17 pages, PMBS 2024
Published: 2024

4. The hypothetical track-length fitting algorithm for energy measurement in liquid argon TPCs

Author: DUNE Collaboration, Abud, A. Abed, Abi, B., Acciarri, R., Acero, M. A., Adames, M. R., Adamov, G., Adamowski, M., Adams, D., Adinolfi, M., Adriano, C., Aduszkiewicz, A., Aguilar, J., Akbar, F., Alex, N. S., Allison, K., Monsalve, S. Alonso, Alrashed, M., Alton, A., Alvarez, R., Alves, T., Amar, H., Amedo, P., Anderson, J., Andreopoulos, C., Andreotti, M., Andrews, M. P., Andrianala, F., Andringa, S., Anfimov, N., Ankowski, A., Antic, D., Antoniassi, M., Antonova, M., Antoshkin, A., Aranda-Fernandez, A., Arellano, L., Diaz, E. Arrieta, Arroyave, M. A., Asaadi, J., Ashkenazi, A., Asner, D., Asquith, L., Atkin, E., Auguste, D., Aurisano, A., Aushev, V., Autiero, D., Azam, M. B., Azfar, F., Back, A., Back, H., Back, J. J., Bagaturia, I., Bagby, L., Balashov, N., Balasubramanian, S., Baldi, P., Baldini, W., Baldonedo, J., Baller, B., Bambah, B., Banerjee, R., Barao, F., Barbu, D., Barenboim, G., Alzás, P. Barham, Barker, G. J., Barkhouse, W., Barr, G., Monarca, J. Barranco, Barros, A., Barros, N., Barrow, D., Barrow, J. L., Basharina-Freshville, A., Bashyal, A., Basque, V., Batchelor, C., Bathe-Peters, L., Battat, J. B. R., Battisti, F., Bay, F., Bazetto, M. C. Q., Alba, J. L. L. Bazo, Beacom, J. F., Bechetoille, E., Behera, B., Belchior, E., Bell, G., Bellantoni, L., Bellettini, G., Bellini, V., Beltramello, O., Benekos, N., Montiel, C. Benitez, Benjamin, D., Neves, F. Bento, Berger, J., Berkman, S., Bernal, J., Bernardini, P., Bersani, A., Bertolucci, S., Betancourt, M., Rodríguez, A. Betancur, Bevan, A., Bezawada, Y., Bezerra, A. T., Bezerra, T. J., Bhat, A., Bhatnagar, V., Bhatt, J., Bhattacharjee, M., Bhattacharya, M., Bhuller, S., Bhuyan, B., Biagi, S., Bian, J., Biery, K., Bilki, B., Bishai, M., Bitadze, A., Blake, A., Blaszczyk, F. D., Blazey, G. C., Blucher, E., Bodek, A., Bogenschuetz, J., Boissevain, J., Bolognesi, S., Bolton, T., Bomben, L., Bonesini, M., Bonilla-Diaz, C., Bonini, F., Booth, A., Boran, F., Bordoni, S., Merlo, R. Borges, Borkum, A., Bostan, N., Bouet, R., Boza, J., Bracinik, J., Brahma, B., Brailsford, D., Bramati, F., Branca, A., Brandt, A., Bremer, J., Brew, C., Brice, S. J., Brio, V., Brizzolari, C., Bromberg, C., Brooke, J., Bross, A., Brunetti, G., Brunetti, M., Buchanan, N., Budd, H., Buergi, J., Bundock, A., Burgardt, D., Butchart, S., V., G. Caceres, Cagnoli, I., Cai, T., Calabrese, R., Calcutt, J., Calivers, L., Calvo, E., Caminata, A., Camino, A. F., Campanelli, W., Campani, A., Benitez, A. Campos, Canci, N., Capó, J., Caracas, I., Caratelli, D., Carber, D., Carceller, J. M., Carini, G., Carlus, B., Carneiro, M. F., Carniti, P., Terrazas, I. Caro, Carranza, H., Carrara, N., Carroll, L., Carroll, T., Carter, A., Casarejos, E., Casazza, D., Forero, J. F. Castaño, Castaño, F. A., Castillo, A., Castromonte, C., Catano-Mur, E., Cattadori, C., Cavalier, F., Cavanna, F., Centro, S., Cerati, G., Cerna, C., Cervelli, A., Villanueva, A. Cervera, Chakraborty, K., Chalifour, M., Chappell, A., Charitonidis, N., Chatterjee, A., Chen, H., Chen, M., Chen, W. C., Chen, Y., Chen-Wishart, Z., Cherdack, D., Chi, C., Chiapponi, F., Chirco, R., Chitirasreemadam, N., Cho, K., Choate, S., Choi, G., Chokheli, D., Chong, P. S., Chowdhury, B., Christian, D., Chukanov, A., Chung, M., Church, E., Cicala, M. F., Cicerchia, M., Cicero, V., Ciolini, R., Clarke, P., Cline, G., Coan, T. E., Cocco, A. G., Coelho, J. A. B., Cohen, A., Collazo, J., Collot, J., Conley, E., Conrad, J. M., Convery, M., Copello, S., Cova, P., Cox, C., Cremaldi, L., Cremonesi, L., Crespo-Anadón, J. I., Crisler, M., Cristaldo, E., Crnkovic, J., Crone, G., Cross, R., Cudd, A., Cuesta, C., Cui, Y., Curciarello, F., Cussans, D., Dai, J., Dalager, O., Dallavalle, R., Dallaway, W., D'Amico, R., da Motta, H., Dar, Z. A., Darby, R., Peres, L. Da Silva, David, Q., Davies, G. S., Davini, S., Dawson, J., De Aguiar, R., De Almeida, P., Debbins, P., De Bonis, I., Decowski, M. P., de Gouvêa, A., De Holanda, P. C., Astiz, I. L. De Icaza, De Jong, P., Sanchez, P. Del Amo, De la Torre, A., De Lauretis, G., Delbart, A., Delepine, D., Delgado, M., Dell'Acqua, A., Monache, G. Delle, Delmonte, N., De Lurgio, P., Demario, R., De Matteis, G., Neto, J. R. T. de Mello, DeMuth, D. M., Dennis, S., Densham, C., Denton, P., Deptuch, G. W., De Roeck, A., De Romeri, V., Detje, J. P., Devine, J., Dharmapalan, R., Dias, M., Diaz, A., Díaz, J. S., Díaz, F., Di Capua, F., Di Domenico, A., Di Domizio, S., Di Falco, S., Di Giulio, L., Ding, P., Di Noto, L., Diociaiuti, E., Distefano, C., Diurba, R., Diwan, M., Djurcic, Z., Doering, D., Dolan, S., Dolek, F., Dolinski, M. J., Domenici, D., Domine, L., Donati, S., Donon, Y., Doran, S., Douglas, D., Doyle, T. A., Dragone, A., Drielsma, F., Duarte, L., Duchesneau, D., Duffy, K., Dugas, K., Dunne, P., Dutta, B., Duyang, H., Dwyer, D. A., Dyshkant, A. S., Dytman, S., Eads, M., Earle, A., Edayath, S., Edmunds, D., Eisch, J., Englezos, P., Ereditato, A., Erjavec, T., Escobar, C. O., Evans, J. J., Ewart, E., Ezeribe, A. C., Fahey, K., Fajt, L., Falcone, A., Fani', M., Farnese, C., Farrell, S., Farzan, Y., Fedoseev, D., Felix, J., Feng, Y., Fernandez-Martinez, E., Ferry, G., Fialova, E., Fields, L., Filip, P., Filkins, A., Filthaut, F., Fine, R., Fiorillo, G., Fiorini, M., Fogarty, S., Foreman, W., Fowler, J., Franc, J., Francis, K., Franco, D., Franklin, J., Freeman, J., Fried, J., Friedland, A., Fuess, S., Furic, I. K., Furman, K., Furmanski, A. P., Gaba, R., Gabrielli, A., Gago, A. M., Galizzi, F., Gallagher, H., Gallice, N., Galymov, V., Gamberini, E., Gamble, T., Ganacim, F., Gandhi, R., Ganguly, S., Gao, F., Gao, S., Garcia-Gamez, D., García-Peris, M. Á., Gardim, F., Gardiner, S., Gastler, D., Gauch, A., Gauvreau, J., Gauzzi, P., Gazzana, S., Ge, G., Geffroy, N., Gelli, B., Gent, S., Gerlach, L., Ghorbani-Moghaddam, Z., Giammaria, T., Gibin, D., Gil-Botella, I., Gilligan, S., Gioiosa, A., Giovannella, S., Girerd, C., Giri, A. K., Giugliano, C., Giusti, V., Gnani, D., Gogota, O., Gollapinni, S., Gollwitzer, K., Gomes, R. A., Bermeo, L. V. Gomez, Fajardo, L. S. Gomez, Gonnella, F., Gonzalez-Diaz, D., Gonzalez-Lopez, M., Goodman, M. C., Goswami, S., Gotti, C., Goudeau, J., Goudzovski, E., Grace, C., Gramellini, E., Gran, R., Granados, E., Granger, P., Grant, C., Gratieri, D. R., Grauso, G., Green, P., Greenberg, S., Greer, J., Griffith, W. C., Groetschla, F. T., Grzelak, K., Gu, L., Gu, W., Guarino, V., Guarise, M., Guenette, R., Guerzoni, M., Guffanti, D., Guglielmi, A., Guo, B., Guo, F. Y., Gupta, A., Gupta, V., Gurung, G., Gutierrez, D., Guzowski, P., Guzzo, M. M., Gwon, S., Habig, A., Hadavand, H., Haegel, L., Haenni, R., Hagaman, L., Hahn, A., Haiston, J., Hakenmüller, J., Hamernik, T., Hamilton, P., Hancock, J., Happacher, F., Harris, D. A., Hart, A. L., Hartnell, J., Hartnett, T., Harton, J., Hasegawa, T., Hasnip, C. M., Hatcher, R., Hayrapetyan, K., Hays, J., Hazen, E., He, M., Heavey, A., Heeger, K. M., Heise, J., Hellmuth, P., Henry, S., Herner, K., Hewes, V., Higuera, A., Hilgenberg, C., Hillier, S. J., Himmel, A., Hinkle, E., Hirsch, L. R., Ho, J., Hoff, J., Holin, A., Holvey, T., Hoppe, E., Horiuchi, S., Horton-Smith, G. A., Houdy, T., Howard, B., Howell, R., Hristova, I., Hronek, M. S., Huang, J., Huang, R. G., Hulcher, Z., Ibrahim, M., Iles, G., Ilic, N., Iliescu, A. M., Illingworth, R., Ingratta, G., Ioannisian, A., Irwin, B., Isenhower, L., Oliveira, M. Ismerio, Itay, R., Jackson, C. M., Jain, V., James, E., Jang, W., Jargowsky, B., Jena, D., Jentz, I., Ji, X., Jiang, C., Jiang, J., Jiang, L., Jipa, A., Jo, J. H., Joaquim, F. R., Johnson, W., Jollet, C., Jones, B., Jones, R., Jovancevic, N., Judah, M., Jung, C. K., Jung, K. Y., Junk, T., Jwa, Y., Kabirnezhad, M., Kaboth, A. C., Kadenko, I., Kakorin, I., Kalitkina, A., Kalra, D., Kandemir, M., Kaplan, D. M., Karagiorgi, G., Karaman, G., Karcher, A., Karyotakis, Y., Kasai, S., Kasetti, S. P., Kashur, L., Katsioulas, I., Kauther, A., Kazaryan, N., Ke, L., Kearns, E., Keener, P. T., Kelly, K. J., Kemp, E., Kemularia, O., Kermaidic, Y., Ketchum, W., Kettell, S. H., Khabibullin, M., Khan, N., Khvedelidze, A., Kim, D., Kim, J., Kim, M. J., King, B., Kirby, B., Kirby, M., Kish, A., Klein, J., Kleykamp, J., Klustova, A., Kobilarcik, T., Koch, L., Koehler, K., Koerner, L. W., Koh, D. H., Kolupaeva, L., Korablev, D., Kordosky, M., Kosc, T., Kose, U., Kostelecký, V. A., Kothekar, K., Kotler, I., Kovalcuk, M., Kozhukalov, V., Krah, W., Kralik, R., Kramer, M., Kreczko, L., Krennrich, F., Kreslo, I., Kroupova, T., Kubota, S., Kubu, M., Kudenko, Y., Kudryavtsev, V. A., Kufatty, G., Kuhlmann, S., Kulagin, S., Kumar, J., Kumar, P., Kumaran, S., Kunzmann, J., Kuravi, R., Kurita, N., Kuruppu, C., Kus, V., Kutter, T., Kvasnicka, J., Labree, T., Lackey, T., Lalău, I., Lambert, A., Land, B. J., Lane, C. E., Lane, N., Lang, K., Langford, T., Langstaff, M., Lanni, F., Lantwin, O., Larkin, J., Lasorak, P., Last, D., Laudrain, A., Laundrie, A., Laurenti, G., Lavaut, E., Laycock, P., Lazanu, I., LaZur, R., Lazzaroni, M., Le, T., Leardini, S., Learned, J., LeCompte, T., Legin, V., Miotto, G. Lehmann, Lehnert, R., de Oliveira, M. A. Leigui, Leitner, M., Silverio, D. Leon, Lepin, L. M., Li, J. -Y, Li, S. W., Li, Y., Liao, H., Lin, C. S., Lindebaum, D., Linden, S., Lineros, R. A., Lister, A., Littlejohn, B. R., Liu, H., Liu, J., Liu, Y., Lockwitz, S., Lokajicek, M., Lomidze, I., Long, K., Lopes, T. V., Lopez, J., de Rego, I. López, López-March, N., Lord, T., LoSecco, J. M., Louis, W. C., Sanchez, A. Lozano, Lu, X. -G., Luk, K. B., Lunday, B., Luo, X., Luppi, E., MacFarlane, D., Machado, A. A., Machado, P., Macias, C. T., Macier, J. R., MacMahon, M., Maddalena, A., Madera, A., Madigan, P., Magill, S., Magueur, C., Mahn, K., Maio, A., Major, A., Majumdar, K., Mameli, S., Man, M., Mandujano, R. C., Maneira, J., Manly, S., Mann, A., Manolopoulos, K., Plata, M. Manrique, Corchado, S. Manthey, Manyam, V. N., Marchan, M., Marchionni, A., Marciano, W., Marfatia, D., Mariani, C., Maricic, J., Marinho, F., Marino, A. D., Markiewicz, T., Marques, F. Das Chagas, Marquet, C., Marshak, M., Marshall, C. M., Marshall, J., Martina, L., Martín-Albo, J., Martinez, N., Caicedo, D. A. Martinez, López, F. Martínez, Miravé, P. Martínez, Martynenko, S., Mascagna, V., Massari, C., Mastbaum, A., Matichard, F., Matsuno, S., Matteucci, G., Matthews, J., Mauger, C., Mauri, N., Mavrokoridis, K., Mawby, I., Mazza, R., McAskill, T., McConkey, N., McFarland, K. S., McGrew, C., McNab, A., Meazza, L., Meddage, V. C. N., Mefodiev, A., Mehta, B., Mehta, P., Melas, P., Mena, O., Mendez, H., Mendez, P., Méndez, D. P., Menegolli, A., Meng, G., Mercuri, A. C. E. A., Meregaglia, A., Messier, M. D., Metallo, S., Metcalf, W., Mewes, M., Meyer, H., Miao, T., Micallef, J., Miccoli, A., Michna, G., Milincic, R., Miller, F., Miller, G., Miller, W., Mineev, O., Minotti, A., Miralles, L., Mironov, C., Miryala, S., Miscetti, S., Mishra, C. S., Mishra, P., Mishra, S. R., Mislivec, A., Mitchell, M., Mladenov, D., Mocioiu, I., Mogan, A., Moggi, N., Mohanta, R., Mohayai, T. A., Mokhov, N., Molina, J., Bueno, L. Molina, Montagna, E., Montanari, A., Montanari, C., Montanari, D., Montanino, D., Zetina, L. M. Montaño, Mooney, M., Moor, A. F., Moore, Z., Moreno, D., Moreno-Palacios, O., Morescalchi, L., Moretti, D., Moretti, R., Morris, C., Mossey, C., Moura, C. A., Mouster, G., Mu, W., Mualem, L., Mueller, J., Muether, M., Muheim, F., Muir, A., Mukhamejanov, Y., Mulhearn, M., Munford, D., Munteanu, L. J., Muramatsu, H., Muraz, J., Murphy, M., Murphy, T., Muse, J., Mytilinaki, A., Nachtman, J., Nagai, Y., Nagu, S., Nandakumar, R., Naples, D., Narita, S., Navrer-Agasson, A., Nayak, N., Nebot-Guinot, M., Nehm, A., Nelson, J. K., Neogi, O., Nesbit, J., Nessi, M., Newbold, D., Newcomer, M., Nichol, R., Nicolas-Arnaldos, F., Nikolica, A., Nikolov, J., Niner, E., Nishimura, K., Norman, A., Norrick, A., Novella, P., Nowak, A., Nowak, J. A., Oberling, M., Ochoa-Ricoux, J. P., Oh, S., Oh, S. B., Olivier, A., Olshevskiy, A., Olson, T., Onel, Y., Onishchuk, Y., Oranday, A., Osbiston, M., Vélez, J. A. Osorio, O'Sullivan, L., Ormachea, L. Otiniano, Ott, J., Pagani, L., Palacio, G., Palamara, O., Palestini, S., Paley, J. M., Pallavicini, M., Palomares, C., Pan, S., Panda, P., Vazquez, W. Panduro, Pantic, E., Paolone, V., Papaleo, R., Papanestis, A., Papoulias, D., Paramesvaran, S., Paris, A., Parke, S., Parozzi, E., Parsa, S., Parsa, Z., Parveen, S., Parvu, M., Pasciuto, D., Pascoli, S., Pasqualini, L., Pasternak, J., Patrick, C., Patrizii, L., Patterson, R. B., Patzak, T., Paudel, A., Paulucci, L., Pavlovic, Z., Pawloski, G., Payne, D., Pec, V., Pedreschi, E., Peeters, S. J. M., Pellico, W., Perez, A. Pena, Pennacchio, E., Penzo, A., Peres, O. L. G., Gonzalez, Y. F. Perez, Pérez-Molina, L., Pernas, C., Perry, J., Pershey, D., Pessina, G., Petrillo, G., Petta, C., Petti, R., Pfaff, M., Pia, V., Pickering, L., Pietropaolo, F., Pimentel, V. L., Pinaroli, G., Pincha, S., Pinchault, J., Pitts, K., Plows, K., Pollack, C., Pollman, T., Pompa, F., Pons, X., Poonthottathil, N., Popov, V., Poppi, F., Porter, J., Paixão, L. G. Porto, Potekhin, M., Potenza, R., Pozzato, M., Prakash, T., Pratt, C., Prest, M., Psihas, F., Pugnere, D., Qian, X., Queen, J., Raaf, J. L., Radeka, V., Rademacker, J., Radics, B., Raffaelli, F., Rafique, A., Raguzin, E., Rahaman, U., Rai, M., Rajagopalan, S., Rajaoalisoa, M., Rakhno, I., Rakotondravohitra, L., Ralte, L., Delgado, M. A. Ramirez, Ramson, B., Rappoldi, A., Raselli, G., Ratoff, P., Ray, R., Razafinime, H., Razakamiandra, R. F., Rea, E. M., Real, J. S., Rebel, B., Rechenmacher, R., Reichenbacher, J., Reitzner, S. D., Sfar, H. Rejeb, Renner, E., Renshaw, A., Rescia, S., Resnati, F., Restrepo, Diego, Reynolds, C., Ribas, M., Riboldi, S., Riccio, C., Riccobene, G., Ricol, J. S., Rigan, M., Rincón, E. V., Ritchie-Yates, A., Ritter, S., Rivera, D., Rivera, R., Robert, A., Rocha, J. L. Rocabado, Rochester, L., Roda, M., Rodrigues, P., Alonso, M. J. Rodriguez, Rondon, J. Rodriguez, Rosauro-Alcaraz, S., Rosier, P., Ross, D., Rossella, M., Rossi, M., Ross-Lonergan, M., Roy, N., Roy, P., Rubbia, C., Ruggeri, A., Ferreira, G. Ruiz, Russell, B., Ruterbories, D., Rybnikov, A., Sacerdoti, S., Saha, S., Sahoo, S. K., Sahu, N., Sala, P., Samios, N., Samoylov, O., Sanchez, M. C., Bravo, A. Sánchez, Sánchez-Castillo, A., Sanchez-Lucas, P., Sandberg, V., Sanders, D. A., Sanfilippo, S., Sankey, D., Santoro, D., Saoulidou, N., Sapienza, P., Sarasty, C., Sarcevic, I., Sarra, I., Savage, G., Savinov, V., Scanavini, G., Scaramelli, A., Scarff, A., Schefke, T., Schellman, H., Schifano, S., Schlabach, P., Schmitz, D., Schneider, A. W., Scholberg, K., Schukraft, A., Schuld, B., Segade, A., Segreto, E., Selyunin, A., Senadheera, D., Senise, C. R., Sensenig, J., Shaevitz, M. H., Shanahan, P., Sharma, P., Kumar, R., Poudel, S. Sharma, Shaw, K., Shaw, T., Shchablo, K., Shen, J., Shepherd-Themistocleous, C., Sheshukov, A., Shi, J., Shi, W., Shin, S., Shivakoti, S., Shoemaker, I., Shooltz, D., Shrock, R., Siddi, B., Siden, M., Silber, J., Simard, L., Sinclair, J., Sinev, G., Singh, Jaydip, Singh, J., Singh, L., Singh, P., Singh, V., Chauhan, S. Singh, Sipos, R., Sironneau, C., Sirri, G., Siyeon, K., Skarpaas, K., Smedley, J., Smith, E., Smith, J., Smith, P., Smolik, J., Smy, M., Snape, M., Snider, E. L., Snopok, P., Snowden-Ifft, D., Nunes, M. Soares, Sobel, H., Soderberg, M., Sokolov, S., Salinas, C. J. Solano, Söldner-Rembold, S., Solomey, N., Solovov, V., Sondheim, W. E., Sorel, M., Sotnikov, A., Soto-Oton, J., Sousa, A., Soustruznik, K., Spinella, F., Spitz, J., Spooner, N. J. C., Spurgeon, K., Stalder, D., Stancari, M., Stanco, L., Steenis, J., Stein, R., Steiner, H. M., Lisbôa, A. F. Steklain, Stepanova, A., Stewart, J., Stillwell, B., Stock, J., Stocker, F., Stokes, T., Strait, M., Strauss, T., Strigari, L., Stuart, A., Suarez, J. G., Subash, J., Surdo, A., Suter, L., Sutera, C. M., Sutton, K., Suvorov, Y., Svoboda, R., Swain, S. K., Szczerbinska, B., Szelc, A. M., Sztuc, A., Taffara, A., Talukdar, N., Tamara, J., Tanaka, H. A., Tang, S., Taniuchi, N., Casanova, A. M. Tapia, Oregui, B. Tapia, Tapper, A., Tariq, S., Tarpara, E., Tatar, E., Tayloe, R., Tedeschi, D., Teklu, A. M., Vidal, J. Tena, Tennessen, P., Tenti, M., Terao, K., Terranova, F., Testera, G., Thakore, T., Thea, A., Thomas, S., Thompson, A., Thorn, C., Timm, S. C., Tiras, E., Tishchenko, V., Tiwari, S., Todorović, N., Tomassetti, L., Tonazzo, A., Torbunov, D., Torti, M., Tortola, M., Tortorici, F., Tosi, N., Totani, D., Toups, M., Touramanis, C., Tran, D., Travaglini, R., Trevor, J., Triller, E., Trilov, S., Truchon, J., Truncali, D., Trzaska, W. H., Tsai, Y., Tsai, Y. -T., Tsamalaidze, Z., Tsang, K. V., Tsverava, N., Tu, S. Z., Tufanli, S., Tunnell, C., Turnberg, S., Turner, J., Tuzi, M., Tyler, J., Tyley, E., Tzanov, M., Uchida, M. A., González, J. Ureña, Urheim, J., Usher, T., Utaegbulam, H., Uzunyan, S., Vagins, M. R., Vahle, P., Valder, S., Valdiviesso, G. A., Valencia, E., Valentim, R., Vallari, Z., Vallazza, E., Valle, J. W. F., Van Berg, R., Van de Water, R. G., Forero, D. V., Vannozzi, A., Van Nuland-Troost, M., Varanini, F., Oliva, D. Vargas, Vasina, S., Vaughan, N., Vaziri, K., Vázquez-Ramos, A., Vega, J., Ventura, S., Verdugo, A., Vergani, S., Verzocchi, M., Vetter, K., Vicenzi, M., de Souza, H. Vieira, Vignoli, C., Vilela, C., Villa, E., Viola, S., Viren, B., Vizarreta, R., Hernandez, A. P. Vizcaya, Vuong, Q., Waldron, A. V., Wallbank, M., Walsh, J., Walton, T., Wang, H., Wang, J., Wang, L., Wang, M. H. L. S., Wang, X., Wang, Y., Warburton, K., Warner, D., Warsame, L., Wascko, M. O., Waters, D., Watson, A., Wawrowska, K., Weber, A., Weber, C. M., Weber, M., Wei, H., Weinstein, A., Westerdale, S., Wetstein, M., Whalen, K., White, A., Whitehead, L. H., Whittington, D., Wilhlemi, J., Wilking, M. J., Wilkinson, A., Wilkinson, C., Wilson, F., Wilson, R. J., Winter, P., Wisniewski, W., Wolcott, J., Wolfs, J., Wongjirad, T., Wood, A., Wood, K., Worcester, E., Worcester, M., Wospakrik, M., Wresilo, K., Wret, C., Wu, S., Wu, W., Wurm, M., Wyenberg, J., Xiao, Y., Xiotidis, I., Yaeggy, B., Yahlali, N., Yandel, E., Yang, J., Yang, K., Yang, T., Yankelevich, A., Yershov, N., Yonehara, K., Young, T., Yu, B., Yu, H., Yu, J., Yu, Y., Yuan, W., Zaki, R., Zalesak, J., Zambelli, L., Zamorano, B., Zani, A., Zapata, O., Zazueta, L., Zeller, G. P., Zennamo, J., Zeug, K., Zhang, C., Zhang, S., Zhao, M., Zhivun, E., Zimmerman, E. D., Zucchelli, S., Zuklin, J., Zutshi, V., and Zwaska, R.
Subjects: Physics - Instrumentation and Detectors, High Energy Physics - Experiment
Abstract: This paper introduces the hypothetical track-length fitting algorithm, a novel method for measuring the kinetic energies of ionizing particles in liquid argon time projection chambers (LArTPCs). The algorithm finds the most probable offset in track length for a track-like object by comparing the measured ionization density as a function of position with a theoretical prediction of the energy loss as a function of the energy, including models of electron recombination and detector response. The algorithm can be used to measure the energies of particles that interact before they stop, such as charged pions that are absorbed by argon nuclei. The algorithm's energy measurement resolutions and fractional biases are presented as functions of particle kinetic energy and number of track hits using samples of stopping secondary charged pions in data collected by the ProtoDUNE-SP detector, and also in a detailed simulation. Additional studies describe impact of the dE/dx model on energy measurement performance. The method described in this paper to characterize the energy measurement performance can be repeated in any LArTPC experiment using stopping secondary charged pions.
Published: 2024

