46,304 results on '"Rosado AS"'
Search Results
2. Uncertainty Decomposition and Error Margin Detection of Homodyned-K Distribution in Quantitative Ultrasound
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Ameri, Dorsa, Tehrani, Ali K. Z., Rosado-Mendez, Ivan M., and Rivaz, Hassan
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Electrical Engineering and Systems Science - Signal Processing ,Computer Science - Artificial Intelligence ,Electrical Engineering and Systems Science - Image and Video Processing ,Physics - Medical Physics ,Statistics - Machine Learning - Abstract
Homodyned K-distribution (HK-distribution) parameter estimation in quantitative ultrasound (QUS) has been recently addressed using Bayesian Neural Networks (BNNs). BNNs have been shown to significantly reduce computational time in speckle statistics-based QUS without compromising accuracy and precision. Additionally, they provide estimates of feature uncertainty, which can guide the clinician's trust in the reported feature value. The total predictive uncertainty in Bayesian modeling can be decomposed into epistemic (uncertainty over the model parameters) and aleatoric (uncertainty inherent in the data) components. By decomposing the predictive uncertainty, we can gain insights into the factors contributing to the total uncertainty. In this study, we propose a method to compute epistemic and aleatoric uncertainties for HK-distribution parameters ($\alpha$ and $k$) estimated by a BNN, in both simulation and experimental data. In addition, we investigate the relationship between the prediction error and both uncertainties, shedding light on the interplay between these uncertainties and HK parameters errors., Comment: 4 pages, 2 figures
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- 2024
3. Simulaci\'on de la distribuci\'on de alimento en el cultivo de camar\'on
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Rosado, Renato L. Conforme and Bocanegra, Francisco C. Calderon
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Computer Science - Artificial Intelligence - Abstract
This document presents the experimentation of 4 cases of food distribution for shrimp farming. The distributions are based on the location of the automatic feeders. Three cases applied in reality and a fourth case where the food is irrigated on the crop simultaneously and uniformly. In a first stage, the simulation of the three distribution cases is successfully adjusted to reality, where the trend of the shrimp growth curve is correlated with the historical data curve. A second stage where you experiment in 16 configurations that are based on the amount of food, the density of biomass and the distribution of the food. The simulation adopts the concepts of genetic algorithms to improve the population and fuzzy logic as an agent evaluation technique for decision-making against the quality of physical-chemical parameters in the simulated environment. The results of these interactions reveal a reduction in the simulated total culture time from 22 weeks to 14 weeks.
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- 2024
4. Cross-correlation of Luminous Red Galaxies with ML-selected AGN in HSC-SSP: Unobscured AGN residing in more massive halos
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Rosado, Rodrigo Córdova, Goulding, Andy D., Greene, Jenny E., Petter, Grayson C., Hickox, Ryan C., Kokron, Nickolas, Strauss, Michael A., Givans, Jahmour J., Toba, Yoshiki, and Henderson, Cassandra Starr
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Astrophysics - Astrophysics of Galaxies - Abstract
Active galactic nuclei (AGN) are the signposts of black hole growth, and likely play an important role in galaxy evolution. An outstanding question is whether AGN of different spectral types indicate different evolutionary stages in the coevolution of black holes and galaxies. We present the angular correlation function between an AGN sample selected from the Hyper Suprime Camera Subaru Strategic Program (HSC-SSP) optical + Wide-field Infrared Survey Explorer (WISE) mid-IR photometry, and a luminous red galaxy (LRG) sample from HSC-SSP. We investigate AGN clustering strength as a function of their luminosity and spectral features across three independent HSC fields totaling $\sim600\,{\rm deg^{2}}$, for $z\in0.6-1.2$ and AGN with $L_{6\mu m}>3\times10^{44}{\rm\,erg\,s^{-1}}$. There are $\sim28,500$ AGN and $\sim1.5$ million LRGs in our primary analysis. We determine the inferred average halo mass for the full AGN sample ($M_h \approx 10^{12.9}h^{-1}M_\odot$), and note that it does not evolve significantly as a function of redshift (over this narrow range) or luminosity. We find that, on average, unobscured AGN ($M_h \approx10^{13.3}h^{-1}M_\odot$) occupy $\sim4.5\times$ more massive halos than obscured AGN ($M_h \approx10^{12.6}h^{-1}M_\odot$), at $5\sigma$ statistical significance using 1-D uncertainties, and at $3\sigma$ using the full covariance matrix, suggesting a physical difference between unobscured and obscured AGN, beyond the line-of-sight viewing angle. Furthermore, we find evidence for a halo mass dependence on reddening level within the Type I AGN population, which could support the existence of a previously claimed dust-obscured phase in AGN-host galaxy coevolution. However, we also find that even quite small systematic shifts in the redshift distributions of the AGN sample could plausibly explain current and previously observed differences in $M_{h}$., Comment: 31 pages, 14 figures, submitted to ApJ
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- 2024
5. Exploring Listening Assessment in a Colombian EFL Context: A Case Study
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Ana Gutiérrez-Rojas and Nayibe Rosado-Mendinueta
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Listening comprehension is a crucial skill in English as a Foreign Language education, yet listening assessment still needs to be explored. This study aims to understand how listening is assessed in a Colombian private language institution and its potential connection to students' underperformance in listening proficiency tests. We characterize the listening assessment used in B1-level classes through a descriptive case study. Utilizing a rubric, we analyzed fourteen listening tasks from various sources, including course materials and a mock PET exam. Our analysis had two primary objectives: (a) to uncover the rationale behind test design and its alignment with the curriculum, and (b) to evaluate the knowledge types targeted and the forms of listening assessment employed using categorization. Our findings reveal that despite the curriculum's holistic listening development goals, assessments predominantly focus on phonological knowledge through dictation tests, in which students primarily engage with audio media and recordings. These findings suggest a misalignment in the way listening is approached during the whole course, the examinations used to assess listening during the B1 level, and the use of an external standardized test as the exit exam. This study holds potential implications for curriculum alignment and the enhancement of language assessment literacy within our context, shedding light on potential factors contributing to students' underperformance in listening comprehension.
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- 2024
6. Scheduling on a Stochastic Number of Machines
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Buchem, Moritz, Eberle, Franziska, Rosado, Hugo Kooki Kasuya, Schewior, Kevin, and Wiese, Andreas
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Computer Science - Data Structures and Algorithms - Abstract
We consider a new scheduling problem on parallel identical machines in which the number of machines is initially not known, but it follows a given probability distribution. Only after all jobs are assigned to a given number of bags, the actual number of machines is revealed. Subsequently, the jobs need to be assigned to the machines without splitting the bags. This is the stochastic version of a related problem introduced by Stein and Zhong [SODA 2018, TALG 2020] and it is, for example, motivated by bundling jobs that need to be scheduled by data centers. We present two PTASs for the stochastic setting, computing job-to-bag assignments that (i) minimize the expected maximum machine load and (ii) maximize the expected minimum machine load (like in the Santa Claus problem), respectively. The former result follows by careful enumeration combined with known PTASs. For the latter result, we introduce an intricate dynamic program that we apply to a suitably rounded instance.
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- 2024
7. Using graph neural networks to reconstruct charged pion showers in the CMS High Granularity Calorimeter
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Aamir, M., Acar, B., Adamov, G., Adams, T., Adloff, C., Afanasiev, S., Agrawal, C., Ahmad, A., Ahmed, H. A., Akbar, S., Akchurin, N., Akgul, B., Akgun, B., Akpinar, R. O., Aktas, E., AlKadhim, A., Alexakhin, V., Alimena, J., Alison, J., Alpana, A., Alshehri, W., Dominguez, P. Alvarez, Alyari, M., Amendola, C., Amir, R. B., Andersen, S. B., Andreev, Y., Antoszczuk, P. D., Aras, U., Ardila, L., Aspell, P., Avila, M., Awad, I., Aydilek, O., Azimi, Z., Pretel, A. Aznar, Bach, O. A., Bainbridge, R., Bakshi, A., Bam, B., Banerjee, S., Barney, D., Bayraktar, O., Beaudette, F., Beaujean, F., Becheva, E., Behera, P. K., Belloni, A., Bergauer, T., Besancon, M., Bylund, O. Bessidskaia, Bhatt, L., Bhowmil, D., Blekman, F., Blinov, P., Bloch, P., Bodek, A., Boger, a., Bonnemaison, A., Bouyjou, F., Brennan, L., Brondolin, E., Brusamolino, A., Bubanja, I., Perraguin, A. Buchot, Bunin, P., Misura, A. Burazin, Butler-nalin, A., Cakir, A., Callier, S., Campbell, S., Canderan, K., Cankocak, K., Cappati, A., Caregari, S., Carron, S., Carty, C., Cauchois, A., Ceard, L., Cerci, S., Chang, P. J., Chatterjee, R. M., Chatterjee, S., Chattopadhyay, P., Chatzistavrou, T., Chaudhary, M. S., Chauhan, A., Chen, J. A., Chen, J., Chen, Y., Cheng, K., Cheung, H., Chhikara, J., Chiron, A., Chiusi, M., Chokheli, D., Chudasama, R., Clement, E., Mendez, S. Coco, Coko, D., Coskun, K., Couderc, F., Crossman, B., Cui, Z., Cuisset, T., Cummings, G., Curtis, E. M., D'Alfonso, M., D-hler-ball, J., Dadazhanova, O., Damgov, J., Das, I., DasGupta, S., Dauncey, P., Mendes, A. David Tinoco, Davies, G., Davignon, O., DeLa, P. deBarbaroC., DeSilva, M., DeWit, A., Debbins, P., Defranchis, M. M., Delagnes, E., Devouge, P., Dewangan, C., DiGuglielmo, G., Diehl, L., Dilsiz, K., Dincer, G. G., Dittmann, J., Dragicevic, M., Du, D., Dubinchik, B., Dugad, S., Dulucq, F., Dumanoglu, I., Duran, B., Dutta, S., Dutta, V., Dychkant, A., Dünser, M., Edberg, T., Ehle, I. T., Berni, A. El, Elias, F., Eno, S. C., Erdogan, E. N., Erkmen, B., Ershov, Y., Ertorer, E. Y., Extier, S., Eychenne, L., Fedar, Y. E., Fedi, G., De Almeida, J. P. Figueiredo De De Sá Sousa, Alves, B. A. Fontana Santos Santos, Frahm, E., Francis, K., Freeman, J., French, T., Gaede, F., Gandhi, P. K., Ganjour, S., Garcia-Bellido, A., Gastaldi, F., Gazi, L., Gecse, Z., Gerwig, H., Gevin, O., Ghosh, S., Gill, K., Gleyzer, S., Godinovic, N., Goek, M., Goettlicher, P., Goff, R., Golunov, A., Gonultas, B., Martínez, J. D. González, Gorbounov, N., Gouskos, L., Gray, A., Gray, L., Grieco, C., Groenroos, S., Groner, D., Gruber, A., Grummer, A., Grönroos, S., Guilloux, F., Guler, Y., Gungordu, A. D., Guo, J., Guo, K., Guler, E. Gurpinar, Gutti, H. K., Guvenli, A. A., Gülmez, E., Hacisahinoglu, B., Halkin, Y., Machado, G. Hamilton Ilha, Hare, H. S., Hatakeyama, K., Heering, A. H., Hegde, V., Heintz, U., Hinton, N., Hinzmann, A., Hirschauer, J., Hitlin, D., Hos, İ., Hou, B., Hou, X., Howard, A., Howe, C., Hsieh, H., Hsu, T., Hua, H., Hummer, F., Imran, M., Incandela, J., Iren, E., Isildak, B., Jackson, P. S., Jackson, W. J., Jain, S., Jana, P., Jaroslavceva, J., Jena, S., Jige, A., Jordano, P. P., Joshi, U., Kaadze, K., Kafizov, A., Kalipoliti, L., Tharayil, A. Kallil, Kaluzinska, O., Kamble, S., Kaminskiy, A., Kanemura, M., Kanso, H., Kao, Y., Kapic, A., Kapsiak, C., Karjavine, V., Karmakar, S., Karneyeu, A., Kaya, M., Topaksu, A. Kayis, Kaynak, B., Kazhykarim, Y., Khan, F. A., Khudiakov, A., Kieseler, J., Kim, R. S., Klijnsma, T., Kloiber, E. G., Klute, M., Kocak, Z., Kodali, K. R., Koetz, K., Kolberg, T., Kolcu, O. B., Komaragiri, J. R., Komm, M., Kopsalis, I., Krause, H. A., Krawczyk, M. A., Vinayakam, T. R. Krishnaswamy, Kristiansen, K., Kristic, A., Krohn, M., Kronheim, B., Krüger, K., Kudtarkar, C., Kulis, S., Kumar, M., Kumar, N., Kumar, S., Verma, R. Kumar, Kunori, S., Kunts, A., Kuo, C., Kurenkov, A., Kuryatkov, V., Kyre, S., Ladenson, J., Lamichhane, K., Landsberg, G., Langford, J., Laudrain, A., Laughlin, R., Lawhorn, J., Dortz, O. Le, Lee, S. W., Lektauers, A., Lelas, D., Leon, M., Levchuk, L., Li, A. J., Li, J., Li, Y., Liang, Z., Liao, H., Lin, K., Lin, W., Lin, Z., Lincoln, D., Linssen, L., Litomin, A., Liu, G., Liu, Y., Lobanov, A., Lohezic, V., Loiseau, T., Lu, C., Lu, R., Lu, S. Y., Lukens, P., Mackenzie, M., Magnan, A., Magniette, F., Mahjoub, A., Mahon, D., Majumder, G., Makarenko, V., Malakhov, A., Malgeri, L., Mallios, S., Mandloi, C., Mankel, A., Mannelli, M., Mans, J., Mantilla, C., Martinez, G., Massa, C., Masterson, P., Matthewman, M., Matveev, V., Mayekar, S., Mazlov, I., Mehta, A., Mestvirishvili, A., Miao, Y., Milella, G., Mirza, I. R., Mitra, P., Moccia, S., Mohanty, G. B., Monti, F., Moortgat, F., Murthy, S., Music, J., Musienko, Y., Nabili, S., Nayak, S., Nelson, J. W., Nema, A., Neutelings, I., Niedziela, J., Nikitenko, A., Noonan, D., Noy, M., Nurdan, K., Obraztsov, S., Ochando, C., Ogul, H., Olsson, J., Onel, Y., Ozkorucuklu, S., Paganis, E., Palit, P., Pan, R., Pandey, S., Pantaleo, F., Papageorgakis, C., Paramesvaran, S., Paranjpe, M. M., Parolia, S., Parsons, A. G., Parygin, P., Paulini, M., Paus, C., Peñaló, K., Pedro, K., Pekic, V., Peltola, T., Peng, B., Perego, A., Perini, D., Petrilli, A., Pham, H., Pierre-Emile, T., Podem, S. K., Popov, V., Portales, L., Potok, O., Pradeep, P. B., Pramanik, R., Prosper, H., Prvan, M., Qasim, S. R., Qu, H., Quast, T., Trivino, A. Quiroga, Rabour, L., Raicevic, N., Rajpoot, H., Rao, M. A., Rapacz, K., Redjeb, W., Reinecke, M., Revering, M., Roberts, A., Rohlf, J., Rosado, P., Rose, A., Rothman, S., Rout, P. K., Rovere, M., Rumerio, P., Rusack, R., Rygaard, L., Ryjov, V., Sadivnycha, S., Sahin, M. Ö., Sakarya, U., Salerno, R., Saradhy, R., Saraf, M., Sarbandi, K., Sarkisla, M. A., Satyshev, I., Saud, N., Sauvan, J., Schindler, G., Schmidt, A., Schmidt, I., Schmitt, M. H., Sculac, A., Sculac, T., Sedelnikov, A., Seez, C., Sefkow, F., Selivanova, D., Selvaggi, M., Sergeychik, V., Sert, H., Shahid, M., Sharma, P., Sharma, R., Sharma, S., Shelake, M., Shenai, A., Shih, C. W., Shinde, R., Shmygol, D., Shukla, R., Sicking, E., Silva, P., Simsek, C., Simsek, E., Sirasva, B. K., Sirois, Y., Song, S., Song, Y., Soudais, G., Sriram, S., StJacques, R. R., StahlLeiton, A. G., Steen, A., Stein, J., Strait, J., Strobbe, N., Su, X., Sukhov, E., Suleiman, A., Cerci, D. Sunar, Suryadevara, P., Swain, K., Syal, C., Tali, B., Tanay, K., Tang, W., Tanvir, A., Tao, J., Tarabini, A., Tatli, T., Taylor, R., Taysi, Z. C., Teafoe, G., Tee, C. Z., Terrill, W., Thienpont, D., Thomas, R., Titov, M., Todd, C., Todd, E., Toms, M., Tosun, A., Troska, J., Tsai, L., Tsamalaidze, Z., Tsionou, D., Tsipolitis, G., Tsirigoti, M., Tu, R., Polat, S. N. Tural, Undleeb, S., Usai, E., Uslan, E., Ustinov, V., Vernazza, E., Viahin, O., Viazlo, O., Vichoudis, P., Vijay, A., Virdee, T., Voirin, E., Vojinovic, M., Voytishin, N., Vámi, T. Á., Wade, A., Walter, D., Wang, C., Wang, F., Wang, J., Wang, K., Wang, X., Wang, Y., Wang, Z., Wanlin, E., Wayne, M., Wetzel, J., Whitbeck, A., Wickwire, R., Wilmot, D., Wilson, J., Wu, H., Xiao, M., Yang, J., Yazici, B., Ye, Y., Yetkin, T., Yi, R., Yohay, R., Yu, T., Yuan, C., Yuan, X., Yuksel, O., YushmanoV, I., Yusuff, I., Zabi, A., Zareckis, D., Zarubin, A., Zehetner, P., Zghiche, A., Zhang, C., Zhang, D., Zhang, H., Zhang, J., Zhang, Z., Zhao, X., Zhong, J., Zhou, Y., and Zorbilmez, Ç.
