Author: "Krumholz, M." / Language: english - Searchworks@Jio Institute Digital Library Search Results

26 results on '"Krumholz, M."'

1. Constraining the LyC escape fraction from LEGUS star clusters with SIGNALS HII region observations: A pilot study of NGC 628

Author: Teh, J. W., Grasha, K., Krumholz, M. R., Battisti, A., Calzetti, D., Rousseau-Nepton, L., Rhea, C., Adamo, A., Kennicutt, R. C., Grebel, E. K., Cook, D. O., Combes, F., Messa, M., Linden, S., Klessen, R. S., Vilchez, J. M., Fumagalli, M., McLeod, A. F., Smith, L. J., Chemin, L., Wang, J., Sabbi, E., Sacchi, E., Petric, A., Della Bruna, L., and Boselli, A.
Subjects: Astrophysics of Galaxies (astro-ph.GA), FOS: Physical sciences, Astrophysics - Astrophysics of Galaxies
Abstract: The ionising radiation of young and massive stars is a crucial form of stellar feedback. Most ionising (Lyman-continuum; LyC, $\lambda < 912A$) photons are absorbed close to the stars that produce them, forming compact HII regions, but some escape into the wider galaxy. Quantifying the fraction of LyC photons that escape is an open problem. In this work, we present a semi-novel method to estimate the escape fraction by combining broadband photometry of star clusters from the Legacy ExtraGalactic UV Survey (LEGUS) with HII regions observed by the Star formation, Ionized gas, and Nebular Abundances Legacy Survey (SIGNALS) in the nearby spiral galaxy NGC 628. We first assess the completeness of the combined catalogue, and find that 49\% of HII regions lack corresponding star clusters as a result of a difference in the sensitivities of the LEGUS and SIGNALS surveys. For HII regions that do have matching clusters, we infer the escape fraction from the difference between the ionising power required to produce the observed HII luminosity and the predicted ionising photon output of their host star clusters; the latter is computed using a combination of LEGUS photometric observations and a stochastic stellar population synthesis code SLUG (Stochastically Lighting Up Galaxies). Overall, we find an escape fraction of $f_{esc} = 0.09^{+0.06}_{-0.06}$ across our sample of 42 HII regions; in particular, we find HII regions with high $f_{esc}$ are predominantly regions with low H$\alpha$-luminosity. We also report possible correlation between $f_{esc}$ and the emission lines [O ii]/[N ii] and [O ii]/H$\beta$., Comment: Accepted for publication at MNRAS
Published: 2023