5. Convex Reformulation of Information Constrained Linear State Estimation with Mixed-Binary Variables for Outlier Accommodation

Author: Hu, Wang, Jiang, Zeyi, Mohsenian-Rad, Hamed, and Farrell, Jay A.
Subjects: Electrical Engineering and Systems Science - Systems and Control
Abstract: This article considers the challenge of accommodating outlier measurements in state estimation. The Risk-Averse Performance-Specified (RAPS) state estimation approach addresses outliers as a measurement selection Bayesian risk minimization problem subject to an information accuracy constraint, which is a non-convex optimization problem. Prior explorations into RAPS rely on exhaustive search, which becomes computationally infeasible as the number of measurements increases. This paper derives a convex formulation for the RAPS optimization problems via transforming the mixed-binary variables into linear constraints. The convex reformulation herein can be solved by convex programming toolboxes, significantly enhancing computational efficiency. We explore two specifications: Full-RAPS, utilizing the full information matrix, and Diag-RAPS, focusing on diagonal elements only. The simulation comparison demonstrates that Diag-RAPS is faster and more efficient than Full-RAPS. In comparison with Kalman Filter (KF) and Threshold Decisions (TD), Diag-RAPS consistently achieves the lowest risk, while achieving the performance specification when it is feasible., Comment: Accepted by the 2024 IEEE Conference on Decision and Control
Published: 2024

6. Gemini High-resolution Optical SpecTrograph (GHOST) at Gemini-South: Instrument performance and integration, first science, and next steps

Author: Kalari, V. M., Diaz, R. J., Robertson, G., McConnachie, A., Ireland, M., Salinas, R., Young, P., Simpson, C., Hayes, C., Nielsen, J., Burley, G., Pazder, J., Gomez-Jimenez, M., Martioli, E., Howell, S. B., Jeong, M., Juneau, S., Ruiz-Carmona, R., Margheim, S., Sheinis, A., Anthony, A., Baker, G., Berg, T. A. M., Cao, T., Chapin, E., Chin, T., Chiboucas, K., Churilov, V., Deibert, E., Densmore, A., Dunn, J., Edgar, M. L., Heo, J., Henderson, D., Farrell, T., Font, J., Firpo, V., Fuentes, J., Labrie, K., Lambert, S., Lawrence, J., Lothrop, J., McDermid, R., Miller, B. W., Perez, G., Placco, V. M., Prado, P., Quiroz, C., Ramos, F., Rutten, R., Silva, K. M. G., Thomas-Osip, J., Urrutia, C., Vacca, W. D., Venn, K., Waller, F., Waller, L., White, M., Xu, S., and Zhelem, R.
Subjects: Astrophysics - Instrumentation and Methods for Astrophysics, Astrophysics - Solar and Stellar Astrophysics
Abstract: The Gemini South telescope is now equipped with a new high-resolution spectrograph called GHOST (the Gemini High-resolution Optical SpecTrograph). This instrument provides high-efficiency, high-resolution spectra covering 347-1060 nm in a single exposure of either one or two targets simultaneously, along with precision radial velocity spectroscopy utilizing an internal calibration source. It can operate at a spectral element resolving power of either 76000 or 56000, and can reach a SNR$\sim$5 in a 1hr exposure on a V$\sim$20.8 mag target in median site seeing, and dark skies (per resolution element). GHOST was installed on-site in June 2022, and we report performance after full integration to queue operations in November 2023, in addition to scientific results enabled by the integration observing runs. These results demonstrate the ability to observe a wide variety of bright and faint targets with high efficiency and precision. With GHOST, new avenues to explore high-resolution spectroscopy have opened up to the astronomical community. These are described, along with the planned and potential upgrades to the instrument., Comment: Accepted in the Astronomical Journal; 26 pages, 24 figures and 4 tables
Published: 2024

7. High Energy Physics from Low Energy Physics

Author: Farrell, Roland C.
Subjects: Quantum Physics, High Energy Physics - Lattice, High Energy Physics - Phenomenology, Nuclear Theory
Abstract: The separation between physics at low and high energies is essential for physics to have any utility; the details of quantum gravity are not necessary to calculate the trajectory of a cannon ball. However, physics at low and high energies are not completely independent, and this thesis explores two ways that they are related. The first is through a UV/IR symmetry that relates scattering processes at low and high energies. This UV/IR symmetry manifests in geometrical properties of the $S$-matrix, and of the RG flow of the coupling constants in the corresponding effective field theory. Low energy nuclear physics nearly realizes this UV/IR symmetry, providing an explanation for the smallness of shape parameters in the effective range expansion of nucleon-nucleon scattering, and inspiring a new way to organize the interactions between neutrons and protons. The second is through the use of quantum computers to simulate lattice gauge theories. Quantum simulations rely on the universality of the rules of quantum mechanics, which can be applied equally well to describe a (low energy) transmon qubit at 15 milli-Kelvin as a (high energy) 1 TeV quark. This thesis presents the first simulations of one dimensional lattice quantum chromodynamics on a quantum computer, culminating in a real-time simulation of beta-decay. Results from the first simulations of a lattice gauge theory on 100+ qubits of a quantum computer are also presented. The methods developed in this thesis for quantum simulation are ``physics-aware", and are guided by the symmetries and hierarchies in length scales of the systems being studied. Without these physics-aware methods, 100+ qubit simulations of lattice gauge theories would not have been possible on the noisy quantum computers that are presently available., Comment: PhD Thesis: 420 pages, 101 figures
Published: 2024

8. High-order finite element methods for three-dimensional multicomponent convection-diffusion

Author: Baier-Reinio, Aaron and Farrell, Patrick E.
Subjects: Mathematics - Numerical Analysis, 65N30, 76M10, 76T30
Abstract: We derive and analyze a broad class of finite element methods for numerically simulating the stationary, low Reynolds number flow of concentrated mixtures of several distinct chemical species in a common thermodynamic phase. The underlying partial differential equations that we discretize are the Stokes$\unicode{x2013}$Onsager$\unicode{x2013}$Stefan$\unicode{x2013}$Maxwell (SOSM) equations, which model bulk momentum transport and multicomponent diffusion within ideal and non-ideal mixtures. Unlike previous approaches, the methods are straightforward to implement in two and three spatial dimensions, and allow for high-order finite element spaces to be employed. The key idea in deriving the discretization is to suitably reformulate the SOSM equations in terms of the species mass fluxes and chemical potentials, and discretize these unknown fields using stable $H(\textrm{div}) \unicode{x2013} L^2$ finite element pairs. We prove that the methods are convergent and yield a symmetric linear system for a Picard linearization of the SOSM equations, which staggers the updates for concentrations and chemical potentials. We also discuss how the proposed approach can be extended to the Newton linearization of the SOSM equations, which requires the simultaneous solution of mole fractions, chemical potentials, and other variables. Our theoretical results are supported by numerical experiments and we present an example of a physical application involving the microfluidic non-ideal mixing of hydrocarbons.
Published: 2024