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Physics - Instrumentation and Detectors ,High Energy Physics - Experiment ,Physics - Data Analysis, Statistics and Probability - Abstract
A novel method to reconstruct the energy of hadronic showers in the CMS High Granularity Calorimeter (HGCAL) is presented. The HGCAL is a sampling calorimeter with very fine transverse and longitudinal granularity. The active media are silicon sensors and scintillator tiles readout by SiPMs and the absorbers are a combination of lead and Cu/CuW in the electromagnetic section, and steel in the hadronic section. The shower reconstruction method is based on graph neural networks and it makes use of a dynamic reduction network architecture. It is shown that the algorithm is able to capture and mitigate the main effects that normally hinder the reconstruction of hadronic showers using classical reconstruction methods, by compensating for fluctuations in the multiplicity, energy, and spatial distributions of the shower's constituents. The performance of the algorithm is evaluated using test beam data collected in 2018 prototype of the CMS HGCAL accompanied by a section of the CALICE AHCAL prototype. The capability of the method to mitigate the impact of energy leakage from the calorimeter is also demonstrated., Comment: Prepared for submission to JINST
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- 2024
8. The PLATO Mission
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Rauer, Heike, Aerts, Conny, Cabrera, Juan, Deleuil, Magali, Erikson, Anders, Gizon, Laurent, Goupil, Mariejo, Heras, Ana, Lorenzo-Alvarez, Jose, Marliani, Filippo, Martin-Garcia, Cesar, Mas-Hesse, J. Miguel, O'Rourke, Laurence, Osborn, Hugh, Pagano, Isabella, Piotto, Giampaolo, Pollacco, Don, Ragazzoni, Roberto, Ramsay, Gavin, Udry, Stéphane, Appourchaux, Thierry, Benz, Willy, Brandeker, Alexis, Güdel, Manuel, Janot-Pacheco, Eduardo, Kabath, Petr, Kjeldsen, Hans, Min, Michiel, Santos, Nuno, Smith, Alan, Suarez, Juan-Carlos, Werner, Stephanie C., Aboudan, Alessio, Abreu, Manuel, Acuña, Lorena, Adams, Moritz, Adibekyan, Vardan, Affer, Laura, Agneray, François, Agnor, Craig, Børsen-Koch, Victor Aguirre, Ahmed, Saad, Aigrain, Suzanne, Al-Bahlawan, Ashraf, Gil, M de los Angeles Alcacera, Alei, Eleonora, Alencar, Silvia, Alexander, Richard, Alfonso-Garzón, Julia, Alibert, Yann, Prieto, Carlos Allende, Almeida, Leonardo, Sobrino, Roi Alonso, Altavilla, Giuseppe, Althaus, Christian, Trujillo, Luis Alonso Alvarez, Amarsi, Anish, Eiff, Matthias Ammler-von, Amôres, Eduardo, Andrade, Laerte, Antoniadis-Karnavas, Alexandros, António, Carlos, del Moral, Beatriz Aparicio, Appolloni, Matteo, Arena, Claudio, Armstrong, David, Aliaga, Jose Aroca, Asplund, Martin, Audenaert, Jeroen, Auricchio, Natalia, Avelino, Pedro, Baeke, Ann, Baillié, Kevin, Balado, Ana, Balestra, Andrea, Ball, Warrick, Ballans, Herve, Ballot, Jerome, Barban, Caroline, Barbary, Gaële, Barbieri, Mauro, Forteza, Sebastià Barceló, Barker, Adrian, Barklem, Paul, Barnes, Sydney, Navascues, David Barrado, Barragan, Oscar, Baruteau, Clément, Basu, Sarbani, Baudin, Frederic, Baumeister, Philipp, Bayliss, Daniel, Bazot, Michael, Beck, Paul G., Bedding, Tim, Belkacem, Kevin, Bellinger, Earl, Benatti, Serena, Benomar, Othman, Bérard, Diane, Bergemann, Maria, Bergomi, Maria, Bernardo, Pierre, Biazzo, Katia, Bignamini, Andrea, Bigot, Lionel, Billot, Nicolas, Binet, Martin, Biondi, David, Biondi, Federico, Birch, Aaron C., Bitsch, Bertram, Ceballos, Paz Victoria Bluhm, Bódi, Attila, Bognár, Zsófia, Boisse, Isabelle, Bolmont, Emeline, Bonanno, Alfio, Bonavita, Mariangela, Bonfanti, Andrea, Bonfils, Xavier, Bonito, Rosaria, Bonomo, Aldo Stefano, Börner, Anko, Saikia, Sudeshna Boro, Martín, Elisa Borreguero, Borsa, Francesco, Borsato, Luca, Bossini, Diego, Bouchy, Francois, Boué, Gwenaël, Boufleur, Rodrigo, Boumier, Patrick, Bourrier, Vincent, Bowman, Dominic M., Bozzo, Enrico, Bradley, Louisa, Bray, John, Bressan, Alessandro, Breton, Sylvain, Brienza, Daniele, Brito, Ana, Brogi, Matteo, Brown, Beverly, Brown, David, Brun, Allan Sacha, Bruno, Giovanni, Bruns, Michael, Buchhave, Lars A., Bugnet, Lisa, Buldgen, Gaël, Burgess, Patrick, Busatta, Andrea, Busso, Giorgia, Buzasi, Derek, Caballero, José A., Cabral, Alexandre, Calderone, Flavia, Cameron, Robert, Cameron, Andrew, Campante, Tiago, Martins, Bruno Leonardo Canto, Cara, Christophe, Carone, Ludmila, Carrasco, Josep Manel, Casagrande, Luca, Casewell, Sarah L., Cassisi, Santi, Castellani, Marco, Castro, Matthieu, Catala, Claude, Fernández, Irene Catalán, Catelan, Márcio, Cegla, Heather, Cerruti, Chiara, Cessa, Virginie, Chadid, Merieme, Chaplin, William, Charpinet, Stephane, Chiappini, Cristina, Chiarucci, Simone, Chiavassa, Andrea, Chinellato, Simonetta, Chirulli, Giovanni, Christensen-Dalsgaard, Jorgen, Church, Ross, Claret, Antonio, Clarke, Cathie, Claudi, Riccardo, Clermont, Lionel, Coelho, Hugo, Coelho, Joao, Cogato, Fabrizio, Colomé, Josep, Condamin, Mathieu, Conseil, Simon, Corbard, Thierry, Correia, Alexandre C. M., Corsaro, Enrico, Cosentino, Rosario, Costes, Jean, Cottinelli, Andrea, Covone, Giovanni, Creevey, Orlagh L., Crida, Aurelien, Csizmadia, Szilard, Cunha, Margarida, Curry, Patrick, da Costa, Jefferson, da Silva, Francys, Dalal, Shweta, Damasso, Mario, Damiani, Cilia, Damiani, Francesco, Chagas, Maria Liduina das, Davies, Melvyn, Davies, Guy, Davies, Ben, Davison, Gary, de Almeida, Leandro, de Angeli, Francesca, de Barros, Susana Cristina Cabral, Leão, Izan de Castro, de Freitas, Daniel Brito, de Freitas, Marcia Cristina, De Martino, Domitilla, de Medeiros, José Renan, de Paula, Luiz Alberto, de Plaa, Jelle, De Ridder, Joris, Deal, Morgan, Decin, Leen, Deeg, Hans, Degl'Innocenti, Scilla, Deheuvels, Sebastien, del Burgo, Carlos, Del Sordo, Fabio, Delgado-Mena, Elisa, Demangeon, Olivier, Denk, Tilmann, Derekas, Aliz, Desidera, Silvano, Dexet, Marc, Di Criscienzo, Marcella, Di Giorgio, Anna Maria, Di Mauro, Maria Pia, Rial, Federico Jose Diaz, Díaz-García, José-Javier, Dima, Marco, Dinuzzi, Giacomo, Dionatos, Odysseas, Distefano, Elisa, Nascimento Jr., Jose-Dias do, Domingo, Albert, D'Orazi, Valentina, Dorn, Caroline, Doyle, Lauren, Duarte, Elena, Ducellier, Florent, Dumaye, Luc, Dumusque, Xavier, Dupret, Marc-Antoine, Eggenberger, Patrick, Ehrenreich, David, Eigmüller, Philipp, Eising, Johannes, Emilio, Marcelo, Eriksson, Kjell, Ermocida, Marco, Giribaldi, Riano Isidoro Escate, Eschen, Yoshi, Estrela, Inês, Evans, Dafydd Wyn, Fabbian, Damian, Fabrizio, Michele, Faria, João Pedro, Farina, Maria, Farinato, Jacopo, Feliz, Dax, Feltzing, Sofia, Fenouillet, Thomas, Ferrari, Lorenza, Ferraz-Mello, Sylvio, Fialho, Fabio, Fienga, Agnes, Figueira, Pedro, Fiori, Laura, Flaccomio, Ettore, Focardi, Mauro, Foley, Steve, Fontignie, Jean, Ford, Dominic, Fornazier, Karin, Forveille, Thierry, Fossati, Luca, Franca, Rodrigo de Marca, da Silva, Lucas Franco, Frasca, Antonio, Fridlund, Malcolm, Furlan, Marco, Gabler, Sarah-Maria, Gaido, Marco, Gallagher, Andrew, Galli, Emanuele, Garcia, Rafael A., Hernández, Antonio García, Munoz, Antonio Garcia, García-Vázquez, Hugo, Haba, Rafael Garrido, Gaulme, Patrick, Gauthier, Nicolas, Gehan, Charlotte, Gent, Matthew, Georgieva, Iskra, Ghigo, Mauro, Giana, Edoardo, Gill, Samuel, Girardi, Leo, Winter, Silvia Giuliatti, Giusi, Giovanni, da Silva, João Gomes, Zazo, Luis Jorge Gómez, Gomez-Lopez, Juan Manuel, Hernández, Jonay Isai González, Murillo, Kevin Gonzalez, Gorius, Nicolas, Gouel, Pierre-Vincent, Goulty, Duncan, Granata, Valentina, Grenfell, John Lee, Grießbach, Denis, Grolleau, Emmanuel, Grouffal, Salomé, Grziwa, Sascha, Guarcello, Mario Giuseppe, Gueguen, Loïc, Guenther, Eike Wolf, Guilhem, Terrasa, Guillerot, Lucas, Guiot, Pierre, Guterman, Pascal, Gutiérrez, Antonio, Gutiérrez-Canales, Fernando, Hagelberg, Janis, Haldemann, Jonas, Hall, Cassandra, Handberg, Rasmus, Harrison, Ian, Harrison, Diana L., Hasiba, Johann, Haswell, Carole A., Hatalova, Petra, Hatzes, Artie, Haywood, Raphaelle, Hébrard, Guillaume, Heckes, Frank, Heiter, Ulrike, Hekker, Saskia, Heller, René, Helling, Christiane, Helminiak, Krzysztof, Hemsley, Simon, Heng, Kevin, Hermans, Aline, Hermes, JJ, Torres, Nadia Hidalgo, Hinkel, Natalie, Hobbs, David, Hodgkin, Simon, Hofmann, Karl, Hojjatpanah, Saeed, Houdek, Günter, Huber, Daniel, Huesler, Joseph, Hui-Bon-Hoa, Alain, Huygen, Rik, Huynh, Duc-Dat, Iro, Nicolas, Irwin, Jonathan, Irwin, Mike, Izidoro, André, Jacquinod, Sophie, Jannsen, Nicholas Emborg, Janson, Markus, Jeszenszky, Harald, Jiang, Chen, Mancebo, Antonio José Jimenez, Jofre, Paula, Johansen, Anders, Johnston, Cole, Jones, Geraint, Kallinger, Thomas, Kálmán, Szilárd, Kanitz, Thomas, Karjalainen, Marie, Karjalainen, Raine, Karoff, Christoffer, Kawaler, Steven, Kawata, Daisuke, Keereman, Arnoud, Keiderling, David, Kennedy, Tom, Kenworthy, Matthew, Kerschbaum, Franz, Kidger, Mark, Kiefer, Flavien, Kintziger, Christian, Kislyakova, Kristina, Kiss, László, Klagyivik, Peter, Klahr, Hubert, Klevas, Jonas, Kochukhov, Oleg, Köhler, Ulrich, Kolb, Ulrich, Koncz, Alexander, Korth, Judith, Kostogryz, Nadiia, Kovács, Gábor, Kovács, József, Kozhura, Oleg, Krivova, Natalie, Kučinskas, Arunas, Kuhlemann, Ilyas, Kupka, Friedrich, Laauwen, Wouter, Labiano, Alvaro, Lagarde, Nadege, Laget, Philippe, Laky, Gunter, Lam, Kristine