2. Sensitivity of the Cherenkov Telescope Array to a dark matter signal from the Galactic centre

Author: Abdalla, H., Abe, H., Abe, S., Abusleme, A., Acero, F., Acharyya, A., Acín Portella, V., Ackley, K., Adam, R., Adams, C., Adhikari, S. S., Aguado-Ruesga, I., Agudo, I., Aguilera, R., Aguirre-Santaella, A., Aharonian, F., Alberdi, A., Alfaro, R., Alfaro, J., Alispach, C., Aloisio, R., Alves Batista, R., Amans, J. -P, Amati, L., Amato, E., Ambrogi, L., Ambrosi, G., Ambrosio, M., Ammendola, R., Anderson, J., Anduze, M., Angüner, E. O., Antonelli, L. A., Antonuccio, V., Antoranz, P., Anutarawiramkul, R., Aragunde Gutierrez, J., Aramo, C., Araudo, A., Araya, M., Arbet-Engels, A., Arcaro, C., Arendt, V., Armand, C., Armstrong, T., Arqueros, F., Arrabito, L., Arsioli, B., Artero, M., Asano, K., Ascasíbar, Y., Aschersleben, J., Ashley, M., Attinà, P., Aubert, P., Singh, C. B., Baack, D., Babic, A., Backes, M., Baena, V., Bajtlik, S., Baktash, A., Balazs, C., Balbo, M., Ballester, O., Ballet, J., Balmaverde, B., Bamba, A., Bandiera, R., Baquero Larriva, A., Barai, P., Barbier, C., Barbosa Martins, V., Barcelo, M., Barkov, M., Barnard, M., Baroncelli, L., Barres Almeida, U., Barrio, J. A., Bastieri, D., Batista, P. I., Batkovic, I., Bauer, C., Bautista-González, R., Baxter, J., Becciani, U., Becerra González, J., Becherini, Y., Beck, G., Becker Tjus, J., Bednarek, W., Belfiore, A., Bellizzi, L., Belmont, R., Benbow, W., Berge, D., Bernardini, E., Bernardos, M. I., Bernlöhr, K., Berti, A., Berton, M., Bertucci, B., Beshley, V., Bhatt, N., Bhattacharyya, S., Bhattacharyya, W., Bi, B., Bicknell, G., Biederbeck, N., Bigongiari, C., Biland, A., Bird, R., Bissaldi, E., Biteau, J., Bitossi, M., Blanch, O., Blank, M., Blazek, J., Bobin, J., Boccato, C., Bocchino, F., Boehm, C., Bohacova, M., Boisson, C., Boix, J., Bolle, J. -P, Bolmont, J., Bonanno, G., Bonavolontà, C., Bonneau Arbeletche, L., Bonnoli, G., Bordas, P., Borkowski, J., Bórquez, S., Bose, R., Bose, D., Bosnjak, Z., Bottacini, E., Böttcher, M., Botticella, M. T., Boutonnet, C., Bouyjou, F., Bozhilov, V., Bozzo, E., Brahimi, L., Braiding, C., Brau-Nogué, S., Breen, S., Bregeon, J., Breuhaus, M., Brill, A., Brisken, W., Brocato, E., Brown, A. M., Brügge, K., Brun, P., Brun, F., Brunetti, L., Brunetti, G., Bruno, P., Bruno, A., Bruzzese, A., Bucciantini, N., Buckley, J., Bühler, R., Bulgarelli, A., Bulik, T., Bünning, M., Bunse, M., Burton, M., Burtovoi, A., Buscemi, M., Buschjäger, S., Busetto, G., Buss, J., Byrum, K., Caccianiga, A., Cadoux, F., Calanducci, A., Calderón, C., Calvo Tovar, J., Cameron, R., Campaña, P., Canestrari, R., Cangemi, F., Cantlay, B., Capalbi, M., Capasso, M., Cappi, M., Caproni, A., Capuzzo-Dolcetta, R., Caraveo, P., Cárdenas, V., Cardiel, L., Cardillo, M., Carlile, C., Caroff, S., Carosi, R., Carosi, A., Carquín, E., Carrère, M., Casandjian, J. -M, Casanova, S., Cascone, E., Cassol, F., Castro-Tirado, A. J., Catalani, F., Catalano, O., Cauz, D., Ceccanti, A., Celestino Silva, C., Celli, S., Cerny, K., Cerruti, M., Chabanne, E., Chadwick, P., Chai, Y., Chambery, P., Champion, C., Chandra, S., Chaty, S., Chen, A., Cheng, K., Chernyakova, M., Chiaro, G., Chiavassa, A., Chikawa, M., Chitnis, V. R., Chudoba, J., Chytka, L., Cikota, S., Circiello, A., Clark, P., Çolak, M., Colombo, E., Colome, J., Colonges, S., Comastri, A., Compagnino, A., Conforti, V., Congiu, E., Coniglione, R., Conrad, J., Conte, F., Contreras, J. L., Coppi, P., Cornat, R., Coronado-Blazquez, J., Cortina, J., Costa, A., Costantini, H., Cotter, G., Courty, B., Covino, S., Crestan, S., Cristofari, P., Crocker, R., Croston, J., Cubuk, K., Cuevas, O., Cui, X., Cusumano, G., Cutini, S., D’aì, A., D’amico, G., D’ammando, F., D’avanzo, P., Da Vela, P., Dadina, M., Dai, S., Dalchenko, M., Dall’ Ora, M., Daniel, M. K., Dauguet, J., Davids, I., Davies, J., Dawson, B., Angelis, A., Araújo Carvalho, A. E., Bony Lavergne, M., Caprio, V., Cesare, G., Frondat, F., Gouveia Dal Pino, E. M., La Calle, I., Lotto, B., Luca, A., Martino, D., Menezes, R. M., Naurois, M., Oña Wilhelmi, E., Palma, F., Persio, F., Simone, N., Souza, V., Del Santo, M., Del Valle, M. V., Delagnes, E., Deleglise, G., Delfino Reznicek, M., Delgado, C., Delgado Giler, A. G., Delgado Mengual, J., Della Ceca, R., Della Valle, M., Della Volpe, D., Depaoli, D., Depouez, D., Devin, J., Di Girolamo, T., Di Giulio, C., Di Piano, A., Di Pierro, F., Di Venere, L., Díaz, C., Díaz-Bahamondes, C., Dib, C., Diebold, S., Digel, S., Dima, R., Djannati-Ataï, A., Djuvsland, J., Dmytriiev, A., Docher, K., Domínguez, A., Dominis Prester, D., Donath, A., Donini, A., Dorner, D., Doro, M., Dos Anjos, R. D. C., Dournaux, J. -L, Downes, T., Drake, G., Drass, H., Dravins, D., Duangchan, C., Duara, A., Dubus, G., Ducci, L., Duffy, C., Dumora, D., Dundas Morå, K., Durkalec, A., Dwarkadas, V. V., Ebr, J., Eckner, C., Eder, J., Ederoclite, A., Edy, E., Egberts, K., Einecke, S., Eisch, J., Eleftheriadis, C., Elsässer, D., Emery, G., Emmanoulopoulos, D., Ernenwein, J. -P, Errando, M., Escarate, P., Escudero, J., Espinoza, C., Ettori, S., Eungwanichayapant, A., Evans, P., Evoli, C., Fairbairn, M., Falceta-Goncalves, D., Falcone, A., Fallah Ramazani, V., Falomo, R., Farakos, K., Fasola, G., Fattorini, A., Favre, Y., Fedora, R., Fedorova, E., Fegan, S., Feijen, K., Feng, Q., Ferrand, G., Ferrara, G., Ferreira, O., Fesquet, M., Fiandrini, E., Fiasson, A., Filipovic, M., Fink, D., Finley, J. P., Fioretti, V., Fiorillo, D. F. G., Fiorini, M., Flis, S., Flores, H., Foffano, L., Föhr, C., Fonseca, M. V., Font, L., Fontaine, G., Fornieri, O., Fortin, P., Fortson, L., Fouque, N., Fournier, A., Fraga, B., Franceschini, A., Franco, F. J., Franco Ordovas, A., Freixas Coromina, L., Fresnillo, L., Fruck, C., Fugazza, D., Fujikawa, Y., Fujita, Y., Fukami, S., Fukazawa, Y., Fukui, Y., Fulla, D., Funk, S., Furniss, A., Gabella, O., Gabici, S., Gaggero, D., Galanti, G., Galaz, G., Galdemard, P., Gallant, Y., Galloway, D., Gallozzi, S., Gammaldi, V., Garcia, R., Garcia, E., García, E., Garcia López, R., Garczarczyk, M., Gargano, F., Gargano, C., Garozzo, S., Gascon, D., Gasparetto, T., Gasparrini, D., Gasparyan, H., Gaug, M., Geffroy, N., Gent, A., Germani, S., Gesa, L., Ghalumyan, A., Ghedina, A., Ghirlanda, G., Gianotti, F., Giarrusso, S., Giarrusso, M., Giavitto, G., Giebels, B., Giglietto, N., Gika, V., Gillardo, F., Gimenes, R., Giordano, F., Giovannini, G., Giro, E., Giroletti, M., Giuliani, A., Giunti, L., Gjaja, M., Glicenstein, J. -F, Gliwny, P., Godinovic, N., Göksu, H., Goldoni, P., Gómez, J. L., Gómez-Vargas, G., González, M. M., González, J. M., Gothe, K. S., Götz, D., Goulart Coelho, J., Gourgouliatos, K., Grabarczyk, T., Graciani, R., Grandi, P., Grasseau, G., Grasso, D., Green, A. J., Green, D., Green, J., Greenshaw, T., Grenier, I., Grespan, P., Grillo, A., Grondin, M. -H, Grube, J., Guarino, V., Guest, B., Gueta, O., Gündüz, M., Gunji, S., Gusdorf, A., Gyuk, G., Hackfeld, J., Hadasch, D., Haga, J., Hagge, L., Hahn, A., Hajlaoui, J. E., Hakobyan, H., Halim, A., Hamal, P., Hanlon, W., Hara, S., Harada, Y., Hardcastle, M. J., Harvey, M., Hashiyama, K., Hassan Collado, T., Haubold, T., Haupt, A., Hautmann, U. A., Havelka, M., Hayashi, K., Hayashida, M., He, H., Heckmann, L., Heller, M., Helo, J. C., Henault, F., Henri, G., Hermann, G., Hermel, R., Hernández Cadena, S., Herrera Llorente, J., Herrero, A., Hervet, O., Hinton, J., Hiramatsu, A., Hiroshima, N., Hirotani, K., Hnatyk, B., Hnatyk, R., Hoang, J. K., Hoffmann, D., Hofmann, W., Hoischen, C., Holder, J., Holler, M., Hona, B., Horan, D., Hörandel, J., Horns, D., Horvath, P., Houles, J., Hovatta, T., Hrabovsky, M., Hrupec, D., Huang, Y., Huet, J. -M, Hughes, G., Hui, D., Hull, G., Humensky, T. B., Hütten, M., Iaria, R., Iarlori, M., Illa, J. M., Imazawa, R., Impiombato, D., Inada, T., Incardona, F., Ingallinera, A., Inome, Y., Inoue, S., Inoue, T., Inoue, Y., Insolia, A., Iocco, F., Ioka, K., Ionica, M., Iori, M., Iovenitti, S., Iriarte, A., Ishio, K., Ishizaki, W., Iwamura, Y., Jablonski, C., Jacquemier, J., Jacquemont, M., Jamrozy, M., Janecek, P., Jankowsky, F., Jardin-Blicq, A., Jarnot, C., Jean, P., Jiménez Martínez, I., Jin, W., Jocou, L., Jordana, N., Josselin, M., Jouvin, L., Jung-Richardt, I., Junqueira, F. J. P. A., Juramy-Gilles, C., Jurysek, J., Kaaret, P., Kadowaki, L. H. S., Kagaya, M., Kalekin, O., Kankanyan, R., Kantzas, D., Karas, V., Karastergiou, A., Karkar, S., Kasai, E., Kasperek, J., Katagiri, H., Kataoka, J., Katarzyński, K., Katsuda, S., Katz, U., Kawanaka, N., Kazanas, D., Kerszberg, D., Khélifi, B., Kherlakian, M. C., Kian, T. P., Kieda, D. B., Kihm, T., Kim, S., Kimeswenger, S., Kisaka, S., Kissmann, R., Kleijwegt, R., Kleiner, T., Kluge, G., Kluźniak, W., Knapp, J., Knödlseder, J., Kobakhidze, A., Kobayashi, Y., Koch, B., Kocot, J., Kohri, K., Kokkotas, K., Komin, N., Kong, A., Kosack, K., Kowal, G., Krack, F., Krause, M., Krennrich, F., Krumholz, M., Kubo, H., Kudryavtsev, V., Kunwar, S., Kuroda, Y., Kushida, J., Kushwaha, P., La Barbera, A., La Palombara, N., La Parola, V., La Rosa, G., Lahmann, R., Lamanna, G., Lamastra, A., Landoni, M., Landriu, D., Lang, R. G., Lapington, J., Laporte, P., Lason, P., Lasuik, J., Lazendic-Galloway, J., Le Flour, T., Le Sidaner, P., Leach, S., Leckngam, A., Lee, S. -H, Lee, W. H., Lee, S., Leigui Oliveira, M. A., Lemière, A., Lemoine-Goumard, M., Lenain, J. -P, Leone, F., Leray, V., Leto, G., Leuschner, F., Levy, C., Lindemann, R., Lindfors, E., Linhoff, L., Liodakis, I., Lipniacka, A., Lloyd, S., Lobo, M., Lohse, T., Lombardi, S., Longo, F., Lopez, A., López, M., López-Coto, R., Loporchio, S., Louis, F., Louys, M., Lucarelli, F., Lucchesi, D., Ludwig Boudi, H., Luque-Escamilla, P. L., Lyard, E., Maccarone, M. C., Maccarone, T., Mach, E., Maciejewski, A. J., Mackey, J., Madejski, G. M., Maeght, P., Maggio, C., Maier, G., Majczyna, A., Majumdar, P., Makariev, M., Mallamaci, M., Malta Nunes Almeida, R., Maltezos, S., Malyshev, D., Mandat, D., Maneva, G., Manganaro, M., Manicò, G., Manigot, P., Mannheim, K., Maragos, N., Marano, D., Marconi, M., Marcowith, A., Marculewicz, M., Marčun, B., Marín, J., Marinello, N., Marinos, P., Mariotti, M., Markoff, S., Marquez, P., Marsella, G., Martí, J., Martin, J. -M, Martin, P., Martinez, O., Martínez, M., Martínez, G., Martínez, O., Martínez-Huerta, H., Marty, C., Marx, R., Masetti, N., Massimino, P., Mastichiadis, A., Matsumoto, H., Matthews, N., Maurin, G., Max-Moerbeck, W., Maxted, N., Mazin, D., Mazziotta, M. N., Mazzola, S. M., Mbarubucyeye, J. D., Mc Comb, L., Mchardy, I., Mckeague, S., Mcmuldroch, S., Medina, E., Medina Miranda, D., Melandri, A., Melioli, C., Melkumyan, D., Menchiari, S., Mender, S., Mereghetti, S., Merino Arévalo, G., Mestre, E., Meunier, J. -L, Meures, T., Meyer, M., Micanovic, S., Miceli, M., Michailidis, M., Michałowski, J., Miener, T., Mievre, I., Miller, J., Minaya, I. A., Mineo, T., Minev, M., Miranda, J. M., Mirzoyan, R., Mitchell, A., Mizuno, T., Mode, B., Moderski, R., Mohrmann, L., Molina, E., Molinari, E., Teresa Montaruli, Monteiro, I., Moore, C., Moralejo, A., Morcuende-Parrilla, D., Moretti, E., Morganti, L., Mori, K., Moriarty, P., Morik, K., Morlino, G., Morris, P., Morselli, A., Mosshammer, K., Moya, P., Mukherjee, R., Muller, J., Mundell, C., Mundet, J., Murach, T., Muraczewski, A., Muraishi, H., Murase, K., Musella, I., Musumarra, A., Nagai, A., Nagar, N., Nagataki, S., Naito, T., Nakamori, T., Nakashima, K., Nakayama, K., Nakhjiri, N., Naletto, G., Naumann, D., Nava, L., Navarro, R., Nawaz, M. A., Ndiyavala, H., Neise, D., Nellen, L., Nemmen, R., Newbold, M., Neyroud, N., Ngernphat, K., Nguyen Trung, T., Nicastro, L., Nickel, L., Niemiec, J., Nieto, D., Nievas, M., Nigro, C., Nikołajuk, M., Ninci, D., Nishijima, K., Noda, K., Nogami, Y., Nolan, S., Nomura, R., Norris, R., Nosek, D., Nöthe, M., Novosyadlyj, B., Novotny, V., Nozaki, S., Nunio, F., O’brien, P., Obara, K., Oger, R., Ohira, Y., Ohishi, M., Ohm, S., Ohtani, Y., Oka, T., Okazaki, N., Okumura, A., Olive, J. -F, Oliver, C., Olivera, G., Olmi, B., Ong, R. A., Orienti, M., Orito, R., Orlandini, M., Orlando, S., Orlando, E., Osborne, J. P., Ostrowski, M., Otte, N., Ovcharov, E., Owen, E., Oya, I., Ozieblo, A., Padovani, M., Pagano, I., Pagliaro, A., Paizis, A., Palatiello, M., Palatka, M., Palazzi, E., Panazol, J. -L, Paneque, D., Panes, B., Panny, S., Pantaleo, F. R., Panter, M., Paoletti, R., Paolillo, M., Papitto, A., Paravac, A., Paredes, J. M., Pareschi, G., Park, N., Parmiggiani, N., Parsons, R. D., Paśko, P., Patel, S., Patricelli, B., Pauletta, G., Pavletić, L., Pavy, S., Pe’er, A., Pech, M., Pecimotika, M., Pellegriti, M. G., Peñil Del Campo, P., Penno, M., Pepato, A., Perard, S., Perennes, C., Peres, G., Peresano, M., Pérez-Aguilera, A., Pérez-Romero, J., Pérez-Torres, M. A., Perri, M., Persic, M., Petrera, S., Petrucci, P. -O, Petruk, O., Peyaud, B., Pfrang, K., Pian, E., Piano, G., Piatteli, P., Pietropaolo, E., Pillera, R., Pilszyk, B., Pimentel, D., Pintore, F., Pio García, C., Pirola, G., Piron, F., Pisarski, A., Pita, S., Pohl, M., Poireau, V., Poledrelli, P., Pollo, A., Polo, M., Pongkitivanichkul, C., Porthault, J., Powell, J., Pozo, D., Prado, R. R., Prandini, E., Prasit, P., Prast, J., Pressard, K., Principe, G., Priyadarshi, C., Produit, N., Prokhorov, D., Prokoph, H., Prouza, M., Przybilski, H., Pueschel, E., Pühlhofer, G., Puljak, I., Pumo, M. L., Punch, M., Queiroz, F., Quinn, J., Quirrenbach, A., Rainò, S., Rajda, P. J., Rando, R., Razzaque, S., Rebert, E., Recchia, S., Reichherzer, P., Reimer, O., Reimer, A., Reisenegger, A., Remy, Q., Renaud, M., Reposeur, T., Reville, B., Reymond, J. -M, Reynolds, J., Rhode, W., Ribeiro, D., Ribó, M., Richards, G., Richtler, T., Rico, J., Rieger, F., Riitano, L., Ripepi, V., Riquelme, M., Riquelme, D., Rivoire, S., Rizi, V., Roache, E., Röben, B., Roche, M., Rodriguez, J., Rodriguez Fernandez, G., Rodriguez Ramirez, J. C., Rodríguez