9. DUNE Phase II: Scientific Opportunities, Detector Concepts, Technological Solutions

Author: DUNE Collaboration, Abud, A. Abed, Abi, B., Acciarri, R., Acero, M. A., Adames, M. R., Adamov, G., Adamowski, M., Adams, D., Adinolfi, M., Adriano, C., Aduszkiewicz, A., Aguilar, J., Akbar, F., Allison, K., Monsalve, S. Alonso, Alrashed, M., Alton, A., Alvarez, R., Alves, T., Amar, H., Amedo, P., Anderson, J., Andreopoulos, C., Andreotti, M., Andrews, M. P., Andrianala, F., Andringa, S., Anfimov, N., Ankowski, A., Antic, D., Antoniassi, M., Antonova, M., Antoshkin, A., Aranda-Fernandez, A., Arellano, L., Diaz, E. Arrieta, Arroyave, M. A., Asaadi, J., Ashkenazi, A., Asner, D. M., Asquith, L., Atkin, E., Auguste, D., Aurisano, A., Aushev, V., Autiero, D., Azam, M. B., Azfar, F., Back, A., Back, H., Back, J. J., Bagaturia, I., Bagby, L., Balashov, N., Balasubramanian, S., Baldi, P., Baldini, W., Baldonedo, J., Baller, B., Bambah, B., Banerjee, R., Barao, F., Barbu, D., Barenboim, G., Barham~Alzás, P., Barker, G. J., Barkhouse, W., Barr, G., Monarca, J. Barranco, Barros, A., Barros, N., Barrow, D., Barrow, J. L., Basharina-Freshville, A., Bashyal, A., Basque, V., Batchelor, C., Bathe-Peters, L., Battat, J. B. R., Battisti, F., Bay, F., Bazetto, M. C. Q., Alba, J. L. L. Bazo, Beacom, J. F., Bechetoille, E., Behera, B., Belchior, E., Bell, G., Bellantoni, L., Bellettini, G., Bellini, V., Beltramello, O., Benekos, N., Montiel, C. Benitez, Benjamin, D., Neves, F. Bento, Berger, J., Berkman, S., Bernal, J., Bernardini, P., Bersani, A., Bertolucci, S., Betancourt, M., Rodríguez, A. Betancur, Bevan, A., Bezawada, Y., Bezerra, A. T., Bezerra, T. J., Bhat, A., Bhatnagar, V., Bhatt, J., Bhattacharjee, M., Bhattacharya, M., Bhuller, S., Bhuyan, B., Biagi, S., Bian, J., Biery, K., Bilki, B., Bishai, M., Bitadze, A., Blake, A., Blaszczyk, F. D., Blazey, G. C., Blucher, E., Bodek, A., Bogenschuetz, J., Boissevain, J., Bolognesi, S., Bolton, T., Bomben, L., Bonesini, M., Bonilla-Diaz, C., Bonini, F., Booth, A., Boran, F., Bordoni, S., Merlo, R. Borges, Borkum, A., Bostan, N., Bouet, R., Boza, J., Bracinik, J., Brahma, B., Brailsford, D., Bramati, F., Branca, A., Brandt, A., Bremer, J., Brew, C., Brice, S. J., Brio, V., Brizzolari, C., Bromberg, C., Brooke, J., Bross, A., Brunetti, G., Brunetti, M., Buchanan, N., Budd, H., Buergi, J., Bundock, A., Burgardt, D., Butchart, S., V., G. Caceres, Cagnoli, I., Cai, T., Calabrese, R., Calcutt, J., Calivers, L., Calvo, E., Caminata, A., Camino, A. F., Campanelli, W., Campani, A., Benitez, A. Campos, Canci, N., Capó, J., Caracas, I., Caratelli, D., Carber, D., Carceller, J. M., Carini, G., Carlus, B., Carneiro, M. F., Carniti, P., Terrazas, I. Caro, Carranza, H., Carrara, N., Carroll, L., Carroll, T., Carter, A., Casarejos, E., Casazza, D., Forero, J. F. Castaño, Castaño, F. A., Castillo, A., Castromonte, C., Catano-Mur, E., Cattadori, C., Cavalier, F., Cavanna, F., Centro, S., Cerati, G., Cerna, C., Cervelli, A., Villanueva, A. Cervera, Chakraborty, K., Chakraborty, S., Chalifour, M., Chappell, A., Charitonidis, N., Chatterjee, A., Chen, H., Chen, M., Chen, W. C., Chen, Y., Chen-Wishart, Z., Cherdack, D., Chi, C., Chiapponi, F., Chirco, R., Chitirasreemadam, N., Cho, K., Choate, S., Chokheli, D., Chong, P. S., Chowdhury, B., Christian, D., Chukanov, A., Chung, M., Church, E., Cicala, M. F., Cicerchia, M., Cicero, V., Ciolini, R., Clarke, P., Cline, G., Coan, T. E., Cocco, A. G., Coelho, J. A. B., Cohen, A., Collazo, J., Collot, J., Conley, E., Conrad, J. M., Convery, M., Copello, S., Cortez, A. F. V., Cova, P., Cox, C., Cremaldi, L., Cremonesi, L., Crespo-Anadón, J. I., Crisler, M., Cristaldo, E., Crnkovic, J., Crone, G., Cross, R., Cudd, A., Cuesta, C., Cui, Y., Curciarello, F., Cussans, D., Dai, J., Dalager, O., Dallavalle, R., Dallaway, W., D'Amico, R., da Motta, H., Dar, Z. A., Darby, R., Peres, L. Da Silva, David, Q., Davies, G. S., Davini, S., Dawson, J., De Aguiar, R., De Almeida, P., Debbins, P., De Bonis, I., Decowski, M. P., de Gouvêa, A., De Holanda, P. C., Astiz, I. L. De Icaza, De Jong, P., Sanchez, P. Del Amo, De la Torre, A., De Lauretis, G., Delbart, A., Delepine, D., Delgado, M., Dell'Acqua, A., Monache, G. Delle, Delmonte, N., De Lurgio, P., Demario, R., De Matteis, G., Neto, J. R. T. de Mello, DeMuth, D. M., Dennis, S., Densham, C., Denton, P., Deptuch, G. W., De Roeck, A., De Romeri, V., Detje, J. P., Devine, J., Dharmapalan, R., Dias, M., Diaz, A., Díaz, J. S., Díaz, F., Di Capua, F., Di Domenico, A., Di Domizio, S., Di Falco, S., Di Giulio, L., Ding, P., Di Noto, L., Diociaiuti, E., Distefano, C., Diurba, R., Diwan, M., Djurcic, Z., Doering, D., Dolan, S., Dolek, F., Dolinski, M. J., Domenici, D., Domine, L., Donati, S., Donon, Y., Doran, S., Douglas, D., Doyle, T. A., Dragone, A., Drielsma, F., Duarte, L., Duchesneau, D., Duffy, K., Dugas, K., Dunne, P., Dutta, B., Duyang, H., Dwyer, D. A., Dyshkant, A. S., Dytman, S., Eads, M., Earle, A., Edayath, S., Edmunds, D., Eisch, J., Englezos, P., Ereditato, A., Erjavec, T., Escobar, C. O., Evans, J. J., Ewart, E., Ezeribe, A. C., Fahey, K., Fajt, L., Falcone, A., Fani', M., Farnese, C., Farrell, S., Farzan, Y., Fedoseev, D., Felix, J., Feng, Y., Fernandez-Martinez, E., Fernández-Posada, D., Ferry, G., Fialova, E., Fields, L., Filip, P., Filkins, A., Filthaut, F., Fine, R., Fiorillo, G., Fiorini, M., Fogarty, S., Foreman, W., Fowler, J., Franc, J., Francis, K., Franco, D., Franklin, J., Freeman, J., Fried, J., Friedland, A., Fuess, S., Furic, I. K., Furman, K., Furmanski, A. P., Gaba, R., Gabrielli, A., M~Gago, A., Galizzi, F., Gallagher, H., Gallice, N., Galymov, V., Gamberini, E., Gamble, T., Ganacim, F., Gandhi, R., Ganguly, S., Gao, F., Gao, S., Garcia-Gamez, D., García-Peris, M. Á., Gardim, F., Gardiner, S., Gastler, D., Gauch, A., Gauvreau, J., Gauzzi, P., Gazzana, S., Ge, G., Geffroy, N., Gelli, B., Gent, S., Gerlach, L., Ghorbani-Moghaddam, Z., Giammaria, T., Gibin, D., Gil-Botella, I., Gilligan, S., Gioiosa, A., Giovannella, S., Girerd, C., Giri, A. K., Giugliano, C., Giusti, V., Gnani, D., Gogota, O., Gollapinni, S., Gollwitzer, K., Gomes, R. A., Bermeo, L. V. Gomez, Fajardo, L. S. Gomez, Gonnella, F., Gonzalez-Diaz, D., Gonzalez-Lopez, M., Goodman, M. C., Goswami, S., Gotti, C., Goudeau, J., Goudzovski, E., Grace, C., Gramellini, E., Gran, R., Granados, E., Granger, P., Grant, C., Gratieri, D. R., Grauso, G., Green, P., Greenberg, S., Greer, J., Griffith, W. C., Groetschla, F. T., Grzelak, K., Gu, L., Gu, W., Guarino, V., Guarise, M., Guenette, R., Guerzoni, M., Guffanti, D., Guglielmi, A., Guo, B., Guo, F. Y., Gupta, A., Gupta, V., Gurung, G., Gutierrez, D., Guzowski, P., Guzzo, M. M., Gwon, S., Habig, A., Hadavand, H., Haegel, L., Haenni, R., Hagaman, L., Hahn, A., Haiston, J., Hakenmüller, J., Hamernik, T., Hamilton, P., Hancock, J., Happacher, F., Harris, D. A., Hart, A., Hartnell, J., Hartnett, T., Harton, J., Hasegawa, T., Hasnip, C. M., Hatcher, R., Hayrapetyan, K., Hays, J., Hazen, E., He, M., Heavey, A., Heeger, K. M., Heise, J., Hellmuth, P., Henry, S., Hernández-García, J., Herner, K., Hewes, V., Higuera, A., Hilgenberg, C., Hillier, S. J., Himmel, A., Hinkle, E., Hirsch, L. R., Ho, J., Hoff, J., Holin, A., Holvey, T., Hoppe, E., Horiuchi, S., Horton-Smith, G. A., Houdy, T., Howard, B., Howell, R., Hristova, I., Hronek, M. S., Huang, J., Huang, R. G., Hulcher, Z., Ibrahim, M., Iles, G., Ilic, N., Iliescu, A. M., Illingworth, R., Ingratta, G., Ioannisian, A., Irwin, B., Isenhower, L., Oliveira, M. Ismerio, Itay, R., Jackson, C. M., Jain, V., James, E., Jang, W., Jargowsky, B., Jena, D., Jentz, I., Ji, X., Jiang, C., Jiang, J., Jiang, L., Jipa, A., Jo, J. H., Joaquim, F. R., Johnson, W., Jollet, C., Jones, B., Jones, R., Jovancevic, N., Judah, M., Jung, C. K., Junk, T., Jwa, Y., Kabirnezhad, M., Kaboth, A. C., Kadenko, I., Kakorin, I., Kalitkina, A., Kalra, D., Kandemir, M., Kaplan, D. M., Karagiorgi, G., Karaman, G., Karcher, A., Karyotakis, Y., Kasai, S., Kasetti, S. P., Kashur, L., Katsioulas, I., Kauther, A., Kazaryan, N., Ke, L., Kearns, E., Keener, P. T., Kelly, K. J., Kemp, E., Kemularia, O., Kermaidic, Y., Ketchum, W., Kettell, S. H., Khabibullin, M., Khan, N., Khvedelidze, A., Kim, D., Kim, J., Kim, M. J., King, B., Kirby, B., Kirby, M., Kish, A., Klein, J., Kleykamp, J., Klustova, A., Kobilarcik, T., Koch, L., Koehler, K., Koerner, L. W., Koh, D. H., Kolupaeva, L., Korablev, D., Kordosky, M., Kosc, T., Kose, U., Kostelecký, V. A., Kothekar, K., Kotler, I., Kovalcuk, M., Kozhukalov, V., Krah, W., Kralik, R., Kramer, M., Kreczko, L., Krennrich, F., Kreslo, I., Kroupova, T., Kubota, S., Kubu, M., Kudenko, Y., Kudryavtsev, V. A., Kufatty, G., Kuhlmann, S., Kulagin, S., Kumar, J., Kumar, P., Kumaran, S., Kunzmann, J., Kuravi, R., Kurita, N., Kuruppu, C., Kus, V., Kutter, T., Kuźniak, M., Kvasnicka, J., Labree, T., Lackey, T., Lalău, I., Lambert, A., Land, B. J., Lane, C. E., Lane, N., Lang, K., Langford, T., Langstaff, M., Lanni, F., Lantwin, O., Larkin, J., Lasorak, P., Last, D., Laudrain, A., Laundrie, A., Laurenti, G., Lavaut, E., Laycock, P., Lazanu, I., LaZur, R., Lazzaroni, M., Le, T., Leardini, S., Learned, J., LeCompte, T., Legin, V., Miotto, G. Lehmann, Lehnert, R., de Oliveira, M. A. Leigui, Leitner, M., Silverio, D. Leon, Lepin, L. M., -Y~Li, J., Li, S. W., Li, Y., Liao, H., Lin, C. S., Lindebaum, D., Linden, S., Lineros, R. A., Lister, A., Littlejohn, B. 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M., Weber, M., Wei, H., Weinstein, A., Westerdale, S., Wetstein, M., Whalen, K., White, A., Whitehead, L. H., Whittington, D., Wilhlemi, J., Wilking, M. J., Wilkinson, A., Wilkinson, C., Wilson, F., Wilson, R. J., Winter, P., Wisniewski, W., Wolcott, J., Wolfs, J., Wongjirad, T., Wood, A., Wood, K., Worcester, E., Worcester, M., Wospakrik, M., Wresilo, K., Wret, C., Wu, S., Wu, W., Wurm, M., Wyenberg, J., Xiao, Y., Xiotidis, I., Yaeggy, B., Yahlali, N., Yandel, E., Yang, J., Yang, K., Yang, T., Yankelevich, A., Yershov, N., Yonehara, K., Young, T., Yu, B., Yu, H., Yu, J., Yu, Y., Yuan, W., Zaki, R., Zalesak, J., Zambelli, L., Zamorano, B., Zani, A., Zapata, O., Zazueta, L., Zeller, G. P., Zennamo, J., Zeug, K., Zhang, C., Zhang, S., Zhao, M., Zhivun, E., Zimmerman, E. D., Zucchelli, S., Zuklin, J., Zutshi, V., and Zwaska, R.
Subjects: Physics - Instrumentation and Detectors, High Energy Physics - Experiment
Abstract: The international collaboration designing and constructing the Deep Underground Neutrino Experiment (DUNE) at the Long-Baseline Neutrino Facility (LBNF) has developed a two-phase strategy toward the implementation of this leading-edge, large-scale science project. The 2023 report of the US Particle Physics Project Prioritization Panel (P5) reaffirmed this vision and strongly endorsed DUNE Phase I and Phase II, as did the European Strategy for Particle Physics. While the construction of the DUNE Phase I is well underway, this White Paper focuses on DUNE Phase II planning. DUNE Phase-II consists of a third and fourth far detector (FD) module, an upgraded near detector complex, and an enhanced 2.1 MW beam. The fourth FD module is conceived as a "Module of Opportunity", aimed at expanding the physics opportunities, in addition to supporting the core DUNE science program, with more advanced technologies. This document highlights the increased science opportunities offered by the DUNE Phase II near and far detectors, including long-baseline neutrino oscillation physics, neutrino astrophysics, and physics beyond the standard model. It describes the DUNE Phase II near and far detector technologies and detector design concepts that are currently under consideration. A summary of key R&D goals and prototyping phases needed to realize the Phase II detector technical designs is also provided. DUNE's Phase II detectors, along with the increased beam power, will complete the full scope of DUNE, enabling a multi-decadal program of groundbreaking science with neutrinos.
Published: 2024

10. The Discovery of Three Galactic Wolf-Rayet Stars

Author: Marin, Laurella C., Massey, Philip, Skiff, Brian A., and Farrell, Kennedy A.
Subjects: Astrophysics - Solar and Stellar Astrophysics, Astrophysics - Astrophysics of Galaxies
Abstract: Wolf-Rayet stars (WRs) are evolved massive stars in the brief stage before they undergo core collapse. Not only are they rare, but they also can be particularly difficult to find due to the high extinction in the Galactic plane. This paper discusses the discovery of three new Galactic WRs previously classified as H$\alpha$ emission stars, but thanks to Gaia spectra, we were able to identify the broad, strong emission lines that characterize WRs. Using the Lowell Discovery Telescope and the DeVeny spectrograph, we obtained spectra for each star. Two are WC9s, and the third is a WN6 + O6.5 V binary. The latter is a known eclipsing system with a 4.4 day period from ASAS-SN data. We calculate absolute visual magnitudes for all three stars to be between -7 and -6, which is consistent with our expectations of these subtypes. These discoveries highlight the incompleteness of the WR census in our local volume of the Milky Way and suggest the potential for future Galactic WR discoveries from Gaia low-dispersion spectra. Furthermore, radial velocity studies of the newly found binary will provide direct mass estimates and orbital parameters, adding to our knowledge of the role that binarity plays in massive star evolution., Comment: Accepted for publication in the Astronomical Journal
Published: 2024

11. DOME Registry: Implementing community-wide recommendations for reporting supervised machine learning in biology

Author: Attafi, Omar Abdelghani, Clementel, Damiano, Kyritsis, Konstantinos, Capriotti, Emidio, Farrell, Gavin, Fragkouli, Styliani-Christina, Castro, Leyla Jael, Hatos, András, Lenaerts, Tom, Mazurenko, Stanislav, Mozaffari, Soroush, Pradelli, Franco, Ruch, Patrick, Savojardo, Castrense, Turina, Paola, Zambelli, Federico, Piovesan, Damiano, Monzon, Alexander Miguel, Psomopoulos, Fotis, and Tosatto, Silvio C. E.
Subjects: Quantitative Biology - Other Quantitative Biology
Abstract: Supervised machine learning (ML) is used extensively in biology and deserves closer scrutiny. The DOME recommendations aim to enhance the validation and reproducibility of ML research by establishing standards for key aspects such as data handling and processing, optimization, evaluation, and model interpretability. The recommendations help to ensure that key details are reported transparently by providing a structured set of questions. Here, we introduce the DOME Registry (URL: registry.dome-ml.org), a database that allows scientists to manage and access comprehensive DOME-related information on published ML studies. The registry uses external resources like ORCID, APICURON and the Data Stewardship Wizard to streamline the annotation process and ensure comprehensive documentation. By assigning unique identifiers and DOME scores to publications, the registry fosters a standardized evaluation of ML methods. Future plans include continuing to grow the registry through community curation, improving the DOME score definition and encouraging publishers to adopt DOME standards, promoting transparency and reproducibility of ML in the life sciences.
Published: 2024

12. Toward a Comprehensive Grid of Cepheid Models with MESA I. Uncertainties of the Evolutionary Tracks of Intermediate-Mass Stars

Author: Ziółkowska, Oliwia, Smolec, Radosław, Thoul, Anne, Farrell, Eoin, Rathour, Rajeev Singh, and Hocdé, Vincent
Subjects: Astrophysics - Solar and Stellar Astrophysics
Abstract: Helium-burning stars, in particular Cepheids, are especially difficult to model, as the choice of free parameters can greatly impact the shape of the blue loops - the part of the evolutionary track at which instability strip is crossed. Contemporary one-dimensional stellar evolution codes, like MESA (Modules for Experiments in Stellar Astrophysics), come with a large number of free parameters that allow to model the physical processes in stellar interiors under many assumptions. The uncertainties that arise from this freedom are rarely discussed in the literature despite their impact on the evolution of the model. We calculate a grid of evolutionary models with MESA, varying several controls, like solar mixture of heavy elements, mixing length theory prescription, nuclear reaction rates, scheme to determine convective boundaries, atmosphere model, temporal and spatial resolution, and quantify their impact on age and location of the evolutionary track on the HR diagram from the main sequence till the end of core-helium burning. Our investigation was conducted for a full range of masses and metallicities expected for classical Cepheids. The uncertainties are significant, especially during core-helium burning, reaching or exceeding the observational uncertainties of log Teff and log L for detached eclipsing binary systems. For models below 9 solar masses, thin convective shells develop and evolve erratically, not allowing the models to converge. A careful inspection of Kippenhahn diagrams and convergence study is advised for a given mass and metallicity, to assess how severe this problem is and to what extent it may affect the evolution.
Published: 2024

13. An augmented Lagrangian preconditioner for the control of the Navier--Stokes equations

Author: Leveque, Santolo, Benzi, Michele, and Farrell, Patrick E.
Subjects: Mathematics - Numerical Analysis
Abstract: We address the solution of the distributed control problem for the steady, incompressible Navier--Stokes equations. We propose an inexact Newton linearization of the optimality conditions. Upon discretization by a finite element scheme, we obtain a sequence of large symmetric linear systems of saddle-point type. We use an augmented Lagrangian-based block triangular preconditioner in combination with the flexible GMRES method at each Newton step. The preconditioner is applied inexactly via a suitable multigrid solver. Numerical experiments indicate that the resulting method appears to be fairly robust with respect to viscosity, mesh size, and the choice of regularization parameter when applied to 2D problems.
Published: 2024

14. First Measurement of the Total Inelastic Cross-Section of Positively-Charged Kaons on Argon at Energies Between 5.0 and 7.5 GeV

Author: DUNE Collaboration, Abud, A. Abed, Abi, B., Acciarri, R., Acero, M. A., Adames, M. R., Adamov, G., Adamowski, M., Adams, D., Adinolfi, M., Adriano, C., Aduszkiewicz, A., Aguilar, J., Akbar, F., Allison, K., Monsalve, S. Alonso, Alrashed, M., Alton, A., Alvarez, R., Alves, T., Amar, H., Amedo, P., Anderson, J., Andreopoulos, C., Andreotti, M., Andrews, M. P., Andrianala, F., Andringa, S., Anfimov, N., Ankowski, A., Antic, D., Antoniassi, M., Antonova, M., Antoshkin, A., Aranda-Fernandez, A., Arellano, L., Diaz, E. Arrieta, Arroyave, M. A., Asaadi, J., Ashkenazi, A., Asner, D., Asquith, L., Atkin, E., Auguste, D., Aurisano, A., Aushev, V., Autiero, D., Azam, M. B., Azfar, F., Back, A., Back, H., Back, J. J., Bagaturia, I., Bagby, L., Balashov, N., Balasubramanian, S., Baldi, P., Baldini, W., Baldonedo, J., Baller, B., Bambah, B., Banerjee, R., Barao, F., Barbu, D., Barenboim, G., Barham~Alzás, P., Barker, G. J., Barkhouse, W., Barr, G., Monarca, J. 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Borges, Borkum, A., Bostan, N., Bouet, R., Boza, J., Bracinik, J., Brahma, B., Brailsford, D., Bramati, F., Branca, A., Brandt, A., Bremer, J., Brew, C., Brice, S. J., Brio, V., Brizzolari, C., Bromberg, C., Brooke, J., Bross, A., Brunetti, G., Brunetti, M., Buchanan, N., Budd, H., Buergi, J., Bundock, A., Burgardt, D., Butchart, S., V., G. Caceres, Cagnoli, I., Cai, T., Calabrese, R., Calcutt, J., Calivers, L., Calvo, E., Caminata, A., Camino, A. F., Campanelli, W., Campani, A., Benitez, A. Campos, Canci, N., Capó, J., Caracas, I., Caratelli, D., Carber, D., Carceller, J. M., Carini, G., Carlus, B., Carneiro, M. F., Carniti, P., Terrazas, I. Caro, Carranza, H., Carrara, N., Carroll, L., Carroll, T., Carter, A., Casarejos, E., Casazza, D., Forero, J. F. Castaño, Castaño, F. A., Castillo, A., Castromonte, C., Catano-Mur, E., Cattadori, C., Cavalier, F., Cavanna, F., Centro, S., Cerati, G., Cerna, C., Cervelli, A., Villanueva, A. 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Subjects: High Energy Physics - Experiment, Physics - Instrumentation and Detectors
Abstract: ProtoDUNE Single-Phase (ProtoDUNE-SP) is a 770-ton liquid argon time projection chamber that operated in a hadron test beam at the CERN Neutrino Platform in 2018. We present a measurement of the total inelastic cross section of charged kaons on argon as a function of kaon energy using 6 and 7 GeV/$c$ beam momentum settings. The flux-weighted average of the extracted inelastic cross section at each beam momentum setting was measured to be 380$\pm$26 mbarns for the 6 GeV/$c$ setting and 379$\pm$35 mbarns for the 7 GeV/$c$ setting.
Published: 2024

15. A Collective Action Approach to Improving Attitudes and Self-Efficacy towards Gender Equality among Male STEM Academics

Author: Zachary W. Petzel, Lynn Farrell, Teresa McCormack, Rhiannon N. Turner, Karen Rafferty, and Ioana M. Latu
Abstract: Despite the implementation of equality interventions within higher education, progress towards gender parity in science, technology, engineering, and mathematics (STEM) remains slow. Male educators often exhibit poorer engagement with diversity initiatives, potentially contributing to persisting gender disparities in STEM given men's longstanding dominance in these programs. Two experiments investigate how equality interventions should be designed to maximize support from male educators. Experiment 1 (N = 72; M[subscript age] = 39.72, SD[subscript age] = 12.33) used virtual reality to manipulate 2 factors among male academics: (1) exposure to gender inequality and (2) virtually taking the perspective of a female scientist. Using self-report and behavioral measures, viewing an empirical presentation outlining the prevalence of gender issues in STEM yielded the greatest support for equality initiatives following successful perspective-taking. Experiment 2 (N = 120; M[subscript age] = 32.48, SD[subscript age] = 10.36) varied two additional factors among male academics: (1) evidence-based methods to reduce gender biases in STEM (i.e., promoting self-efficacy) and (2) blaming male academics for gender inequalities. Promoting self-efficacy and blaming men for disparities led to greater confidence in male academics' ability to address gender inequalities in their field. Notably, higher self-efficacy accounted for greater support for equality initiatives and internal motives to engage with diversity programs. Findings provide an empirical framework and high-tech training tools for promoting engagement with diversity initiatives among male educators, informing development of interventions within higher education to improve student and faculty experiences in STEM.
Published: 2024
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16. Co-Creating an Equality Diversity and Inclusion Learning Analytics Dashboard for Addressing Awarding Gaps in Higher Education

Author: Vaclav Bayer, Paul Mulholland, Martin Hlosta, Tracie Farrell, Christothea Herodotou, and Miriam Fernandez
Abstract: Educational outcomes from traditionally underrepresented groups are generally worse than for their more advantaged peers. This problem is typically known as the awarding gap (we use the term awarding gap over 'attainment gap' as attainment places the responsibility on students to attain at equal levels) and continues to pose a challenge for educational systems across the world. While Learning Analytics (LA) dashboards help identify patterns contributing to the awarding gap, they often lack stakeholder involvement, offering very little support to institutional Equality, Diversity and Inclusion (EDI) leads or educators to pinpoint and address these gaps. This paper introduces an innovative EDI LA dashboard, co-created with diverse stakeholders. Rigorously evaluated, the dashboard provides fine-grained insights and course-level analysis, empowering institutions to effectively address awarding gaps and contribute to a diverse and inclusive higher education landscape.
Published: 2024
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17. National Guard Youth Challenge Program: Actions Needed to Enhance Oversight and Assess Performance. Report to Congressional Committees. GAO-24-106172

Author: US Government Accountability Office (GAO) and Farrell, Brenda S.
Abstract: Since its inception in 1993, the National Guard Youth Challenge Program has produced over 200,000 graduates across dozens of sites located in the states, the District of Columbia, and Puerto Rico. Currently, the program operates 39 sites. House Report 117-88, accompanying the Department of Defense Appropriations Bill for Fiscal Year 2022, included a provision for the Government Accountability Office (GAO) to review the National Guard Youth Challenge Program, including its implementation and oversight. This report describes (1) how selected sites implemented core program components, and examines the extent to which the Office of the Secretary of Defense (OSD) and the National Guard Bureau (NGB) have (2) conducted oversight of the Challenge Program and (3) assessed its performance, among other objectives. GAO reviewed program policies, inspections, and audits; surveyed program officials at a nongeneralizable sample of 13 sites; and interviewed OSD, NGB, and site officials.
Published: 2023

18. Non-coding RNA yREX3 from human extracellular vesicles exerts macrophage-mediated cardioprotection via a novel gene-methylating mechanism.