Wai Fun, Lambrechts, Michiel, Lammer, Helmut, Lanza, Antonino Francesco, Lanzafame, Alessandro, Martiz, Mariel Lares, Laskar, Jacques, Latter, Henrik, Lavanant, Tony, Lawrenson, Alastair, Lazzoni, Cecilia, Lebre, Agnes, Lebreton, Yveline, Etangs, Alain Lecavelier des, Leinhardt, Zoe, Leleu, Adrien, Lendl, Monika, Leto, Giuseppe, Levillain, Yves, Libert, Anne-Sophie, Lichtenberg, Tim, Ligi, Roxanne, Lignieres, Francois, Lillo-Box, Jorge, Linsky, Jeffrey, Liu, John Scige, Loidolt, Dominik, Longval, Yuying, Lopes, Ilídio, Lorenzani, Andrea, Ludwig, Hans-Guenter, Lund, Mikkel, Lundkvist, Mia Sloth, Luri, Xavier, Maceroni, Carla, Madden, Sean, Madhusudhan, Nikku, Maggio, Antonio, Magliano, Christian, Magrin, Demetrio, Mahy, Laurent, Maibaum, Olaf, Malac-Allain, LeeRoy, Malapert, Jean-Christophe, Malavolta, Luca, Maldonado, Jesus, Mamonova, Elena, Manchon, Louis, Mann, Andrew, Mantovan, Giacomo, Marafatto, Luca, Marconi, Marcella, Mardling, Rosemary, Marigo, Paola, Marinoni, Silvia, Marques, Érico, Marques, Joao Pedro, Marrese, Paola Maria, Marshall, Douglas, Perales, Silvia Martínez, Mary, David, Marzari, Francesco, Masana, Eduard, Mascher, Andrina, Mathis, Stéphane, Mathur, Savita, Figueiredo, Ana Carolina Mattiuci, Maxted, Pierre F. L., Mazeh, Tsevi, Mazevet, Stephane, Mazzei, Francesco, McCormac, James, McMillan, Paul, Menou, Lucas, Merle, Thibault, Meru, Farzana, Mesa, Dino, Messina, Sergio, Mészáros, Szabolcs, Meunier, Nadége, Meunier, Jean-Charles, Micela, Giuseppina, Michaelis, Harald, Michel, Eric, Michielsen, Mathias, Michtchenko, Tatiana, Miglio, Andrea, Miguel, Yamila, Milligan, David, Mirouh, Giovanni, Mitchell, Morgan, Moedas, Nuno, Molendini, Francesca, Molnár, László, Mombarg, Joey, Montalban, Josefina, Montalto, Marco, Monteiro, Mário J. P. F. G., Morales, Juan Carlos, Morales-Calderon, Maria, Morbidelli, Alessandro, Mordasini, Christoph, Moreau, Chrystel, Morel, Thierry, Morello, Guiseppe, Morin, Julien, Mortier, Annelies, Mosser, Benoît, Mourard, Denis, Mousis, Olivier, Moutou, Claire, Mowlavi, Nami, Moya, Andrés, Muehlmann, Prisca, Muirhead, Philip, Munari, Matteo, Musella, Ilaria, Mustill, Alexander James, Nardetto, Nicolas, Nardiello, Domenico, Narita, Norio, Nascimbeni, Valerio, Nash, Anna, Neiner, Coralie, Nelson, Richard P., Nettelmann, Nadine, Nicolini, Gianalfredo, Nielsen, Martin, Niemi, Sami-Matias, Noack, Lena, Noels-Grotsch, Arlette, Noll, Anthony, Norazman, Azib, Norton, Andrew J., Nsamba, Benard, Ofir, Aviv, Ogilvie, Gordon, Olander, Terese, Olivetto, Christian, Olofsson, Göran, Ong, Joel, Ortolani, Sergio, Oshagh, Mahmoudreza, Ottacher, Harald, Ottensamer, Roland, Ouazzani, Rhita-Maria, Paardekooper, Sijme-Jan, Pace, Emanuele, Pajas, Miriam, Palacios, Ana, Palandri, Gaelle, Palle, Enric, Paproth, Carsten, Parro, Vanderlei, Parviainen, Hannu, Granado, Javier Pascual, Passegger, Vera Maria, Pastor-Morales, Carmen, Pätzold, Martin, Pedersen, May Gade, Hidalgo, David Pena, Pepe, Francesco, Pereira, Filipe, Persson, Carina M., Pertenais, Martin, Peter, Gisbert, Petit, Antoine C., Petit, Pascal, Pezzuto, Stefano, Pichierri, Gabriele, Pietrinferni, Adriano, Pinheiro, Fernando, Pinsonneault, Marc, Plachy, Emese, Plasson, Philippe, Plez, Bertrand, Poppenhaeger, Katja, Poretti, Ennio, Portaluri, Elisa, Portell, Jordi, de Mello, Gustavo Frederico Porto, Poyatos, Julien, Pozuelos, Francisco J., Moroni, Pier Giorgio Prada, Pricopi, Dumitru, Prisinzano, Loredana, Quade, Matthias, Quirrenbach160, ndreas, Reina6, Julio Arturo Rabanal, Soares, Maria Cristina Rabello, Raimondo, Gabriella, Rainer, Monica, Rodón, Jose Ramón, Ramón-Ballesta, Alejandro, Zapata, Gonzalo Ramos, Rätz, Stefanie, Rauterberg, Christoph, Redman, Bob, Redmer, Ronald, Reese, Daniel, Regibo, Sara, Reiners, Ansgar, Reinhold, Timo, Renie, Christian, Ribas, Ignasi, Ribeiro, Sergio, Ricciardi, Thiago Pereira, Rice, Ken, Richard, Olivier, Riello, Marco, Rieutord, Michel, Ripepi, Vincenzo, Rixon, Guy, Rockstein, Steve, Rodríguez, María Teresa Rodrigo, Díaz, Luisa Fernanda Rodríguez, Garcia, Juan Pablo Rodriguez, Rodriguez-Gomez, Julio, Roehlly, Yannick, Roig, Fernando, Rojas-Ayala, Bárbara, Rolf, Tobias, Rørsted, Jakob Lysgaard, Rosado, Hugo, Rosotti, Giovanni, Roth, Olivier, Roth, Markus, Rousseau, Alex, Roxburgh, Ian, Roy, Fabrice, Royer, Pierre, Ruane, Kirk, Mastropasqua, Sergio Rufini, de Galarreta, Claudia Ruiz, Russi, Andrea, Saar, Steven, Saillenfest, Melaine, Salaris, Maurizio, Salmon, Sebastien, Saltas, Ippocratis, Samadi, Réza, Samadi, Aunia, Samra, Dominic, da Silva, Tiago Sanches, Carrasco, Miguel Andrés Sánchez, Santerne, Alexandre, Santoli, Francesco, Santos, Ângela R. G., Mesa, Rosario Sanz, Sarro, Luis Manuel, Scandariato, Gaetano, Schäfer, Martin, Schlafly, Edward, Schmider, François-Xavier, Schneider, Jean, Schou, Jesper, Schunker, Hannah, Schwarzkopf, Gabriel Jörg, Serenelli, Aldo, Seynaeve, Dries, Shan, Yutong, Shapiro, Alexander, Shipman, Russel, Sicilia, Daniela, Sanmartin, Maria Angeles Sierra, Sigot, Axelle, Silliman, Kyle, Silvotti, Roberto, Simon, Attila E., Napoli, Ricardo Simoyama, Skarka, Marek, Smalley, Barry, Smiljanic, Rodolfo, Smit, Samuel, Smith, Alexis, Smith, Leigh, Snellen, Ignas, Sódor, Ádám, Sohl, Frank, Solanki, Sami K., Sortino, Francesca, Sousa, Sérgio, Southworth, John, Souto, Diogo, Sozzetti, Alessandro, Stamatellos, Dimitris, Stassun, Keivan, Steller, Manfred, Stello, Dennis, Stelzer, Beate, Stiebeler, Ulrike, Stokholm, Amalie, Storelvmo, Trude, Strassmeier, Klaus, Strøm, Paul Anthony, Strugarek, Antoine, Sulis, Sophia, Švanda, Michal, Szabados, László, Szabó, Róbert, Szabó, Gyula M., Szuszkiewicz, Ewa, Talens, Geert Jan, Teti, Daniele, Theisen, Tom, Thévenin, Frédéric, Thoul, Anne, Tiphene, Didier, Titz-Weider, Ruth, Tkachenko, Andrew, Tomecki, Daniel, Tonfat, Jorge, Tosi, Nicola, Trampedach, Regner, Traven, Gregor, Triaud, Amaury, Trønnes, Reidar, Tsantaki, Maria, Tschentscher, Matthias, Turin, Arnaud, Tvaruzka, Adam, Ulmer, Bernd, Ulmer-Moll, Solène, Ulusoy, Ceren, Umbriaco, Gabriele, Valencia, Diana, Valentini, Marica, Valio, Adriana, Guijarro, Ángel Luis Valverde, Van Eylen, Vincent, Van Grootel, Valerie, van Kempen, Tim A., Van Reeth, Timothy, Van Zelst, Iris, Vandenbussche, Bart, Vasiliou, Konstantinos, Vasilyev, Valeriy, de Mascarenhas, David Vaz, Vazan, Allona, Nunez, Marina Vela, Velloso, Eduardo Nunes, Ventura, Rita, Ventura, Paolo, Venturini, Julia, Trallero, Isabel Vera, Veras, Dimitri, Verdugo, Eva, Verma, Kuldeep, Vibert, Didier, Martinez, Tobias Vicanek, Vida, Krisztián, Vigan, Arthur, Villacorta, Antonio, Villaver, Eva, Aparicio, Marcos Villaverde, Viotto, Valentina, Vorobyov, Eduard, Vorontsov, Sergey, Wagner, Frank W., Walloschek, Thomas, Walton, Nicholas, Walton, Dave, Wang, Haiyang, Waters, Rens, Watson, Christopher, Wedemeyer, Sven, Weeks, Angharad, Weingril, Jörg, Weiss, Annita, Wendler, Belinda, West, Richard, Westerdorff, Karsten, Westphal, Pierre-Amaury, Wheatley, Peter, White, Tim, Whittaker, Amadou, Wickhusen, Kai, Wilson, Thomas, Windsor, James, Winter, Othon, Winther, Mark Lykke, Winton, Alistair, Witteck, Ulrike, Witzke, Veronika, Woitke, Peter, Wolter, David, Wuchterl, Günther, Wyatt, Mark, Yang, Dan, Yu, Jie, Sanchez, Ricardo Zanmar, Osorio, María Rosa Zapatero, Zechmeister, Mathias, Zhou, Yixiao, Ziemke, Claas, and Zwintz, Konstanze
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Astrophysics - Instrumentation and Methods for Astrophysics ,Astrophysics - Earth and Planetary Astrophysics ,Astrophysics - Solar and Stellar Astrophysics - Abstract
PLATO (PLAnetary Transits and Oscillations of stars) is ESA's M3 mission designed to detect and characterise extrasolar planets and perform asteroseismic monitoring of a large number of stars. PLATO will detect small planets (down to <2 R_(Earth)) around bright stars (<11 mag), including terrestrial planets in the habitable zone of solar-like stars. With the complement of radial velocity observations from the ground, planets will be characterised for their radius, mass, and age with high accuracy (5 %, 10 %, 10 % for an Earth-Sun combination respectively). PLATO will provide us with a large-scale catalogue of well-characterised small planets up to intermediate orbital periods, relevant for a meaningful comparison to planet formation theories and to better understand planet evolution. It will make possible comparative exoplanetology to place our Solar System planets in a broader context. In parallel, PLATO will study (host) stars using asteroseismology, allowing us to determine the stellar properties with high accuracy, substantially enhancing our knowledge of stellar structure and evolution. The payload instrument consists of 26 cameras with 12cm aperture each. For at least four years, the mission will perform high-precision photometric measurements. Here we review the science objectives, present PLATO's target samples and fields, provide an overview of expected core science performance as well as a description of the instrument and the mission profile at the beginning of the serial production of the flight cameras. PLATO is scheduled for a launch date end 2026. This overview therefore provides a summary of the mission to the community in preparation of the upcoming operational phases.