Vázquez, J. J., Roepke, F., Rojas, G., Romanato, L., Romano, P., Romeo, G., Romero Lobato, F., Romoli, C., Roncadelli, M., Ronda, S., Rosado, J., Rosales Leon, A., Rowell, G., Rudak, B., Rugliancich, A., Ruíz Del Mazo, J. E., Rujopakarn, W., Rulten, C., Russell, C., Russo, F., Sadeh, I., Sæther Hatlen, E., Safi-Harb, S., Saha, L., Saha, P., Sahakian, V., Sailer, S., Saito, T., Sakaki, N., Sakurai, S., Salesa Greus, F., Salina, G., Salzmann, H., Sanchez, D., Sánchez-Conde, M., Sandaker, H., Sandoval, A., Sangiorgi, P., Sanguillon, M., Sano, H., Santander, M., Santangelo, A., Santos, E. M., Santos-Lima, R., Sanuy, A., Sapozhnikov, L., Saric, T., Sarkar, S., Sasaki, H., Sasaki, N., Satalecka, K., Sato, Y., Saturni, F. G., Sawada, M., Sawangwit, U., Schaefer, J., Scherer, A., Scherpenberg, J., Schipani, P., Schleicher, B., Schmoll, J., Schneider, M., Schoorlemmer, H., Schovanek, P., Schussler, F., Schwab, B., Schwanke, U., Schwarz, J., Schweizer, T., Sciacca, E., Scuderi, S., Seglar Arroyo, M., Segreto, A., Seitenzahl, I., Semikoz, D., Sergijenko, O., Serna Franco, J. E., Servillat, M., Seweryn, K., Sguera, V., Shalchi, A., Shang, R. Y., Sharma, P., Shellard, R. C., Sidoli, L., Sieiro, J., Siejkowski, H., Silk, J., Sillanpää, A., Singh, B. B., Singh, K. K., Sinha, A., Siqueira, C., Sironi, G., Sitarek, J., Sizun, P., Sliusar, V., Slowikowska, A., Sobczyńska, D., Sobrinho, R. W., Sol, H., Sottile, G., Spackman, H., Specovius, A., Spencer, S., Spengler, G., Spiga, D., Spolon, A., Springer, W., Stamerra, A., Stanič, S., Starling, R., Stawarz, Ł., Steenkamp, R., Stefanik, S., Stegmann, C., Steiner, A., Steinmassl, S., Stella, C., Steppa, C., Sternberger, R., Sterzel, M., Stevens, C., Stevenson, B., Stolarczyk, T., Stratta, G., Straumann, U., Strišković, J., Strzys, M., Stuik, R., Suchenek, M., Suda, Y., Sunada, Y., Suomijarvi, T., Suric, T., Sutcliffe, P., Suzuki, H., Świerk, P., Szepieniec, T., Tacchini, A., Tachihara, K., Tagliaferri, G., Tajima, H., Tajima, N., Tak, D., Takahashi, K., Takahashi, H., Takahashi, M., Takata, J., Takeishi, R., Tam, T., Tanaka, M., Tanaka, T., Tanaka, S., Tateishi, D., Tavani, M., Tavecchio, F., Tavernier, T., Taylor, L., Taylor, A., Tejedor, L. A., Temnikov, P., Terada, Y., Terauchi, K., Terrazas, J. 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O., Antonelli, L. A., Aramo, C., Araudo, A., Armstrong, T., Arqueros, F., Asano, K., Ascas??bar, Y., Ashley, M., Balazs, C., Ballester, O., Baquero Larriva, A., Barbosa Martins, V., Barkov, M., Barres de Almeida, U., Barrio, J. A., Bastieri, D., Becerra, J., Beck, G., Becker Tjus, J., Benbow, W., Benito, M., Berge, D., Bernardini, E., Bernl??hr, K., Berti, A., Bertucci, B., Beshley, V., Biasuzzi, B., Biland, A., Bissaldi, E., Biteau, J., Blanch, O., Blazek, J., Bocchino, F., Boisson, C., Bonneau Arbeletche, L., Bordas, P., Bosnjak, Z., Bottacini, E., Bozhilov, V., Bregeon, J., Brill, A., Bringmann, T., Brown, A. 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B., H??tten, M., Iarlori, M., Inada, T., Inoue, S., Iocco, F., Iori, M., Jamrozy, M., Janecek, P., Jin, W., Jouvin, L., Jurysek, J., Karukes, E., Katarzy??ski, K., Kazanas, D., Kerszberg, D., Kherlakian, M. C., Kissmann, R., Kn??dlseder, J., Kobayashi, Y., Kohri, K., Komin, N., Kubo, H., Kushida, J., Lamanna, G., Lapington, J., Laporte, P., Leigui de Oliveira, M. A., Lenain, J., Leone, F., Leto, G., Lindfors, E., Lohse, T., Lombardi, S., Longo, F., Lopez, A., L??pez, M., L??pez-Coto, R., Loporchio, S., Luque-Escamilla, P. L., Mach, E., Maggio, C., Maier, G., Mallamaci, M., Malta Nunes de Almeida, R., Mandat, D., Manganaro, M., Mangano, S., Manic??, G., Marculewicz, M., Mariotti, M., Markoff, S., Marquez, P., Mart??, J., Martinez, O., Mart??nez, M., Mart??nez, G., Mart??nez-Huerta, H., Maurin, G., Mazin, D., Mbarubucyeye, J. D., Medina Miranda, D., Meyer, M., Miceli, M., Miener, T., Minev, M., Miranda, J. 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C., Siejkowski, H., Silk, J., Siqueira, C., Sliusar, V., S??owikowska, A., Sokolenko, A., Sol, H., Spencer, S., Stamerra, A., Stani??, S., Starling, R., Stolarczyk, T., Straumann, U., Stri??kovi??, J., Suda, Y., Suomijarvi, T., wierk, P., Tavecchio, F., Taylor, L., Tejedor, L. A., Teshima, M., Testa, V., Tibaldo, L., Todero Peixoto, C. J., Tokanai, F., Tonev, D., Tosti, G., Tosti, L., Tothill, N., Truzzi, S., Travnicek, P., Vagelli, V., Vallage, B., Vallania, P., van Eldik, C., Vandenbroucke, J., Varner, G. S., Vassiliev, V., V??zquez Acosta, M., Vecchi, M., Ventura, S., Vercellone, S., Vergani, S., Verna, G., Viana, A., Vigorito, C. F., Vink, J., Vitale, V., Vorobiov, S., Vovk, I., Vuillaume, T., Wagner, S. J., Walter, R., Watson, J., Weniger, C., White, R., White, M., Wiemann, R., Wierzcholska, A., Will, M., Williams, D. A., Wischnewski, R., Yanagita, S., Yang, L., Yoshikoshi, T., Zacharias, M., Zaharijas, G., Zakaria, A. A., Zampieri, L., Zanin, R., Zaric, D., Zavrtanik, M., Zavrtanik, D., Zdziarski, A. A., Zech, A., Zechlin, H., Zhdanov, V. I., ivec, M., ITA, USA, GBR, FRA, DEU, ESP, AUT, BEL, BRA, HRV, DNK, JPN, IRL, NLD, POL, SVN, CHE, High Energy Astrophys. & Astropart. Phys (API, FNWI), GRAPPA (ITFA, IoP, FNWI), Centre National de la Recherche Scientifique (CNRS)-École polytechnique (X)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Diderot - Paris 7 (UPD7), Université Montpellier 2 - Sciences et Techniques (UM2)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS), Astrophysique Interprétation Modélisation (AIM (UMR_7158 / UMR_E_9005 / UM_112)), Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris Diderot - Paris 7 (UPD7), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS)-Université de Paris (UP), Institut national des sciences de l'Univers (INSU - CNRS)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Observatoire Midi-Pyrénées (OMP), Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Centre National de la Recherche Scientifique (CNRS), Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université de Paris (UP), Iocco, Fabio, Anguner, E. O., Ascasibar, Y., Bernlohr, K., Colak, M., D'Ai, A., de Angelis, A., de Caprio, V., de Cassia dos Anjos, R., de Lotto, B., de Martino, D., de Ona Wilhelmi, E., de Palma, F., Dominguez, A., Elsasser, D., Gonzalez, M. M., Hernandez Cadena, S., Horandel, J., Hutten, M., Katarzynski, K., Knodlseder, J., Lopez, M., Lopez-Coto, R., Manico, G., Marti, J., Martinez, M., Martinez, G., Martinez-Huerta, H., Nikolajuk, M., Pavletic, L., Perez-Romero, J., Puhlhofer, G., Raino, S., Ribo, M., Saether Hatlen, E., Sanchez-Conde, M., Slowikowska, A., Stanic, S., Striskovic, J., Swierk, P., Vazquez Acosta, M., Zivec, M., Consortium, The CTA, Acharyya A., Adam R., Adams C., Agudo I., Aguirre-Santaella A., Alfaro R., Alfaro J., Alispach C., Aloisio R., Alves Batista R., Amati L., Ambrosi G., Anguner E.O., Antonelli L.A., Aramo C., Araudo A., Armstrong T., Arqueros F., Asano K., Ascasibar Y., Ashley M., Balazs C., Ballester O., Baquero Larriva A., Barbosa Martins V., Barkov M., Barres de Almeida U., Barrio J.A., Bastieri D., Becerra J., Beck G., Becker Tjus J., Benbow W., Benito M., Berge D., Bernardini E., Bernlohr K., Berti A., Bertucci B., Beshley V., Biasuzzi B., Biland A., Bissaldi E., Biteau J., Blanch O., Blazek J., Bocchino F., Boisson C., Bonneau Arbeletche L., Bordas P., Bosnjak Z., Bottacini E., Bozhilov V., Bregeon J., Brill A., Bringmann T., Brown A.M., Brun P., Brun F., Bruno P., Bulgarelli A., Burton M., Burtovoi A., Buscemi M., Cameron R., Capasso M., Caproni A., Capuzzo-Dolcetta R., Caraveo P., Carosi R., Carosi A., Casanova S., Cascone E., Cassol F., Catalani F., Cauz D., Cerruti M., Chadwick P., Chaty S., Chen A., Chernyakova M., Chiaro G., Chiavassa A., Chikawa M., Chudoba J., Colak M., Conforti V., Coniglione R., Conte F., Contreras J.L., Coronado-Blazquez J., Costa A., Costantini H., Cotter G., Cristofari P., D'Ai A., D'Ammando F., Damone L.A., Daniel M.K., Dazzi F., de Angelis A., de Caprio V., de Cassia dos Anjos R., de Gouveia Dal Pino E.M., de Lotto B., de Martino D., de Ona Wilhelmi E., de Palma F., de Souza V., Delgado C., Delgado Giler A.G., della Volpe D., Depaoli D., Di Girolamo T., Di Pierro F., Di Venere L., Diebold S., Dmytriiev A., Dominguez A., Donini A., Doro M., Ebr J., Eckner C., Edwards T.D.P., Ekoume T.R.N., Elsasser D., Evoli C., Falceta-Goncalves D., Fedorova E., Fegan S., Feng Q., Ferrand G., Ferrara G., Fiandrini E., Fiasson A., Filipovic M., Fioretti V., Fiori M., Foffano L., Fontaine G., Fornieri O., Franco F.J., Fukami S., Fukui Y., Gaggero D., Galaz G., Gammaldi V., Garcia E., Garczarczyk M., Gascon D., Gent A., Ghalumyan A., Gianotti F., Giarrusso M., Giavitto G., Giglietto N., Giordano F., Giuliani A., Glicenstein J., Gnatyk R., Goldoni P., Gonzalez M.M., Gourgouliatos K., Granot J., Grasso D., Green J., Grillo A., Gueta O., Gunji S., Halim A., Hassan T., Heller M., Hernandez Cadena S., Hiroshima N., Hnatyk B., Hofmann W., Holder J., Horan D., Horandel J., Horvath P., Hovatta T., Hrabovsky M., Hrupec D., Hughes G., Humensky T.B., Hutten M., Iarlori M., Inada T., Inoue S., Iocco F., Iori M., Jamrozy M., Janecek P., Jin W., Jouvin L., Jurysek J., Karukes E., Katarzynski K., Kazanas D., Kerszberg D., Kherlakian M.C., Kissmann R., Knodlseder J., Kobayashi Y., Kohri K., Komin N., Kubo H., Kushida J., Lamanna G., Lapington J., Laporte P., Leigui de Oliveira M.A., Lenain J., Leone F., Leto G., Lindfors E., Lohse T., Lombardi S., Longo F., Lopez A., Lopez M., Lopez-Coto R., Loporchio S., Luque-Escamilla P.L., Mach E., Maggio C., Maier G., Mallamaci M., Malta Nunes de Almeida R., Mandat D., Manganaro M., Mangano S., Manico G., Marculewicz M., Mariotti M., Markoff S., Marquez P., Marti J., Martinez O., Martinez M., Martinez G., Martinez-Huerta H., Maurin G., Mazin D., Mbarubucyeye J.D., Medina Miranda D., Meyer M., Miceli M., Miener T., Minev M., Miranda J.M., Mirzoyan R., Mizuno T., Mode B., Moderski R., Mohrmann L., Molina E., Montaruli T., Moralejo A., Morcuende-Parrilla D., Morselli A., Mukherjee R., Mundell C., Nagai A., Nakamori T., Nemmen R., Niemiec J., Nieto D., Nikolajuk M., Ninci D., Noda K., Nosek D., Nozaki S., Ohira Y., Ohishi M., Ohtani Y., Oka T., Okumura A., Ong R.A., Orienti M., Orito R., Orlandini M., Orlando S., Orlando E., Ostrowski M., Oya I., Pagano I., Pagliaro A., Palatiello M., Pantaleo F.R., Paredes J.M., Pareschi G., Parmiggiani N., Patricelli B., Pavletic L., Pe'Er A., Pecimotika M., Perez-Romero J., Persic M., Petruk O., Pfrang K., Piano G., Piatteli P., Pietropaolo E., Pillera R., Pilszyk B., Pintore F., Pohl M., Poireau V., Prado R.R., Prandini E., Prast J., Principe G., Prokoph H., Prouza M., Przybilski H., Puhlhofer G., Pumo M.L., Queiroz F., Quirrenbach A., Raino S., Rando R., Razzaque S., Recchia S., Reimer O., Reisenegger A., Renier Y., Rhode W., Ribeiro D., Ribo M., Richtler T., Rico J., Rieger F., Rinchiuso L., Rizi V., Rodriguez J., Rodriguez Fernandez G., Rodriguez Ramirez J.C., Rojas G., Romano P., Romeo G., Rosado J., Rowell G., Rudak B., Russo F., Sadeh I., Saether Hatlen E., Safi-Harb S., Salesa Greus F., Salina G., Sanchez D., Sanchez-Conde M., Sangiorgi P., Sano H., Santander M., Santos E.M., Santos-Lima R., Sanuy A., Sarkar S., Saturni F.G., Sawangwit U., Schussler F., Schwanke U., Sciacca E., Scuderi S., Seglar-Arroyo M., Sergijenko O., Servillat M., Seweryn K., Shalchi A., Sharma P., Shellard R.C., Siejkowski H., Silk J., Siqueira C., Sliusar V., Slowikowska A., Sokolenko A., Sol H., Spencer S., Stamerra A., Stanic S., Starling R., Stolarczyk T., Straumann U., Striskovic J., Suda Y., Suomijarvi T., Swierk P., Tavecchio F., Taylor L., Tejedor L.A., Teshima M., Testa V., Tibaldo L., Todero Peixoto C.J., Tokanai F., Tonev D., Tosti G., Tosti L., Tothill N., Truzzi S., Travnicek P., Vagelli V., Vallage B., Vallania P., van Eldik C., Vandenbroucke J., Varner G.S., Vassiliev V., Vazquez Acosta M., Vecchi M., Ventura S., Vercellone S., Vergani S., Verna G., Viana A., Vigorito C.F., Vink J., Vitale V., Vorobiov S., Vovk I., Vuillaume T., Wagner S.J., Walter R., Watson J., Weniger C., White R., White M., Wiemann R., Wierzcholska A., Will M., Williams D.A., Wischnewski R., Yanagita S., Yang L., Yoshikoshi T., Zacharias M., Zaharijas G., Zakaria A.A., Zampieri L., Zanin R., Zaric D., Zavrtanik M., Zavrtanik D., Zdziarski A.A., Zech A., Zechlin H., Zhdanov V.I., and Zivec M.
Subjects: Cherenkov Telescope Array, MATÉRIA ESCURA, scale: TeV, Astronomy, atmosphere [Cherenkov counter], dark matter experiment, Dark matter theory, energy resolution, Gamma ray experiments, Particle, Astrophysics, cosmic background radiation, 01 natural sciences, 7. Clean energy, High Energy Physics - Phenomenology (hep-ph), benchmark, WIMP, HESS, energy: flux, TeV [scale], relativistic [charged particle], gamma ray experiment, MAGIC (telescope), Monte Carlo, Event reconstruction, Physics, High Energy Astrophysical Phenomena (astro-ph.HE), Contraction, spatial distribution, track data analysis, density [dark matter], Clumpy, Astrophysics::Instrumentation and Methods for Astrophysics, imaging, High Energy Physics - Phenomenology, dark matter experiments, dark matter theory, gamma ray experiments, galaxy morphology, Dark matter experiments, Física nuclear, VERITAS, Astrophysics - High Energy Astrophysical Phenomena, Simulations, noise, Astrophysics::High Energy Astrophysical Phenomena, Dark matter, satellite, Cosmic background radiation, FOS: Physical sciences, Annihilation, dark matter: density, Astrophysics::Cosmology and Extragalactic Astrophysics, Cherenkov counter: atmosphere, heavy [dark matter], annihilation [dark matter], GLAST, Galaxy morphology, cosmic radiation [p], 0103 physical sciences, Cherenkov [radiation], Candidates, ddc:530, AGN, Cherenkov radiation, Radiative Processes, thermal [cross section], 010308 nuclear & particles physics, Física, dark matter: annihilation, Gamma-Ray Signals, dark matter, Galactic Center, TeV gamma-ray astronomy, Astronomy and Astrophysics, Mass, radiation: Cherenkov, sensitivity, MAGIC, Galaxy, Astronomía, dark matter: heavy, gamma ray, p: cosmic radiation, [PHYS.HPHE]Physics [physics]/High Energy Physics - Phenomenology [hep-ph], correlation, charged particle: relativistic, flux [energy], galaxy, supersymmetry, [PHYS.ASTR]Physics [physics]/Astrophysics [astro-ph], cross section: thermal