Author: Ciullo, Alessandra, Li, Liang, Li, Chang, Tsi, Kara, Farrell, Colin, Pellegrini, Matteo, Marbán, Eduardo, and Ibrahim, Ahmed
Subjects: Efferocytosis, Inflammation, Macrophages, Myocardial infarction, Pick1, Small non-coding RNA, Extracellular Vesicles, Macrophages, Animals, Humans, DNA Methylation, Carrier Proteins, Myocardial Infarction, Nuclear Proteins, Rats, RNA, Long Noncoding, Male
Abstract: BACKGROUND AND AIMS: Extracellular vesicles (EVs) secreted by cardiosphere-derived cells exert immunomodulatory effects through the transmission of small non-coding RNAs. METHODS: The mechanism and role of yREX3, a small Y RNA abundant in EVs in myocardial injury, was investigated. RESULTS: yREX3 attenuates cardiac ischaemic injury by selective DNA methylation. Synthetic yREX3 encapsulated in lipid nanoparticles triggers broad transcriptomic changes in macrophages, localizes to the nucleus, and mediates epigenetic silencing of protein interacting with C kinase-1 (Pick1) through methylation of upstream CpG sites. Moreover, yREX3 interacts with polypyrimidine tract binding protein 3 (PTBP3) to methylate the Pick1 gene locus in a DNA methyltransferase-dependent manner. Suppression of Pick1 in macrophages potentiates Smad3 signalling and enhances efferocytosis, minimizing heart necrosis in rats with myocardial infarction. Adoptive transfer of Pick1-deficient macrophages recapitulates the cardioprotective effects of yREX3 in vivo. CONCLUSIONS: These findings highlight the role of a small Y RNA mined from EVs with a novel gene-methylating mechanism.
Published: 2024

19. Universal corrections to the superfluid gap in a cold Fermi gas

Author: Beane, Silas R., Capatti, Zeno, and Farrell, Roland C.
Subjects: Nuclear Theory, Condensed Matter - Quantum Gases, Condensed Matter - Superconductivity, High Energy Physics - Phenomenology
Abstract: A framework for computing the superfluid gap in an effective field theory (EFT) of fermions interacting via momentum-independent contact forces is developed. The leading universal corrections in the EFT are one-loop in-medium effects at the Fermi surface, and reproduce the well-known Gor'kov-Melik-Barkhudarov result. The complete subleading universal corrections are presented here, and include one-loop effects away from the Fermi surface, two-loop in-medium effects, as well as modifications to the fermion propagator. Together, these effects are found to reduce the gap at low densities. Applications to neutron superfluidity in neutron stars are also discussed., Comment: 10 pages + appendices. 10 figures
Published: 2024

20. Nonlinear Binscatter Methods

Author: Cattaneo, Matias D., Crump, Richard K., Farrell, Max H., and Feng, Yingjie
Subjects: Statistics - Methodology, Economics - Econometrics, Mathematics - Statistics Theory
Abstract: Binned scatter plots are a powerful statistical tool for empirical work in the social, behavioral, and biomedical sciences. Available methods rely on a quantile-based partitioning estimator of the conditional mean regression function to primarily construct flexible yet interpretable visualization methods, but they can also be used to estimate treatment effects, assess uncertainty, and test substantive domain-specific hypotheses. This paper introduces novel binscatter methods based on nonlinear, possibly nonsmooth M-estimation methods, covering generalized linear, robust, and quantile regression models. We provide a host of theoretical results and practical tools for local constant estimation along with piecewise polynomial and spline approximations, including (i) optimal tuning parameter (number of bins) selection, (ii) confidence bands, and (iii) formal statistical tests regarding functional form or shape restrictions. Our main results rely on novel strong approximations for general partitioning-based estimators covering random, data-driven partitions, which may be of independent interest. We demonstrate our methods with an empirical application studying the relation between the percentage of individuals without health insurance and per capita income at the zip-code level. We provide general-purpose software packages implementing our methods in Python, R, and Stata.
Published: 2024

21. Optimization-Based Outlier Accommodation for Tightly Coupled RTK-Aided Inertial Navigation Systems in Urban Environments

Author: Hu, Wang, Hu, Yingjie, Stas, Mike, and Farrell, Jay A.
Subjects: Computer Science - Robotics, Electrical Engineering and Systems Science - Systems and Control
Abstract: Global Navigation Satellite Systems (GNSS) aided Inertial Navigation System (INS) is a fundamental approach for attaining continuously available absolute vehicle position and full state estimates at high bandwidth. For transportation applications, stated accuracy specifications must be achieved, unless the navigation system can detect when it is violated. In urban environments, GNSS measurements are susceptible to outliers, which motivates the important problem of accommodating outliers while either achieving a performance specification or communicating that it is not feasible. Risk-Averse Performance-Specified (RAPS) is designed to optimally select measurements to address this problem. Existing RAPS approaches lack a method applicable to carrier phase measurements, which have the benefit of measurement errors at the centimeter level along with the challenge of being biased by integer ambiguities. This paper proposes a RAPS framework that combines Real-time Kinematic (RTK) in a tightly coupled INS for urban navigation applications. Experimental results demonstrate the effectiveness of this RAPS-INS-RTK framework, achieving 85.84% and 92.07% of horizontal and vertical errors less than 1.5 meters and 3 meters, respectively, using a smartphone-grade Inertial Measurement Unit (IMU) from a deep-urban dataset. This performance not only surpasses the Society of Automotive Engineers (SAE) requirements, but also shows a 10% improvement compared to traditional methods., Comment: 8 pages, 2 figures. accepted by the 27th IEEE International Conference on Intelligent Transportation Systems (IEEE ITSC 2024)
Published: 2024

22. High-order conservative and accurately dissipative numerical integrators via auxiliary variables

Author: Andrews, Boris D. and Farrell, Patrick E.
Subjects: Mathematics - Numerical Analysis, 65M60 (Primary) 65L05, 65P10 (Secondary)
Abstract: Numerical methods for the simulation of transient systems with structure-preserving properties are known to exhibit greater accuracy and physical reliability, in particular over long durations. These schemes are often built on powerful geometric ideas for broad classes of problems, such as Hamiltonian or reversible systems. However, there remain difficulties in devising timestepping schemes that conserve non-quadratic invariants or dissipation laws. In this work, we propose an approach for the construction of timestepping schemes that preserve dissipation laws and conserve multiple general invariants, via finite elements in time and the systematic introduction of auxiliary variables. The approach generalises several existing ideas in the literature, including Gauss methods, the framework of Cohen & Hairer, and the energy- and helicity-conserving scheme of Rebholz. We demonstrate the ideas by devising novel arbitrary-order schemes that conserve to machine precision all known invariants of Hamiltonian ODEs, including the Kepler and Kovalevskaya problems, and arbitrary-order schemes for the compressible Navier-Stokes equations that conserve mass, momentum, and energy, and provably possess non-decreasing entropy., Comment: 63 pages, 13 figures
Published: 2024