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- 2024
9. HST SHEL: Enabling Comparative Exoplanetology with HST/STIS
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Allen, Natalie H., Sing, David K., Espinoza, Néstor, O'Steen, Richard, Nikolov, Nikolay K., Rustamkulov, Zafar, Evans-Soma, Thomas M., Rosado, Lakeisha M. Ramos, Alam, Munazza K., López-Morales, Mercedes, Stevenson, Kevin B., Wakeford, Hannah R., May, Erin M., Brahm, Rafael, and Pinto, Marcelo Tala
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Astrophysics - Earth and Planetary Astrophysics ,Astrophysics - Instrumentation and Methods for Astrophysics - Abstract
The Hubble Space Telescope (HST) has been our most prolific tool to study exoplanet atmospheres. As the age of JWST begins, there is a wealth of HST archival data that is useful to strengthen our inferences from JWST. Notably, HST/STIS and its 0.3-1 $\mu$m wavelength coverage extends past JWST's 0.6 $\mu$m wavelength cutoff and holds an abundance of potential information: alkali (Na, K) and molecular (TiO, VO) species opacities, aerosol information, and the presence of stellar contamination. However, time series observations with HST suffer from significant instrumental systematics and can be highly dependent on choices made during the transit fitting process. This makes comparing transmission spectra of planets with different data reduction methodologies challenging, as it is difficult to discern if an observed trend is caused by differences in data reduction or underlying physical processes. Here, we present the Sculpting Hubble's Exoplanet Legacy (SHEL) program, which aims to build a consistent data reduction and light curve analysis methodology and associated database of transmission spectra from archival HST observations. In this paper, we present the SHEL analysis framework for HST/STIS and its low-resolution spectroscopy modes, G430L and G750L. We apply our methodology to four notable hot Jupiters: WASP-39 b, WASP-121 b, WASP-69 b, and WASP-17 b, and use these examples to discuss nuances behind analysis with HST/STIS. Our results for WASP-39 b, WASP-121 b, and WASP-17 b are consistent with past publications, but our analysis of WASP-69 b differs and shows evidence of either a strong scattering slope or stellar contamination. The data reduction pipeline and tutorials are available on Github., Comment: 36 pages, 25 figures, 4 tables. Accepted for publication in the Astronomical Journal
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- 2024
10. The Construction of Large-scale Structure Catalogs for the Dark Energy Spectroscopic Instrument
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Ross, A. J., Aguilar, J., Ahlen, S., Alam, S., Anand, A., Bailey, S., Bianchi, D., Brieden, S., Brooks, D., Burtin, E., Rosell, A. Carnero, Chaussidon, E., Claybaugh, T., Cole, S., Dawson, K., de la Macorra, A., de Mattia, A., Dey, Arjun, Dey, Biprateep, Doel, P., Fanning, K., Ferraro, S., Ereza, J., Font-Ribera, A., Forero-Romero, J. E., Gaztañaga, E., Gil-Marín, H., Gontcho, S. Gontcho A, Gonzalez-Morales, A. X., Guy, J., Hahn, C., Heydenreich, S., Honscheid, K., Howlett, C., Ishak, M., Karim, T., Kirkby, D., Kisner, T., Kong, H., Kremin, A., Krolewski, A., Lambert, A., Landriau, M., Lasker, J., Guillou, L. Le, Levi, M. E., Manera, M., Martini, P., McDonald, P., Meisner, A., Miquel, R., Moon, J., Moustakas, J., Muñoz-Gutiérrez, A., Myers, A. D., Nadathur, S., Napolitano, L., Newman, J. A., Nie, J., Niz, G., Palanque-Delabrouille, N., Percival, W. J., Poppett, C., Prada, F., Raichoor, A., Ravoux, C., Rezaie, M., Rosado-Marin, A., Rossi, G., Samushia, L., Sanchez, E., Schlafly, E. F., Schlegel, D., Seo, H., Smith, A., Sprayberry, D., Tarlé, G., Valcin, D., Vargas-Magaña, M., Weaver, B. A., Wilson, M., Yu, J., Zarrouk, P., Zhao, C., Zhou, R., and Zou, H.
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Astrophysics - Cosmology and Nongalactic Astrophysics - Abstract
We present the technical details on how large-scale structure (LSS) catalogs are constructed from redshifts measured from spectra observed by the Dark Energy Spectroscopic Instrument (DESI). The LSS catalogs provide the information needed to determine the relative number density of DESI tracers as a function of redshift and celestial coordinates and, e.g., determine clustering statistics. We produce catalogs that are weighted subsamples of the observed data, each matched to a weighted `random' catalog that forms an unclustered sampling of the probability density that DESI could have observed those data at each location. Precise knowledge of the DESI observing history and associated hardware performance allows for a determination of the DESI footprint and the number of times DESI has covered it at sub-arcsecond level precision. This enables the completeness of any DESI sample to be modeled at this same resolution. The pipeline developed to create LSS catalogs has been designed to easily allow robustness tests and enable future improvements. We describe how it allows ongoing work improving the match between galaxy and random catalogs, such as including further information when assigning redshifts to randoms, accounting for fluctuations in target density, accounting for variation in the redshift success rate, and accommodating blinding schemes., Comment: Accepted (by JCAP) version of supporting publication of DESI 2024II: Sample definitions, characteristics, and two-point clustering statistics
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- 2024
11. Forward modeling fluctuations in the DESI LRGs target sample using image simulations
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Kong, Hui, Ross, Ashley J., Honscheid, Klaus, Lang, Dustin, Porredon, Anna, de Mattia, Arnaud, Rezaie, Mehdi, Zhou, Rongpu, Schlafly, Edward, Moustakas, John, Rosado-Marin, Alberto, Aguilar, Jessica Nicole, Ahlen, Steven, Brooks, David, Chaussidon, Edmond, Claybaugh, Todd, Cole, Shaun, de la Macorra, Axel, Dey, Arjun, Dey, Biprateep, Doel, Peter, Fanning, Kevin, Forero-Romero, Jaime E., Gaztanaga, Enrique, Gontcho, Satya Gontcho A, Gutierrez, Gaston, Howlett, Cullan, Juneau, Stephanie, Kremin, Anthony, Landriau, Martin, Levi, Michael, Manera, Marc, Martini, Paul, Meisner, Aaron, Miquel, Ramon, Mueller, Eva-Maria, Myers, Adam, Newman, Jeffrey A., Nie, Jundan, Niz, Gustavo, Percival, Will, Poppett, Claire, Prada, Francisco, Rossi, Graziano, Sanchez, Eusebio, Schlegel, David, Schubnell, Michael, Seo, Hee-Jong, Sprayberry, David, Tarle, Gregory, Magana, Mariana Vargas, Weaver, Benjamin Alan, and Zou, Hu
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Astrophysics - Cosmology and Nongalactic Astrophysics - Abstract
We use the forward modeling pipeline, Obiwan, to study the imaging systematics of the Luminous Red Galaxies (LRGs) targeted by the Dark Energy Spectroscopic Instrument (DESI). We update the Obiwan pipeline, which had previously been developed to simulate the optical images used to target DESI data, to further simulate WISE images in the infrared. This addition makes it possible to simulate the DESI LRGs sample, which utilizes WISE data in the target selection. Deep DESI imaging data combined with a method to account for biases in their shapes is used to define a truth sample of potential LRG targets. We simulate a total of 15 million galaxies to obtain a simulated LRG sample (Obiwan LRGs) that predicts the variations in target density due to imaging properties. We find that the simulations predict the trends with depth observed in the data, including how they depend on the intrinsic brightness of the galaxies. We observe that faint LRGs are the main contributing power of the imaging systematics trend induced by depth. We also find significant trends in the data against Galactic extinction that are not predicted by Obiwan. These trends depend strongly on the particular map of Galactic extinction chosen to test against, implying Large-Scale Structure systematic contamination (e.g. Cosmic-Infrared Background) in the Galactic extinction maps is a likely root cause. We additionally observe that the DESI LRGs sample exhibits a complex dependency on a combination of seeing, depth, and intrinsic galaxy brightness, which is not replicated by Obiwan, suggesting discrepancies between the current simulation settings and the actual observations. The detailed findings we present should be used to guide any observational systematics mitigation treatment for the clustering of the DESI LRG sample., Comment: 46 pages, 26 figures
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- 2024
12. Hunting a charged Higgs boson pair in proton-proton collisions
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Arroyo-Ureña, M. A., Herrera-Chacón, E. A., Rosado-Navarro, S., and Salazar, Humberto
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High Energy Physics - Phenomenology - Abstract
We explore the production and the possible detection of a charged scalar Higgs pair $H^-H^+$ decaying into a final state $\mu\nu_{\mu}cb$ in proton-proton collisions, i.e, $pp\to H^- H^+\to \mu\nu_{\mu} cb$. These charged scalars are predicted in the Two-Higgs Doublet Model of type III (2HDM-III), particularly we analyze masses of such a particle of the order of the top quark mass. The analysis is applied to the Large Hadron Collider (LHC) and its next step, the High Luminosity LHC (HL-LHC). As a test and validation of the model, we identify regions of the 2HDM-III parameter space that accommodate the current excess of events at $3\sigma$ in the process $\mathcal{BR}(t\to H^{\pm}b)\times \mathcal{BR}(H^{\pm}\to cb)$ for $M_{H^{\pm}}=130$ GeV reported by ATLAS collaboration. Additional experimental constraints are also included. Based on it, we propose realistic scenarios that could be brought to experimental scrutiny at the LHC and HL-LHC. Assuming the best scenario, we predict a signal significance of $5\sigma$ for the charged scalar boson mass $M_{H^{\pm}}$ in the $120-240$ GeV interval., Comment: 31 pages, 22 figures, 9 tables
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- 2024
13. Microbiota recovery in a chronosquences of impoverished Cerrado soils with biosolids applications
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Huang, Laibin, Rosado, Alexandre Soares, Wright, Alonna, Corrêa, Rodrigo Studart, Silva, Lucas, and Mazza Rodrigues, Jorge L
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Agricultural ,Veterinary and Food Sciences ,Biological Sciences ,Ecology ,Environmental Management ,Environmental Sciences ,Forestry Sciences ,Life on Land ,Microbiota ,Soil Microbiology ,Brazil ,Soil ,Mining ,Biodiversity ,Ecosystem ,Environmental Restoration and Remediation ,Soil microbiome ,Biodiversity regeneration ,Mine rehabilitation ,Biosolids ,Cerrado - Abstract
Mining activities put the Brazilian savannas, a global biodiversity hotspot, in danger of species and soil carbon losses. Experiments employing biosolids have been applied to rejuvenate this degraded ecosystem, but a lingering question yet to be answered is whether the microbiota that inhabits these impoverished soils can be recovered towards its initial steady state after vegetation recovery. Here, we selected an 18-year-old restoration chronosequence of biosolids-treated, untreated mining and native soils to investigate the soil microbiota recovery based on composition, phylogeny, and diversity, as well as the potential factors responsible for ecosystem recovery. Our results revealed that the soil microbiota holds a considerable recovery potential in the degraded Cerrado biome. Biosolids application not only improved soil health, but also led to 41.7 % recovery of the whole microbial community, featuring significantly higher microbiota diversity and enriched groups (e.g., Firmicutes) that benefit carbon storage compared to untreated mining and native soils. The recovered community showed significant compositional distinctions from the untreated mining or native soils, rather than phylogenetic differences, with physiochemical properties explaining 55 % of the overall community changes. This study advances our understanding of soil microbiota dynamics in response to disturbance and restoration by shedding light on its recovery associated with biosolid application in a degraded biodiverse ecosystem.
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- 2024
14. $\gamma_5$ subtleties in distinct regularizations: the Bumblebee model example
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Rosado, Ricardo J. C., Cherchiglia, Adriano, Sampaio, Marcos, and Hiller, Brigitte
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High Energy Physics - Phenomenology - Abstract
We examine the subtleties of regularization schemes in four-dimensional space ($4S$), related in particular to the introduction of the $\gamma_5$ matrix. To illustrate we use a "Bumblebee" model featuring dynamically induced Lorentz symmetry violation. The analysis centers on how different regularization methods affect the solutions to the gap equation in this model. We highlight the resolution of ambiguities associated with the $\gamma_5$ matrix in ultraviolet divergent integrals by employing an enhanced Implicit Regularization (IREG) method. This method extends IREG to a quasi-four-dimensional space, $Q4S = 4S \oplus X$, drawing parallels with the consistent approach of Dimensional Reduction (DRED). Comparative analysis is conducted against results from the 't Hooft-Veltman regularization scheme, conventional IREG in strict $4S$, and sharp momentum cutoff techniques. Our results illustrate a scheme to compute $\gamma_5$ interactions in physical dimension of divergent amplitudes, confirming the approach in [1].
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- 2024
15. HOD-Dependent Systematics in Emission Line Galaxies for the DESI 2024 BAO analysis
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Garcia-Quintero, C., Mena-Fernández, J., Rocher, A., Yuan, S., Hadzhiyska, B., Alves, O., Rashkovetskyi, M., Seo, H., Padmanabhan, N., Nadathur, S., Howlett, C., Ishak, M., Medina-Varela, L., McDonald, P., Ross, A. J., Xie, Y., Chen, X., Bera, A., Aguilar, J., Ahlen, S., Andrade, U., BenZvi, S., Brooks, D., Burtin, E., Chen, S., Claybaugh, T., Cole, S., de la Macorra, A., de Mattia, A., Dey, A., Dey, B., Ding, Z., Doel, P., Fanning, K., Forero-Romero, J. E., Gaztañaga, E., Gil-Marín, H., Gontcho, S. Gontcho A, Gutierrez, G., Guy, J., Hahn, C., Honscheid, K., Kremin, A., Landriau, M., Guillou, L. Le, Levi, M. E., Manera, M., Martini, P., Meisner, A., Miquel, R., Moustakas, J., Mueller, E., Muñoz-Gutiérrez, A., Myers, A. D., Newman, J. A., Nie, J., Niz, G., Paillas, E., Palanque-Delabrouille, N., Percival, W. J., Poppett, C., Pérez-Fernández, A., Rosado-Marin, A., Rossi, G., Ruggeri, R., Sanchez, E., Schlegel, D., Schubnell, M., Sprayberry, D., Tarlé, G., Vargas-Magaña, M., Weaver, B. A., Yu, J., Zhang, H., Zhou, R., and Zou, H.
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Astrophysics - Cosmology and Nongalactic Astrophysics - Abstract
The Dark Energy Spectroscopic Instrument (DESI) will provide precise measurements of Baryon Acoustic Oscillations (BAO) to constrain the expansion history of the Universe and set stringent constraints on dark energy. Therefore, precise control of the global error budget due to various systematic effects is required for the DESI 2024 BAO analysis. In this work, we focus on the robustness of the BAO analysis against the Halo Occupation Distribution (HOD) modeling for the Emission Line Galaxy (ELG) tracer. Based on a common dark matter simulation, our analysis relies on HOD mocks tuned to early DESI data, namely the One-Percent survey data. To build the mocks, we use several HOD models for the ELG tracer as well as extensions to the baseline HOD models. Among these extensions, we consider distinct recipes for galactic conformity and assembly bias. We perform two independent analyses in the Fourier space and in the configuration space. We recover the BAO signal from two-point measurements after performing reconstruction on our mocks. Additionally, we also apply the control variates technique to reduce sample variance noise. Our BAO analysis can recover the isotropic BAO parameter $\alpha_\text{iso}$ within 0.1\% and the Alcock Paczynski parameter $\alpha_\text{AP}$ within 0.3\%. Overall, we find that our systematic error due to the HOD dependence is below 0.17\%, with the Fourier space analysis being more robust against the HOD systematics. We conclude that our analysis pipeline is robust enough against the HOD systematics for the ELG tracer in the DESI 2024 BAO analysis., Comment: Supporting publication of DESI 2024 III: Baryon Acoustic Oscillations from Galaxies and Quasars
- Published
- 2024
16. HOD-Dependent Systematics for Luminous Red Galaxies in the DESI 2024 BAO Analysis
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Mena-Fernández, J., Garcia-Quintero, C., Yuan, S., Hadzhiyska, B., Alves, O., Rashkovetskyi, M., Seo, H., Padmanabhan, N., Nadathur, S., Howlett, C., Alam, S., Rocher, A., Ross, A. J., Sanchez, E., Ishak, M., Aguilar, J., Ahlen, S., Andrade, U., BenZvi, S., Brooks, D., Burtin, E., Chen, S., Chen, X., Claybaugh, T., Cole, S., de la Macorra, A., de Mattia, A., Dey, Arjun, Dey, B., Ding, Z., Doel, P., Fanning, K., Forero-Romero, J. E., Gaztañaga, E., Gil-Marín, H., Gontcho, S. Gontcho A, Gutierrez, G., Guy, J., Hahn, C., Honscheid, K., Juneau, S., Kremin, A., Landriau, M., Guillou, L. Le, Levi, M. E., Manera, M., Martini, P., Medina-Varela, L., Meisner, A., Miquel, R., Moustakas, J., Mueller, E., Muñoz-Gutiérrez, A., Myers, A. D., Newman, J. A., Nie, J., Niz, G., Paillas, E., Palanque-Delabrouille, N., Percival, W. J., Poppett, C., Pérez-Fernández, A., Rosado-Marin, A., Rossi, G., Ruggeri, R., Saulder, C., Schlegel, D., Schubnell, M., Sprayberry, D., Tarlé, G., Vargas-Magaña, M., Weaver, B. A., Yu, J., Zhang, H., and Zou, H.