Abstract: Full list of authors: Acharyya, A.; Adam, R.; Adams, C.; Agudo, I.; Aguirre-Santaella, A.; Alfaro, R.; Alfaro, J.; Alispach, C.; Aloisio, R.; Alves Batista, R.; Amati, L.; Ambrosi, G.; Angüner, E. O.; Antonelli, L. A.; Aramo, C.; Araudo, A.; Armstrong, T.; Arqueros, F.; Asano, K.; Ascasíbar, Y. Ashley, M.; Balazs, C.; Ballester, O.; Baquero Larriva, A.; Barbosa Martins, V.; Barkov, M.; Barres de Almeida, U.; Barrio, J. A.; Bastieri, D.; Becerra, J.; Beck, G.; Becker Tjus, J.; Benbow, W.; Benito, M.; Berge, D.; Bernardini, E.; Bernlöhr, K.; Berti, A.; Bertucci, B.; Beshley, V.; Biasuzzi, B.; Biland, A.; Bissaldi, E.; Biteau, J.; Blanch, O.; Blazek, J.; Bocchino, F.; Boisson, C.; Bonneau Arbeletche, L.; Bordas, P.; Bosnjak, Z.; Bottacini, E.; Bozhilov, V.; Bregeon, J.; Brill, A.; Bringmann, T.; Brown, A. M.; Brun, P.; Brun, F.; Bruno, P.; Bulgarelli, A.; Burton, M.; Burtovoi, A.; Buscemi, M.; Cameron, R.; Capasso, M.; Caproni, A.; Capuzzo-Dolcetta, R.; Caraveo, P.; Carosi, R.; Carosi, A.; Casanova, S.; Cascone, E.; Cassol, F.; Catalani, F.; Cauz, D.; Cerruti, M.; Chadwick, P.; Chaty, S.; Chen, A.; Chernyakova, M.; Chiaro, G.; Chiavassa, A.; Chikawa, M.; Chudoba, J.; Çolak, M.; Conforti, V.; Coniglione, R.; Conte, F.; Contreras, J. L.; Coronado-Blazquez, J.; Costa, A.; Costantini, H.; Cotter, G.; Cristofari, P.; D'Aimath, A.; D'Ammando, F.; Damone, L. A.; Daniel, M. K.; Dazzi, F.; De Angelis, A.; De Caprio, V.; de Cássia dos Anjos, R.; de Gouveia Dal Pino, E. M.; De Lotto, B.; De Martino, D.; de Oña Wilhelmi, E.; De Palma, F.; de Souza, V.; Delgado, C.; Delgado Giler, A. G.; della Volpe, D.; Depaoli, D.; Di Girolamo, T.; Di Pierro, F.; Di Venere, L.; Diebold, S.; Dmytriiev, A.; Domínguez, A.; Donini, A.; Doro, M.; Ebr, J.; Eckner, C.; Edwards, T. D. P.; Ekoume, T. R. N.; Elsässer, D.; Evoli, C.; Falceta-Goncalves, D.; Fedorova, E.; Fegan, S.; Feng, Q.; Ferrand, G.; Ferrara, G.; Fiandrini, E.; Fiasson, A.; Filipovic, M.; Fioretti, V.; Fiori, M.; Foffano, L.; Fontaine, G.; Fornieri, O.; Franco, F. J.; Fukami, S.; Fukui, Y.; Gaggero, D.; Galaz, G.; Gammaldi, V.; Garcia, E.; Garczarczyk, M.; Gascon, D.; Gent, A.; Ghalumyan, A.; Gianotti, F.; Giarrusso, M.; Giavitto, G.; Giglietto, N.; Giordano, F.; Giuliani, A.; Glicenstein, J.; Gnatyk, R.; Goldoni, P.; González, M. M.; Gourgouliatos, K.; Granot, J.; Grasso, D.; Green, J.; Grillo, A.; Gueta, O.; Gunji, S.; Halim, A.; Hassan, T.; Heller, M.; Hernández Cadena, S.; Hiroshima, N.; Hnatyk, B.; Hofmann, W.; Holder, J.; Horan, D.; Hörandel, J.; Horvath, P.; Hovatta, T.; Hrabovsky, M.; Hrupec, D.; Hughes, G.; Humensky, T. B.; Hütten, M.; Iarlori, M.; Inada, T.; Inoue, S.; Iocco, F.; Iori, M.; Jamrozy, M.; Janecek, P.; Jin, W.; Jouvin, L.; Jurysek, J.; Karukes, E.; Katarzyński, K.; Kazanas, D.; Kerszberg, D.; Kherlakian, M. C.; Kissmann, R.; Knödlseder, J.; Kobayashi, Y.; Kohri, K.; Komin, N.; Kubo, H.; Kushida, J.; Lamanna, G.; Lapington, J.; Laporte, P.; Leigui de Oliveira, M. A.; Lenain, J.; Leone, F.; Leto, G.; Lindfors, E.; Lohse, T.; Lombardi, S.; Longo, F.; Lopez, A.; López, M.; López-Coto, R.; Loporchio, S.; Luque-Escamilla, P. L.; Mach, E.; Maggio, C.; Maier, G.; Mallamaci, M.; Malta Nunes de Almeida, R.; Mandat, D.; Manganaro, M.; Mangano, S.; Manicò, G.; Marculewicz, M.; Mariotti, M.; Markoff, S.; Marquez, P.; Martí, J.; Martinez, O.; Martínez, M.; Martínez, G.; Martínez-Huerta, H.; Maurin, G.; Mazin, D.; Mbarubucyeye, J. D.; Medina Miranda, D.; Meyer, M.; Miceli, M.; Miener, T.; Minev, M.; Miranda, J. M.; Mirzoyan, R.; Mizuno, T.; Mode, B.; Moderski, R.; Mohrmann, L.; Molina, E.; Montaruli, T.; Moralejo, A.; Morcuende-Parrilla, D.; Morselli, A.; Mukherjee, R.; Mundell, C.; Nagai, A.; Nakamori, T.; Nemmen, R.; Niemiec, J.; Nieto, D.; Nikołajuk, M.; Ninci, D.; Noda, K.; Nosek, D.; Nozaki, S.; Ohira, Y.; Ohishi, M.; Ohtani, Y.; Oka, T.; Okumura, A.; Ong, R. A.; Orienti, M.; Orito, R.; Orlandini, M.; Orlando, S.; Orlando, E.; Ostrowski, M.; Oya, I.; Pagano, I.; Pagliaro, A.; Palatiello, M.; Pantaleo, F. R.; Paredes, J. M.; Pareschi, G.; Parmiggiani, N.; Patricelli, B.; Pavletić, L.; Pe'er, A.; Pecimotika, M.; Pérez-Romero, J.; Persic, M.; Petruk, O.; Pfrang, K.; Piano, G.; Piatteli, P.; Pietropaolo, E.; Pillera, R.; Pilszyk, B.; Pintore, F.; Pohl, M.; Poireau, V.; Prado, R. R.; Prandini, E.; Prast, J.; Principe, G.; Prokoph, H.; Prouza, M.; Przybilski, H.; Pühlhofer, G.; Pumo, M. L.; Queiroz, F.; Quirrenbach, A.; Rainò, S.; Rando, R.; Razzaque, S.; Recchia, S.; Reimer, O.; Reisenegger, A.; Renier, Y.; Rhode, W.; Ribeiro, D.; Ribó, M.; Richtler, T.; Rico, J.; Rieger, F.; Rinchiuso, L.; Rizi, V.; Rodriguez, J.; Rodriguez Fernandez, G.; Rodriguez Ramirez, J. C.; Rojas, G.; Romano, P.; Romeo, G.; Rosado, J.; Rowell, G.; Rudak, B.; Russo, F.; Sadeh, I.; Sæther Hatlen, E.; Safi-Harb, S.; Salesa Greus, F.; Salina, G.; Sanchez, D.; Sánchez-Conde, M.; Sangiorgi, P.; Sano, H.; Santander, M.; Santos, E. M.; Santos-Lima, R.; Sanuy, A.; Sarkar, S.; Saturni, F. G.; Sawangwit, U.; Schussler, F.; Schwanke, U.; Sciacca, E.; Scuderi, S.; Seglar-Arroyo, M.; Sergijenko, O.; Servillat, M.; Seweryn, K.; Shalchi, A.; Sharma, P.; Shellard, R. C.; Siejkowski, H.; Silk, J.; Siqueira, C.; Sliusar, V.; Słowikowska, A.; Sokolenko, A.; Sol, H.; Spencer, S.; Stamerra, A.; Stanič, S.; Starling, R.; Stolarczyk, T.; Straumann, U.; Strišković, J.; Suda, Y.; Suomijarvi, T.; Świerk, P.; Tavecchio, F.; Taylor, L.; Tejedor, L. A.; Teshima, M.; Testa, V.; Tibaldo, L.; Todero Peixoto, C. J.; Tokanai, F.; Tonev, D.; Tosti, G.; Tosti, L.; Tothill, N.; Truzzi, S.; Travnicek, P.; Vagelli, V.; Vallage, B.; Vallania, P.; van Eldik, C.; Vandenbroucke, J.; Varner, G. S.; Vassiliev, V.; Vázquez Acosta, M.; Vecchi, M.; Ventura, S.; Vercellone, S.; Vergani, S.; Verna, G.; Viana, A.; Vigorito, C. F.; Vink, J.; Vitale, V.; Vorobiov, S.; Vovk, I.; Vuillaume, T.; Wagner, S. J.; Walter, R.; Watson, J.; Weniger, C.; White, R.; White, M.; Wiemann, R.; Wierzcholska, A.; Will, M.; Williams, D. A.; Wischnewski, R.; Yanagita, S.; Yang, L.; Yoshikoshi, T.; Zacharias, M.; Zaharijas, G.; Zakaria, A. A.; Zampieri, L.; Zanin, R.; Zaric, D.; Zavrtanik, M.; Zavrtanik, D.; Zdziarski, A. A.; Zech, A.; Zechlin, H.; Zhdanov, V. I.; Živec, M.-- This is an open access article published by IOP Publishing Ltd on behalf of Sissa Medialab. Original content from this work may be used under the terms of the Creative Commons Attribution 4.0 licence. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI., We provide an updated assessment of the power of the Cherenkov Telescope Array (CTA) to search for thermally produced dark matter at the TeV scale, via the associated gamma-ray signal from pair-annihilating dark matter particles in the region around the Galactic centre. We find that CTA will open a new window of discovery potential, significantly extending the range of robustly testable models given a standard cuspy profile of the dark matter density distribution. Importantly, even for a cored profile, the projected sensitivity of CTA will be sufficient to probe various well-motivated models of thermally produced dark matter at the TeV scale. This is due to CTA's unprecedented sensitivity, angular and energy resolutions, and the planned observational strategy. The survey of the inner Galaxy will cover a much larger region than corresponding previous observational campaigns with imaging atmospheric Cherenkov telescopes. CTA will map with unprecedented precision the large-scale diffuse emission in high-energy gamma rays, constituting a background for dark matter searches for which we adopt state-of-the-art models based on current data. Throughout our analysis, we use up-to-date event reconstruction Monte Carlo tools developed by the CTA consortium, and pay special attention to quantifying the level of instrumental systematic uncertainties, as well as background template systematic errors, required to probe thermally produced dark matter at these energies. © 2021 The Author(s)., We gratefully acknowledge financial support from the following agencies and organisations: State Committee of Science of Armenia, Armenia; The Australian Research Council, Astronomy Australia Ltd, The University of Adelaide, Australian National University, Monash University, The University of New South Wales, The University of Sydney, Western Sydney University, Australia; Federal Ministry of Education, Science and Research, and Innsbruck University, Austria; Conselho Nacional de Desenvolvimento Cientifico e Tecnologico (CNPq), Fundacao de Amparo a Pesquisa do Estado do Rio de Janeiro (FAPERJ), Fundacao de Amparo a Pesquisa do Estado de Sao Paulo (FAPESP), Ministry of Science, Technology, Innovations and Communications (MCTIC), and Instituto Serrapilheira, Brasil; Ministry of Education and Science, National RI Roadmap Project DO1-153/28.08.2018, Bulgaria; The Natural Sciences and Engineering Research Council of Canada and the Canadian Space Agency, Canada; CONICYT-Chile grants CATA AFB 170002, ANID PIA/APOYO AFB 180002, ACT 1406, FONDECYT-Chile grants, 1161463, 1170171, 1190886, 1171421, 1170345, 1201582, Gemini-ANID 32180007, Chile; Croatian Science Foundation, Rudjer Boskovic Institute, University of Osijek, University of Rijeka, University of Split, Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture, University of Zagreb, Faculty of Electrical Engineering and Computing, Croatia; Ministry of Education, Youth and Sports, MEYS LM2015046, LM2018105, LTT17006, EU/MEYS CZ.02.1.01/0.0/0.0/16_013/0001403, CZ.02.1.01/0.0/0.0/18_046/0016007 and CZ.02.1.01/0.0/0.0/16_019/0000754, Czech Republic; Academy of Finland (grant nr.317636, 320045, 317383 and 320085), Finland; Ministry of Higher Education and Research, CNRS-INSU and CNRS-IN2P3, CEA-Irfu, ANR, Regional Council Ile de France, Labex ENIGMASS, OSUG2020, P2IO and OCEVU, France; Max Planck Society, BMBF, DESY, Helmholtz Association, Germany; Department of Atomic Energy, Department of Science and Technology, India; Istituto Nazionale di Astrofisica (INAF), Istituto Nazionale di Fisica Nucleare (INFN), MIUR, Istituto Nazionale di Astrofisica (INAF-OABRERA) Grant Fondazione Cariplo/Regione Lombardia ID 2014-1980/RST_ERC, Italy; ICRR, University of Tokyo, JSPS, MEXT, Japan; Netherlands Research School for Astronomy (NOVA), Netherlands Organization for Scientific Research (NWO), Netherlands; University of Oslo, Norway; Ministry of Science and Higher Education, DIR/WK/2017/12, the National Centre for Research and Development and the National Science Centre, UMO-2016/22/M/ST9/00583, Poland; Slovenian Research Agency, grants P1-0031, P1-0385, I0-0033, J1-9146, J1-1700, N1-0111, and the Young Researcher program, Slovenia; South African Department of Science and Technology and National Research Foundation through the South African Gamma-Ray Astronomy Programme, South Africa; The Spanish Ministry of Science and Innovation and the Spanish Research State Agency (AEI) through grants AYA2016-79724-C4-1-P, AYA2016-80889-P, AYA2016-76012-C3-1-P, BES-2016-076342, ESP2017-87055-C2-1-P, FPA2017-82729-C6-1-R, FPA2017-82729-C6-2-R, FPA2017-82729-C6-3-R, FPA2017-82729-C6-4-R, FPA2017-82729-C6-5-R, FPA2017-82729-C6-6-R, PGC2018-095161-B-I00, PGC2018-095512-B-I00; the \Centro de Excelencia Severo Ochoa"program through grants no. SEV-2015-0548, SEV-2016-0597, SEV-2016-0588, SEV-2017-0709; the "Unidad de Excelencia Maria de Maeztu" program through grant no. MDM-2015-0509; the "Ramon y Cajal" programme through grants RYC-2013-14511, RyC-2013-14660, RYC-2017-22665; and the MultiDark Consolider Network FPA2017-90566-REDC. Atraccion de Talento contract no. 2016-T1/TIC-1542 granted by the Comunidad de Madrid; the "Postdoctoral Junior Leader Fellowship" programme from La Caixa Banking Foundation, grants no. LCF/BQ/LI18/11630014 and LCF/BQ/PI18/11630012; the "Programa Operativo" FEDER2014-2020, Consejeria de Economia y Conocimiento de la Junta de Andalucia (ref. 1257737), PAIDI 2020 (ref. P18-FR-1580), and Universidad de Jaen; the Spanish AEI EQC2018-005094-P FEDER 2014-2020; the European Union's "Horizon 2020" research and innovation programme under Marie Sklodowska-Curie grant agreement no. 665919; and the ESCAPE project with grant no. GA:824064, Spain; Swedish Research Council, Royal Physiographic Society of Lund, Royal Swedish Academy of Sciences, The Swedish National Infrastructure for Computing (SNIC) at Lunarc (Lund), Sweden; State Secretariat for Education, Research and Innovation (SERI) and Swiss National Science Foundation (SNSF), Switzerland; Durham University, Leverhulme Trust, Liverpool University, University of Leicester, University of Oxford, Royal Society, Science and Technology Facilities Council, U.K.; U.S. National Science Foundation, U.S. Department of Energy, Argonne National Laboratory, Barnard College, University of California, University of Chicago, Columbia University, Georgia Institute of Technology, Institute for Nuclear and Particle Astrophysics (INPAC-MRPI program), Iowa State University, the Smithsonian Institution, Washington University McDonnell Center for the Space Sciences, The University of Wisconsin and the Wisconsin Alumni Research Foundation, U.S.A. The research leading to these results has received funding from the European Union's Seventh Framework Programme (FP7/2007-2013) under grant agreements No 262053 and No 317446. This project is receiving funding from the European Union's Horizon 2020 research and innovation programs under agreement No 676134.
Published: 2022