23. Supernova Pointing Capabilities of DUNE

Author: DUNE Collaboration, Abud, A. Abed, Abi, B., Acciarri, R., Acero, M. A., Adames, M. R., Adamov, G., Adamowski, M., Adams, D., Adinolfi, M., Adriano, C., Aduszkiewicz, A., Aguilar, J., Aimard, B., Akbar, F., Allison, K., Monsalve, S. Alonso, Alrashed, M., Alton, A., Alvarez, R., Alves, T., Amar, H., Amedo, P., Anderson, J., Andrade, D. A., Andreopoulos, C., Andreotti, M., Andrews, M. P., Andrianala, F., Andringa, S., Anfimov, N., Ankowski, A., Antoniassi, M., Antonova, M., Antoshkin, A., Aranda-Fernandez, A., Arellano, L., Diaz, E. Arrieta, Arroyave, M. A., Asaadi, J., Ashkenazi, A., Asner, D., Asquith, L., Atkin, E., Auguste, D., Aurisano, A., Aushev, V., Autiero, D., Azfar, F., Back, A., Back, H., Back, J. J., Bagaturia, I., Bagby, L., Balashov, N., Balasubramanian, S., Baldi, P., Baldini, W., Baldonedo, J., Baller, B., Bambah, B., Banerjee, R., Barao, F., Barenboim, G., Alzás, P. Barham, Barker, G. J., Barkhouse, W., Barr, G., Monarca, J. Barranco, Barros, A., Barros, N., Barrow, D., Barrow, J. L., Basharina-Freshville, A., Bashyal, A., Basque, V., Batchelor, C., Bathe-Peters, L., Battat, J. B. R., Battisti, F., Bay, F., Bazetto, M. C. Q., Alba, J. L. L. Bazo, Beacom, J. F., Bechetoille, E., Behera, B., Belchior, E., Bell, G., Bellantoni, L., Bellettini, G., Bellini, V., Beltramello, O., Benekos, N., Montiel, C. Benitez, Benjamin, D., Neves, F. Bento, Berger, J., Berkman, S., Bernal, J., Bernardini, P., Bersani, A., Bertolucci, S., Betancourt, M., Rodríguez, A. Betancur, Bevan, A., Bezawada, Y., Bezerra, A. T., Bezerra, T. J., Bhat, A., Bhatnagar, V., Bhatt, J., Bhattacharjee, M., Bhattacharya, M., Bhuller, S., Bhuyan, B., Biagi, S., Bian, J., Biery, K., Bilki, B., Bishai, M., Bitadze, A., Blake, A., Blaszczyk, F. D., Blazey, G. C., Blucher, E., Bogenschuetz, J., Boissevain, J., Bolognesi, S., Bolton, T., Bomben, L., Bonesini, M., Bonilla-Diaz, C., Bonini, F., Booth, A., Boran, F., Bordoni, S., Merlo, R. Borges, Borkum, A., Bostan, N., Bracinik, J., Braga, D., Brahma, B., Brailsford, D., Bramati, F., Branca, A., Brandt, A., Bremer, J., Brew, C., Brice, S. J., Brio, V., Brizzolari, C., Bromberg, C., Brooke, J., Bross, A., Brunetti, G., Brunetti, M., Buchanan, N., Budd, H., Buergi, J., Burgardt, D., Butchart, S., V., G. Caceres, Cagnoli, I., Cai, T., Calabrese, R., Calcutt, J., Calin, M., Calivers, L., Calvo, E., Caminata, A., Camino, A. F., Campanelli, W., Campani, A., Benitez, A. Campos, Canci, N., Capó, J., Caracas, I., Caratelli, D., Carber, D., Carceller, J. M., Carini, G., Carlus, B., Carneiro, M. F., Carniti, P., Terrazas, I. Caro, Carranza, H., Carrara, N., Carroll, L., Carroll, T., Carter, A., Casarejos, E., Casazza, D., Forero, J. F. Castaño, Castaño, F. A., Castillo, A., Castromonte, C., Catano-Mur, E., Cattadori, C., Cavalier, F., Cavanna, F., Centro, S., Cerati, G., Cerna, C., Cervelli, A., Villanueva, A. Cervera, Chakraborty, K., Chakraborty, S., Chalifour, M., Chappell, A., Charitonidis, N., Chatterjee, A., Chen, H., Chen, M., Chen, W. C., Chen, Y., Chen-Wishart, Z., Cherdack, D., Chi, C., Chiapponi, F., Chirco, R., Chitirasreemadam, N., Cho, K., Choate, S., Chokheli, D., Chong, P. S., Chowdhury, B., Christian, D., Chukanov, A., Chung, M., Church, E., Cicala, M. F., Cicerchia, M., Cicero, V., Ciolini, R., Clarke, P., Cline, G., Coan, T. E., Cocco, A. G., Coelho, J. A. B., Cohen, A., Collazo, J., Collot, J., Conley, E., Conrad, J. M., Convery, M., Copello, S., Cova, P., Cox, C., Cremaldi, L., Cremonesi, L., Crespo-Anadón, J. I., Crisler, M., Cristaldo, E., Crnkovic, J., Crone, G., Cross, R., Cudd, A., Cuesta, C., Cui, Y., Curciarello, F., Cussans, D., Dai, J., Dalager, O., Dallavalle, R., Dallaway, W., da Motta, H., Dar, Z. A., Darby, R., Peres, L. Da Silva, David, Q., Davies, G. S., Davini, S., Dawson, J., De Aguiar, R., De Almeida, P., Debbins, P., De Bonis, I., Decowski, M. P., de Gouvêa, A., De Holanda, P. C., Astiz, I. L. De Icaza, De Jong, P., Sanchez, P. Del Amo, De la Torre, A., De Lauretis, G., Delbart, A., Delepine, D., Delgado, M., Dell'Acqua, A., Monache, G. Delle, Delmonte, N., De Lurgio, P., Demario, R., De Matteis, G., Neto, J. R. T. de Mello, DeMuth, D. M., Dennis, S., Densham, C., Denton, P., Deptuch, G. W., De Roeck, A., De Romeri, V., Detje, J. P., Devine, J., Dharmapalan, R., Dias, M., Diaz, A., Díaz, J. S., Díaz, F., Di Capua, F., Di Domenico, A., Di Domizio, S., Di Falco, S., Di Giulio, L., Ding, P., Di Noto, L., Diociaiuti, E., Distefano, C., Diurba, R., Diwan, M., Djurcic, Z., Doering, D., Dolan, S., Dolek, F., Dolinski, M. J., Domenici, D., Domine, L., Donati, S., Donon, Y., Doran, S., Douglas, D., Doyle, T. A., Dragone, A., Drielsma, F., Duarte, L., Duchesneau, D., Duffy, K., Dugas, K., Dunne, P., Dutta, B., Duyang, H., Dwyer, D. A., Dyshkant, A. S., Dytman, S., Eads, M., Earle, A., Edayath, S., Edmunds, D., Eisch, J., Englezos, P., Ereditato, A., Erjavec, T., Escobar, C. O., Evans, J. J., Ewart, E., Ezeribe, A. C., Fahey, K., Fajt, L., Falcone, A., Fani', M., Farnese, C., Farrell, S., Farzan, Y., Fedoseev, D., Felix, J., Feng, Y., Fernandez-Martinez, E., Ferry, G., Fields, L., Filip, P., Filkins, A., Filthaut, F., Fine, R., Fiorillo, G., Fiorini, M., Fogarty, S., Foreman, W., Fowler, J., Franc, J., Francis, K., Franco, D., Franklin, J., Freeman, J., Fried, J., Friedland, A., Fuess, S., Furic, I. K., Furman, K., Furmanski, A. P., Gaba, R., Gabrielli, A., Gago, A. M, Galizzi, F., Gallagher, H., Gallas, A., Gallice, N., Galymov, V., Gamberini, E., Gamble, T., Ganacim, F., Gandhi, R., Ganguly, S., Gao, F., Gao, S., Garcia-Gamez, D., García-Peris, M. Á., Gardim, F., Gardiner, S., Gastler, D., Gauch, A., Gauvreau, J., Gauzzi, P., Gazzana, S., Ge, G., Geffroy, N., Gelli, B., Gent, S., Gerlach, L., Ghorbani-Moghaddam, Z., Giammaria, T., Gibin, D., Gil-Botella, I., Gilligan, S., Gioiosa, A., Giovannella, S., Girerd, C., Giri, A. K., Giugliano, C., Giusti, V., Gnani, D., Gogota, O., Gollapinni, S., Gollwitzer, K., Gomes, R. A., Bermeo, L. V. Gomez, Fajardo, L. S. Gomez, Gonnella, F., Gonzalez-Diaz, D., Gonzalez-Lopez, M., Goodman, M. C., Goswami, S., Gotti, C., Goudeau, J., Goudzovski, E., Grace, C., Gramellini, E., Gran, R., Granados, E., Granger, P., Grant, C., Gratieri, D. R., Grauso, G., Green, P., Greenberg, S., Greer, J., Griffith, W. C., Groetschla, F. T., Grzelak, K., Gu, L., Gu, W., Guarino, V., Guarise, M., Guenette, R., Guerard, E., Guerzoni, M., Guffanti, D., Guglielmi, A., Guo, B., Guo, Y., Gupta, A., Gupta, V., Gurung, G., Gutierrez, D., Guzowski, P., Guzzo, M. M., Gwon, S., Habig, A., Hadavand, H., Haegel, L., Haenni, R., Hagaman, L., Hahn, A., Haiston, J., Hakenmüller, J., Hamernik, T., Hamilton, P., Hancock, J., Happacher, F., Harris, D. A., Hartnell, J., Hartnett, T., Harton, J., Hasegawa, T., Hasnip, C., Hatcher, R., Hayrapetyan, K., Hays, J., Hazen, E., He, M., Heavey, A., Heeger, K. M., Heise, J., Henry, S., Morquecho, M. A. Hernandez, Herner, K., Hewes, V., Higuera, A., Hilgenberg, C., Hillier, S. J., Himmel, A., Hinkle, E., Hirsch, L. R., Ho, J., Hoff, J., Holin, A., Holvey, T., Hoppe, E., Horiuchi, S., Horton-Smith, G. A., Hostert, M., Houdy, T., Howard, B., Howell, R., Hristova, I., Hronek, M. S., Huang, J., Huang, R. G., Hulcher, Z., Ibrahim, M., Iles, G., Ilic, N., Iliescu, A. M., Illingworth, R., Ingratta, G., Ioannisian, A., Irwin, B., Isenhower, L., Oliveira, M. Ismerio, Itay, R., Jackson, C. M., Jain, V., James, E., Jang, W., Jargowsky, B., Jena, D., Jentz, I., Ji, X., Jiang, C., Jiang, J., Jiang, L., Jipa, A., Joaquim, F. R., Johnson, W., Jollet, C., Jones, B., Jones, R., Fernández, D. José, Jovancevic, N., Judah, M., Jung, C. K., Junk, T., Jwa, Y., Kabirnezhad, M., Kaboth, A. C., Kadenko, I., Kakorin, I., Kalitkina, A., Kalra, D., Kandemir, M., Kaplan, D. M., Karagiorgi, G., Karaman, G., Karcher, A., Karyotakis, Y., Kasai, S., Kasetti, S. P., Kashur, L., Katsioulas, I., Kauther, A., Kazaryan, N., Ke, L., Kearns, E., Keener, P. T., Kelly, K. J., Kemp, E., Kemularia, O., Kermaidic, Y., Ketchum, W., Kettell, S. H., Khabibullin, M., Khan, N., Khvedelidze, A., Kim, D., Kim, J., King, B., Kirby, B., Kirby, M., Kish, A., Klein, J., Kleykamp, J., Klustova, A., Kobilarcik, T., Koch, L., Koehler, K., Koerner, L. W., Koh, D. H., Kolupaeva, L., Korablev, D., Kordosky, M., Kosc, T., Kose, U., Kostelecký, V. A., Kothekar, K., Kotler, I., Kovalcuk, M., Kozhukalov, V., Krah, W., Kralik, R., Kramer, M., Kreczko, L., Krennrich, F., Kreslo, I., Kroupova, T., Kubota, S., Kubu, M., Kudenko, Y., Kudryavtsev, V. A., Kufatty, G., Kuhlmann, S., Kumar, J., Kumar, P., Kumaran, S., Kunze, P., Kunzmann, J., Kuravi, R., Kurita, N., Kuruppu, C., Kus, V., Kutter, T., Kvasnicka, J., Labree, T., Lackey, T., Lambert, A., Land, B. J., Lane, C. E., Lane, N., Lang, K., Langford, T., Langstaff, M., Lanni, F., Lantwin, O., Larkin, J., Lasorak, P., Last, D., Laudrain, A., Laundrie, A., Laurenti, G., Lavaut, E., Lawrence, A., Laycock, P., Lazanu, I., Lazzaroni, M., Le, T., Leardini, S., Learned, J., LeCompte, T., Lee, C., Legin, V., Miotto, G. Lehmann, Lehnert, R., de Oliveira, M. A. Leigui, Leitner, M., Silverio, D. Leon, Lepin, L. M., Li, J. -Y, Li, S. W., Li, Y., Liao, H., Lin, C. S., Lindebaum, D., Linden, S., Lineros, R. A., Ling, J., Lister, A., Littlejohn, B. R., Liu, H., Liu, J., Liu, Y., Lockwitz, S., Lokajicek, M., Lomidze, I., Long, K., Lopes, T. V., Lopez, J., de Rego, I. López, López-March, N., Lord, T., LoSecco, J. M., Louis, W. C., Sanchez, A. Lozano, Lu, X. -G., Luk, K. B., Lunday, B., Luo, X., Luppi, E., Maalmi, J., MacFarlane, D., Machado, A. A., Machado, P., Macias, C. T., Macier, J. R., MacMahon, M., Maddalena, A., Madera, A., Madigan, P., Magill, S., Magueur, C., Mahn, K., Maio, A., Major, A., Majumdar, K., Man, M., Mandujano, R. C., Maneira, J., Manly, S., Mann, A., Manolopoulos, K., Plata, M. Manrique, Corchado, S. Manthey, Manyam, V. N., Marchan, M., Marchionni, A., Marciano, W., Marfatia, D., Mariani, C., Maricic, J., Marinho, F., Marino, A. D., Markiewicz, T., Marques, F. Das Chagas, Marquet, C., Marsden, D., Marshak, M., Marshall, C. M., Marshall, J., Martina, L., Martín-Albo, J., Martinez, N., Caicedo, D. A. Martinez, López, F. Martínez, Miravé, P. Martínez, Martynenko, S., Mascagna, V., Massari, C., Mastbaum, A., Matichard, F., Matsuno, S., Matteucci, G., Matthews, J., Mauger, C., Mauri, N., Mavrokoridis, K., Mawby, I., Mazza, R., Mazzacane, A., McAskill, T., McConkey, N., McFarland, K. S., McGrew, C., McNab, A., Meazza, L., Meddage, V. C. N., Mehta, B., Mehta, P., Melas, P., Mena, O., Mendez, H., Mendez, P., Méndez, D. P., Menegolli, A., Meng, G., Mercuri, A. C. E. A., Meregaglia, A., Messier, M. D., Metallo, S., Metcalf, J., Metcalf, W., Mewes, M., Meyer, H., Miao, T., Miccoli, A., Michna, G., Mikola, V., Milincic, R., Miller, F., Miller, G., Miller, W., Mineev, O., Minotti, A., Miralles, L., Miranda, O. G., Mironov, C., Miryala, S., Miscetti, S., Mishra, C. S., Mishra, S. R., Mislivec, A., Mitchell, M., Mladenov, D., Mocioiu, I., Mogan, A., Moggi, N., Mohanta, R., Mohayai, T. A., Mokhov, N., Molina, J., Bueno, L. Molina, Montagna, E., Montanari, A., Montanari, C., Montanari, D., Montanino, D., Zetina, L. M. Montaño, Mooney, M., Moor, A. F., Moore, Z., Moreno, D., Moreno-Palacios, O., Morescalchi, L., Moretti, D., Moretti, R., Morris, C., Mossey, C., Mote, M., Moura, C. A., Mouster, G., Mu, W., Mualem, L., Mueller, J., Muether, M., Muheim, F., Muir, A., Mulhearn, M., Munford, D., Munteanu, L. J., Muramatsu, H., Muraz, J., Murphy, M., Murphy, T., Muse, J., Mytilinaki, A., Nachtman, J., Nagai, Y., Nagu, S., Nandakumar, R., Naples, D., Narita, S., Nath, A., Navrer-Agasson, A., Nayak, N., Nebot-Guinot, M., Nehm, A., Nelson, J. K., Neogi, O., Nesbit, J., Nessi, M., Newbold, D., Newcomer, M., Nichol, R., Nicolas-Arnaldos, F., Nikolica, A., Nikolov, J., Niner, E., Nishimura, K., Norman, A., Norrick, A., Novella, P., Nowak, J. A., Oberling, M., Ochoa-Ricoux, J. P., Oh, S., Oh, S. B., Olivier, A., Olshevskiy, A., Olson, T., Onel, Y., Onishchuk, Y., Oranday, A., Osbiston, M., Vélez, J. A. Osorio, Ormachea, L. Otiniano, Ott, J., Pagani, L., Palacio, G., Palamara, O., Palestini, S., Paley, J. M., Pallavicini, M., Palomares, C., Pan, S., Panda, P., Vazquez, W. Panduro, Pantic, E., Paolone, V., Papadimitriou, V., Papaleo, R., Papanestis, A., Papoulias, D., Paramesvaran, S., Paris, A., Parke, S., Parozzi, E., Parsa, S., Parsa, Z., Parveen, S., Parvu, M., Pasciuto, D., Pascoli, S., Pasqualini, L., Pasternak, J., Patrick, C., Patrizii, L., Patterson, R. B., Patzak, T., Paudel, A., Paulucci, L., Pavlovic, Z., Pawloski, G., Payne, D., Pec, V., Pedreschi, E., Peeters, S. J. M., Pellico, W., Perez, A. Pena, Pennacchio, E., Penzo, A., Peres, O. L. G., Gonzalez, Y. F. Perez, Pérez-Molina, L., Pernas, C., Perry, J., Pershey, D., Pessina, G., Petrillo, G., Petta, C., Petti, R., Pfaff, M., Pia, V., Pickering, L., Pietropaolo, F., Pimentel, V. L., Pinaroli, G., Pinchault, J., Pitts, K., Plows, K., Plunkett, R., Pollack, C., Pollman, T., Polo-Toledo, D., Pompa, F., Pons, X., Poonthottathil, N., Popov, V., Poppi, F., Porter, J., Potekhin, M., Potenza, R., Pozimski, J., Pozzato, M., Prakash, T., Pratt, C., Prest, M., Psihas, F., Pugnere, D., Qian, X., Queen, J., Raaf, J. L., Radeka, V., Rademacker, J., Radics, B., Rafique, A., Raguzin, E., Rai, M., Rajagopalan, S., Rajaoalisoa, M., Rakhno, I., Rakotondravohitra, L., Ralte, L., Delgado, M. A. Ramirez, Ramson, B., Rappoldi, A., Raselli, G., Ratoff, P., Ray, R., Razafinime, H., Rea, E. M., Real, J. S., Rebel, B., Rechenmacher, R., Reggiani-Guzzo, M., Reichenbacher, J., Reitzner, S. D., Sfar, H. Rejeb, Renner, E., Renshaw, A., Rescia, S., Resnati, F., Restrepo, Diego, Reynolds, C., Ribas, M., Riboldi, S., Riccio, C., Riccobene, G., Ricol, J. S., Rigan, M., Rincón, E. V., Ritchie-Yates, A., Ritter, S., Rivera, D., Rivera, R., Robert, A., Rocha, J. L. Rocabado, Rochester, L., Roda, M., Rodrigues, P., Alonso, M. J. Rodriguez, Roeth, A. J., Rondon, J. Rodriguez, Rosauro-Alcaraz, S., Rosier, P., Ross, D., Rossella, M., Rossi, M., Ross-Lonergan, M., Roy, N., Roy, P., Rubbia, C., Ruggeri, A., Ferreira, G. Ruiz, Russell, B., Ruterbories, D., Rybnikov, A., Saa-Hernandez, A., Saakyan, R., Sacerdoti, S., Sahoo, S. K., Sahu, N., Sala, P., Samios, N., Samoylov, O., Sanchez, M. C., Bravo, A. Sánchez, Sanchez-Lucas, P., Sandberg, V., Sanders, D. A., Sanfilippo, S., Sankey, D., Santoro, D., Saoulidou, N., Sapienza, P., Sarasty, C., Sarcevic, I., Sarra, I., Savage, G., Savinov, V., Scanavini, G., Scaramelli, A., Scarff, A., Schefke, T., Schellman, H., Schifano, S., Schlabach, P., Schmitz, D., Schneider, A. W., Scholberg, K., Schukraft, A., Schuld, B., Segade, A., Segreto, E., Selyunin, A., Senise, C. R., Sensenig, J., Shaevitz, M. H., Shanahan, P., Sharma, P., Kumar, R., Shaw, K., Shaw, T., Shchablo, K., Shen, J., Shepherd-Themistocleous, C., Sheshukov, A., Shi, W., Shin, S., Shivakoti, S., Shoemaker, I., Shooltz, D., Shrock, R., Siddi, B., Siden, M., Silber, J., Simard, L., Sinclair, J., Sinev, G., Singh, Jaydip, Singh, J., Singh, L., Singh, P., Singh, V., Chauhan, S. Singh, Sipos, R., Sironneau, C., Sirri, G., Siyeon, K., Skarpaas, K., Smedley, J., Smith, E., Smith, J., Smith, P., Smolik, J., Smy, M., Snape, M., Snider, E. L., Snopok, P., Snowden-Ifft, D., Nunes, M. Soares, Sobel, H., Soderberg, M., Sokolov, S., Salinas, C. J. Solano, Söldner-Rembold, S., Soleti, S. R., Solomey, N., Solovov, V., Sondheim, W. E., Sorel, M., Sotnikov, A., Soto-Oton, J., Sousa, A., Soustruznik, K., Spinella, F., Spitz, J., Spooner, N. J. C., Spurgeon, K., Stalder, D., Stancari, M., Stanco, L., Steenis, J., Stein, R., Steiner, H. M., Lisbôa, A. F. Steklain, Stepanova, A., Stewart, J., Stillwell, B., Stock, J., Stocker, F., Stokes, T., Strait, M., Strauss, T., Strigari, L., Stuart, A., Suarez, J. G., Subash, J., Surdo, A., Suter, L., Sutera, C. M., Sutton, K., Suvorov, Y., Svoboda, R., Swain, S. K., Szczerbinska, B., Szelc, A. M., Sztuc, A., Taffara, A., Talukdar, N., Tamara, J., Tanaka, H. A., Tang, S., Taniuchi, N., Casanova, A. M. Tapia, Oregui, B. Tapia, Tapper, A., Tariq, S., Tarpara, E., Tatar, E., Tayloe, R., Tedeschi, D., Teklu, A. M., Vidal, J. Tena, Tennessen, P., Tenti, M., Terao, K., Terranova, F., Testera, G., Thakore, T., Thea, A., Thiebault, A., Thomas, S., Thompson, A., Thorn, C., Timm, S. C., Tiras, E., Tishchenko, V., Todorović, N., Tomassetti, L., Tonazzo, A., Torbunov, D., Torti, M., Tortola, M., Tortorici, F., Tosi, N., Totani, D., Toups, M., Touramanis, C., Tran, D., Travaglini, R., Trevor, J., Triller, E., Trilov, S., Truchon, J., Truncali, D., Trzaska, W. H., Tsai, Y., Tsai, Y. -T., Tsamalaidze, Z., Tsang, K. V., Tsverava, N., Tu, S. Z., Tufanli, S., Tunnell, C., Turner, J., Tuzi, M., Tyler, J., Tyley, E., Tzanov, M., Uchida, M. A., González, J. Ureña, Urheim, J., Usher, T., Utaegbulam, H., Uzunyan, S., Vagins, M. R., Vahle, P., Valder, S., Valdiviesso, G. A., Valencia, E., Valentim, R., Vallari, Z., Vallazza, E., Valle, J. W. F., Van Berg, R., Van de Water, R. G., Forero, D. V., Vannozzi, A., Van Nuland-Troost, M., Varanini, F., Oliva, D. Vargas, Vasina, S., Vaughan, N., Vaziri, K., Vázquez-Ramos, A., Vega, J., Ventura, S., Verdugo, A., Vergani, S., Verzocchi, M., Vetter, K., Vicenzi, M., de Souza, H. Vieira, Vignoli, C., Vilela, C., Villa, E., Viola, S., Viren, B., Vizcaya-Hernandez, A., Vrba, T., Vuong, Q., Waldron, A. V., Wallbank, M., Walsh, J., Walton, T., Wang, H., Wang, J., Wang, L., Wang, M. H. L. S., Wang, X., Wang, Y., Warburton, K., Warner, D., Warsame, L., Wascko, M. O., Waters, D., Watson, A., Wawrowska, K., Weber, A., Weber, C. M., Weber, M., Wei, H., Weinstein, A., Wenzel, H., Westerdale, S., Wetstein, M., Whalen, K., Whilhelmi, J., White, A., Whitehead, L. H., Whittington, D., Wilking, M. J., Wilkinson, A., Wilkinson, C., Wilson, F., Wilson, R. J., Winter, P., Wisniewski, W., Wolcott, J., Wolfs, J., Wongjirad, T., Wood, A., Wood, K., Worcester, E., Worcester, M., Wospakrik, M., Wresilo, K., Wret, C., Wu, S., Wu, W., Wurm, M., Wyenberg, J., Xiao, Y., Xiotidis, I., Yaeggy, B., Yahlali, N., Yandel, E., Yang, K., Yang, T., Yankelevich, A., Yershov, N., Yonehara, K., Young, T., Yu, B., Yu, H., Yu, J., Yu, Y., Yuan, W., Zaki, R., Zalesak, J., Zambelli, L., Zamorano, B., Zani, A., Zapata, O., Zazueta, L., Zeller, G. P., Zennamo, J., Zeug, K., Zhang, C., Zhang, S., Zhao, M., Zhivun, E., Zimmerman, E. D., Zucchelli, S., Zuklin, J., Zutshi, V., and Zwaska, R.
Subjects: High Energy Physics - Experiment, Astrophysics - High Energy Astrophysical Phenomena, Astrophysics - Instrumentation and Methods for Astrophysics, Astrophysics - Solar and Stellar Astrophysics, Nuclear Experiment, Physics - Instrumentation and Detectors
Abstract: The determination of the direction of a stellar core collapse via its neutrino emission is crucial for the identification of the progenitor for a multimessenger follow-up. A highly effective method of reconstructing supernova directions within the Deep Underground Neutrino Experiment (DUNE) is introduced. The supernova neutrino pointing resolution is studied by simulating and reconstructing electron-neutrino charged-current absorption on $^{40}$Ar and elastic scattering of neutrinos on electrons. Procedures to reconstruct individual interactions, including a newly developed technique called ``brems flipping'', as well as the burst direction from an ensemble of interactions are described. Performance of the burst direction reconstruction is evaluated for supernovae happening at a distance of 10 kpc for a specific supernova burst flux model. The pointing resolution is found to be 3.4 degrees at 68% coverage for a perfect interaction-channel classification and a fiducial mass of 40 kton, and 6.6 degrees for a 10 kton fiducial mass respectively. Assuming a 4% rate of charged-current interactions being misidentified as elastic scattering, DUNE's burst pointing resolution is found to be 4.3 degrees (8.7 degrees) at 68% coverage., Comment: 25 pages, 16 figures
Published: 2024

24. Physics-informed machine learning approaches to reactor antineutrino detection

Author: Farrell, Sophia, Bergevin, Marc, and Bernstein, Adam
Subjects: Physics - Instrumentation and Detectors, High Energy Physics - Experiment, Physics - Data Analysis, Statistics and Probability
Abstract: Nuclear reactors produce a high flux of MeV-scale antineutrinos that can be observed through inverse beta-decay (IBD) interactions in particle detectors. Reliable detection of reactor IBD signals depends on suppression of backgrounds, both by physical shielding and vetoing and by pattern recognition and rejection in acquired data. A particularly challenging background to reactor antineutrino detection is from cosmogenically induced fast neutrons, which can mimic the characteristics of an IBD signal. In this work, we explore two methods of machine learning -- a tree-based classifier and a graph-convolutional neural network -- to improve rejection of fast neutron-induced background events in a water Cherenkov detector. The tree-based classifier examines classification at the reconstructed feature level, while the graphical network classifies events using only the raw signal data. Both methods improve the sensitivity for a background-dominant search over traditional cut-and-count methods, with the greatest improvement being from the tree-based classification method. These performance enhancements are relevant for reactor monitoring applications that make use of deep underground oil-based or water-based kiloton-scale detectors with multichannel, PMT-based readouts, and they are likely extensible to other similar physics analyses using this class of detector., Comment: 11 pages, 4 figures, for submission to Phys. Rev. Applied
Published: 2024

25. Cyberwar Strategy and Tactics: An Analysis of Cyber Goals, Strategies, Tactics, and Techniques

Author: Tinnel, Laura S., Saydjari, O. Sami, and Farrell, Dave
Subjects: Computer Science - Cryptography and Security
Abstract: Cyberwar strategy and tactics today are primitive and ad-hoc, resulting in an ineffective and reactive cyber fighting force. A Cyberwar Playbook is an encoding of knowledge on how to effectively handle a variety of cyberwar situations. It takes a troubleshooting approach and defines the cyber tactics, techniques and procedures one may employ to counter or avert cyber-based attacks. It provides focus and clarity in time of chaos allowing a clear path of response to be chosen.
Published: 2024

26. Data-Driven Personalized Energy Consumption Range Estimation for Plug-in Hybrid Electric Vehicles in Urban Traffic

Author: Ozkan, Mehmet Fatih, Farrell, James, Telloni, Marcello, Mendez, Luis, Pirvan, Radu, Chrstos, Jeffrey P., Canova, Marcello, and Stockar, Stephanie
Subjects: Electrical Engineering and Systems Science - Systems and Control
Abstract: In urban traffic environments, driver behaviors exhibit considerable diversity in vehicle operation, encompassing a range of acceleration and braking maneuvers as well as adherence to traffic regulations, such as speed limits. It is well-established that these intrinsic driving behaviors significantly influence vehicle energy consumption. Therefore, establishing a quantitative relationship between driver behavior and energy usage is essential for identifying energy-efficient driving practices and optimizing routes within urban traffic. This study introduces a data-driven approach to predict the equivalent fuel consumption of a plug-in hybrid electric vehicle (PHEV) based on an integrated model of driver behavior and vehicle energy consumption. Unlike traditional models that provide point predictions of fuel consumption, this approach uses Conformalized Quantile Regression (CQR) to offer prediction intervals that capture the variability and uncertainty in fuel consumption. These intervals reflect changes in fuel consumption, as well as variations in driver behavior, and vehicle and route conditions. To develop this model, driver-specific data were collected through a driver-in-the-loop simulator, which tested different human drivers responses. The CQR model was then trained and validated using the experimental data from the driver-in-the-loop simulator, augmented by the synthetic data generated from Monte Carlo simulations conducted using a calibrated microscopic driver behavior and vehicle energy model. The CQR model was evaluated by comparing its predictions of equivalent fuel consumption intervals with those of baseline prediction interval methods that rely solely on conformal prediction., Comment: MECC 2024 accepted paper
Published: 2024

27. Steps Toward Quantum Simulations of Hadronization and Energy-Loss in Dense Matter

Author: Farrell, Roland C., Illa, Marc, and Savage, Martin J.
Subjects: Quantum Physics, High Energy Physics - Lattice, High Energy Physics - Phenomenology, Nuclear Theory
Abstract: A framework for simulating the real-time dynamics of particles in dense matter using quantum computers is developed. As a demonstration, we perform classical simulations of heavy-hadrons propagating through a dense medium in the Schwinger model. Measurements of the time-dependent energy and charge density are used to identify mechanisms responsible for energy loss and hadron production (hadronization). A study of entanglement dynamics highlights the importance of quantum coherence between the particles that make up the dense medium. Throughout this work, care is taken to isolate, and remove, phenomena that arise solely from a finite lattice spacing. It is found that signatures of entanglement are more sensitive to lattice artifacts than other observables. Toward quantum simulations, we present an efficient method and the corresponding quantum circuits for preparing ground states in the presence of heavy mesons. These circuits are used to estimate the resources required to simulate in-medium energy loss and hadronization in the Schwinger model using quantum computers., Comment: 22 pages, 10 figures, 3 tables
Published: 2024