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Astrophysics - Cosmology and Nongalactic Astrophysics - Abstract
In this paper, we present the estimation of systematics related to the halo occupation distribution (HOD) modeling in the baryon acoustic oscillations (BAO) distance measurement of the Dark Energy Spectroscopic Instrument (DESI) 2024 analysis. This paper focuses on the study of HOD systematics for luminous red galaxies (LRG). We consider three different HOD models for LRGs, including the base 5-parameter vanilla model and two extensions to it, that we refer to as baseline and extended models. The baseline model is described by the 5 vanilla HOD parameters, an incompleteness factor and a velocity bias parameter, whereas the extended one also includes a galaxy assembly bias and a satellite profile parameter. We utilize the 25 dark matter simulations available in the AbacusSummit simulation suite at $z=$ 0.8 and generate mock catalogs for our different HOD models. To test the impact of the HOD modeling in the position of the BAO peak, we run BAO fits for all these sets of simulations and compare the best-fit BAO-scaling parameters $\alpha_{\rm iso}$ and $\alpha_{\rm AP}$ between every pair of HOD models. We do this for both Fourier and configuration spaces independently, using post-reconstruction measurements. We find a 3.3$\sigma$ detection of HOD systematic for $\alpha_{\rm AP}$ in configuration space with an amplitude of 0.19%. For the other cases, we did not find a 3$\sigma$ detection, and we decided to compute a conservative estimation of the systematic using the ensemble of shifts between all pairs of HOD models. By doing this, we quote a systematic with an amplitude of 0.07% in $\alpha_{\rm iso}$ for both Fourier and configuration spaces; and of 0.09% in $\alpha_{\rm AP}$ for Fourier space., Comment: 36 pages, 9 figures. Supporting publication of DESI 2024 III: Baryon Acoustic Oscillations from Galaxies and Quasars
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- 2024
17. Semi-analytical covariance matrices for two-point correlation function for DESI 2024 data
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Rashkovetskyi, M., Forero-Sánchez, D., de Mattia, A., Eisenstein, D. J., Padmanabhan, N., Seo, H., Ross, A. J., Aguilar, J., Ahlen, S., Alves, O., Andrade, U., Brooks, D., Burtin, E., Claybaugh, T., Cole, S., de la Macorra, A., Ding, Z., Doel, P., Fanning, K., Ferraro, S., Font-Ribera, A., Forero-Romero, J. E., Garcia-Quintero, C., Gil-Marín, H., Gontcho, S. Gontcho A, Gonzalez-Morales, A. X., Gutierrez, G., Honscheid, K., Howlett, C., Juneau, S., Kremin, A., Guillou, L. Le, Manera, M., Medina-Varela, L., Mena-Fernández, J., Miquel, R., Mueller, E., Muñoz-Gutiérrez, A., Myers, A. D., Nie, J., Niz, G., Paillas, E., Percival, W. J., Poppett, C., Pérez-Fernández, A., Rezaie, M., Rosado-Marin, A., Rossi, G., Ruggeri, R., Sanchez, E., Saulder, C., Schlegel, D., Schubnell, M., Sprayberry, D., Tarlé, G., Weaver, B. A., Yu, J., Zhao, C., and Zou, H.
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Astrophysics - Cosmology and Nongalactic Astrophysics ,Physics - Data Analysis, Statistics and Probability - Abstract
We present an optimized way of producing the fast semi-analytical covariance matrices for the Legendre moments of the two-point correlation function, taking into account survey geometry and mimicking the non-Gaussian effects. We validate the approach on simulated (mock) catalogs for different galaxy types, representative of the Dark Energy Spectroscopic Instrument (DESI) Data Release 1, used in 2024 analyses. We find only a few percent differences between the mock sample covariance matrix and our results, which can be expected given the approximate nature of the mocks, although we do identify discrepancies between the shot-noise properties of the DESI fiber assignment algorithm and the faster approximation used in the mocks. Importantly, we find a close agreement (<~ 5% relative differences) in the projected errorbars for distance scale parameters for the baryon acoustic oscillation measurements. This confirms our method as an attractive alternative to simulation-based covariance matrices, especially for non-standard models or galaxy sample selections, in particular, relevant to the broad current and future analyses of DESI data., Comment: Supporting publication of DESI 2024 III: Baryon Acoustic Oscillations from Galaxies and Quasars (arXiv:2404.03000). 29 pages, 4 figures. Prepared for submission to JCAP. Code available at https://github.com/oliverphilcox/RascalC and https://github.com/misharash/RascalC-scripts/tree/DESI2024. Data points from the plots available at https://zenodo.org/doi/10.5281/zenodo.10895161
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- 2024
18. DESI 2024 VI: Cosmological Constraints from the Measurements of Baryon Acoustic Oscillations
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DESI Collaboration, Adame, A. G., Aguilar, J., Ahlen, S., Alam, S., Alexander, D. M., Alvarez, M., Alves, O., Anand, A., Andrade, U., Armengaud, E., Avila, S., Aviles, A., Awan, H., Bahr-Kalus, B., Bailey, S., Baltay, C., Bault, A., Behera, J., BenZvi, S., Bera, A., Beutler, F., Bianchi, D., Blake, C., Blum, R., Brieden, S., Brodzeller, A., Brooks, D., Buckley-Geer, E., Burtin, E., Calderon, R., Canning, R., Rosell, A. Carnero, Cereskaite, R., Cervantes-Cota, J. L., Chabanier, S., Chaussidon, E., Chaves-Montero, J., Chen, S., Chen, X., Claybaugh, T., Cole, S., Cuceu, A., Davis, T. M., Dawson, K., de la Macorra, A., de Mattia, A., Deiosso, N., Dey, A., Dey, B., Ding, Z., Doel, P., Edelstein, J., Eftekharzadeh, S., Eisenstein, D. J., Elliott, A., Fagrelius, P., Fanning, K., Ferraro, S., Ereza, J., Findlay, N., Flaugher, B., Font-Ribera, A., Forero-Sánchez, D., Forero-Romero, J. E., Frenk, C. S., Garcia-Quintero, C., Gaztañaga, E., Gil-Marín, H., Gontcho, S. Gontcho A, Gonzalez-Morales, A. X., Gonzalez-Perez, V., Gordon, C., Green, D., Gruen, D., Gsponer, R., Gutierrez, G., Guy, J., Hadzhiyska, B., Hahn, C., Hanif, M. M. S, Herrera-Alcantar, H. K., Honscheid, K., Howlett, C., Huterer, D., Iršič, V., Ishak, M., Juneau, S., Karaçaylı, N. G., Kehoe, R., Kent, S., Kirkby, D., Kremin, A., Krolewski, A., Lai, Y., Lan, T. -W., Landriau, M., Lang, D., Lasker, J., Goff, J. M. Le, Guillou, L. Le, Leauthaud, A., Levi, M. E., Li, T. S., Linder, E., Lodha, K., Magneville, C., Manera, M., Margala, D., Martini, P., Maus, M., McDonald, P., Medina-Varela, L., Meisner, A., Mena-Fernández, J., Miquel, R., Moon, J., Moore, S., Moustakas, J., Mudur, N., Mueller, E., Muñoz-Gutiérrez, A., Myers, A. D., Nadathur, S., Napolitano, L., Neveux, R., Newman, J. A., Nguyen, N. M., Nie, J., Niz, G., Noriega, H. E., Padmanabhan, N., Paillas, E., Palanque-Delabrouille, N., Pan, J., Penmetsa, S., Percival, W. J., Pieri, M. M., Pinon, M., Poppett, C., Porredon, A., Prada, F., Pérez-Fernández, A., Pérez-Ràfols, I., Rabinowitz, D., Raichoor, A., Ramírez-Pérez, C., Ramirez-Solano, S., Ravoux, C., Rashkovetskyi, M., Rezaie, M., Rich, J., Rocher, A., Rockosi, C., Roe, N. A., Rosado-Marin, A., Ross, A. J., Rossi, G., Ruggeri, R., Ruhlmann-Kleider, V., Samushia, L., Sanchez, E., Saulder, C., Schlafly, E. F., Schlegel, D., Schubnell, M., Seo, H., Shafieloo, A., Sharples, R., Silber, J., Slosar, A., Smith, A., Sprayberry, D., Tan, T., Tarlé, G., Taylor, P., Trusov, S., Ureña-López, L. A., Vaisakh, R., Valcin, D., Valdes, F., Vargas-Magaña, M., Verde, L., Walther, M., Wang, B., Wang, M. S., Weaver, B. A., Weaverdyck, N., Wechsler, R. H., Weinberg, D. H., White, M., Yu, J., Yu, Y., Yuan, S., Yèche, C., Zaborowski, E. A., Zarrouk, P., Zhang, H., Zhao, C., Zhao, R., Zhou, R., Zhuang, T., and Zou, H.
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Astrophysics - Cosmology and Nongalactic Astrophysics - Abstract
We present cosmological results from the measurement of baryon acoustic oscillations (BAO) in galaxy, quasar and Lyman-$\alpha$ forest tracers from the first year of observations from the Dark Energy Spectroscopic Instrument (DESI), to be released in the DESI Data Release 1. DESI BAO provide robust measurements of the transverse comoving distance and Hubble rate, or their combination, relative to the sound horizon, in seven redshift bins from over 6 million extragalactic objects in the redshift range $0.1
-1$ and $w_a<0$. This preference is 2.6$\sigma$ for the DESI+CMB combination, and persists or grows when SN~Ia are added in, giving results discrepant with the $\Lambda$CDM model at the $2.5\sigma$, $3.5\sigma$ or $3.9\sigma$ levels for the addition of Pantheon+, Union3, or DES-SN5YR datasets respectively. For the flat $\Lambda$CDM model with the sum of neutrino mass $\sum m_\nu$ free, combining the DESI and CMB data yields an upper limit $\sum m_\nu < 0.072$ $(0.113)$ eV at 95% confidence for a $\sum m_\nu>0$ $(\sum m_\nu>0.059)$ eV prior. These neutrino-mass constraints are substantially relaxed in models beyond $\Lambda$CDM. [Abridged.], Comment: This DESI Collaboration Key Publication is part of the 2024 publication series using the first year of observations (see https://data.desi.lbl.gov/doc/papers). Typos corrected and a new figure and discussion added to Appendix A - Published
- 2024
19. DESI 2024 IV: Baryon Acoustic Oscillations from the Lyman Alpha Forest
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DESI Collaboration, Adame, A. G., Aguilar, J., Ahlen, S., Alam, S., Alexander, D. M., Alvarez, M., Alves, O., Anand, A., Andrade, U., Armengaud, E., Avila, S., Aviles, A., Awan, H., Bailey, S., Baltay, C., Bault, A., Bautista, J., Behera, J., BenZvi, S., Beutler, F., Bianchi, D., Blake, C., Blum, R., Brieden, S., Brodzeller, A., Brooks, D., Buckley-Geer, E., Burtin, E., Calderon, R., Canning, R., Rosell, A. Carnero, Cereskaite, R., Cervantes-Cota, J. L., Chabanier, S., Chaussidon, E., Chaves-Montero, J., Chen, S., Chen, X., Claybaugh, T., Cole, S., Cuceu, A., Davis, T. M., Dawson, K., de la Cruz, R., de la Macorra, A., de Mattia, A., Deiosso, N., Dey, A., Dey, B., Ding, J., Ding, Z., Doel, P., Edelstein, J., Eftekharzadeh, S., Eisenstein, D. J., Elliott, A., Fagrelius, P., Fanning, K., Ferraro, S., Ereza, J., Findlay, N., Flaugher, B., Font-Ribera, A., Forero-Sánchez, D., Forero-Romero, J. E., Garcia-Quintero, C., Gaztañaga, E., Gil-Marín, H., Gontcho, S. Gontcho A, Gonzalez-Morales, A. X., Gonzalez-Perez, V., Gordon, C., Green, D., Gruen, D., Gsponer, R., Gutierrez, G., Guy, J., Hadzhiyska, B., Hahn, C., Hanif, M. M. S, Herrera-Alcantar, H. K., Honscheid, K., Howlett, C., Huterer, D., Iršič, V., Ishak, M., Juneau, S., Karaçayli, N. G., Kehoe, R., Kent, S., Kirkby, D., Kremin, A., Krolewski, A., Lai, Y., Lan, T. -W., Landriau, M., Lang, D., Lasker, J., Goff, J. M. Le, Guillou, L. Le, Leauthaud, A., Levi, M. E., Li, T. S., Linder, E., Lodha, K., Magneville, C., Manera, M., Margala, D., Martini, P., Maus, M., McDonald, P., Medina-Varela, L., Meisner, A., Mena-Fernández, J., Miquel, R., Moon, J., Moore, S., Moustakas, J., Mueller, E., Muñoz-Gutiérrez, A., Myers, A. D., Nadathur, S., Napolitano, L., Neveux, R., Newman, J. A., Nguyen, N. M., Nie, J., Niz, G., Noriega, H. E., Padmanabhan, N., Paillas, E., Palanque-Delabrouille, N., Pan, J., Penmetsa, S., Percival, W. J., Pieri, M. M., Pinon, M., Poppett, C., Porredon, A., Prada, F., Pérez-Fernández, A., Pérez-Ràfols, I., Rabinowitz, D., Raichoor, A., Ramírez-Pérez, C., Ramirez-Solano, S., Rashkovetskyi, M., Ravoux, C., Rezaie, M., Rich, J., Rocher, A., Rockosi, C., Roe, N. A., Rosado-Marin, A., Ross, A. J., Rossi, G., Ruggeri, R., Ruhlmann-Kleider, V., Samushia, L., Sanchez, E., Saulder, C., Schlafly, E. F., Schlegel, D., Schubnell, M., Seo, H., Sharples, R., Silber, J., Sinigaglia, F., Slosar, A., Smith, A., Sprayberry, D., Tan, T., Tarlé, G., Trusov, S., Vaisakh, R., Valcin, D., Valdes, F., Vargas-Magaña, M., Verde, L., Walther, M., Wang, B., Wang, M. S., Weaver, B. A., Weaverdyck, N., Wechsler, R. H., Weinberg, D. H., White, M., Yu, J., Yu, Y., Yuan, S., Yèche, C., Zaborowski, E. A., Zarrouk, P., Zhang, H., Zhao, C., Zhao, R., Zhou, R., and Zou, H.