3. The resolved stellar populations in the LEGUS galaxies

Author: Sabbi, E., Calzetti, D., Ubeda, L., Adamo, A., Cignoni, M., Thilker, D., Alessandra Aloisi, Elmegreen, B. G., Elmegreen, D. M., Gouliermis, D. A., Grebel, E. K., Messa, M., Smith, L. J., Tosi, M., Dolphin, A., Andrews, J. E., Ashworth, G., Bright, S. N., Brown, T. M., Chandar, R., Christian, C., Clayton, G. C., Cook, D. O., Dale, D. A., Mink, S. E., Dobbs, C., Evans, A. S., Fumagalli, M., Gallagher, J. S., Grasha, K., Herrero, A., Hunter, D. A., Johnson, K. E., Kahre, L., Kennicutt, R. C., Kim, H., Krumholz, M. R., Lee, J. C., Lennon, D., Martin, C., Nair, P., Nota, A., Ostlin, G., Pellerin, A., Prieto, J., Regan, M. W., Ryon, J. E., Sacchi, E., Schaerer, D., Schiminovich, D., Shabani, F., Dyk, S. D., Walterbos, R., Whitmore, B. C., and Wofford, A.
Subjects: Astrophysics of Galaxies (astro-ph.GA), FOS: Physical sciences, Astrophysics::Solar and Stellar Astrophysics, Astrophysics::Earth and Planetary Astrophysics, Astrophysics::Cosmology and Extragalactic Astrophysics, Astrophysics - Astrophysics of Galaxies, Astrophysics::Galaxy Astrophysics
Abstract: The Legacy ExtraGalactic UV Survey (LEGUS) is a multiwavelength Cycle 21 Treasury program on the Hubble Space Telescope. It studied 50 nearby star-forming galaxies in five bands from the near UV to the I-band, combining new Wide Field Camera 3 observations with archival Advanced Camera for Surveys data. LEGUS was designed to investigate how star formation occurs and develops on both small and large scales, and how it relates to the galactic environments. In this paper we present the photometric catalogs for all the apparently single stars identified in the 50 LEGUS galaxies. Photometric catalogs and mosaicked images for all filters are available for download. We present optical and near UV color-magnitude diagrams for all the galaxies. For each galaxy we derived the distance from the tip of the red giant branch. We then used the NUV color-magnitude diagrams to identify stars more massive than 14 Mo, and compared their number with the number of massive stars expected from the GALEX FUV luminosity. Our analysis shows that the fraction of massive stars forming in star clusters and stellar associations is about constant with the star formation rate. This lack of a relation suggests that the time scale for evaporation of unbound structures is comparable or longer than 10 Myr. At low star formation rates this translates to an excess of mass in clustered environments as compared to model predictions of cluster evolution, suggesting that a significant fraction of stars form in unbound systems., 71 pages, 15 figures, 4 tables, Accpeted for publication on ApJS
Published: 2018

4. The Catalogue for Astrophysical Turbulence Simulations (CATS).

Author: Burkhart, B., Appel, S. M., Bialy, S., Cho, J., Christensen, A. J., Collins, D., Federrath, C., Fielding, D. B., Finkbeiner, D., Hill, A. S., Ibáńez-Mejía, J. C., Krumholz, M. R., Lazarian, A., Li, M., Mocz, P., Low, M.-M. Mac, Naiman, J., Portillo, S. K. N., Shane, B., and Slepian, Z.
Subjects: TURBULENCE, STELLAR evolution, ASTRONOMICAL catalogs, CATS, POWER spectra
Abstract: Turbulence is a key process in many fields of astrophysics. Advances in numerical simulations of fluids over the last several decades have revolutionized our understanding of turbulence and related processes such as star formation and cosmic ray propagation. However, data from numerical simulations of astrophysical turbulence are often not made public. We introduce a new simulation-oriented database for the astronomical community: the Catalogue for Astrophysical Turbulence Simulations (CATS), located at www.mhdturbulence.com. CATS includes magnetohydrodynamic (MHD) turbulent box simulation data products generated by the public codes athena++ , arepo , enzo, and flash. CATS also includes several synthetic observational data sets, such as turbulent HI data cubes. We also include measured power spectra and three-point correlation functions from some of these data. We discuss the importance of open-source statistical and visualization tools for the analysis of turbulence simulations such as those found in CATS. [ABSTRACT FROM AUTHOR]
Published: 2020
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5. THE MOSFIRE DEEP EVOLUTION FIELD (MOSDEF) SURVEY: REST-FRAME OPTICAL SPECTROSCOPY FOR similar to 1500 H-SELECTED GALAXIES AT 1.37 <= z <= 3.8

Author: Kriek, M, Shapley, AE, Reddy, NA, Siana, B, Coil, AL, Mobasher, B, Freeman, WR, de Groot, L, Price, SH, Sanders, R, Shivaei, I, Brammer, GB, Momcheva, IG, Skelton, RE, van Dokkum, PG, Whitaker, KE, Aird, J, Azadi, M, Kassis, M, Bullock, JS, Conroy, C, Dave, R, Keres, D, and Krumholz, M
Subjects: formation [galaxies], surveys, distances and redshifts [galaxies], evolution [galaxies], high-redshift [galaxies]
Published: 2015

6. Connecting young star clusters to CO molecular gas in NGC 7793 with ALMA–LEGUS.

Author: Grasha, K, Calzetti, D, Bittle, L, Johnson, K E, Donovan Meyer, J, Kennicutt, R C, Elmegreen, B G, Adamo, A, Krumholz, M R, and Fumagalli, M
Subjects: MOLECULAR gastronomy, STAR clusters, MOLECULAR clouds, GALAXIES, ASTRONOMICAL observations
Abstract: We present an investigation of the relationship between giant molecular cloud (GMC) properties and the associated stellar clusters in the nearby flocculent galaxy NGC 7793. We combine the star cluster catalogue from the HST LEGUS (Legacy ExtraGalactic UV Survey) programme with the 15 pc resolution ALMA CO(2–1) observations. We find a strong spatial correlation between young star clusters and GMCs such that all clusters still associated with a GMC are younger than 11 Myr and display a median age of 2 Myr. The age distribution increases gradually as the cluster–GMC distance increases, with star clusters that are spatially unassociated with molecular gas exhibiting a median age of 7 Myr. Thus, star clusters are able to emerge from their natal clouds long before the time-scale required for clouds to disperse. To investigate if the hierarchy observed in the stellar components is inherited from the GMCs, we quantify the amount of clustering in the spatial distributions of the components and find that the star clusters have a fractal dimension slope of −0.35 ± 0.03, significantly more clustered than the molecular cloud hierarchy with slope of −0.18 ± 0.04 over the range 40–800 pc. We find, however, that the spatial clustering becomes comparable in strength for GMCs and star clusters with slopes of −0.44 ± 0.03 and −0.45 ± 0.06, respectively, when we compare massive (>105 M⊙) GMCs to massive and young star clusters. This shows that massive star clusters trace the same hierarchy as their parent GMCs, under the assumption that the star formation efficiency is a few per cent. [ABSTRACT FROM AUTHOR]
Published: 2018
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7. Molecular gas masses of gamma-ray burst host galaxies.