28. MCMC inversions of the internal rotation of Kepler subgiants

Author: Buldgen, G., Fellay, L., Bétrisey, J., Deheuvels, S., Farnir, M., and Farrell, E.
Subjects: Astrophysics - Solar and Stellar Astrophysics
Abstract: The measurement of the internal rotation of post-main sequence stars using data from space-based photometry missions has demonstrated the need for an efficient angular momentum transport in stellar interiors. So far, no clear solution has emerged and explaining the observed trends remain a challenge for stellar modellers. We aim at constraining both the shape of the internal rotation profile of six Kepler subgiants studied in details in 2014 and the properties of the missing angular momentum transport process acting in stellar interiors from MCMC inversions of the internal rotation. We apply a new MCMC inversion technique to existing Kepler subgiant targets and test various shapes of the internal rotation profile of all six original subgiants observed in 2014. We also constrain the limitations on the number of free parameters that can be used in the MCMC inversion, showing the limitations in the amount of information in the seismic data. First, we show that large-scale fossil magnetic fields are not able to explain the internal rotation of subgiants, similarly to what was determined from detailed studies of Kepler red giants. We are also able to constrain the location of the transition in the internal rotation profile for the most evolved stars in the available set of subgiants. We find that some of them exhibit a transition located close to the border of the helium core while one clearly does not. We conclude that it might be possible that various processes might be at play to explain our observations, but that revealing the physical nature of the angular momentum process will require a consistent detailed modelling of all subgiants available, particularly the least evolved. In addition, increasing the number of stars for which such inferences are possible (e.g. with the future PLATO mission) is paramount given the key role they play in validating transport process candidates., Comment: Accepted for publication in Astronomy and Astrophysics
Published: 2024

29. Storage of wind power energy: main facts and feasibility − hydrogen as an option

Author: Amarapala Vidya, Darwish Abdul Salam K., and Farrell Peter
Subjects: wind energy storage, hydrogen fuel cell, renewable energy, zero emission, offshore wind energy, net zero, sri lanka, Energy conservation, TJ163.26-163.5, Renewable energy sources, TJ807-830
Abstract: The befalling of natural disasters has been experienced at an alarming level in the last decade due to discharging excessive amounts of CO2 into the atmosphere. The world needs to decarbonise itself sooner than later. To combat environmental impact and the climate change, several key initiatives were taken by countries like the UK, Japan, Europe, and Canada. That includes decarbonising the power sector entirely by bringing in renewable energy in place of fossil fuel on an agreed timeline. Many countries have committed to zero emission by 2050. However, it will not be easy to depend on 100% of renewable energy grid without renewable energy storage capability to assure grid stability. Therefore, this publication's key fundamental objective is to discuss the most suitable energy storage for energy generated by wind. A review of the available storage methods for renewable energy and specifically for possible storage for wind energy is accomplished. Factors that are needed to be considered for storage selection and the requirements are discussed. Wind farm capacity is one of the essential parameters that could affect selection procedures. It is recommended that detailed calculations be made of available energy and the excess power amount to be stored. However, the article discusses the most viable storage options such as liquid metal batteries grid embedded storage for frequency and voltage stability and produces green Hydrogen from surplus wind energy, especially in Sri Lanka.
Published: 2023
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30. High risk and impact factors on construction management process − case study of COVID-19 of a hospital in Iraq

Author: Al-Saffar Mustafa, Darwish Abdul Salam K., and Farrell Peter
Subjects: risk management, covid-19, crisis, hospital construction projects, iraq, Energy conservation, TJ163.26-163.5, Renewable energy sources, TJ807-830
Abstract: The pandemic of COVID-19 crisis suddenly appeared worldwide, and there were no proper crisis management procedures taken in advance to contain such a problem. Moreover, it has had harmful and unmeasured consequences on most life sectors, including construction, which has been severely impacted during the pandemic. This paper aims to review factors with a high-risk impact on hospitals' construction projects during the outbreak of COVID-19 in developing countries by considering the case of Iraq's construction sector. A mixed methodology of qualitative and quantitative research approaches was used. The qualitative method involved (1) a literature review and (2) semi-structured interviews to identify high-risk factors that affect construction projects during the outbreak of COVID-19. The quantitative method involved (1) collecting survey data from 205 industry professionals and experts to determine each risk factor's importance and influence. Cronbach's alpha test to check the reliability of the collected data set, and (3) a fuzzy inference system method was used to assess the impact of each factor on construction projects during the pandemic. The findings of this study indicate that the construction industry has been hit severely during the COVID-19 in Iraq. Moreover, 17 high-risk sub-factors under six main construction factors involve health and safety, risk management, management deficiency, financial, supply chain management and contractual impact hospital construction projects. Furthermore, the most significant risk factors had impacted hospital construction projects by calculating their means were (1) commitment to safety and health recommendations with a level of impact equal to 4.81; (2) risk management procedures with a level of impact equal to 4.63; (3) equipment delivery delays with a level of impact equal to 4.54; (4) worker acceptance of COVID-19 vaccination with a level of impact equal to 4.36; (5) increase of price material with a level of impact equal to 4.18; (6) lack of use of the latest technology with a level of impact equal to 4.09; (7) delay in payments with a level of impact equal to 3.90; and (8) lack of training to deal with the pandemic with a level of impact equal to 3.81. As such, this paper contributes by providing effective policies and measures to mitigate the impact of COVID-19 on hospital construction projects in Iraq.
Published: 2023
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31. Addressing Diversity, Bias, and Racism in Applied Behavior Analysis: Reflective Practices for Behavior Analytic Professionals in Schools

Author: Jonte' C. Taylor, L. Lynn Stansberry Brusnahan, Erin F. Farrell, and Marcus Fuller
Abstract: Students with challenging behaviors can be some of the most vulnerable persons in educational settings when it comes to behavioral analytic practices. The potential for bias and racism influencing behavior analysis is elevated if those observing and evaluating behavior are not cognizant of cultural and societal differences. Behavior professionals should strive for cultural understanding to perform their work in a nonbiased manner. This includes being vigilant in the pursuit of cultural competence and sociopolitical awareness. One vehicle for growth and development in behavior analytic practice is through self-reflection. The current article examines the constructs that can lead to nonbiased and antiracist behavior analysis through self-reflective questioning. In particular, we introduce the self-reflection tools of the ABC Diversity Iceberg, and Multicultural Reflective Behavior Analytic Practice to minimize biases and support antiracism in behavioral observation and analysis.
Published: 2024
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32. Using Mixed Methods to Evaluate Modified Schema-Based Instruction in General Education Classrooms

Author: Jessica A. Bowman, John McDonnell, Karen Karp, Olivia F. Coleman, Carrie Clifton, Lyndsey Aiono Conradi, Joanna Ryan, and Michael Farrell
Abstract: In this convergent mixed methods design study, single-subject and qualitative data were collected concurrently to provide an in-depth picture of the impact of a modified schema-based instructional intervention. The intervention was delivered using instructional trials embedded across general education math lessons and a modified concrete-semi-concrete-abstract instructional sequence. This study investigated the impact of the intervention on the word-problem-solving, strategy use, and concept acquisition of three students with extensive support needs. The paraprofessional-delivered intervention was implemented in elementary general education mathematics classrooms using embedded instruction and focused on teaching students to solve addition and subtraction word-problems. Single-subject data indicated that all three students learned to solve word-problems given concrete materials but needed more time to master the use of semi concrete supports. Qualitative data indicated that students used taught and untaught strategies to solve word-problems, and mastered addition word-problems before subtraction when they were taught simultaneously. Data were integrated in narrative format to explore how strategy use and concept acquisition related to student word-problem-solving performance. Limitations and implications for research are discussed.
Published: 2024
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33. Middle School Staff's Perspectives on the Impact of the Olweus Bullying Prevention Program on Interpersonal Relationships

Author: Melissa Washington-Nortey, Terri N. Sullivan, Rihana Ahm, Jelani Crosby, Albert Farrell, Kevin Sutherland, and Stephanie Hitti
Abstract: The current study used thematic analysis to examine school staff perspectives on the impact of the Olweus Bullying Prevention Program (OBPP) on school climate in terms of the quality of student-student and student-teacher relationships in two low-income, urban middle schools in the United States. Data were collected using focus groups and interviews. Participants included teachers (n = 26), administrators (n = 8), and Bullying Prevention Coordination Committee members (BPCCs; n = 8). Results indicated that providing explicit instruction about bullying, nurturing student-teacher trust by effectively addressing student concerns, and providing consistent opportunities for informal, collaborative engagement facilitated positive school-based interpersonal relationships and behavioral change. Implications for policy and intervention development are discussed.
Published: 2024
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34. Relativistic Brueckner–Hartree–Fock Calculations for Cold and Hot Neutron Stars

Author: Farrell, Delaney and Weber, Fridolin
Subjects: Astronomical Sciences, Physical Sciences, Astronomical and Space Sciences, Atomic, Molecular, Nuclear, Particle and Plasma Physics, Physical Chemistry (incl. Structural), Astronomy & Astrophysics, Astronomical sciences, Particle and high energy physics, Space sciences
Abstract: Abstract: This study investigates the properties of symmetric and asymmetric nuclear matter using the relativistic Brueckner–Hartree–Fock formalism, examining both zero and finite temperatures up to 70 MeV. Employing the full Dirac space, we incorporate three Bonn potentials (A, B, and C), which account for meson masses, coupling strengths, cutoff parameters, and form factors. The calculated properties of asymmetric nuclear matter form the basis for constructing equation-of-state (EOS) models tailored for neutron stars. These models, in turn, enable the computation of bulk properties for nonrotating, uniformly rotating, and differentially rotating neutron stars. Notably, the EOS models studied in this paper are sufficiently versatile to accommodate the mass of the most massive neutron star ever detected, PSR J0952–0607, estimated to be 2.35 ± 0.17 M ⊙. Furthermore, they yield masses and radii for PSR J0030+451 that align with the confidence intervals established for this pulsar.
Published: 2024

35. Mitral Annular Disjunction: An Under-Recognized Entity in Pediatrics.

Author: Alfares, Fahad, Sohn, Jae, Lee, Yoo, Farrell, Rachel, Delling, Francesca, Avasarala, Kishor, Moon-Grady, Anita, Anwar, Shafkat, and Austin, Karyn
Subjects: mitral annular disjunction, mitral valve prolapse, pediatrics, sudden cardiac arrest, ventricular arrhythmia
Abstract: Mitral annular disjunction (MAD) is a rare and under-recognized entity in the pediatric population. We present 2 cases of MAD in previously healthy pediatric patients and highlight clinical scenarios where MAD should be suspected.
Published: 2024

36. Rapidly rotating Population III stellar models as a source of primary nitrogen

Author: Tsiatsiou, Sophie, Sibony, Yves, Nandal, Devesh, Sciarini, Luca, Hirai, Yutaka, Ekstrom, Sylvia, Farrell, Eoin, Murphy, Laura, Choplin, Arthur, Hirschi, Raphael, Chiappini, Cristina, Liu, Boyuan, Bromm, Volker, Groh, Jose, and Meynet, Georges
Subjects: Astrophysics - Solar and Stellar Astrophysics, Astrophysics - Astrophysics of Galaxies
Abstract: The first stars might have been fast rotators. This would have important consequences for their radiative, mechanical and chemical feedback. We discuss the impact of fast initial rotation on the evolution of massive Population III models and on their nitrogen and oxygen stellar yields. We explore the evolution of Population III stars with initial masses in the range of 9Msol < Mini < 120Msol starting with an initial rotation on the Zero Age Main Sequence equal to 70% of the critical one. We find that with the physics of rotation considered here, our rapidly-rotating Population III stellar models do not follow a homogeneous evolution. They lose very little mass in case mechanical winds are switched on when the surface rotation becomes equal or larger than the critical velocity. Impact on the ionising flux appears modest when compared to moderately-rotating models. Fast rotation favours, in models with initial masses above ~20Msol, the appearance of a very extended intermediate convective zone around the H-burning shell during the core He-burning phase. This shell has important consequences on the sizes of the He- and CO-cores and thus impacts the final fate of stars. Moreover, it has a strong impact on nucleosynthesis boosting the production of primary 14N. Fast initial rotation impacts significantly the chemical feedback of Population III stars. Observations of extremely metal-poor stars and/or starbursting regions are essential to provide constraints on the properties of the first stars., Comment: Accepted in A&A. Pages 17. Figures 15. Tables 2
Published: 2024
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37. A method for non-linear inversion of the stellar structure applied to gravity-mode pulsators

Author: Farrell, Eoin, Buldgen, Gaël, Meynet, Georges, Eggenberger, Patrick, Dupret, Marc-Antoine, and Bowman, Dominic M.
Subjects: Astrophysics - Solar and Stellar Astrophysics
Abstract: We present a method for a non-linear asteroseismic inversion suitable for gravity-mode pulsators and apply it to slowly pulsating B-type (SPB) stars. Our inversion method is based on the iterative improvement of a parameterised static stellar structure model, which in turn is based on constraints from the observed oscillation periods. We present tests to demonstrate that the method is successful in recovering the properties of artificial targets both inside and outside the parameter space. We also present a test of our method on the well-studied SPB star KIC 7760680. We believe that this method is promising for carrying out detailed analyses of observations of SPB and $\gamma$ Dor stars and will provide complementary information to evolutionary models., Comment: Accepted in A&A
Published: 2024

38. Forward lateral photovoltage scanning problem: Perturbation approach and existence-uniqueness analysis

Author: Alì, Giuseppe, Farrell, Patricio, and Rotundo, Nella
Subjects: Mathematical Physics
Abstract: In this paper, we present analytical results for the so-called forward lateral photovoltage scanning (LPS) problem. The (inverse) LPS model predicts doping variations in crystal by measuring the current leaving the crystal generated by a laser at various positions. The forward model consists of a set of nonlinear elliptic equations coupled with a measuring device modeled by a resistance. Standard methods to ensure the existence and uniqueness of the forward model cannot be used in a straightforward manner due to the presence of an additional generation term modeling the effect of the laser on the crystal. Hence, we scale the original forward LPS problem and employ a perturbation approach to derive the leading order system and the correction up to the second order in an appropriate small parameter. While these simplifications pose no issues from a physical standpoint, they enable us to demonstrate the analytic existence and uniqueness of solutions for the simplified system using standard arguments from elliptic theory adapted to the coupling with the measuring device.
Published: 2024

39. PyCPL: The ESO Common Pipeline Library in Python v1.0

Author: Deshpande, Mrunmayi S., Lorente, Nuria P. F., Horton, Anthony, Miszalski, Brent, Palsa, Ralf, Lundin, Lars, Heng, Anthony, and Farrell, Aidan
Subjects: Astrophysics - Instrumentation and Methods for Astrophysics
Abstract: PyCPL provides full access to ESO's Common Pipeline Library ( CPL) for astronomical data reduction within a Python environment. Not only does it offer a Python interface to the robust CPL library, but it also lets users and developers fully utilise the rest of the scientific Python ecosystem. We have written a C++ layer to CPL and with pybind11 (a third-party library) created a Pythonic API to CPL. Since CPL has been around for so long, it has been thoroughly tested and understood. In 2003 it was developed in C due to its efficiency and speed of execution. With the community however moving away from C/C++ programming and embracing Python for data processing tasks, there is a need to provide access to the CPL utilities within a Python environment. With the latest version being released users can now install PyCPL to run existing CPL recipes (written in C) and access the results from Python. It also provides the ability to create new recipes in Python using the functionality provided by CPL., Comment: This paper was for a poster presented in ADASS XXXIII. poster number P923
Published: 2024

40. The Active Asteroids Citizen Science Program: Overview and First Results

Author: Chandler, Colin Orion, Trujillo, Chadwick A., Oldroyd, William J., Kueny, Jay K., Burris, William A., Hsieh, Henry H., DeSpain, Jarod A., Sedaghat, Nima, Sheppard, Scott S., Farrell, Kennedy A., Trilling, David E., Gustafsson, Annika, Magbanua, Mark Jesus Mendoza, Mazzucato, Michele T., Bosch, Milton K. D., Shaw-Diaz, Tiffany, Gonano, Virgilio, Lamperti, Al, Campos, José A. da Silva, Goodwin, Brian L., Terentev, Ivan A., Dukes, Charles J. A., and Deen, Sam
Subjects: Astrophysics - Earth and Planetary Astrophysics
Abstract: We present the Citizen Science program Active Asteroids and describe discoveries stemming from our ongoing project. Our NASA Partner program is hosted on the Zooniverse online platform and launched on 2021 August 31, with the goal of engaging the community in the search for active asteroids -- asteroids with comet-like tails or comae. We also set out to identify other unusual active solar system objects, such as active Centaurs, active quasi-Hilda asteroids, and Jupiter-family comets (JFCs). Active objects are rare in large part because they are difficult to identify, so we ask volunteers to assist us in searching for active bodies in our collection of millions of images of known minor planets. We produced these cutout images with our project pipeline that makes use of publicly available Dark Energy Camera (DECam) data. Since the project launch, roughly 8,300 volunteers have scrutinized some 430,000 images to great effect, which we describe in this work. In total we have identified previously unknown activity on 15 asteroids, plus one Centaur, that were thought to be asteroidal (i.e., inactive). Of the asteroids, we classify four as active quasi-Hilda asteroids, seven as JFCs, and four as active asteroids, consisting of one Main-belt comet (MBC) and three MBC candidates. We also include our findings concerning known active objects that our program facilitated, an unanticipated avenue of scientific discovery. These include discovering activity occurring during an orbital epoch for which objects were not known to be active, and the reclassification of objects based on our dynamical analyses., Comment: 35 pages, 5 figures, 3 tables
Published: 2024
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41. A Framework for Strategic Discovery of Credible Neural Network Surrogate Models under Uncertainty

Author: Singh, Pratyush Kumar, Farrell-Maupin, Kathryn A., and Faghihi, Danial
Subjects: Computer Science - Computational Engineering, Finance, and Science, Computer Science - Machine Learning
Abstract: The widespread integration of deep neural networks in developing data-driven surrogate models for high-fidelity simulations of complex physical systems highlights the critical necessity for robust uncertainty quantification techniques and credibility assessment methodologies, ensuring the reliable deployment of surrogate models in consequential decision-making. This study presents the Occam Plausibility Algorithm for surrogate models (OPAL-surrogate), providing a systematic framework to uncover predictive neural network-based surrogate models within the large space of potential models, including various neural network classes and choices of architecture and hyperparameters. The framework is grounded in hierarchical Bayesian inferences and employs model validation tests to evaluate the credibility and prediction reliability of the surrogate models under uncertainty. Leveraging these principles, OPAL-surrogate introduces a systematic and efficient strategy for balancing the trade-off between model complexity, accuracy, and prediction uncertainty. The effectiveness of OPAL-surrogate is demonstrated through two modeling problems, including the deformation of porous materials for building insulation and turbulent combustion flow for the ablation of solid fuels within hybrid rocket motors.
Published: 2024