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Astrophysics - Cosmology and Nongalactic Astrophysics - Abstract
We present the measurement of Baryon Acoustic Oscillations (BAO) from the Lyman-$\alpha$ (Ly$\alpha$) forest of high-redshift quasars with the first-year dataset of the Dark Energy Spectroscopic Instrument (DESI). Our analysis uses over $420\,000$ Ly$\alpha$ forest spectra and their correlation with the spatial distribution of more than $700\,000$ quasars. An essential facet of this work is the development of a new analysis methodology on a blinded dataset. We conducted rigorous tests using synthetic data to ensure the reliability of our methodology and findings before unblinding. Additionally, we conducted multiple data splits to assess the consistency of the results and scrutinized various analysis approaches to confirm their robustness. For a given value of the sound horizon ($r_d$), we measure the expansion at $z_{\rm eff}=2.33$ with 2\% precision, $H(z_{\rm eff}) = (239.2 \pm 4.8) (147.09~{\rm Mpc} /r_d)$ km/s/Mpc. Similarly, we present a 2.4\% measurement of the transverse comoving distance to the same redshift, $D_M(z_{\rm eff}) = (5.84 \pm 0.14) (r_d/147.09~{\rm Mpc})$ Gpc. Together with other DESI BAO measurements at lower redshifts, these results are used in a companion paper to constrain cosmological parameters., Comment: This DESI Collaboration Key Publication is part of the 2024 publication series using the first year of observations (see https://data.desi.lbl.gov/doc/papers). Minor changes in v4, version accepted for publication in JCAP
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- 2024
20. Optimal Reconstruction of Baryon Acoustic Oscillations for DESI 2024
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Paillas, E., Ding, Z., Chen, X., Seo, H., Padmanabhan, N., de Mattia, A., Ross, A. J., Nadathur, S., Howlett, C., Aguilar, J., Ahlen, S., Alves, O., Andrade, U., Brooks, D., Buckley-Geer, E., Burtin, E., Chen, S., Claybaugh, T., Cole, S., Dawson, K., de la Macorra, A., Dey, Arjun, Doel, P., Fanning, K., Ferraro, S., Forero-Romero, J. E., Garcia-Quintero, C., Gaztañaga, E., Gil-Marín, H., Gontcho, S. Gontcho A, Gutierrez, G., Hahn, C., Hanif, M. M. S, Honscheid, K., Ishak, M., Kehoe, R., Kremin, A., Landriau, M., Guillou, L. Le, Levi, M. E., Manera, M., Martini, P., Medina-Varela, L., Meisner, A., Mena-Fernández, J., Miquel, R., Moustakas, J., Mueller, E., Muñoz-Gutiérrez, A., Myers, A. D., Newman, J. A., Nie, J., Niz, G., Palanque-Delabrouille, N., Percival, W. J., Poppett, C., Prada, F., Pérez-Fernández, A., Rashkovetskyi, M., Rezaie, M., Rosado-Marin, A., Rossi, G., Ruggeri, R., Sanchez, E., Saulder, C., Schlafly, E. F., Schlegel, D., Schubnell, M., Sprayberry, D., Tarlé, G., Valcin, D., Vargas-Magaña, M., Yu, J., Yuan, S., Zhou, R., and Zou, H.
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Astrophysics - Cosmology and Nongalactic Astrophysics - Abstract
Baryon acoustic oscillations (BAO) provide a robust standard ruler to measure the expansion history of the Universe through galaxy clustering. Density-field reconstruction is now a widely adopted procedure for increasing the precision and accuracy of the BAO detection. With the goal of finding the optimal reconstruction settings to be used in the DESI 2024 galaxy BAO analysis, we assess the sensitivity of the post-reconstruction BAO constraints to different choices in our analysis configuration, performing tests on blinded data from the first year of DESI observations (DR1), as well as on mocks that mimic the expected clustering and selection properties of the DESI DR1 target samples. Overall, we find that BAO constraints remain robust against multiple aspects in the reconstruction process, including the choice of smoothing scale, treatment of redshift-space distortions, fiber assignment incompleteness, and parameterizations of the BAO model. We also present a series of tests that DESI followed in order to assess the maturity of the end-to-end galaxy BAO pipeline before the unblinding of the large-scale structure catalogs., Comment: Supporting publication of DESI 2024 III: Baryon Acoustic Oscillations from Galaxies and Quasars
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- 2024
21. DESI 2024 III: Baryon Acoustic Oscillations from Galaxies and Quasars
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DESI Collaboration, Adame, A. G., Aguilar, J., Ahlen, S., Alam, S., Alexander, D. M., Alvarez, M., Alves, O., Anand, A., Andrade, U., Armengaud, E., Avila, S., Aviles, A., Awan, H., Bailey, S., Baltay, C., Bault, A., Behera, J., BenZvi, S., Beutler, F., Bianchi, D., Blake, C., Blum, R., Brieden, S., Brodzeller, A., Brooks, D., Buckley-Geer, E., Burtin, E., Calderon, R., Canning, R., Rosell, A. Carnero, Cereskaite, R., Cervantes-Cota, J. L., Chabanier, S., Chaussidon, E., Chaves-Montero, J., Chen, S., Chen, X., Claybaugh, T., Cole, S., Cuceu, A., Davis, T. M., Dawson, K., de la Macorra, A., de Mattia, A., Deiosso, N., Dey, A., Dey, B., Ding, Z., Doel, P., Edelstein, J., Eftekharzadeh, S., Eisenstein, D. J., Elliott, A., Fagrelius, P., Fanning, K., Ferraro, S., Ereza, J., Findlay, N., Flaugher, B., Font-Ribera, A., Forero-Sánchez, D., Forero-Romero, J. E., Garcia-Quintero, C., Gaztañaga, E., Gil-Marín, H., Gontcho, S. Gontcho A, Gonzalez-Morales, A. X., Gonzalez-Perez, V., Gordon, C., Green, D., Gruen, D., Gsponer, R., Gutierrez, G., Guy, J., Hadzhiyska, B., Hahn, C., Hanif, M. M. S, Herrera-Alcantar, H. K., Honscheid, K., Howlett, C., Huterer, D., Iršič, V., Ishak, M., Juneau, S., Karaçaylı, N. G., Kehoe, R., Kent, S., Kirkby, D., Kremin, A., Krolewski, A., Lai, Y., Lan, T. -W., Landriau, M., Lang, D., Lasker, J., Goff, J. M. Le, Guillou, L. Le, Leauthaud, A., Levi, M. E., Li, T. S., Linder, E., Lodha, K., Magneville, C., Manera, M., Margala, D., Martini, P., Maus, M., McDonald, P., Medina-Varela, L., Meisner, A., Mena-Fernández, J., Miquel, R., Moon, J., Moore, S., Moustakas, J., Mudur, N., Mueller, E., Muñoz-Gutiérrez, A., Myers, A. D., Nadathur, S., Napolitano, L., Neveux, R., Newman, J. A., Nguyen, N. M., Nie, J., Niz, G., Noriega, H. E., Padmanabhan, N., Paillas, E., Palanque-Delabrouille, N., Pan, J., Penmetsa, S., Percival, W. J., Pieri, M., Pinon, M., Poppett, C., Porredon, A., Prada, F., Pérez-Fernández, A., Pérez-Ràfols, I., Rabinowitz, D., Raichoor, A., Ramírez-Pérez, C., Ramirez-Solano, S., Rashkovetskyi, M., Rezaie, M., Rich, J., Rocher, A., Rockosi, C., Roe, N. A., Rosado-Marin, A., Ross, A. J., Rossi, G., Ruggeri, R., Ruhlmann-Kleider, V., Samushia, L., Sanchez, E., Saulder, C., Schlafly, E. F., Schlegel, D., Schubnell, M., Seo, H., Sharples, R., Silber, J., Slosar, A., Smith, A., Sprayberry, D., Swanson, J., Tan, T., Tarlé, G., Trusov, S., Vaisakh, R., Valcin, D., Valdes, F., Vargas-Magaña, M., Verde, L., Walther, M., Wang, B., Wang, M. S., Weaver, B. A., Weaverdyck, N., Wechsler, R. H., Weinberg, D. H., White, M., Yu, J., Yu, Y., Yuan, S., Yèche, C., Zaborowski, E. A., Zarrouk, P., Zhang, H., Zhao, C., Zhao, R., Zhou, R., and Zou, H.
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Astrophysics - Cosmology and Nongalactic Astrophysics - Abstract
We present the DESI 2024 galaxy and quasar baryon acoustic oscillations (BAO) measurements using over 5.7 million unique galaxy and quasar redshifts in the range 0.1
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- 2024
22. Dark Matter Line Searches with the Cherenkov Telescope Array
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Abe, S., Abhir, J., Abhishek, A., Acero, F., Acharyya, A., Adam, R., Aguasca-Cabot, A., Agudo, I., Aguirre-Santaella, A., Alfaro, J., Alfaro, R., Alvarez-Crespo, N., Batista, R. Alves, Amans, J. -P., Amato, E., Ambrosi, G., Angel, L., Aramo, C., Arcaro, C., Arnesen, T. T. H., Arrabito, L., Asano, K., Ascasibar, Y., Aschersleben, J., Ashkar, H., Backes, M., Baktash, A., Balazs, C., Balbo, M., Larriva, A. Baquero, Martins, V. Barbosa, de Almeida, U. Barres, Barrio, J. A., Batković, I., Batzofin, R., Baxter, J., González, J. Becerra, Beck, G., Benbow, W., Berge, D., Bernardini, E., Bernete, J., Bernlöhr, K., Berti, A., Bertucci, B., Bhattacharjee, P., Bhattacharyya, S., Bigongiari, C., Biland, A., Bissaldi, E., Biteau, J., Blanch, O., Blazek, J., Bocchino, F., Boisson, C., Bolmont, J., Bonnoli, G., Bonollo, A., Bordas, P., Bosnjak, Z., Bottacini, E., Böttcher, M., Bringmann, T., Bronzini, E., Brose, R., Brown, A. M., Brunelli, G., Bulgarelli, A., Bulik, T., Burelli, I., Burmistrov, L., Burton, M., Buscemi, M., Bylund, T., Cailleux, J., Campoy-Ordaz, A., Cantlay, B. K., Capasso, G., Caproni, A., Capuzzo-Dolcetta, R., Caraveo, P., Caroff, S., Carosi, A., Carosi, R., Carquin, E., Carrasco, M. -S., Cassol, F., Castaldini, L., Castrejon, N., Castro-Tirado, A. J., Cerasole, D., Cerruti, M., Chadwick, P. M., Chaty, S., Chen, A. W., Chernyakova, M., Chiavassa, A., Chudoba, J., Chytka, L., Cicciari, G. M., Cifuentes, A., Araujo, C. H. Coimbra, Colapietro, M., Conforti, V., Conte, F., Contreras, J. L., Costa, A., Costantini, H., Cotter, G., Cristofari, P., Cuevas, O., Curtis-Ginsberg, Z., D'Amico, G., D'Ammando, F., Dai, S., Dalchenko, M., Dazzi, F., De Angelis, A., de Lavergne, M. de Bony, De Caprio, V., Pino, E. M. de Gouveia Dal, De Lotto, B., De Lucia, M., de Menezes, R., de Naurois, M., de Souza, V., del Peral, L., del Valle, M. V., Giler, A. G. Delgado, Mengual, J. Delgado, Delgado, C., Dell'aiera, M., della Volpe, D., Depaoli, D., Di Girolamo, T., Di Piano, A., Di Pierro, F., Di Tria, R., Di Venere, L., Díaz, C., Diebold, S., Dinesh, A., Djuvsland, J., Dominik, R. M., Prester, D. Dominis, Donini, A., Dorner, D., Dörner, J., Doro, M., Dournaux, J. -L., Duangchan, C., Dubos, C., Ducci, L., Dwarkadas, V. V., Ebr, J., Eckner, C., Egberts, K., Einecke, S., Elsässer, D., Emery, G., Errando, M., Escanuela, C., Escarate, P., Godoy, M. Escobar, Escudero, J., Esposito, P., Ettori, S., Falceta-Goncalves, D., Fedorova, E., Fegan, S., Feng, Q., Ferrand, G., Ferrarotto, F., Fiandrini, E., Fiasson, A., Filipovic, M., Fioretti, V., Fiori, M., Foffano, L., Guiteras, L. Font, Fontaine, G., Fröse, S., Fukazawa, Y., Fukui, Y., Furniss, A., Galanti, G., Galaz, G., Galelli, C., Gallozzi, S., Gammaldi, V., Garczarczyk, M., Gasbarra, C., Gasparrini, D., Ghalumyan, A., Gianotti, F., Giarrusso, M., Paiva, J. G. Giesbrecht Formiga, Giglietto, N., Giordano, F., Giuffrida, R., Glicenstein, J. -F., Glombitza, J., Goldoni, P., González, J. M., González, M. M., Coelho, J. Goulart, Gradetzke, T., Granot, J., Grasso, D., Grau, R., Gréaux, L., Green, D., Green, J. G., Grolleron, G., Guedes, L. M. V., Gueta, O., Hackfeld, J., Hadasch, D., Hamal, P., Hanlon, W., Hara, S., Harvey, V. M., Hassan, T., Hayashi, K., Heß, B., Heckmann, L., Heller, M., Cadena, S. Hernández, Hervet, O., Hinton, J., Hiroshima, N., Hnatyk, B., Hnatyk, R., Hofmann, W., Holder, J., Horan, D., Horvath, P., Hovatta, T., Hrabovsky, M., Hrupec, D., Iarlori, M., Inada, T., Incardona, F., Inoue, S., Inoue, Y., Iocco, F., Iori, M., Ishio, K., Jamrozy, M., Janecek, P., Jankowsky, F., Jean, P., Quiles, J. Jimenez, Jin, W., Juramy-Gilles, C., Jurysek, J., Kagaya, M., Kalekin, O., Karas, V., Katagiri, H., Kataoka, J., Kaufmann, S., Kazanas, D., Kerszberg, D., Kieda, D. B., Kleiner, T., Kluge, G., Kobayashi, Y., Kohri, K., Komin, N., Kornecki, P., Kosack, K., Kowal, G., Kubo, H., Kushida, J., La Barbera, A., La Palombara, N., Láinez, M., Lamastra, A., Lapington, J., Laporte, P., Lazarević, S., Lazendic-Galloway, J., Lemoine-Goumard, M., Lenain, J. -P., Leone, F., Leonora, E., Leto, G., Lindfors, E., Linhoff, M., Liodakis, I., Lipniacka, A., Lombardi, S., Longo, F., López-Coto, R., López-Moya, M., López-Oramas, A., Loporchio, S., Bahilo, J. Lozano, Luque-Escamilla, P. L., Macias, O., Majumdar, P., Mallamaci, M., Malyshev, D., Mandat, D., Manicò, G., Mariotti, M., Márquez, I., Marquez, P., Marsella, G., Martí, J., Martínez, G. A., Martínez, M., Martinez, O., Marty, C., Mas-Aguilar, A., Mastropietro, M., Mazin, D., Menchiari, S., Mestre, E., Meunier, J. -L., Meyer, D. M. -A., Meyer, M., Miceli, D., Miceli, M., Michailidis, M., Michałowski, J., Miener, T., Miranda, J. M., Mitchell, A., Mizote, M., Mizuno, T., Moderski, R., Molero, M., Molfese, C., Molina, E., Montaruli, T., Moralejo, A., Morcuende, D., Morselli, A., Moulin, E., Zamanillo, V. Moya, Munari, K., Murach, T., Muraczewski, A., Muraishi, H., Nakamori, T., Nayak, A., Nemmen, R., Neto, J. P., Nickel, L., Niemiec, J., Nieto, D., Rosillo, M. Nievas, Nikołajuk, M., Nikolić, L., Nishijima, K., Noda, K., Nosek, D., Novotny, V., Nozaki, S., Ohishi, M., Ohtani, Y., Okumura, A., Olive, J. -F., Ong, R. A., Orienti, M., Orito, R., Orlandini, M., Orlando, E., Orlando, S., Ostrowski, M., Otero-Santos, J., Oya, I., Pagano, I., Pagliaro, A., Palatiello, M., Panebianco, G., Paneque, D., Pantaleo, F. R., Paredes, J. M., Parmiggiani, N., Patricelli, B., Pe'er, A., Pech, M., Pecimotika, M., Pensec, U., Peresano, M., Pérez-Romero, J., Persic, M., Peters, K. P., Petruk, O., Piano, G., Pierre, E., Pietropaolo, E., Pihet, M., Pinchbeck, L., Pirola, G., Pittori, C., Plard, C., Podobnik, F., Pohl, M., Pollet, V., Ponti, G., Prandini, E., Principe, G., Priyadarshi, C., Produit, N., Prouza, M., Pueschel, E., Pühlhofer, G., Pumo, M. L., Queiroz, F., Quirrenbach, A., Rainò, S., Rando, R., Razzaque, S., Regeard, M., Reimer, A., Reimer, O., Reisenegger, A., Rhode, W., Ribeiro, D., Ribó, M., Ricci, C., Richtler, T., Rico, J., Rieger, F., Riitano, L., Rizi, V., Roache, E., Fernandez, G. Rodriguez, Frías, M. D. Rodríguez, Rodríguez-Vázquez, J. J., Romano, P., Romeo, G., Rosado, J., de Leon, A. Rosales, Rowell, G., Rudak, B., Ruiter, A. J., Rulten, C. B., Sadeh, I., Saha, L., Saito, T., Salzmann, H., Sánchez-Conde, M., Sandaker, H., Sangiorgi, P., Sano, H., Santander, M., Santos-Lima, R., Sapienza, V., Šarić, T., Sarkar, A., Sarkar, S., Saturni, F. G., Savarese, S., Scherer, A., Schiavone, F., Schipani, P., Schleicher, B., Schovanek, P., Schubert, J. L., Schwanke, U., Arroyo, M. Seglar, Seitenzahl, I. R., Sergijenko, O., Servillat, M., Siegert, T., Siejkowski, H., Siqueira, C., Sliusar, V., Slowikowska, A., Sol, H., Spencer, S. T., Spiga, D., Stamerra, A., Stanič, S., Starecki, T., Starling, R., Stawarz, Ł., Steppa, C., Hatlen, E. Sæther, Stolarczyk, T., Strišković, J., Suda, Y., Świerk, P., Tajima, H., Tak, D., Takahashi, M., Takeishi, R., Tavernier, T., Tejedor, L. A., Terauchi, K., Teshima, M., Testa, V., Tian, W. W., Tibaldo, L., Tibolla, O., Peixoto, C. J. Todero, Torradeflot, F., Torres, D. F., Tosti, G., Tothill, N., Toussenel, F., Tramacere, A., Travnicek, P., Tripodo, G., Trois, A., Truzzi, S., Tutone, A., Vaclavek, L., Vacula, M., Vallania, P., Vallés, R., van Eldik, C., van Scherpenberg, J., Vandenbroucke, J., Vassiliev, V., Acosta, M. Vázquez, Vecchi, M., Ventura, S., Vercellone, S., Verna, G., Viana, A., Viaux, N., Vigliano, A., Vignatti, J., Vigorito, C. F., Villanueva, J., Visentin, E., Vitale, V., Vodeb, V., Voisin, V., Voitsekhovskyi, V., Vorobiov, S., Voutsinas, G., Vovk, I., Vuillaume, T., Wagner, S. J., Walter, R., White, M., White, R., Wierzcholska, A., Will, M., Williams, D. A., Wohlleben, F., Wolter, A., Yamamoto, T., Yang, L., Yoshida, T., Yoshikoshi, T., Zaharijas, G., Zampieri, L., Sanchez, R. Zanmar, Zavrtanik, D., Zavrtanik, M., Zdziarski, A. A., Zech, A., Zhang, W., Zhdanov, V. I., Ziętara, K., Živec, M., and Zuriaga-Puig, J.