Author: Michałowski, Michał J., Karska, A., Rizzo, J. R., Baes, M., Castro-Tirado, A. J., Hjorth, J., Hunt, L. K., Kamphuis, P., Koprowski, M. P., Krumholz, M. R., Malesani, D., Nicuesa Guelbenzu, A., Rasmussen, J., Rossi, A., Schady, P., Sollerman, J., and van der Werf, P.
Subjects: GALAXIES, GAMMA rays, STAR formation, ACCRETION (Astrophysics), CARBON monoxide & the environment
Abstract: Context. Long gamma-ray bursts (GRBs) can potentially be used as a tool to study star formation and recent gas accretion onto galaxies. However, the information about gas properties of GRB hosts is scarce. In particular, very few carbon monoxide (CO) line detections of individual GRB hosts have been reported. It has also been suggested that GRB hosts have lower molecular gas masses than expected from their star formation rates (SFRs). Aims. The objectives of this paper are to analyse molecular gas properties of the first substantial sample of GRB hosts and test whether they are deficient in molecular gas. Methods. We obtained CO(2-1) observations of seven GRB hosts with the APEX and IRAM 30 m telescopes. We analysed these data together with all other hosts with previous CO observations. From these observations we calculated the molecular gas masses of these galaxies and compared them with the expected values based on their SFRs and metallicities. Reults. We obtained detections for 3 GRB hosts (980425, 080207, and 111005A) and upper limits for the remaining 4 (031203, 060505, 060814, and 100316D). In our entire sample of 12 CO-observed GRB hosts, 3 are clearly deficient in molecular gas, even taking into account their metallicity (980425, 060814, and 080517). Four others are close to the best-fit line for other star-forming galaxies on the SFR-MH2 plot (051022, 060505, 080207, and 100316D). One host is clearly molecule rich (111005A). Finally, the data for 4 GRB hosts are not deep enough to judge whether they are molecule deficient (000418, 030329, 031203, and 090423). The median value of the molecular gas depletion time, MH2/SFR, of GRB hosts is ∼0.3 dex below that of other star-forming galaxies, but this result has low statistical significance. A Kolmogorov–Smirnov test performed on MH2/SFR shows an only ∼2σ difference between GRB hosts and other galaxies. This difference can partly be explained by metallicity effects, since the significance decreases to ∼1σ for MH2/SFR versus metallicity. Conclusions. We found that any molecular gas deficiency of GRB hosts has low statistical significance and that it can be attributed to their lower metallicities; and thus the sample of GRB hosts has molecular properties that are consistent with those of other galaxies, and they can be treated as representative star-forming galaxies. However, the molecular gas deficiency can be strong for GRB hosts if they exhibit higher excitations and/or a lower CO-to-H2 conversion factor than we assume, which would lead to lower molecular gas masses than we derive. Given the concentration of atomic gas recently found close to GRB and supernova sites, indicating recent gas inflow, our results about the weak molecular deficiency imply that such an inflow does not enhance the SFRs significantly, or that atomic gas converts efficiently into the molecular phase, which fuels star formation. Only if the analysis of a larger GRB host sample reveals molecular deficiency (especially close to the GRB position) would this support the hypothesis of star formation that is directly fuelled by atomic gas. [ABSTRACT FROM AUTHOR]
Published: 2018
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8. On the physical mechanisms governing the cloud lifecycle in the Central Molecular Zone of the Milky Way.

Author: Jeffreson, S M R, Kruijssen, J M D, Krumholz, M R, and Longmore, S N
Subjects: MOLECULAR clouds, GRAVITATIONAL instability, GRAVITATIONAL collapse, ASTROPHYSICAL collisions, STAR formation, MILKY Way
Abstract: We apply an analytic theory for environmentally dependent molecular cloud lifetimes to the Central Molecular Zone of the Milky Way. Within this theory, the cloud lifetime in the Galactic Centre is obtained by combining the time-scales for gravitational instability, galactic shear, epicyclic perturbations, and cloud–cloud collisions. We find that at galactocentric radii ∼45–120 pc, corresponding to the location of the ‘100-pc stream’, cloud evolution is primarily dominated by gravitational collapse, with median cloud lifetimes between 1.4 and 3.9 Myr. At all other galactocentric radii, galactic shear dominates the cloud lifecycle, and we predict that molecular clouds are dispersed on time-scales between 3 and 9 Myr, without a significant degree of star formation. Along the outer edge of the 100-pc stream, between radii of 100 and 120 pc, the time-scales for epicyclic perturbations and gravitational free-fall are similar. This similarity of time-scales lends support to the hypothesis that, depending on the orbital geometry and timing of the orbital phase, cloud collapse and star formation in the 100-pc stream may be triggered by a tidal compression at pericentre. Based on the derived time-scales, this should happen in approximately 20 per cent of all accretion events on to the 100-pc stream. [ABSTRACT FROM AUTHOR]
Published: 2018
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9. Full-disc 13CO(1-0) mapping across nearby galaxies of the EMPIRE survey and the CO-to-H2 conversion factor.

Author: Cormier, D., Bigiel, F., Jiménez-Donaire, M. J., Leroy, A. K., Gallagher, M., Usero, A., Sandstrom, K., Bolatto, A., Hughes, A., Kramer, C., Krumholz, M. R., Meier, D. S., Murphy, E. J., Pety, J., Rosolowsky, E., Schinnerer, E., Schruba, A., Sliwa, K., and Walter, F.
Subjects: GALACTIC evolution, CARBON monoxide, TELESCOPES, STAR formation, OPTICAL depth (Astrophysics), ISOTOPOLOGUES
Abstract: Carbon monoxide (CO) provides crucial information about the molecular gas properties of galaxies. While 12CO has been targeted extensively, isotopologues such as 13CO have the advantage of being less optically thick and observations have recently become accessible across full galaxy discs. We present a comprehensive new data set of 13CO(1-0) observations with the IRAM30-m telescope of the full discs of nine nearby spiral galaxies from the EMPIRE survey at a spatial resolution of ~1.5 kpc. 13CO(1-0) is mapped out to 0.7 - 1 r25 and detected at high signal-to-noise ratio throughout our maps. We analyse the 12CO(1-0)-to-13CO(1-0) ratio (ж) as a function of galactocentric radius and other parameters such as the 12CO(2-1)-to- 12CO(1-0) intensity ratio, the 70-to-160 μm flux density ratio, the star formation rate surface density, the star formation efficiency, and the CO-to-H2 conversion factor.We find thatжvaries by a factor of 2 at most within and amongst galaxies, with a median value of 11 and larger variations in the galaxy centres than in the discs.We argue that optical depth effects, most likely due to changes in the mixture of diffuse/dense gas, are favoured explanations for the observed ж variations, while abundance changes may also be at play. We calculate a spatially resolved 13CO(1-0)-to-H2 conversion factor and find an average value of 1.0×1021 cm-2 (K km s-1)-1 over our sample with a standard deviation of a factor of 2. We find that 13CO(1-0) does not appear to be a good predictor of the bulk molecular gas mass in normal galaxy discs due to the presence of a large diffuse phase, but it may be a better tracer of the mass than 12CO(1-0) in the galaxy centres where the fraction of dense gas is larger. [ABSTRACT FROM AUTHOR]
Published: 2018
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10. Exploring the IMF of star clusters: a joint SLUG and LEGUS effort.

Author: Ashworth, G., Fumagalli, M., Krumholz, M. R., Adamo, A., Calzetti, D., Chandar, R., Cignoni, M., Dale, D., Elmegreen, B. G., Gallagher III, J. S., Gouliermis, D. A., Grasha, K., Grebel, E. K., Johnson, K. E., Lee, J., Tosi, M., and Wofford, A.
Subjects: STAR clusters, STELLAR density (Stellar population), STELLAR initial mass function, ASTERISMS (Astronomy), OPEN clusters of stars
Abstract: We present the implementation of a Bayesian formalism within the Stochastically Lighting Up Galaxies (SLUG) stellar population synthesis code, which is designed to investigate variations in the initial mass function (IMF) of star clusters. By comparing observed cluster photometry to large libraries of clusters simulated with a continuously varying IMF, our formalism yields the posterior probability distribution function (PDF) of the cluster mass, age and extinction, jointly with the parameters describing the IMF. We apply this formalism to a sample of star clusters from the nearby galaxy NGC 628, for which broad-band photometry in five filters is available as part of the Legacy ExtraGalactic UV Survey (LEGUS). After allowing the upper-end slope of the IMF (α3)) to vary, we recover PDFs for the mass, age and extinction that are broadly consistent with what is found when assuming an invariant Kroupa IMF. However, the posterior PDF for α3) is very broad due to a strong degeneracy with the cluster mass, and it is found to be sensitive to the choice of priors, particularly on the cluster mass. We find only a modest improvement in the constraining power of α3) when adding Ha photometry from the companion Ha-LEGUS survey. Conversely, Ha photometry significantly improves the age determination, reducing the frequency of multi-modal PDFs. With the aid of mock clusters, we quantify the degeneracy between physical parameters, showing how constraints on the cluster mass that are independent of photometry can be used to pin down the IMF properties of star clusters. [ABSTRACT FROM AUTHOR]
Published: 2017
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11. Literacy and knowledge, attitudes and behavior about mammography in Latinas.

Author: Guerra CE, Krumholz M, and Shea JA
Abstract: This cross-sectional study explored the association between functional health literacy and the knowledge, beliefs, attitudes, and behavior about mammography and self-breast examination in a sample of Latinas attending community health clinics in Philadelphia. The results show that 70% of Latinas had inadequate or marginal functional health literacy. In Latinas, functional health literacy is only weakly associated with knowledge and not associated with beliefs and attitudes about screening mammography, but is significantly associated with having ever had a mammogram. After adjusting for demographic characteristics, functional health literacy was significantly associated with having ever had a mammogram (odds ratio [OR] 1.14, 95% confidence interval [CI] 1.02-1.27). These findings suggest that Latinas with poor functional health literacy are less likely to undergo mammography. Future research should target increasing the knowledge about and rates of screening mammography in patients with low functional health literacy. [ABSTRACT FROM AUTHOR]
Published: 2005
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12. 6-Mercaptopurine in the management of inflammatory bowel disease: short- and long-term toxicity.

Author: Present, Daniel H., Meltzer, Stephen J., Krumholz, Michael P., Wolke, Anita, Korelitz, Burton I., Present, D H, Meltzer, S J, Krumholz, M P, Wolke, A, and Korelitz, B I
Subjects: DRUG toxicity, INFLAMMATORY bowel diseases
Abstract: We assess toxicity related to 6-mercaptopurine in the treatment of inflammatory bowel disease by reporting our experience with 396 patients (120 patients with ulcerative colitis, 276 with Crohn disease) observed over 18 years. Follow-up data for a mean period of 60.3 months were obtained for 90% of the patients. Toxicity directly induced by 6-mercaptopurine included pancreatitis in 13 patients (3.3%), bone marrow depression in 8 (2%), allergic reactions in 8 (2%), and drug hepatitis in 1 (0.3%). These complications were reversible in all cases with no mortality. Most cases of marrow depression occurred earlier in our experience, when the initial drug doses used were higher. Infectious complications were seen in 29 patients (7.4%), of which 7 (1.8%) were severe, including one instance of herpes zoster encephalitis. All infections were reversible with no deaths. Twelve neoplasms (3.1%) were observed, but only 1 (0.3%), a diffuse histiocytic lymphoma of the brain, had a probable association with the use of 6-mercaptopurine. Our data, showing a low incidence of toxicity in 396 patients, coupled with the previously demonstrated efficacy of 6-mercaptopurine in the treatment of inflammatory bowel disease, indicate that the drug is a reasonable alternative in the management of patients with intractable inflammatory bowel disease. [ABSTRACT FROM AUTHOR]
Published: 1989
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13. Inflow of atomic gas fuelling star formation.

Author: Michałowski, M. J., Gentile, G., Hjorth, J., Krumholz, M. R., Tanvir, N. R., Kamphuis, P., Burlon, D., Baes, M., Basa, S., Berta, S., Cerón, J. M. Castro, Crosby, D., D'Elia, V., Elliott, J., Greiner, J., Hunt, L. K., Klose, S., Koprowski, M. P., Le Floc'h, E., and Malesani, D.
Abstract: Gamma-ray burst host galaxies are deficient in molecular gas, and show anomalous metal-poor regions close to GRB positions. Using recent Australia Telescope Compact Array (ATCA) Hi observations we show that they have substantial atomic gas reservoirs. This suggests that star formation in these galaxies may be fuelled by recent inflow of metal-poor atomic gas. While this process is debated, it can happen in low-metallicity gas near the onset of star formation because gas cooling (necessary for star formation) is faster than the Hi-to-H2 conversion. [ABSTRACT FROM PUBLISHER]
Published: 2015
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14. The dependence of the hierarchical distribution of star clusters on galactic environment