42. Performance of a modular ton-scale pixel-readout liquid argon time projection chamber

Author: DUNE Collaboration, Abud, A. Abed, Abi, B., Acciarri, R., Acero, M. A., Adames, M. R., Adamov, G., Adamowski, M., Adams, D., Adinolfi, M., Adriano, C., Aduszkiewicz, A., Aguilar, J., Aimard, B., Akbar, F., Allison, K., Monsalve, S. Alonso, Alrashed, M., Alton, A., Alvarez, R., Alves, T., Amar, H., Amedo, P., Anderson, J., Andrade, D. A., Andreopoulos, C., Andreotti, M., Andrews, M. P., Andrianala, F., Andringa, S., Anfimov, N., Ankowski, A., Antoniassi, M., Antonova, M., Antoshkin, A., Aranda-Fernandez, A., Arellano, L., Diaz, E. Arrieta, Arroyave, M. A., Asaadi, J., Ashkenazi, A., Asner, D., Asquith, L., Atkin, E., Auguste, D., Aurisano, A., Aushev, V., Autiero, D., Azfar, F., Back, A., Back, H., Back, J. J., Bagaturia, I., Bagby, L., Balashov, N., Balasubramanian, S., Baldi, P., Baldini, W., Baldonedo, J., Baller, B., Bambah, B., Banerjee, R., Barao, F., Barenboim, G., Alzás, P. Barham, Barker, G. J., Barkhouse, W., Barr, G., Monarca, J. Barranco, Barros, A., Barros, N., Barrow, D., Barrow, J. L., Basharina-Freshville, A., Bashyal, A., Basque, V., Batchelor, C., Bathe-Peters, L., Battat, J. B. R., Battisti, F., Bay, F., Bazetto, M. C. Q., Alba, J. L. L. Bazo, Beacom, J. F., Bechetoille, E., Behera, B., Belchior, E., Bell, G., Bellantoni, L., Bellettini, G., Bellini, V., Beltramello, O., Benekos, N., Montiel, C. Benitez, Benjamin, D., Neves, F. Bento, Berger, J., Berkman, S., Bernal, J., Bernardini, P., Bersani, A., Bertolucci, S., Betancourt, M., Rodríguez, A. Betancur, Bevan, A., Bezawada, Y., Bezerra, A. T., Bezerra, T. J., Bhat, A., Bhatnagar, V., Bhatt, J., Bhattacharjee, M., Bhattacharya, M., Bhuller, S., Bhuyan, B., Biagi, S., Bian, J., Biery, K., Bilki, B., Bishai, M., Bitadze, A., Blake, A., Blaszczyk, F. D., Blazey, G. C., Blucher, E., Bogenschuetz, J., Boissevain, J., Bolognesi, S., Bolton, T., Bomben, L., Bonesini, M., Bonilla-Diaz, C., Bonini, F., Booth, A., Boran, F., Bordoni, S., Merlo, R. Borges, Borkum, A., Bostan, N., Bracinik, J., Braga, D., Brahma, B., Brailsford, D., Bramati, F., Branca, A., Brandt, A., Bremer, J., Brew, C., Brice, S. J., Brio, V., Brizzolari, C., Bromberg, C., Brooke, J., Bross, A., Brunetti, G., Brunetti, M., Buchanan, N., Budd, H., Buergi, J., Burgardt, D., Butchart, S., V., G. Caceres, Cagnoli, I., Cai, T., Calabrese, R., Calcutt, J., Calin, M., Calivers, L., Calvo, E., Caminata, A., Camino, A. F., Campanelli, W., Campani, A., Benitez, A. Campos, Canci, N., Capó, J., Caracas, I., Caratelli, D., Carber, D., Carceller, J. M., Carini, G., Carlus, B., Carneiro, M. F., Carniti, P., Terrazas, I. Caro, Carranza, H., Carrara, N., Carroll, L., Carroll, T., Carter, A., Casarejos, E., Casazza, D., Forero, J. F. Castaño, Castaño, F. A., Castillo, A., Castromonte, C., Catano-Mur, E., Cattadori, C., Cavalier, F., Cavanna, F., Centro, S., Cerati, G., Cerna, C., Cervelli, A., Villanueva, A. Cervera, Chakraborty, K., Chakraborty, S., Chalifour, M., Chappell, A., Charitonidis, N., Chatterjee, A., Chen, H., Chen, M., Chen, W. C., Chen, Y., Chen-Wishart, Z., Cherdack, D., Chi, C., Chirco, R., Chitirasreemadam, N., Cho, K., Choate, S., Chokheli, D., Chong, P. S., Chowdhury, B., Christian, D., Chukanov, A., Chung, M., Church, E., Cicala, M. F., Cicerchia, M., Cicero, V., Ciolini, R., Clarke, P., Cline, G., Coan, T. E., Cocco, A. G., Coelho, J. A. B., Cohen, A., Collazo, J., Collot, J., Conley, E., Conrad, J. M., Convery, M., Copello, S., Cova, P., Cox, C., Cremaldi, L., Cremonesi, L., Crespo-Anadón, J. I., Crisler, M., Cristaldo, E., Crnkovic, J., Crone, G., Cross, R., Cudd, A., Cuesta, C., Cui, Y., Curciarello, F., Cussans, D., Dai, J., Dalager, O., Dallavalle, R., Dallaway, W., da Motta, H., Dar, Z. A., Darby, R., Peres, L. Da Silva, David, Q., Davies, G. S., Davini, S., Dawson, J., De Aguiar, R., De Almeida, P., Debbins, P., De Bonis, I., Decowski, M. P., de Gouvêa, A., De Holanda, P. C., Astiz, I. L. De Icaza, De Jong, P., Sanchez, P. Del Amo, De la Torre, A., De Lauretis, G., Delbart, A., Delepine, D., Delgado, M., Dell'Acqua, A., Monache, G. Delle, Delmonte, N., De Lurgio, P., Demario, R., De Matteis, G., Neto, J. R. T. de Mello, DeMuth, D. M., Dennis, S., Densham, C., Denton, P., Deptuch, G. W., De Roeck, A., De Romeri, V., Detje, J. P., Devine, J., Dharmapalan, R., Dias, M., Diaz, A., Díaz, J. S., Díaz, F., Di Capua, F., Di Domenico, A., Di Domizio, S., Di Falco, S., Di Giulio, L., Ding, P., Di Noto, L., Diociaiuti, E., Distefano, C., Diurba, R., Diwan, M., Djurcic, Z., Doering, D., Dolan, S., Dolek, F., Dolinski, M. J., Domenici, D., Domine, L., Donati, S., Donon, Y., Doran, S., Douglas, D., Doyle, T. A., Dragone, A., Drielsma, F., Duarte, L., Duchesneau, D., Duffy, K., Dugas, K., Dunne, P., Dutta, B., Duyang, H., Dwyer, D. A., Dyshkant, A. S., Dytman, S., Eads, M., Earle, A., Edayath, S., Edmunds, D., Eisch, J., Englezos, P., Ereditato, A., Erjavec, T., Escobar, C. O., Evans, J. J., Ewart, E., Ezeribe, A. C., Fahey, K., Fajt, L., Falcone, A., Fani', M., Farnese, C., Farrell, S., Farzan, Y., Fedoseev, D., Felix, J., Feng, Y., Fernandez-Martinez, E., Ferry, G., Fields, L., Filip, P., Filkins, A., Filthaut, F., Fine, R., Fiorillo, G., Fiorini, M., Fogarty, S., Foreman, W., Fowler, J., Franc, J., Francis, K., Franco, D., Franklin, J., Freeman, J., Fried, J., Friedland, A., Fuess, S., Furic, I. K., Furman, K., Furmanski, A. P., Gaba, R., Gabrielli, A., Gago, A. M., Galizzi, F., Gallagher, H., Gallas, A., Gallice, N., Galymov, V., Gamberini, E., Gamble, T., Ganacim, F., Gandhi, R., Ganguly, S., Gao, F., Gao, S., Garcia-Gamez, D., García-Peris, M. Á., Gardim, F., Gardiner, S., Gastler, D., Gauch, A., Gauvreau, J., Gauzzi, P., Gazzana, S., Ge, G., Geffroy, N., Gelli, B., Gent, S., Gerlach, L., Ghorbani-Moghaddam, Z., Giammaria, T., Gibin, D., Gil-Botella, I., Gilligan, S., Gioiosa, A., Giovannella, S., Girerd, C., Giri, A. K., Giugliano, C., Giusti, V., Gnani, D., Gogota, O., Gollapinni, S., Gollwitzer, K., Gomes, R. A., Bermeo, L. V. Gomez, Fajardo, L. S. Gomez, Gonnella, F., Gonzalez-Diaz, D., Gonzalez-Lopez, M., Goodman, M. C., Goswami, S., Gotti, C., Goudeau, J., Goudzovski, E., Grace, C., Gramellini, E., Gran, R., Granados, E., Granger, P., Grant, C., Gratieri, D. R., Grauso, G., Green, P., Greenberg, S., Greer, J., Griffith, W. C., Groetschla, F. T., Grzelak, K., Gu, L., Gu, W., Guarino, V., Guarise, M., Guenette, R., Guerard, E., Guerzoni, M., Guffanti, D., Guglielmi, A., Guo, B., Guo, Y., Gupta, A., Gupta, V., Gurung, G., Gutierrez, D., Guzowski, P., Guzzo, M. M., Gwon, S., Habig, A., Hadavand, H., Haegel, L., Haenni, R., Hagaman, L., Hahn, A., Haiston, J., Hakenmueller, J., Hamernik, T., Hamilton, P., Hancock, J., Happacher, F., Harris, D. A., Hartnell, J., Hartnett, T., Harton, J., Hasegawa, T., Hasnip, C., Hatcher, R., Hayrapetyan, K., Hays, J., Hazen, E., He, M., Heavey, A., Heeger, K. M., Heise, J., Henry, S., Morquecho, M. A. Hernandez, Herner, K., Hewes, V., Higuera, A., Hilgenberg, C., Hillier, S. J., Himmel, A., Hinkle, E., Hirsch, L. R., Ho, J., Hoff, J., Holin, A., Holvey, T., Hoppe, E., Horiuchi, S., Horton-Smith, G. A., Hostert, M., Houdy, T., Howard, B., Howell, R., Hristova, I., Hronek, M. S., Huang, J., Huang, R. G., Hulcher, Z., Ibrahim, M., Iles, G., Ilic, N., Iliescu, A. M., Illingworth, R., Ingratta, G., Ioannisian, A., Irwin, B., Isenhower, L., Oliveira, M. Ismerio, Itay, R., Jackson, C. M., Jain, V., James, E., Jang, W., Jargowsky, B., Jena, D., Jentz, I., Ji, X., Jiang, C., Jiang, J., Jiang, L., Jipa, A., Joaquim, F. R., Johnson, W., Jollet, C., Jones, B., Jones, R., Fernández, D. José, Jovancevic, N., Judah, M., Jung, C. K., Junk, T., Jwa, Y., Kabirnezhad, M., Kaboth, A. C., Kadenko, I., Kakorin, I., Kalitkina, A., Kalra, D., Kandemir, M., Kaplan, D. M., Karagiorgi, G., Karaman, G., Karcher, A., Karyotakis, Y., Kasai, S., Kasetti, S. P., Kashur, L., Katsioulas, I., Kauther, A., Kazaryan, N., Ke, L., Kearns, E., Keener, P. T., Kelly, K. J., Kemp, E., Kemularia, O., Kermaidic, Y., Ketchum, W., Kettell, S. H., Khabibullin, M., Khan, N., Khotjantsev, A., Khvedelidze, A., Kim, D., Kim, J., King, B., Kirby, B., Kirby, M., Kish, A., Klein, J., Kleykamp, J., Klustova, A., Kobilarcik, T., Koch, L., Koehler, K., Koerner, L. W., Koh, D. H., Kolupaeva, L., Korablev, D., Kordosky, M., Kosc, T., Kose, U., Kostelecký, V. A., Kothekar, K., Kotler, I., Kovalcuk, M., Kozhukalov, V., Krah, W., Kralik, R., Kramer, M., Kreczko, L., Krennrich, F., Kreslo, I., Kroupova, T., Kubota, S., Kubu, M., Kudenko, Y., Kudryavtsev, V. A., Kufatty, G., Kuhlmann, S., Kulagin, S., Kumar, J., Kumar, P., Kumaran, S., Kunze, P., Kunzmann, J., Kuravi, R., Kurita, N., Kuruppu, C., Kus, V., Kutter, T., Kvasnicka, J., Labree, T., Lackey, T., Lambert, A., Land, B. J., Lane, C. E., Lane, N., Lang, K., Langford, T., Langstaff, M., Lanni, F., Lantwin, O., Larkin, J., Lasorak, P., Last, D., Laudrain, A., Laundrie, A., Laurenti, G., Lavaut, E., Lawrence, A., Laycock, P., Lazanu, I., Lazzaroni, M., Le, T., Leardini, S., Learned, J., LeCompte, T., Lee, C., Legin, V., Miotto, G. Lehmann, Lehnert, R., de Oliveira, M. A. Leigui, Leitner, M., Silverio, D. Leon, Lepin, L. M., Li, J. -Y, Li, S. W., Li, Y., Liao, H., Lin, C. S., Lindebaum, D., Linden, S., Lineros, R. A., Ling, J., Lister, A., Littlejohn, B. R., Liu, H., Liu, J., Liu, Y., Lockwitz, S., Lokajicek, M., Lomidze, I., Long, K., Lopes, T. V., Lopez, J., de Rego, I. López, López-March, N., Lord, T., LoSecco, J. M., Louis, W. C., Sanchez, A. Lozano, Lu, X. -G., Luk, K. B., Lunday, B., Luo, X., Luppi, E., Maalmi, J., MacFarlane, D., Machado, A. A., Machado, P., Macias, C. T., Macier, J. R., MacMahon, M., Maddalena, A., Madera, A., Madigan, P., Magill, S., Magueur, C., Mahn, K., Maio, A., Major, A., Majumdar, K., Man, M., Mandujano, R. C., Maneira, J., Manly, S., Mann, A., Manolopoulos, K., Plata, M. Manrique, Corchado, S. Manthey, Manyam, V. N., Marchan, M., Marchionni, A., Marciano, W., Marfatia, D., Mariani, C., Maricic, J., Marinho, F., Marino, A. D., Markiewicz, T., Marques, F. Das Chagas, Marquet, C., Marsden, D., Marshak, M., Marshall, C. M., Marshall, J., Martina, L., Martín-Albo, J., Martinez, N., Caicedo, D. A. Martinez, López, F. Martínez, Miravé, P. Martínez, Martynenko, S., Mascagna, V., Massari, C., Mastbaum, A., Matichard, F., Matsuno, S., Matteucci, G., Matthews, J., Mauger, C., Mauri, N., Mavrokoridis, K., Mawby, I., Mazza, R., Mazzacane, A., McAskill, T., McConkey, N., McFarland, K. S., McGrew, C., McNab, A., Meazza, L., Meddage, V. C. N., Mefodiev, A., Mehta, B., Mehta, P., Melas, P., Mena, O., Mendez, H., Mendez, P., Méndez, D. P., Menegolli, A., Meng, G., Mercuri, A. C. E. A., Meregaglia, A., Messier, M. D., Metallo, S., Metcalf, J., Metcalf, W., Mewes, M., Meyer, H., Miao, T., Miccoli, A., Michna, G., Mikola, V., Milincic, R., Miller, F., Miller, G., Miller, W., Mineev, O., Minotti, A., Miralles, L., Miranda, O. G., Mironov, C., Miryala, S., Miscetti, S., Mishra, C. S., Mishra, S. R., Mislivec, A., Mitchell, M., Mladenov, D., Mocioiu, I., Mogan, A., Moggi, N., Mohanta, R., Mohayai, T. A., Mokhov, N., Molina, J., Bueno, L. Molina, Montagna, E., Montanari, A., Montanari, C., Montanari, D., Montanino, D., Zetina, L. M. Montaño, Mooney, M., Moor, A. F., Moore, Z., Moreno, D., Moreno-Palacios, O., Morescalchi, L., Moretti, D., Moretti, R., Morris, C., Mossey, C., Mote, M., Moura, C. A., Mouster, G., Mu, W., Mualem, L., Mueller, J., Muether, M., Muheim, F., Muir, A., Mulhearn, M., Munford, D., Munteanu, L. J., Muramatsu, H., Muraz, J., Murphy, M., Murphy, T., Muse, J., Mytilinaki, A., Nachtman, J., Nagai, Y., Nagu, S., Nandakumar, R., Naples, D., Narita, S., Nath, A., Navrer-Agasson, A., Nayak, N., Nebot-Guinot, M., Nehm, A., Nelson, J. K., Neogi, O., Nesbit, J., Nessi, M., Newbold, D., Newcomer, M., Nichol, R., Nicolas-Arnaldos, F., Nikolica, A., Nikolov, J., Niner, E., Nishimura, K., Norman, A., Norrick, A., Novella, P., Nowak, J. A., Oberling, M., Ochoa-Ricoux, J. P., Oh, S., Oh, S. B., Olivier, A., Olshevskiy, A., Olson, T., Onel, Y., Onishchuk, Y., Oranday, A., Osbiston, M., Vélez, J. A. Osorio, Ormachea, L. Otiniano, Ott, J., Pagani, L., Palacio, G., Palamara, O., Palestini, S., Paley, J. M., Pallavicini, M., Palomares, C., Pan, S., Panda, P., Vazquez, W. Panduro, Pantic, E., Paolone, V., Papadimitriou, V., Papaleo, R., Papanestis, A., Papoulias, D., Paramesvaran, S., Paris, A., Parke, S., Parozzi, E., Parsa, S., Parsa, Z., Parveen, S., Parvu, M., Pasciuto, D., Pascoli, S., Pasqualini, L., Pasternak, J., Patrick, C., Patrizii, L., Patterson, R. B., Patzak, T., Paudel, A., Paulucci, L., Pavlovic, Z., Pawloski, G., Payne, D., Pec, V., Pedreschi, E., Peeters, S. J. M., Pellico, W., Perez, A. Pena, Pennacchio, E., Penzo, A., Peres, O. L. G., Gonzalez, Y. F. Perez, Pérez-Molina, L., Pernas, C., Perry, J., Pershey, D., Pessina, G., Petrillo, G., Petta, C., Petti, R., Pfaff, M., Pia, V., Pickering, L., Pietropaolo, F., Pimentel, V. L., Pinaroli, G., Pinchault, J., Pitts, K., Plows, K., Plunkett, R., Pollack, C., Pollman, T., Polo-Toledo, D., Pompa, F., Pons, X., Poonthottathil, N., Popov, V., Poppi, F., Porter, J., Potekhin, M., Potenza, R., Pozimski, J., Pozzato, M., Prakash, T., Pratt, C., Prest, M., Psihas, F., Pugnere, D., Qian, X., Raaf, J. L., Radeka, V., Rademacker, J., Radics, B., Rafique, A., Raguzin, E., Rai, M., Rajagopalan, S., Rajaoalisoa, M., Rakhno, I., Rakotondravohitra, L., Ralte, L., Delgado, M. A. Ramirez, Ramson, B., Rappoldi, A., Raselli, G., Ratoff, P., Ray, R., Razafinime, H., Rea, E. M., Real, J. S., Rebel, B., Rechenmacher, R., Reggiani-Guzzo, M., Reichenbacher, J., Reitzner, S. D., Sfar, H. Rejeb, Renner, E., Renshaw, A., Rescia, S., Resnati, F., Restrepo, D., Reynolds, C., Ribas, M., Riboldi, S., Riccio, C., Riccobene, G., Ricol, J. S., Rigan, M., Rincón, E. V., Ritchie-Yates, A., Ritter, S., Rivera, D., Rivera, R., Robert, A., Rocha, J. L. Rocabado, Rochester, L., Roda, M., Rodrigues, P., Alonso, M. J. Rodriguez, Rondon, J. Rodriguez, Rosauro-Alcaraz, S., Rosier, P., Ross, D., Rossella, M., Rossi, M., Ross-Lonergan, M., Roy, N., Roy, P., Rubbia, C., Ruggeri, A., Ferreira, G. Ruiz, Russell, B., Ruterbories, D., Rybnikov, A., Saa-Hernandez, A., Saakyan, R., Sacerdoti, S., Sahoo, S. K., Sahu, N., Sala, P., Samios, N., Samoylov, O., Sanchez, M. C., Bravo, A. Sánchez, Sanchez-Lucas, P., Sandberg, V., Sanders, D. A., Sanfilippo, S., Sankey, D., Santoro, D., Saoulidou, N., Sapienza, P., Sarasty, C., Sarcevic, I., Sarra, I., Savage, G., Savinov, V., Scanavini, G., Scaramelli, A., Scarff, A., Schefke, T., Schellman, H., Schifano, S., Schlabach, P., Schmitz, D., Schneider, A. W., Scholberg, K., Schukraft, A., Schuld, B., Segade, A., Segreto, E., Selyunin, A., Senise, C. R., Sensenig, J., Shaevitz, M. H., Shanahan, P., Sharma, P., Kumar, R., Shaw, K., Shaw, T., Shchablo, K., Shen, J., Shepherd-Themistocleous, C., Sheshukov, A., Shi, W., Shin, S., Shivakoti, S., Shoemaker, I., Shooltz, D., Shrock, R., Siddi, B., Siden, M., Silber, J., Simard, L., Sinclair, J., Sinev, G., Singh, Jaydip, Singh, J., Singh, L., Singh, P., Singh, V., Chauhan, S. Singh, Sipos, R., Sironneau, C., Sirri, G., Siyeon, K., Skarpaas, K., Smedley, J., Smith, E., Smith, J., Smith, P., Smolik, J., Smy, M., Snape, M., Snider, E. L., Snopok, P., Snowden-Ifft, D., Nunes, M. Soares, Sobel, H., Soderberg, M., Sokolov, S., Salinas, C. J. Solano, Söldner-Rembold, S., Soleti, S. R., Solomey, N., Solovov, V., Sondheim, W. E., Sorel, M., Sotnikov, A., Soto-Oton, J., Sousa, A., Soustruznik, K., Spinella, F., Spitz, J., Spooner, N. J. C., Spurgeon, K., Stalder, D., Stancari, M., Stanco, L., Steenis, J., Stein, R., Steiner, H. M., Lisbôa, A. F. Steklain, Stepanova, A., Stewart, J., Stillwell, B., Stock, J., Stocker, F., Stokes, T., Strait, M., Strauss, T., Strigari, L., Stuart, A., Suarez, J. G., Subash, J., Surdo, A., Suter, L., Sutera, C. M., Sutton, K., Suvorov, Y., Svoboda, R., Swain, S. K., Szczerbinska, B., Szelc, A. M., Sztuc, A., Taffara, A., Talukdar, N., Tamara, J., Tanaka, H. A., Tang, S., Taniuchi, N., Casanova, A. M. Tapia, Oregui, B. Tapia, Tapper, A., Tariq, S., Tarpara, E., Tatar, E., Tayloe, R., Tedeschi, D., Teklu, A. M., Vidal, J. Tena, Tennessen, P., Tenti, M., Terao, K., Terranova, F., Testera, G., Thakore, T., Thea, A., Thiebault, A., Thomas, S., Thompson, A., Thorn, C., Timm, S. C., Tiras, E., Tishchenko, V., Todorović, N., Tomassetti, L., Tonazzo, A., Torbunov, D., Torti, M., Tortola, M., Tortorici, F., Tosi, N., Totani, D., Toups, M., Touramanis, C., Tran, D., Travaglini, R., Trevor, J., Triller, E., Trilov, S., Truchon, J., Truncali, D., Trzaska, W. H., Tsai, Y., Tsai, Y. -T., Tsamalaidze, Z., Tsang, K. V., Tsverava, N., Tu, S. Z., Tufanli, S., Tunnell, C., Turner, J., Tuzi, M., Tyler, J., Tyley, E., Tzanov, M., Uchida, M. A., González, J. Ureña, Urheim, J., Usher, T., Utaegbulam, H., Uzunyan, S., Vagins, M. R., Vahle, P., Valder, S., Valdiviesso, G. A., Valencia, E., Valentim, R., Vallari, Z., Vallazza, E., Valle, J. W. F., Van Berg, R., Van de Water, R. G., Forero, D. V., Vannozzi, A., Van Nuland-Troost, M., Varanini, F., Oliva, D. Vargas, Vasina, S., Vaughan, N., Vaziri, K., Vázquez-Ramos, A., Vega, J., Ventura, S., Verdugo, A., Vergani, S., Verzocchi, M., Vetter, K., Vicenzi, M., de Souza, H. Vieira, Vignoli, C., Vilela, C., Villa, E., Viola, S., Viren, B., Vizcaya-Hernandez, A., Vrba, T., Vuong, Q., Waldron, A. V., Wallbank, M., Walsh, J., Walton, T., Wang, H., Wang, J., Wang, L., Wang, M. H. L. S., Wang, X., Wang, Y., Warburton, K., Warner, D., Warsame, L., Wascko, M. O., Waters, D., Watson, A., Wawrowska, K., Weber, A., Weber, C. M., Weber, M., Wei, H., Weinstein, A., Wenzel, H., Westerdale, S., Wetstein, M., Whalen, K., Whilhelmi, J., White, A., Whitehead, L. H., Whittington, D., Wilking, M. J., Wilkinson, A., Wilkinson, C., Wilson, F., Wilson, R. J., Winter, P., Wisniewski, W., Wolcott, J., Wolfs, J., Wongjirad, T., Wood, A., Wood, K., Worcester, E., Worcester, M., Wospakrik, M., Wresilo, K., Wret, C., Wu, S., Wu, W., Wurm, M., Wyenberg, J., Xiao, Y., Xiotidis, I., Yaeggy, B., Yahlali, N., Yandel, E., Yang, K., Yang, T., Yankelevich, A., Yershov, N., Yonehara, K., Young, T., Yu, B., Yu, H., Yu, J., Yu, Y., Yuan, W., Zaki, R., Zalesak, J., Zambelli, L., Zamorano, B., Zani, A., Zapata, O., Zazueta, L., Zeller, G. P., Zennamo, J., Zeug, K., Zhang, C., Zhang, S., Zhao, M., Zhivun, E., Zimmerman, E. D., Zucchelli, S., Zuklin, J., Zutshi, V., and Zwaska, R.
Subjects: Physics - Instrumentation and Detectors, High Energy Physics - Experiment
Abstract: The Module-0 Demonstrator is a single-phase 600 kg liquid argon time projection chamber operated as a prototype for the DUNE liquid argon near detector. Based on the ArgonCube design concept, Module-0 features a novel 80k-channel pixelated charge readout and advanced high-coverage photon detection system. In this paper, we present an analysis of an eight-day data set consisting of 25 million cosmic ray events collected in the spring of 2021. We use this sample to demonstrate the imaging performance of the charge and light readout systems as well as the signal correlations between the two. We also report argon purity and detector uniformity measurements, and provide comparisons to detector simulations., Comment: 47 pages, 41 figures
Published: 2024