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High Energy Physics - Phenomenology ,Astrophysics - High Energy Astrophysical Phenomena ,High Energy Physics - Experiment - Abstract
Monochromatic gamma-ray signals constitute a potential smoking gun signature for annihilating or decaying dark matter particles that could relatively easily be distinguished from astrophysical or instrumental backgrounds. We provide an updated assessment of the sensitivity of the Cherenkov Telescope Array (CTA) to such signals, based on observations of the Galactic centre region as well as of selected dwarf spheroidal galaxies. We find that current limits and detection prospects for dark matter masses above 300 GeV will be significantly improved, by up to an order of magnitude in the multi-TeV range. This demonstrates that CTA will set a new standard for gamma-ray astronomy also in this respect, as the world's largest and most sensitive high-energy gamma-ray observatory, in particular due to its exquisite energy resolution at TeV energies and the adopted observational strategy focussing on regions with large dark matter densities. Throughout our analysis, we use up-to-date instrument response functions, and we thoroughly model the effect of instrumental systematic uncertainties in our statistical treatment. We further present results for other potential signatures with sharp spectral features, e.g.~box-shaped spectra, that would likewise very clearly point to a particle dark matter origin., Comment: 44 pages JCAP style (excluding author list and references), 19 figures; minor changes to match published version
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- 2024
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23. Baryon Acoustic Oscillation Theory and Modelling Systematics for the DESI 2024 results
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Chen, Shi-Fan, Howlett, Cullan, White, Martin, McDonald, Patrick, Ross, Ashley J., Seo, Hee-Jong, Padmanabhan, Nikhil, Aguilar, J., Ahlen, S., Alam, S., Alves, O., Andrade, U., Blum, R., Brooks, D., Chen, X., Cole, S., Davis, T. M., Dawson, K., de la Macorra, A., Dey, Arjun, Ding, Z., Doel, P., Ferraro, S., Font-Ribera, A., Forero-Sánchez, D., Forero-Romero, J. E., Garcia-Quintero, C., Gaztañaga, E., Gontcho, S. Gontcho A, Hanif, M. M. S, Honscheid, K., Kisner, T., Kremin, A., Lambert, A., Landriau, M., Levi, M. E., Manera, M., Meisner, A., Mena-Fernández, J., Miquel, R., Muñoz-Gutiérrez, A., Paillas, E., Palanque-Delabrouille, N., Percival, W. J., Prada, F., Pérez-Fernández, A., Rashkovetskyi, M., Rezaie, M., Rosado-Marin, A., Rossi, G., Ruggeri, R., Sanchez, E., Schlegel, D., Silber, J., Tarlé, G., Vargas-Magaña, M., Weaver, B. A., Yu, J., Yuan, S., Zhou, R., and Zhou, Z.
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Astrophysics - Cosmology and Nongalactic Astrophysics - Abstract
This paper provides a comprehensive overview of how fitting of Baryon Acoustic Oscillations (BAO) is carried out within the upcoming Dark Energy Spectroscopic Instrument's (DESI) 2024 results using its DR1 dataset, and the associated systematic error budget from theory and modelling of the BAO. We derive new results showing how non-linearities in the clustering of galaxies can cause potential biases in measurements of the isotropic ($\alpha_{\mathrm{iso}}$) and anisotropic ($\alpha_{\mathrm{ap}}$) BAO distance scales, and how these can be effectively removed with an appropriate choice of reconstruction algorithm. We then demonstrate how theory leads to a clear choice for how to model the BAO and develop, implement and validate a new model for the remaining smooth-broadband (i.e., without BAO) component of the galaxy clustering. Finally, we explore the impact of all remaining modelling choices on the BAO constraints from DESI using a suite of high-precision simulations, arriving at a set of best-practices for DESI BAO fits, and an associated theory and modelling systematic error. Overall, our results demonstrate the remarkable robustness of the BAO to all our modelling choices and motivate a combined theory and modelling systematic error contribution to the post-reconstruction DESI BAO measurements of no more than $0.1\%$ ($0.2\%$) for its isotropic (anisotropic) distance measurements. We expect the theory and best-practices laid out to here to be applicable to other BAO experiments in the era of DESI and beyond., Comment: 30 pages, 18 figures, 1 table, updated to match version accepted by MNRAS
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- 2024
24. Long-term outcomes of primary ventral hernia repair associated with rectus diastasis
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Sánchez-Arteaga, Alejandro, Moreno-Suero, Francisco, Feria-Madueño, Adrián, Tinoco-González, José, Bustos-Jiménez, Manuel, Tejero-Rosado, Antonio, Padillo-Ruíz, Javier, and Tallón-Aguilar, Luis
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- 2024
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25. Tuberculosis in otherwise healthy adults with inherited TNF deficiency
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Arias, Andrés A., Neehus, Anna-Lena, Ogishi, Masato, Meynier, Vincent, Krebs, Adam, Lazarov, Tomi, Lee, Angela M., Arango-Franco, Carlos A., Yang, Rui, Orrego, Julio, Corcini Berndt, Melissa, Rojas, Julian, Li, Hailun, Rinchai, Darawan, Erazo-Borrás, Lucia, Han, Ji Eun, Pillay, Bethany, Ponsin, Khoren, Chaldebas, Matthieu, Philippot, Quentin, Bohlen, Jonathan, Rosain, Jérémie, Le Voyer, Tom, Janotte, Till, Amarajeeva, Krishnajina, Soudée, Camille, Brollo, Marion, Wiegmann, Katja, Marquant, Quentin, Seeleuthner, Yoann, Lee, Danyel, Lainé, Candice, Kloos, Doreen, Bailey, Rasheed, Bastard, Paul, Keating, Narelle, Rapaport, Franck, Khan, Taushif, Moncada-Vélez, Marcela, Carmona, María Camila, Obando, Catalina, Alvarez, Jesús, Cataño, Juan Carlos, Martínez-Rosado, Larry Luber, Sanchez, Juan P., Tejada-Giraldo, Manuela, L’Honneur, Anne-Sophie, Agudelo, María L., Perez-Zapata, Lizet J., Arboleda, Diana M., Alzate, Juan Fernando, Cabarcas, Felipe, Zuluaga, Alejandra, Pelham, Simon J., Ensser, Armin, Schmidt, Monika, Velásquez-Lopera, Margarita M., Jouanguy, Emmanuelle, Puel, Anne, Krönke, Martin, Ghirardello, Stefano, Borghesi, Alessandro, Pahari, Susanta, Boisson, Bertrand, Pittaluga, Stefania, Ma, Cindy S., Emile, Jean-François, Notarangelo, Luigi D., Tangye, Stuart G., Marr, Nico, Lachmann, Nico, Salvator, Hélène, Schlesinger, Larry S., Zhang, Peng, Glickman, Michael S., Nathan, Carl F., Geissmann, Frédéric, Abel, Laurent, Franco, José Luis, Bustamante, Jacinta, Casanova, Jean-Laurent, and Boisson-Dupuis, Stéphanie
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- 2024
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26. Validation of independent prognostic significance of blast count in a large cohort of MDS patients
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Al Amri, Raniah, Baloda, Vandana, Monaghan, Sara A., Rosado, Flavia G., Moore, Erika M., Rea, Bryan, Djokic, Miroslav, Aggarwal, Nidhi, Yatsenko, Svetlana A., and Bailey, Nathanael G.
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- 2024
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27. Sociodemographic predictors of perceived weight discrimination
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Gerend, Mary A., Wilkinson, Lucille J., Sutin, Angelina R., Rosado, Javier I., Ehrlich, Katherine B., Smith, David W., and Maner, Jon K.
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- 2024
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28. Acute Consumption of Cooked Green Banana Pulp Beverage (Musa cavendishii) Decreases Plasma Glucose in Healthy Women: A Cross-Sectional Controlled Study
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Zago, Lilia, Pessoa, Heloisa Rodrigues, Rosado, Carolyne Pimentel, da Silva, Andreia Ana, Pasqualone, Antonella, and Koury, Josely Correa
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- 2024
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29. Potential Trimethylamine (TMA)-Producing Bacteria in patients with chronic kidney disease undergoing hemodialysis
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Alvarenga, Livia, Kemp, Julie Ann, Schultz, Júnia, Cardozo, Ludmila F. M. F., Nakao, Lia S., Ribeiro-Alves, Marcelo, Rosado, Alexandre, and Mafra, Denise
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- 2024
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30. The Opioid Epidemic and Faith-Based Responses in Southern Appalachia, USA: An Exploration of Factors for Successful Cross-Sector Collaboration
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McCarty, Brett, Hanlen-Rosado, Emily, Taylor, Jamilah, Yang, Emmy, Corneli, Amy, and Curlin, Farr
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- 2024
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31. Homodyned K-Distribution Parameter Estimation in Quantitative Ultrasound: Autoencoder and Bayesian Neural Network Approaches
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Tehrani, Ali K. Z., Cloutier, Guy, Tang, An, Rosado-Mendez, Ivan M., and Rivaz, Hassan
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Electrical Engineering and Systems Science - Signal Processing - Abstract
Quantitative ultrasound (QUS) analyzes the ultrasound backscattered data to find the properties of scatterers that correlate with the tissue microstructure. Statistics of the envelope of the backscattered radiofrequency (RF) data can be utilized to estimate several QUS parameters. Different distributions have been proposed to model envelope data. The homodyned K-distribution (HK distribution) is one of the most comprehensive distributions that can model ultrasound backscattered envelope data under diverse scattering conditions (varying scatterer number density and coherent scattering). The scatterer clustering parameter (alpha) and the ratio of the coherent to diffuse scattering power (k) are the parameters of this distribution that have been used extensively for tissue characterization in diagnostic ultrasound. The estimation of these two parameters (which we refer to as HK parameters) is done using optimization algorithms in which statistical features such as the envelope point-wise signalto-noise ratio (SNR), skewness, kurtosis, and the log-based moments have been utilized as input to such algorithms. The optimization methods minimize the difference between features and their theoretical value from the HK model. We propose that the true value of these statistical features is a hyperplane that covers a small portion of the feature space. In this paper, we follow two approaches to reduce the effect of sample features' error. We propose a model projection neural network based on denoising autoencoders to project the noisy features into this space based on this assumption. We also investigate if the noise distribution can be learned by the deep estimators. We compare the proposed methods with conventional methods using simulations, an experimental phantom, and data from an in vivo animal model of hepatic steatosis. A demo code are available online at http://code.sonography.ai
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- 2024
32. Understanding the Nonlinear Response of SiPMs
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Moya, Victor and Rosado, Jaime
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Physics - Instrumentation and Detectors ,High Energy Physics - Experiment ,Nuclear Experiment ,Physics - Medical Physics - Abstract
A systematic study of the nonlinear response of Silicon Photomultipliers (SiPMs) has been conducted through Monte Carlo simulations. SiPMs have been proven to show a universal nonlinear response when it is expressed in terms of relative parameters independent of both the gain and the photon detection efficiency (PDE). Nonlinearity has been shown to mainly depend on the balance between the photon rate and the pixel recovery time. However, exponential-like and finite light pulses have been found to lead to different nonlinear behaviors, which also depend on the correlated noise, the overvoltage dependence of the PDE, and the impedance of the readout circuit. Correlated noise has been shown to have a minor impact on nonlinearity, but it can significantly affect the shape of the SiPM output current. Considering these dependencies and previous statistical analysis of the nonlinear response of SiPMs, two simple fitting models have been proposed for exponential-like and finite light pulses, explaining the role of their various terms and parameters. Even though these models have only three fitting parameters, they provide an accurate description of the nonlinear response of SiPMs for a wide range of situations.