Author: Linda J. Smith, Bruce G. Elmegreen, Néstor Sánchez, Daniel A. Dale, Matteo Messa, Mark R. Krumholz, Shyam H. Menon, Michele Fumagalli, Elena Sabbi, Kathryn Grasha, Angela Adamo, Christoph Federrath, David O. Cook, S. T. Linden, Robert C. Kennicutt, Kelsey E. Johnson, Daniela Calzetti, Eva K. Grebel, Menon, S, Grasha, K, Elmegreen, B, Federrath, C, Krumholz, M, Calzetti, D, Sanchez, N, Linden, S, Adamo, A, Messa, M, Cook, D, Dale, D, Grebel, E, Fumagalli, M, Sabbi, E, Johnson, K, Smith, L, and Kennicutt, R
Subjects: ISM: structure, FOS: Physical sciences, Scale (descriptive set theory), Astrophysics, Astrophysics::Cosmology and Extragalactic Astrophysics, Spatial distribution, Fractal dimension, Fractal, Range (statistics), Astrophysics::Solar and Stellar Astrophysics, Solar and Stellar Astrophysics (astro-ph.SR), Astrophysics::Galaxy Astrophysics, Physics, Astronomy and Astrophysics, Astrophysics - Astrophysics of Galaxies, Galaxy, Distribution (mathematics), Star cluster, Astrophysics - Solar and Stellar Astrophysics, Space and Planetary Science, Astrophysics of Galaxies (astro-ph.GA), galaxies: star formation, galaxies: star clusters: general, galaxies: statistic, galaxies: stellar content, galaxies: structure, Astrophysics::Earth and Planetary Astrophysics
Abstract: We use the angular Two Point Correlation Function (TPCF) to investigate the hierarchical distribution of young star clusters in 12 local (3--18 Mpc) star-forming galaxies using star cluster catalogues obtained with the \textit{Hubble Space Telescope} (\textit{HST}) as part of the Treasury Program LEGUS (Legacy ExtraGalactic UV Survey). The sample spans a range of different morphological types, allowing us to infer how the physical properties of the galaxy affect the spatial distribution of the clusters. We also prepare a range of physically motivated toy models to compare with and interpret the observed features in the TPCFs. We find that, conforming to earlier studies, young clusters ($T \la 10\, \mathrm{Myr}$) have power-law TPCFs that are characteristic of fractal distributions with a fractal dimension $D_2$, and this scale-free nature extends out to a maximum scale $l_{\mathrm{corr}}$ beyond which the distribution becomes Poissonian. However, $l_{\mathrm{corr}}$, and $D_2$ vary significantly across the sample, and are correlated with a number of host galaxy physical properties, suggesting that there are physical differences in the underlying star cluster distributions. We also find that hierarchical structuring weakens with age, evidenced by flatter TPCFs for older clusters ($T \ga 10\, \mathrm{Myr}$), that eventually converges to the residual correlation expected from a completely random large-scale radial distribution of clusters in the galaxy in $\sim 100 \, \mathrm{Myr}$. Our study demonstrates that the hierarchical distribution of star clusters evolves with age, and is strongly dependent on the properties of the host galaxy environment., 19 pages, 8 figures. Accepted for publication in MNRAS. Code for analysis and reproducing results available at https://github.com/shm-1996/legus-tpcf
Published: 2021

15. SLUG IV: A novel forward-modelling method to derive the demographics of star clusters

Author: Michele Fumagalli, Daniela Calzetti, Mark R. Krumholz, Angela Adamo, Krumholz, M, Adamo, A, Fumagalli, M, and Calzetti, D
Subjects: Population, FOS: Physical sciences, Astrophysics::Cosmology and Extragalactic Astrophysics, 01 natural sciences, Article, Photometry (optics), 0103 physical sciences, Astrophysics::Solar and Stellar Astrophysics, education, 010303 astronomy & astrophysics, Stellar evolution, Astrophysics::Galaxy Astrophysics, Galaxies: star clusters: general, Methods: statistical, Cosmic dust, Physics, education.field_of_study, Observational error, 010308 nuclear & particles physics, Astronomy and Astrophysics, Astrophysics - Astrophysics of Galaxies, Galaxy, Star cluster, Space and Planetary Science, Sample size determination, Astrophysics of Galaxies (astro-ph.GA), Algorithm, Techniques: photometric, Methods: data analysi
Abstract: We describe a novel method for determining the demographics of a population of star clusters, for example distributions of cluster mass and age, from unresolved photometry. This method has a number of desirable properties: it fully exploits all the information available in a data set without any binning, correctly accounts for both measurement error and sample incompleteness, naturally handles heterogenous data (for example fields that have been imaged with different sets of filters or to different depths), marginalises over uncertain extinctions, and returns the full posterior distributions of the parameters describing star cluster demographics. We demonstrate the method using mock star cluster catalogs and show that our method is robust and accurate, and that it can recover the demographics of star cluster populations significantly better than traditional fitting methods. For realistic sample sizes, our method is sufficiently powerful that its accuracy is ultimately limited by the accuracy of the underlying physical models for stellar evolution and interstellar dust, rather than by statistical uncertainties. Our method is implemented as part of the Stochastically Lighting Up Galaxies (SLUG) stellar populations code, and is freely available., Comment: 18 pages, 13 figures, MNRAS in press
Published: 2019

16. The momentum budget of clustered supernova feedback in a 3D, magnetized medium

Author: Piero Madau, Alessandro Lupi, Eric S. Gentry, Mark R. Krumholz, Gentry, E, Krumholz, M, Madau, P, and Lupi, A
Subjects: International research, Physics, 010308 nuclear & particles physics, European research, Astrophysics::High Energy Astrophysical Phenomena, FOS: Physical sciences, Library science, Astronomy and Astrophysics, Astrophysics::Cosmology and Extragalactic Astrophysics, Hydrodynamic, 01 natural sciences, Astrophysics - Astrophysics of Galaxies, Space and Planetary Science, Research council, Astrophysics of Galaxies (astro-ph.GA), Magnetic fields, 0103 physical sciences, ISM: bubble, 010303 astronomy & astrophysics, Astrophysics::Galaxy Astrophysics, ISM: supernova remnant
Abstract: While the evolution of superbubbles driven by clustered supernovae has been studied by numerous authors, the resulting radial momentum yield is uncertain by as much as an order of magnitude depending on the computational methods and assumed properties of the surrounding interstellar medium (ISM). In this work, we study the origin of these discrepancies, and seek to determine the correct momentum budget for a homogeneous ISM. We carry out 3D hydrodynamic (HD) and magnetohydrodynamic (MHD) simulations of clustered supernova explosions, using a Lagrangian method and checking for convergence with respect to resolution. We find that the terminal momentum of a shell driven by clustered supernovae is dictated primarily by the mixing rate across the contact discontinuity between the hot and cold phases, and that this energy mixing rate is dominated by numerical diffusion even at the highest resolution we can complete, 0.03 $M_\odot$. Magnetic fields also reduce the mixing rate, so that MHD simulations produce higher momentum yields than HD ones at equal resolution. As a result, we obtain only a lower limit on the momentum yield from clustered supernovae. Combining this with our previous 1D results, which provide an upper limit because they allow almost no mixing across the contact discontinuity, we conclude that the momentum yield per supernova from clustered supernovae in a homogeneous ISM is bounded between $2\times 10^5$ and $3\times 10^6$ $M_\odot$ km s$^{-1}$. A converged value for the simple homogeneous ISM remains elusive., 13 page, 11 figures, revised to reflect the published version. Added a deeper analysis estimating physical and numeric mixing rates (Section 4). Added addition simulations to the resolution study
Published: 2019

17. Exploring the IMF of star clusters: a joint SLUG and LEGUS effort

Author: Daniel A. Dale, Kathryn Grasha, Janice C. Lee, Mark R. Krumholz, John S. Gallagher, Michele Cignoni, Dimitrios A. Gouliermis, Angela Adamo, Aida Wofford, D. Calzetti, Bruce G. Elmegreen, G. Ashworth, Rupali Chandar, Michele Fumagalli, Eva K. Grebel, Monica Tosi, K. E. Johnson, Ashworth, G, Fumagalli, M, Krumholz, M, Adamo, A, Calzetti, D, Chandar, R, Cignoni, M, Dale, D, Elmegreen, B, Gallagher, J, Gouliermis, D, Grasha, K, Grebel, E, Johnson, K, Lee, J, Tosi, M, and Wofford, A
Subjects: galaxies: individual: NGC 628, Initial mass function, Stellar population, Posterior probability, FOS: Physical sciences, Astrophysics, Astrophysics::Cosmology and Extragalactic Astrophysics, 01 natural sciences, Photometry (optics), 0103 physical sciences, Prior probability, Cluster (physics), Astrophysics::Solar and Stellar Astrophysics, 010303 astronomy & astrophysics, Astrophysics::Galaxy Astrophysics, Physics, methods: statistical, 010308 nuclear & particles physics, Astronomy, Astronomy and Astrophysics, Astrophysics - Astrophysics of Galaxies, Galaxy, stars: luminosity function, mass function, Star cluster, Space and Planetary Science, Astrophysics of Galaxies (astro-ph.GA), galaxies: star clusters: general
Abstract: We present the implementation of a Bayesian formalism within the Stochastically Lighting Up Galaxies (SLUG) stellar population synthesis code, which is designed to investigate variations in the initial mass function (IMF) of star clusters. By comparing observed cluster photometry to large libraries of clusters simulated with a continuously varying IMF, our formalism yields the posterior probability distribution function (PDF) of the cluster mass, age, and extinction, jointly with the parameters describing the IMF. We apply this formalism to a sample of star clusters from the nearby galaxy NGC 628, for which broad-band photometry in five filters is available as part of the Legacy ExtraGalactic UV Survey (LEGUS). After allowing the upper-end slope of the IMF ($\alpha_3$) to vary, we recover PDFs for the mass, age, and extinction that are broadly consistent with what is found when assuming an invariant Kroupa IMF. However, the posterior PDF for $\alpha_3$ is very broad due to a strong degeneracy with the cluster mass, and it is found to be sensitive to the choice of priors, particularly on the cluster mass. We find only a modest improvement in the constraining power of $\alpha_3$ when adding H$\alpha$ photometry from the companion H$\alpha$-LEGUS survey. Conversely, H$\alpha$ photometry significantly improves the age determination, reducing the frequency of multi-modal PDFs. With the aid of mock clusters we quantify the degeneracy between physical parameters, showing how constraints on the cluster mass that are independent of photometry can be used to pin down the IMF properties of star clusters., Comment: 17 pages, 16 figures, Pre-copyedited version of article accepted for publication in MNRAS following peer review
Published: 2017

18. Hierarchical Star Formation in Turbulent Media: Evidence from Young Star Clusters

Author: Eva K. Grebel, L. Kahre, Dimitrios A. Gouliermis, Daniela Calzetti, Angela Adamo, Michele Fumagalli, Matteo Messa, Mark R. Krumholz, Alessandra Aloisi, J. C. Lee, Daniel A. Dale, Leonardo Ubeda, Hwihyun Kim, Kathryn Grasha, John S. Gallagher, Stacey N. Bright, David O. Cook, Bruce G. Elmegreen, J. E. Ryon, Grasha, K, Elmegreen, B, Calzetti, D, Adamo, A, Aloisi, A, Bright, S, Cook, D, Dale, D, Fumagalli, M, Gallagher, J, Gouliermis, D, Grebel, E, Kahre, L, Kim, H, Krumholz, M, Lee, J, Messa, M, Ryon, J, and Ubeda, L
Subjects: FOS: Physical sciences, Astrophysics, Astrophysics::Cosmology and Extragalactic Astrophysics, 01 natural sciences, Primary (astronomy), Young star, 0103 physical sciences, Cluster (physics), Maximum size, 010303 astronomy & astrophysics, Astrophysics::Galaxy Astrophysics, Physics, stars: formation, 010308 nuclear & particles physics, Turbulence, Star formation, Astronomy and Astrophysics, Astrophysics - Astrophysics of Galaxies, Galaxy, Star cluster, Space and Planetary Science, Astrophysics of Galaxies (astro-ph.GA), galaxies: star formation, galaxies: star clusters: general, galaxies: stellar content, ultraviolet: galaxies, galaxies: structure, ultraviolet: galaxie
Abstract: We present an analysis of the positions and ages of young star clusters in eight local galaxies to investigate the connection between the age difference and separation of cluster pairs. We find that star clusters do not form uniformly but instead are distributed such that the age difference increases with the cluster pair separation to the 0.25-0.6 power, and that the maximum size over which star formation is physically correlated ranges from ~200 pc to ~1 kpc. The observed trends between age difference and separation suggest that cluster formation is hierarchical both in space and time: clusters that are close to each other are more similar in age than clusters born further apart. The temporal correlations between stellar aggregates have slopes that are consistent with turbulence acting as the primary driver of star formation. The velocity associated with the maximum size is proportional to the galaxy's shear, suggesting that the galactic environment influences the maximum size of the star-forming structures., Comment: 13 pages, 10 figures, accepted for publication in ApJ
Published: 2017

19. SLUG - stochastically lighting up galaxies - II. Quantifying the effects of stochasticity on star formation rate indicators

Author: Michele Fumagalli, Mark R. Krumholz, Robert L. da Silva, Da Silva, R, Fumagalli, M, and Krumholz, M
Subjects: Systematic error, statistical [Methods], Cosmology and Nongalactic Astrophysics (astro-ph.CO), Stellar population, Stars: formation, Population, star clusters: general [Galaxies], FOS: Physical sciences, Astrophysics::Cosmology and Extragalactic Astrophysics, Astrophysics, stellar content. [Galaxies], Astrophysics::Solar and Stellar Astrophysics, education, formation [Stars], Astrophysics::Galaxy Astrophysics, Galaxies: star clusters: general, Methods: statistical, Physics, education.field_of_study, numerical [Methods], Methods: numerical, Star formation, photometric [Techniques], Astronomy and Astrophysics, Galaxies: stellar content, Astrophysics - Astrophysics of Galaxies, Galaxy, Stars, Distribution (mathematics), Space and Planetary Science, Astrophysics of Galaxies (astro-ph.GA), Probability distribution, Techniques: photometric, Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: The integrated light of a stellar population, measured through photometric filters that are sensitive to the presence of young stars, is often used to infer the star formation rate (SFR) for that population. However, these techniques rely on an assumption that star formation is a continuous process, whereas in reality stars form in discrete spatially- and temporally-correlated structures. This discreteness causes the light output to undergo significant time-dependent fluctuations, which, if not accounted for, introduce systematic errors in the inferred SFRs due to the intrinsic distribution of luminosities at any fix SFR. We use SLUG, a code that Stochastically Lights Up Galaxies, to simulate galaxies undergoing stochastic star formation. We then use these simulations to present a quantitative analysis of these effects and provide tools for calculating probability distribution functions of SFRs given a set of observations. We show that, depending on the SFR tracer used, stochastic fluctuations can produce non-trivial errors at SFRs as high as 1 M/yr, and biases >0.5 dex at the lowest SFRs. We emphasize that due to the stochastic behavior of blue SFR tracers, one cannot assign a deterministic single value to the SFR of an individual galaxy, but we suggest methods by which future analyses that rely on integrated-light indicators can properly account for these stochastic effects., 13 pages, 8 figures. To appear in MNRAS
Published: 2014