43. Neural Simulation-Based Inference of the Neutron Star Equation of State directly from Telescope Spectra

Author: Brandes, Len, Modi, Chirag, Ghosh, Aishik, Farrell, Delaney, Lindblom, Lee, Heinrich, Lukas, Steiner, Andrew W., Weber, Fridolin, and Whiteson, Daniel
Subjects: Astrophysics - High Energy Astrophysical Phenomena, Astrophysics - Instrumentation and Methods for Astrophysics, General Relativity and Quantum Cosmology, High Energy Physics - Phenomenology, Nuclear Theory
Abstract: Neutron stars provide a unique opportunity to study strongly interacting matter under extreme density conditions. The intricacies of matter inside neutron stars and their equation of state are not directly visible, but determine bulk properties, such as mass and radius, which affect the star's thermal X-ray emissions. However, the telescope spectra of these emissions are also affected by the stellar distance, hydrogen column, and effective surface temperature, which are not always well-constrained. Uncertainties on these nuisance parameters must be accounted for when making a robust estimation of the equation of state. In this study, we develop a novel methodology that, for the first time, can infer the full posterior distribution of both the equation of state and nuisance parameters directly from telescope observations. This method relies on the use of neural likelihood estimation, in which normalizing flows use samples of simulated telescope data to learn the likelihood of the neutron star spectra as a function of these parameters, coupled with Hamiltonian Monte Carlo methods to efficiently sample from the corresponding posterior distribution. Our approach surpasses the accuracy of previous methods, improves the interpretability of the results by providing access to the full posterior distribution, and naturally scales to a growing number of neutron star observations expected in the coming years.
Published: 2024
Full Text: View/download PDF

44. Thermal Weibel instability induced magnetic fields co-exist with linear wakes in laser-ionized plasmas

Author: Wu, Yipeng, Farrell, Audrey, Sinclair, Mitchell, Zhang, Chaojie, Petrushina, Irina, Vafaei-Najafabadi, Navid, Babzien, Marcus, Li, William, Pogorelsky, Igor, Polyanskiy, Mikhail, Fedurin, Mikhail, Kusche, Karl, Palmer, Mark, Marsh, Ken, and Joshi, Chan
Subjects: Physics - Plasma Physics
Abstract: When a moderately intense, few-picoseconds long laser pulse ionizes gas to produce an underdense plasma column, a linear relativistic plasma wave or wake can be excited by the self-modulation instability that may prove useful for multi-bunch acceleration of externally injected electrons or positrons to high energies in a short distance. At the same time, due to the anisotropic temperature distributions of the ionized plasma electrons, the Weibel instability can self-generate magnetic fields throughout such a plasma on a few picosecond timescale. In the present paper we first show using simulations that both these effects do indeed co-exist in space and time in the plasma. Using our simulations, we make preliminary estimates of the transverse emittance growth of an externally injected beam due to the Weibel magnetic fields. We then present results of an experiment that has allowed us to measure the spatiotemporal evolution of the magnetic fields using an ultrashort relativistic electron probe beam. Both the topology and the lifetime of the Weibel instability induced magnetic fields are in reasonable agreement with the simulations.
Published: 2024

45. The XENONnT Dark Matter Experiment

Author: XENON Collaboration, Aprile, E., Aalbers, J., Abe, K., Maouloud, S. Ahmed, Althueser, L., Andrieu, B., Angelino, E., Angevaare, J. R., Antochi, V. C., Martin, D. Antón, Arneodo, F., Balata, M., Baudis, L., Baxter, A. L., Bazyk, M., Bellagamba, L., Biondi, R., Bismark, A., Brookes, E. J., Brown, A., Bruenner, S., Bruno, G., Budnik, R., Bui, T. K., Cai, C., Cardoso, J. M. R., Cassese, F., Chiarini, A., Cichon, D., Chavez, A. P. Cimental, Colijn, A. P., Conrad, J., Corrieri, R., Cuenca-García, J. J., Cussonneau, J. P., Dadoun, O., D'Andrea, V., Decowski, M. P., De Fazio, B., Di Gangi, P., Diglio, S., Disdier, J. M., Douillet, D., Eitel, K., Elykov, A., Farrell, S., Ferella, A. D., Ferrari, C., Fischer, H., Flierman, M., Form, S., Front, D., Fulgione, W., Fuselli, C., Gaemers, P., Gaior, R., Rosso, A. Gallo, Galloway, M., Gao, F., Gardner, R., Garroum, N., Glade-Beucke, R., Grandi, L., Grigat, J., Guan, H., Guerzoni, M., Guida, M., Hammann, R., Higuera, A., Hils, C., Hoetzsch, L., Hood, N. F., Howlett, J., Huhmann, C., Iacovacci, M., Iaquaniello, G., Iven, L., Itow, Y., Jakob, J., Joerg, F., Joy, A., Kara, M., Kavrigin, P., Kazama, S., Kobayashi, M., Koltman, G., Kopec, A., Kuger, F., Landsman, H., Lang, R. F., Levinson, L., Li, I., Li, S., Liang, S., Lindemann, S., Lindner, M., Liu, K., Loizeau, J., Lombardi, F., Long, J., Lopes, J. A. M., Ma, Y., Macolino, C., Mahlstedt, J., Mancuso, A., Manenti, L., Marignetti, F., Undagoitia, T. Marrodán, Martella, P., Martens, K., Masbou, J., Masson, D., Masson, E., Mastroianni, S., Mele, E., Messina, M., Michinelli, R., Miuchi, K., Molinario, A., Moriyama, S., Morå, K., Mosbacher, Y., Murra, M., Müller, J., Ni, K., Nisi, S., Oberlack, U., Orlandi, D., Othegraven, R., Paetsch, B., Palacio, J., Parlati, S., Paschos, P., Pellegrini, Q., Peres, R., Peters, C., Pienaar, J., Pierre, M., Plante, G., Pollmann, T. R., Qi, J., Qin, J., García, D. Ramírez, Rynge, M., Shi, J., Singh, R., Sanchez, L., Santos, J. M. F. dos, Sarnoff, I., Sartorelli, G., Schreiner, J., Schulte, D., Schulte, P., Eißing, H. Schulze, Schumann, M., Lavina, L. Scotto, Selvi, M., Semeria, F., Shagin, P., Shi, S., Shockley, E., Silva, M., Simgen, H., Stephen, J., Stern, M., Stillwell, B. K., Takeda, A., Tan, P. -L., Tatananni, D., Terliuk, A., Thers, D., Toschi, F., Trinchero, G., Tunnell, C., Tönnies, F., Valerius, K., Volta, G., Weinheimer, C., Weiss, M., Wenz, D., Westermann, J., Wittweg, C., Wolf, T., Wu, V. H. S., Xing, Y., Xu, D., Xu, Z., Yamashita, M., Yang, L., Ye, J., Yuan, L., Zavattini, G., Zhong, M., and Zhu, T.
Subjects: Physics - Instrumentation and Detectors, Astrophysics - Instrumentation and Methods for Astrophysics, High Energy Physics - Experiment
Abstract: The multi-staged XENON program at INFN Laboratori Nazionali del Gran Sasso aims to detect dark matter with two-phase liquid xenon time projection chambers of increasing size and sensitivity. The XENONnT experiment is the latest detector in the program, planned to be an upgrade of its predecessor XENON1T. It features an active target of 5.9 tonnes of cryogenic liquid xenon (8.5 tonnes total mass in cryostat). The experiment is expected to extend the sensitivity to WIMP dark matter by more than an order of magnitude compared to XENON1T, thanks to the larger active mass and the significantly reduced background, improved by novel systems such as a radon removal plant and a neutron veto. This article describes the XENONnT experiment and its sub-systems in detail and reports on the detector performance during the first science run., Comment: 32 pages, 19 figures
Published: 2024

46. Graph Neural Network-based Tracking as a Service

Author: Zhao, Haoran, Naylor, Andrew, Hsu, Shih-Chieh, Calafiura, Paolo, Farrell, Steven, Feng, Yongbing, Harris, Philip Coleman, Khoda, Elham E, Mccormack, William Patrick, Rankin, Dylan Sheldon, and Ju, Xiangyang
Subjects: Physics - Computational Physics, High Energy Physics - Experiment, Physics - Data Analysis, Statistics and Probability
Abstract: Recent studies have shown promising results for track finding in dense environments using Graph Neural Network (GNN)-based algorithms. However, GNN-based track finding is computationally slow on CPUs, necessitating the use of coprocessors to accelerate the inference time. Additionally, the large input graph size demands a large device memory for efficient computation, a requirement not met by all computing facilities used for particle physics experiments, particularly those lacking advanced GPUs. Furthermore, deploying the GNN-based track-finding algorithm in a production environment requires the installation of all dependent software packages, exclusively utilized by this algorithm. These computing challenges must be addressed for the successful implementation of GNN-based track-finding algorithm into production settings. In response, we introduce a ``GNN-based tracking as a service'' approach, incorporating a custom backend within the NVIDIA Triton inference server to facilitate GNN-based tracking. This paper presents the performance of this approach using the Perlmutter supercomputer at NERSC., Comment: 7 pages, 4 figures, Proceeding of Connected the Dots Workshop (CTD 2023)
Published: 2024

47. Fast Pulsars, Neutron Stars, and Astrophysical Strange Quark Matter Objects

Author: Farrell, Delaney, Weber, Fridolin, Orsaria, Milva G., Ranea-Sandoval, Ignacio F., Canullán, Martín, Negreiros, Rodrigo, Katayama, Takashi, and Wagaman, Ian
Subjects: Astrophysics - High Energy Astrophysical Phenomena, Astrophysics - Solar and Stellar Astrophysics
Abstract: This book chapter explores key aspects of neutron stars, pulsar glitches, tidal deformability, fast pulsars, the equation of state, and strange quark matter stars. Challenges in directly measuring neutron star radius have led to reliance on spectroscopic and timing techniques, with uncertainties addressed through careful source selection and theoretical modeling. Pulsar glitches reveal insights into the equation of state through angular momentum transfer within the neutron star. Tidal deformability is crucial in gravitational-wave astronomy, exemplified by the GW170817 event. Fast pulsars, instrumental in astrophysical testing, are classified into ordinary pulsars, millisecond pulsars, and magnetars. The EOS is vital for understanding neutron star internal structure, explored through various models. The chapter delves into the theoretical framework for rotating neutron stars, addressing uniform and differential rotation scenarios and their impacts on mass and radius. Additionally, the intriguing concept of quark stars and strange dwarfs is investigated. The various topics discussed in this book chapter contribute to a broader understanding of dense matter physics, astrophysical phenomena, and the potential for transformative discoveries through advanced observational techniques and technologies like gravitational wave detectors, radio telescopes, and X-ray telescopes., Comment: 45 pages, 16 figures
Published: 2024

48. Explaining the high nitrogen abundances observed in high-z galaxies via population III stars of a few thousand solar masses

Author: Nandal, Devesh, Regan, John A., Woods, Tyrone E., Farrell, Eoin, Ekström, Sylvia, and Meynet, Georges
Subjects: Astrophysics - Astrophysics of Galaxies, Astrophysics - Solar and Stellar Astrophysics
Abstract: The chemical enrichment of the early Universe is a crucial element in the formation and evolution of galaxies, and Population III (PopIII) stars must play a vital role in this process. In this study, we examine metal enrichment from massive stars in the early Universe's embryonic galaxies. Using radiation hydrodynamic simulations and stellar evolution modelling, we calculated the expected metal yield from these stars. Specifically, we applied accretion rates from a previous radiation-hydrodynamic simulation to inform our stellar evolution modelling, executed with the Geneva code, across 11 selected datasets, with final stellar masses between 500 and 9000 Msol. Our results demonstrate that the first generation of Pop III stars within a mass range of 2000 to 9000 Msol result in N/O, C/O and O/H ratios compatible with the values observed in very high-z galaxies GN-z11 and CEERS 1019. The ejecta of these Pop III stars are predominantly composed of He, H, and N. Our Pop III chemical enrichment model of the halo can accurately reproduce the observed N/O and C/O ratios, and, by incorporating a hundred times more zero-metallicity interstellar material with the stellar ejecta, it accurately attains the observed O/H ratio. Thus, a sub-population of extremely massive PopIII stars, with masses surpassing approximately 2000 Msol, effectively reproduces the CNO elemental abundances observed in high-z JWST galaxies to date., Comment: Accepted in A&A, 13 pages, 4 figures
Published: 2024

49. Preserving the Hermiticity of the One-Body Density Matrix for a Non-Interacting Fermi Gas

Author: Farrell, L. M., Eaton, D., Chitnelawong, P., Bencheikh, K., and van Zyl, B. P.
Subjects: Mathematical Physics, Condensed Matter - Quantum Gases, Quantum Physics
Abstract: The one-body density matrix (ODM) for a zero temperature non-interacting Fermi gas can be approximately obtained in the semiclassical regime through different $\hbar$-expansion techniques. One would expect that each method of approximating the ODM should yield equivalent density matrices which are both Hermitian and idempotent to any order in $\hbar$. However, the Kirzhnits and Wigner-Kirkwood methods do not yield these properties, while the Grammaticos-Voros method does. Here we show explicitly, for arbitrary $d$-dimensions through an appropriate change into symmetric coordinates, that each method is indeed identical, Hermitian, and idempotent. This change of variables resolves the inconsistencies between the various methods, showing that the non-Hermitian and non-idempotent behavior of the Kirzhnits and Wigner-Kirkwood methods is an artifact of performing a non-symmetric truncation to the semiclassical $\hbar$-expansions. Our work also provides the first explicit derivation of the $d$-dimensional Grammaticos-Voros ODM, originally proposed by Redjati et al (2019 $\textit{J. Phys. Chem. Solids}$ 134 313-8) based on their $d=1,2,3,4$ expressions., Comment: 21 pages
Published: 2024
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50. Outlier Accommodation for GNSS Precise Point Positioning using Risk-Averse State Estimation

Author: Hu, Wang, Uwineza, Jean-Bernard, and Farrell, Jay A.
Subjects: Electrical Engineering and Systems Science - Systems and Control
Abstract: Reliable and precise absolute positioning is necessary in the realm of Connected Automated Vehicles (CAV). Global Navigation Satellite Systems (GNSS) provides the foundation for absolute positioning. Recently enhanced Precise Point Positioning (PPP) technology now offers corrections for GNSS on a global scale, with the potential to achieve accuracy suitable for real-time CAV applications. However, in obstructed sky conditions, GNSS signals are often affected by outliers; therefore, addressing outliers is crucial. In GNSS applications, there are many more measurements available than are required to meet the specification. Therefore, selecting measurements to avoid outliers is of interest. The recently developed Risk-Averse Performance-Specified (RAPS) state estimation optimally selects measurements to minimize outlier risk while meeting a positive semi-definite constraint on performance; at present, the existing solution methods are not suitable for real-time computation and have not been demonstrated using challenging real-world data or in Real-time PPP (RT-PPP) applications. This article makes contributions in a few directions. First, it uses a diagonal performance specification, which reduces computational costs relative to the positive semi-definite constraint. Second, this article considers GNSS RT-PPP applications. Third, the experiments use real-world GNSS data collected in challenging environments. The RT-PPP experimental results show that among the compared methods: all achieve comparable performance in open-sky conditions, and all exceed the Society of Automotive Engineers (SAE) specification; however, in challenging environments, the diagonal RAPS approach shows improvement of 6-19% over traditional methods. Throughout, RAPS achieves the lowest estimation risk., Comment: 7 pages,2 figures, Accepted by 2024 American Control Conference
Published: 2024

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