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- 2024
33. Extraplanar emission in isolated edge-on late-type galaxies. I. The H$\alpha$ distribution versus to the old and young stellar discs
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Sardaneta, Minerva M., Amram, Philippe, Rampazzo, Roberto, Rosado, Margarita, Sanchez-Cruces, Monica, Fuentes-Carrera, Isaura, and Ghosh, Soumavo
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Astrophysics - Astrophysics of Galaxies - Abstract
Isolated galaxies are the ideal reference sample to study the galaxy structure minimising potential environmental effects. We selected a complete sample of 14 nearby, late-type, highly inclined ($i\geq80^{\circ}$), isolated galaxies from the Catalogue of Isolated Galaxies (CIG) which offers a vertical view of their disc structure. We aim to study extraplanar Diffuse Ionized Gas (eDIG) by comparing the old and young disc components traced by near-infrared (NIR) and Ultraviolet (UV) imaging with the H$\alpha$ emission structure. We obtained H$\alpha$ monochromatic maps from the Fabry-Perot (FP) interferometry, while the old and young discs structures are obtained from the photometric analysis of the 2MASS K$_{s}$-band, and GALEX NUV and FUV images, thereby identifying the stellar disc and whether the eDIG is present. The H$\alpha$ morphology is peculiar in CIG 71, CIG 183, CIG 593 showing clear asymmetries. In general, geometric parameters (isophotal position angle, peak light distribution, inclination) measured from H$\alpha$, UV and NIR show minimal differences (e.g. $\Delta i\leq\pm$10$^{\circ}$), suggesting that interaction does not play a significant role in shaping the morphology, as expected in isolated galaxies. From H$\alpha$ maps, the eDIG was detected vertically in 11 out of 14 galaxies. Although the fraction of eDIG is high, the comparison between our sample and a generic sample of inclined spirals suggests that the phenomenon is uncorrelated to the galaxy environment. As suggested by the extraplanar UV emission found in 13 out of 14 galaxies the star formation extends well beyond the disc defined by the H$\alpha$ map., Comment: Accepted for its publication in MNRAS. Manuscript ID: MN-23-2536-MJ.R1
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- 2024
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34. Preliminary Excavations of Secondary burials in San Juan, Puerto Rico
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Marrero-Rosado, José L. and Agarwal, Sabrina C.
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- 2024
35. Comment on 'Generalized James' Effective Hamiltonian Method'
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Rosado, Wilson and Arraut, Ivan
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Physics - General Physics - Abstract
In the paper carried out by Wenjun et al. \cite{Shao2017}, a generalization of the James effective dynamics theory based on a first version of the James method was presented. This however, is not a very rigorous way of deriving the effective third-order expansion for an interaction Hamiltonian with harmonic time-dependence. In fact, here we show that the third-order Hamiltonian obtained in \cite{Shao2017} is not Hermitian for general situations when we consider time-dependence. Its non-Hermitian nature arises from the foundation of the theory itself. In this comment paper, the most general expression of the effective Hamiltonian expanded up to third order is obtained. Our derived effective Hamiltonian is Hermitian even in situations where we have time-dependence., Comment: 6 pages, published in Physical Review A
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- 2023
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36. A $(3+\epsilon)$-approximation algorithm for the minimum sum of radii problem with outliers and extensions for generalized lower bounds
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Buchem, Moritz, Ettmayr, Katja, Rosado, Hugo Kooki Kasuya, and Wiese, Andreas
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Computer Science - Data Structures and Algorithms ,Computer Science - Computational Geometry - Abstract
For a given set of points in a metric space and an integer $k$, we seek to partition the given points into $k$ clusters. For each computed cluster, one typically defines one point as the center of the cluster. A natural objective is to minimize the sum of the cluster center's radii, where we assign the smallest radius $r$ to each center such that each point in the cluster is at a distance of at most $r$ from the center. The best-known polynomial time approximation ratio for this problem is $3.389$. In the setting with outliers, i.e., we are given an integer $m$ and allow up to $m$ points that are not in any cluster, the best-known approximation factor is $12.365$. In this paper, we improve both approximation ratios to $3+\epsilon$. Our algorithms are primal-dual algorithms that use fundamentally new ideas to compute solutions and to guarantee the claimed approximation ratios. For example, we replace the classical binary search to find the best value of a Lagrangian multiplier $\lambda$ by a primal-dual routine in which $\lambda$ is a variable that is raised. Also, we show that for each connected component due to almost tight dual constraints, we can find one single cluster that covers all its points and we bound its cost via a new primal-dual analysis. We remark that our approximation factor of $3+\epsilon$ is a natural limit for the known approaches in the literature. Then, we extend our results to the setting of lower bounds. There are algorithms known for the case that for each point $i$ there is a lower bound $L_{i}$, stating that we need to assign at least $L_{i}$ clients to $i$ if $i$ is a cluster center. For this setting, there is a $ 3.83$ approximation if outliers are not allowed and a ${12.365}$-approximation with outliers. We improve both ratios to $3.5 + \epsilon$ and, at the same time, generalize the type of allowed lower bounds.
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- 2023
37. Rethinking Urban Water Management Through Drivers-Pressures-States-Impacts-Responses Framework Application in Chennai, India
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Rosado, Daniel, Fárez-Román, Valeria, Müller, Felix, Nambi, Indumathi, and Fohrer, Nicola
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- 2024
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38. Alt-Labour and Worker Centres
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Rosado Marzán, César F., Davidov, Guy, book editor, Langille, Brian, book editor, and Lester, Gillian, book editor
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- 2024
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39. PCNEO, a New Proficiency Testing Program for Flow Cytometric Analysis of Plasma Cell Neoplasms From the College of American Pathologists Diagnostic Immunology and Flow Cytometry Committee
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Dorfman, David M., Devitt, Katherine A., Cui, Wei, Bashleben, Christine, Naharro, Elena C. Frye, Hedley, Benjamin, Hupp, Meghan, Karlon, William J., Murphy, Claire E., Cherian, Sindhu, Olteanu, Horatiu, Seifert, Robert P., Rosado, Flavia N., and Linden, Michael A.
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Flow cytometry -- Evaluation ,T cells -- Health aspects ,B cells -- Health aspects ,Plasma cell diseases -- Diagnosis -- Care and treatment ,Health - Abstract
* Context.--In 2018 the College of American Pathologists Diagnostic Immunology and Flow Cytometry Committee designed and implemented a new plasma cell neoplasia flow cytometry proficiency testing program--PCNEO--to allow clinical flow cytometry laboratories to monitor and assess their performance compared with a peer group. Objective.--To report the results from the first 4 years of the PCNEO program. Design.--Program participants were sent 2 sets of challenges per year, each including 1 wet challenge and 2 dry challenges, with associated clinical and laboratory findings. The wet challenges were composed of myeloma cell line specimens (with or without dilution in preserved whole blood) for flow cytometric analysis. The dry (paper) challenges were composed of clinical case summaries and images of flow cytometric test results from various flow cytometry laboratories of committee members. Results.--A total of 116 to 145 laboratories from 17 countries enrolled in the proficiency testing program. For the wet challenges, almost all participants (97%-100%; cumulative, 98.2%) correctly identified the presence of neoplastic plasma cell populations based on flow cytometric analysis of undiluted myeloma cell lines. Slightly fewer participants (89.0%-97.4%; cumulative, 95.2%) correctly identified the presence of neoplastic plasma cell populations based on flow cytometric analysis of diluted myeloma cell lines (10% or 50% dilutions into peripheral blood) intended to better represent a typical clinical sample. There was generally agreement among 80% or more of participants for positive or negative staining for CD38, CD138, CD19, CD20, and surface and cytoplasmic k and X light chains. Similarly, 84% to 100% of participants were able to correctly identify the presence of neoplastic plasma cell populations in paper challenges, including the presence of small, neoplastic plasma cell populations (0.01%-5.0% clonal plasma cells) and the presence of nonneoplastic plasma cell populations (correctly identified by 91 %-96% of participants). Conclusions.--Participant performance in the new proficiency testing program was excellent overall, with the vast majority of participants able to perform flow cytometric analysis and identify neoplastic plasma cell populations and to identify small plasma cell clones or expanded populations of reactive plasma cells in dry challenge flow cytometry results. This program will allow laboratories to verify the accuracy of their testing program and test interpretations for the assessment of patients suspected of having a plasma cell neoplasm. (Arch Pathol Lab Med. 2024;148:699-704; doi: 10.5858/arpa. 2023-0035-CP), The Diagnostic Immunology and Flow Cytometry Committee (DIFCC) acts as an expert scientific and educational resource for the College of American Pathologists in diagnostic immunology and flow cytometry clinical testing. [...]
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- 2024
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40. Utilizing 3-D Digital Models in Synchronous Blended Anatomy & Physiology Courses during the COVID-19 Pandemic
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Luis D. Rosado
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The use of electronic media in the classroom was prevalent during the height of the COVID-19 global pandemic because it afforded the health and safety of students in blended course modalities. This project aimed to quantify the effectiveness of a three-dimensional computer-based human anatomical online platform in a blended synchronous course design. We asked our students to self-report the learning efficacy and overall student engagement of the online learning platform. We found that with intentional course design utilizing in-person anchored Zoom Buddy blended classes and a 3-D anatomy software, students reported high levels of learning efficacy and engagement in anatomy & physiology courses. The course design presented in this paper provides a viable option should we be faced with similar emergency learning situations or when course enrollments are high and class spaces are limited.
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- 2023
41. Influence of the metal post material, tooth location in the dental arch, and metal artifact reduction tool on vertical root fracture diagnosis in cone beam CT
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Rosado, Lucas P. Lopes, Fontenele, Rocharles Cavalcante, Farias-Gomes, Amanda, Freitas, Deborah Queiroz, and Neves, Frederico Sampaio
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- 2024
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42. Promoting clinical reasoning in undergraduate Family Medicine curricula through concept mapping: a qualitative approach
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Fonseca, Marta, Marvão, Pedro, Rosado-Pinto, Patrícia, Rendas, António, and Heleno, Bruno
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- 2024
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43. Keys of accelerators success: evidence from Spain
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Rosado-Cubero, Ana, Hernández, Adolfo, Blanco-Jiménez, Francisco José, and Freire-Rubio, Teresa
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- 2024
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44. Unexpected coexistence of a native and an invasive macrophyte: a functional versus environmental niche perspective
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Florêncio, Fernanda Moreira, Rosado, Aline, Leal, Rodrigo Pedro, and Vecchia, Alice Dalla
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- 2024
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45. Seismic effects at GPS stations: Case study of the 24 August 2016 Amatrice earthquake
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Cibeira Urtiaga, Ángel, Berrocoso, Manuel, Rosado, Belén, and Pazos, Antonio
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- 2024
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46. Relationship between aging and excess body fat with markers of inflammation, skeletal muscle mass and strength in Mexican community-dwelling people
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Mendoza-Núñez, Víctor Manuel, Aguilar-Curiel, Jimena Valeria, Castillo-Martínez, Lilia, Rodríguez-García, Wendy Daniella, Vaquero-Barbosa, Nayeli, Rosado-Pérez, Juana, and Arista-Ugalde, Taide Laurita
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- 2024
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47. Diabetic Neuropathy: Pathophysiology Review
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Strand, Natalie, Anderson, Meredith A., Attanti, Sumedha, Gill, Benjamin, Wie, Christopher, Dawodu, Azizat, Pagan-Rosado, Robert, Harbell, Monica W., and Maloney, Jillian A.
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- 2024
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48. Evaluation of Mastadenovirus and Rotavirus Presence in Phyllostomid, Vespertilionid, and Molossid Bats Captured in Rio Grande do Sul, Southern Brazil
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Sita, Alexandre, Birlem, Gabriela Espíndola, de Souza da Silva, Deivid, Possamai, Gabriela Mattos, Petry, Karla, de Almeida, Paula Rodrigues, Mallmann, Larissa, Stein, Janaína Franciele, Demoliner, Meriane, Gularte, Juliana Schons, Hansen, Alana Witt, Witt, André Alberto, Rigotto, Caroline, Fleck, Juliane Deise, Spilki, Fernando Rosado, da Rocha, Daniela Tonini, and Weber, Matheus Nunes
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- 2024
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49. Amphichorda monjolensis sp. nov., a new fungal species isolated from a Brazilian limestone cave, with an update on acremonium-like species in Bionectriaceae
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Leão, Ana Flávia, Condé, Thiago Oliveira, Dutra, Yan Lucas Gomes, Rosado, André Wilson Campos, Grazziotti, Paulo Henrique, de Carvalho Neves, Soraya, Fraga, Lucio Mauro Soares, Kasuya, Maria Catarina Megumi, and Pereira, Olinto Liparini
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- 2024
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50. FTIR-ATR chemometric analysis on pelagic Sargassum reveals chemical composition changes induced by cold sample transportation and sunlight radiation
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Peniche-Pavía, Héctor A., Tzuc-Naveda, José D., Rosado-Espinosa, Luis A., and Collí-Dulá, Reyna Cristina
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- 2024
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