20. SLUG - Stochastically Lighting Up Galaxies I: Methods and Validating Tests

Author: Michele Fumagalli, Mark R. Krumholz, Robert L. da Silva, Da Silva, R, Fumagalli, M, and Krumholz, M
Subjects: statistical [Methods], Initial mass function, 010504 meteorology & atmospheric sciences, Milky Way, star clusters: general [Galaxies], FOS: Physical sciences, Astrophysics, photometric. [Techniques], Astrophysics::Cosmology and Extragalactic Astrophysics, 01 natural sciences, methods: numerical, Photometry (optics), techniques: photometric, 0103 physical sciences, Astrophysics::Solar and Stellar Astrophysics, 010303 astronomy & astrophysics, Stellar evolution, Instrumentation and Methods for Astrophysics (astro-ph.IM), formation [Stars], Astrophysics::Galaxy Astrophysics, 0105 earth and related environmental sciences, Physics, methods: statistical, numerical [Methods], stars: formation, Star formation, Astronomy and Astrophysics, Galaxy, Stars, Star cluster, Space and Planetary Science, galaxies: star clusters: general, galaxies: stellar content, stellar content [Galaxies], Astrophysics::Earth and Planetary Astrophysics, Astrophysics - Instrumentation and Methods for Astrophysics
Abstract: The effects of stochasticity on the luminosities of stellar populations are an often neglected but crucial element for understanding populations in the low mass or low star formation rate regime. To address this issue, we present SLUG, a new code to "Stochastically Light Up Galaxies". SLUG synthesizes stellar populations using a Monte Carlo technique that treats stochastic sampling properly including the effects of clustering, the stellar initial mass function, star formation history, stellar evolution, and cluster disruption. This code produces many useful outputs, including i) catalogs of star clusters and their properties, such as their stellar initial mass distributions and their photometric properties in a variety of filters, ii) two dimensional histograms of color-magnitude diagrams of every star in the simulation, iii) and the photometric properties of field stars and the integrated photometry of the entire simulated galaxy. After presenting the SLUG algorithm in detail, we validate the code through comparisons with starburst99 in the well-sampled regime, and with observed photometry of Milky Way clusters. Finally, we demonstrate the SLUG's capabilities by presenting outputs in the stochastic regime. SLUG is publicly distributed through the website http://sites.google.com/site/runslug/., 15 pages, 5 tables, 12 figures, Submitted to ApJ. Code is available for download at https://sites.google.com/site/runslug/
Published: 2011

21. Molecular Hydrogen deficiency in HI-poor galaxies and its implications for star formation

Author: Giuseppe Gavazzi, J. Xavier Prochaska, Mark R. Krumholz, Michele Fumagalli, Alessandro Boselli, Fumagalli, M, Krumholz, M, Prochaska, X, Gavazzi, G, and Boselli, A
Subjects: Physics, Cosmology and Nongalactic Astrophysics (astro-ph.CO), Spiral galaxy, 010308 nuclear & particles physics, Gas depletion, Star formation, Hydrogen molecule, FOS: Physical sciences, Astronomy and Astrophysics, Astrophysics, Astrophysics::Cosmology and Extragalactic Astrophysics, Critical value, 01 natural sciences, Galaxy, Stars, FIS/05 - ASTRONOMIA E ASTROFISICA, Far infrared, Space and Planetary Science, 0103 physical sciences, galaxies, 010303 astronomy & astrophysics, Astrophysics::Galaxy Astrophysics, Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: We use a sample of 47 homogeneous and high sensitivity CO images taken from the Nobeyama and BIMA surveys to demonstrate that, contrary to common belief, a significant number (~40%) of HI-deficient nearby spiral galaxies are also depleted in molecular hydrogen. While HI-deficiency by itself is not a sufficient condition for molecular gas depletion, we find that H2 reduction is associated with the removal of HI inside the galaxy optical disk. Those HI-deficient galaxies with normal H2 content have lost HI mainly from outside their optical disks, where the H2 content is low in all galaxies. This finding is consistent with theoretical models in which the molecular fraction in a galaxy is determined primarily by its gas column density. Our result is supported by indirect evidence that molecular deficient galaxies form stars at a lower rate or have dimmer far infrared fluxes than gas rich galaxies, as expected if the star formation rate is determined by the molecular hydrogen content. Our result is consistent with a scenario in which, when the atomic gas column density is lowered inside the optical disk below the critical value required to form molecular hydrogen and stars, spirals become quiescent and passive evolving systems. We speculate that this process would act on the time-scale set by the gas depletion rate and might be a first step for the transition between the blue and red sequence observed in the color-magnitude diagram., 12 pages, 9 figures, accepted for publication in ApJ
Published: 2009

22. Prediction of ICU Readmissions Using Data at Patient Discharge.

Author: Pakbin A, Rafi P, Hurley N, Schulz W, Harlan Krumholz M, and Bobak Mortazavi J
Subjects: Humans, Intensive Care Units, Retrospective Studies, Patient Discharge, Patient Readmission
Abstract: Unplanned readmissions to ICU contribute to high health care costs and poor patient outcomes. 6-7% of all ICU cases see a readmission within 72 hours. Machine learning models on electronic health record data can help identify these cases, providing more information about short and long-term risks to clinicians at the time of ICU discharge. While time-toevent techniques have been used in clinical care, models that identify risks over time using higher-dimensional, non-linear machine learning models need to be developed to present changes in risk with non-linear techniques. This work identifies risks of ICU readmissions at 24 hours, 72 hours, 7 days, 30 days, and bounceback readmissions in the same hospital admission with an AUROC for 72 hours of 0.76 and for bounceback of 0.84.
Published: 2018
Full Text: View/download PDF

23. The intense starburst HDF 850.1 in a galaxy overdensity at z ≈ 5.2 in the Hubble Deep Field.

Author: Walter F, Decarli R, Carilli C, Bertoldi F, Cox P, Da Cunha E, Daddi E, Dickinson M, Downes D, Elbaz D, Ellis R, Hodge J, Neri R, Riechers DA, Weiss A, Bell E, Dannerbauer H, Krips M, Krumholz M, Lentati L, Maiolino R, Menten K, Rix HW, Robertson B, Spinrad H, Stark DP, and Stern D
Abstract: The Hubble Deep Field provides one of the deepest multiwavelength views of the distant Universe and has led to the detection of thousands of galaxies seen throughout cosmic time. An early map of the Hubble Deep Field at a wavelength of 850 micrometres, which is sensitive to dust emission powered by star formation, revealed the brightest source in the field, dubbed HDF 850.1 (ref. 2). For more than a decade, and despite significant efforts, no counterpart was found at shorter wavelengths, and it was not possible to determine its redshift, size or mass. Here we report a redshift of z = 5.183 for HDF 850.1, from a millimetre-wave molecular line scan. This places HDF 850.1 in a galaxy overdensity at z ≈ 5.2, corresponding to a cosmic age of only 1.1 billion years after the Big Bang. This redshift is significantly higher than earlier estimates and higher than those of most of the hundreds of submillimetre-bright galaxies identified so far. The source has a star-formation rate of 850 solar masses per year and is spatially resolved on scales of 5 kiloparsecs, with an implied dynamical mass of about 1.3 × 10(11) solar masses, a significant fraction of which is present in the form of molecular gas. Despite our accurate determination of redshift and position, a counterpart emitting starlight remains elusive.
Published: 2012
Full Text: View/download PDF

24. A technique for compensating for the loose CeraOne screw.

Author: Krumholz ML
Subjects: Dental Implantation, Endosseous, Humans, Molar, Dental Abutments, Dental Implants, Single-Tooth, Dental Prosthesis Repair methods, Dental Prosthesis Retention instrumentation
Abstract: Clinical experience indicates that implant-supported crowns for the replacement of individual molars using the original, regular platform CeraOne protocol (Nobel Biocare) infrequently result in gold screws loosening. This article offers a technique that may prevent the CeraOne gold screw from working loose. It is intended to be a correction for a problem, not a first-time treatment. Also, this is a treatment that should be offered only after the prescribed Brånemark protocol for screw tightening and elimination of excursive contacts has proven ineffective.
Published: 1999

25. Cytosolic alpha-glycerophosphate and lactate dehydrogenase in the lung in endotoxin shock.

Author: Sayeed MM and Krumholz MP
Subjects: Aerobiosis, Animals, Cytosol enzymology, Male, Rats, Shock, Septic etiology, Glycerolphosphate Dehydrogenase metabolism, L-Lactate Dehydrogenase metabolism, Lung enzymology, Shock, Septic enzymology
Abstract: The lung produces lactate aerobically. In endotoxin shock in aerobic production of lactate increases further. We have investigated an enzymic mechanism for the aerobic lactate in the lung. Since an inadequacy of the cytoplasmic hydrogen "shuttle" enzyme alpha-glycerophosphate dehydrogenase (alpha-GPDH) and/or the presence of lactate dehydrogenase (LDH) in excess of alpha-GPDH can cause aerobic formation lactate, we measured alpha-GPDH and LDH in mitochondria-free cytoplasmic fractions of lungs from control and endotoxic shock rats. The shock was induced by an intravenous injection of E coli endotoxin, 16 mg/kg. In lungs of control or endotoxic shock rats, alpha-GPDH was only 10% of the LDH activity. The low absolute levels of alpha-GPDH and the relative deficiency of this enzyme, compared to LDH in the lungs of control and endotoxic shock rats, can potentially contribute to aerobic lactate production.
Published: 1982

26. Clinical trials in ulcerative colitis: II. Historical review.

Author: Margolin ML, Krumholz MP, Fochios SE, and Korelitz BI
Subjects: Anti-Ulcer Agents history, Clinical Trials as Topic, Colitis, Ulcerative history, History, 20th Century, Humans, Sulfasalazine history, Anti-Ulcer Agents therapeutic use, Colitis, Ulcerative drug therapy, Sulfasalazine therapeutic use
Published: 1988

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26 results on '"Krumholz, M."'

1. Constraining the LyC escape fraction from LEGUS star clusters with SIGNALS HII region observations: A pilot study of NGC 628

2. Sensitivity of the Cherenkov Telescope Array to a dark matter signal from the Galactic centre

3. The resolved stellar populations in the LEGUS galaxies

4. The Catalogue for Astrophysical Turbulence Simulations (CATS).

5. THE MOSFIRE DEEP EVOLUTION FIELD (MOSDEF) SURVEY: REST-FRAME OPTICAL SPECTROSCOPY FOR similar to 1500 H-SELECTED GALAXIES AT 1.37 <= z <= 3.8

6. Connecting young star clusters to CO molecular gas in NGC 7793 with ALMA–LEGUS.

7. Molecular gas masses of gamma-ray burst host galaxies.

8. On the physical mechanisms governing the cloud lifecycle in the Central Molecular Zone of the Milky Way.

9. Full-disc 13CO(1-0) mapping across nearby galaxies of the EMPIRE survey and the CO-to-H2 conversion factor.

10. Exploring the IMF of star clusters: a joint SLUG and LEGUS effort.

11. Literacy and knowledge, attitudes and behavior about mammography in Latinas.

12. 6-Mercaptopurine in the management of inflammatory bowel disease: short- and long-term toxicity.

13. Inflow of atomic gas fuelling star formation.

14. The dependence of the hierarchical distribution of star clusters on galactic environment

15. SLUG IV: A novel forward-modelling method to derive the demographics of star clusters

16. The momentum budget of clustered supernova feedback in a 3D, magnetized medium

17. Exploring the IMF of star clusters: a joint SLUG and LEGUS effort

18. Hierarchical Star Formation in Turbulent Media: Evidence from Young Star Clusters

19. SLUG - stochastically lighting up galaxies - II. Quantifying the effects of stochasticity on star formation rate indicators

20. SLUG - Stochastically Lighting Up Galaxies I: Methods and Validating Tests

21. Molecular Hydrogen deficiency in HI-poor galaxies and its implications for star formation

22. Prediction of ICU Readmissions Using Data at Patient Discharge.

23. The intense starburst HDF 850.1 in a galaxy overdensity at z ≈ 5.2 in the Hubble Deep Field.

24. A technique for compensating for the loose CeraOne screw.

25. Cytosolic alpha-glycerophosphate and lactate dehydrogenase in the lung in endotoxin shock.

26. Clinical trials in ulcerative colitis: II. Historical review.

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26 results on '"Krumholz, M."'

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