Author: "Krumholz, M." / Topic: astronomy and astrophysics - Searchworks@Jio Institute Digital Library Search Results

Your search keyword '"Krumholz, M."' showing total 23 results

Start Over Author "Krumholz, M." Topic astronomy and astrophysics

23 results on '"Krumholz, M."'

1. 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. C., Terrier, R., Terzic, T., Teshima, M., Testa, V., Thibaut, D., Thocquenne, F., Tian, W., Tibaldo, L., Tiengo, A., Tiziani, D., Tluczykont, M., Todero Peixoto, C. J., Tokanai, F., Toma, K., Tomankova, L., Tomastik, J., Tonev, D., Tornikoski, M., Torres, D. F., Torresi, E., Tosti, G., Tosti, L., Totani, T., Tothill, N., Toussenel, F., Tovmassian, G., Travnicek, P., Trichard, C., Trifoglio, M., Trois, A., Truzzi, S., Tsiahina, A., Tsuru, T., Turk, B., Tutone, A., Uchiyama, Y., Umana, G., Utayarat, P., Vaclavek, L., Vacula, M., Vagelli, V., Vagnetti, F., Vakili, F., Valdivia, J. A., Valentino, M., Valio, A., Vallage, B., Vallania, P., Valverde Quispe, J. V., Den Berg, A. M., Driel, W., Eldik, C., Rensburg, C., Soelen, B., Vandenbroucke, J., Vanderwalt, J., Vasileiadis, G., Vassiliev, V., Vázquez Acosta, M., Vecchi, M., Vega, A., Veh, J., Veitch, P., Venault, P., Venter, C., Ventura, S., Vercellone, S., Vergani, S., Verguilov, V., Verna, G., Vernetto, S., Verzi, V., Vettolani, G. P., Veyssiere, C., Viale, I., Viana, A., Viaux, N., Vicha, J., Vignatti, J., Vigorito, C. F., Villanueva, J., Vink, J., Vitale, V., Vittorini, V., Vodeb, V., Voelk, H., Vogel, N., Voisin, V., Vorobiov, S., Vovk, I., Vrastil, M., Vuillaume, T., Wagner, S. J., Wagner, R., Wagner, P., Wakazono, K., Wakely, S. P., Walter, R., Ward, M., Warren, D., Watson, J., Webb, N., Wechakama, M., Wegner, P., Weinstein, A., Weniger, C., Werner, F., Wetteskind, H., White, M., White, R., Wierzcholska, A., Wiesand, S., Wijers, R., Wilkinson, M., Will, M., Williams, D. A., Williams, J., Williamson, T., Wolter, A., Wong, Y. W., Wood, M., Wunderlich, C., Yamamoto, T., Yamamoto, H., Yamane, Y., Yamazaki, R., Yanagita, S., Yang, L., Yoo, S., Yoshida, T., Yoshikoshi, T., Yu, P., Yusafzai, A., Zacharias, M., Zaharijas, G., Zaldivar, B., Zampieri, L., Zanmar Sanchez, R., Zaric, D., Zavrtanik, M., Zavrtanik, D., Zdziarski, A. A., Zech, A., Zechlin, H., Zenin, A., Zerwekh, A., Zhdanov, V. 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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. 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., Niko??ajuk, 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., Pavleti??, L., Pe'Er, A., Pecimotika, M., P??rez-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., P??hlhofer, G., Pumo, M. L., Queiroz, F., Quirrenbach, A., Rain??, S., Rando, R., Razzaque, S., Recchia, S., Reimer, O., Reisenegger, A., Renier, Y., Rhode, W., Ribeiro, D., Rib??, 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., S??ther Hatlen, E., Safi-Harb, S., Salesa Greus, F., Salina, G., Sanchez, D., S??nchez-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., 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

2. The brightest young star clusters in NGC 5253

Author: Calzetti, D., Johnson, K. E., Adamo, A., Gallagher J. S., III, Andrews, J. E., Smith, L. J., Clayton, G. C., Lee, J. C., Sabbi, E., Ubeda, L., Kim, H., Ryon, J. E., Thilker, D., Bright, S. N., Zackrisson, E., Kennicutt, R. C., de Mink, S. E., Whitmore, B. C., Aloisi, A., Chandar, R. Cignoni, Cook, D., Dale, D. A., Elmegreen, B. G., Elmegreen, D. M., Evans, A. S., Fumagalli, M., Gouliermis, D. A., Grasha, K., Grebel, E. K., Krumholz, M. R., Walterbos, R., Wofford, A., Brown, T. M., Christian, C., Dobbs, C., Herrero, A., Kahre, L., Messa, M., Nair, P., Nota, A., Östlin, G., Pellerin, A., Sacchi, E., Schaerer, D., Tosi, M., Calzetti, D, Johnson, K, Adamo, A, Gallagher, J, Iii, Andrews, J, Smith, L, Clayton, G, Lee, J, Sabbi, E, Ubeda, L, Kim, H, Ryon, J, Thilker, D, Bright, S, Zackrisson, E, Kennicutt, R, de Mink, S, Whitmore, B, Aloisi, A, Chandar, R., C, Cook, D, Dale, D, Elmegreen, B, Elmegreen, D, Evans, A, Fumagalli, M, Gouliermis, D, Grasha, K, Grebel, E, Krumholz, M, Walterbos, R, Wofford, A, Brown, T, Christian, C, Dobbs, C, Herrero, A, Kahre, L, Messa, M, Nair, P, Nota, A, Östlin, G, Pellerin, A, Sacchi, E, Schaerer, D, Tosi, M, and High Energy Astrophys. & Astropart. Phys (API, FNWI)
Subjects: INITIAL MASS FUNCTION, Astrophysics::High Energy Astrophysical Phenomena, DWARF STARBURST GALAXY, galaxies: dwarf, galaxies: general, galaxies: individual (NGC 5253), galaxies: starburst, galaxies: star clusters: general, FORMING GALAXIES, IONIZED-GAS, STELLAR POPULATIONS, ANTENNAE GALAXIES, H-I, OPTICAL, SPECTROSCOPY, PROTOTYPICAL MERGER, INTERSTELLAR-MEDIUM, FOS: Physical sciences, Starburst region, Astrophysics, Astrophysics::Cosmology and Extragalactic Astrophysics, Astronomi, astrofysik och kosmologi, Young star, star clusters: general [galaxies], Cluster (physics), Astronomy, Astrophysics and Cosmology, Astrophysics::Solar and Stellar Astrophysics, star clusters: general. [Galaxies], Astrophysics::Galaxy Astrophysics, Physics, Nebula, individual (NGC 5253) [Galaxies], Star formation, Astronomy and Astrophysics, general [Galaxies], Astrophysics - Astrophysics of Galaxies, Galaxy, dwarf [Galaxies], Stars, starburst [Galaxies], Star cluster, Space and Planetary Science, Astrophysics of Galaxies (astro-ph.GA), Astrophysics::Earth and Planetary Astrophysics
Abstract: The nearby dwarf starburst galaxy NGC5253 hosts a number of young, massive star clusters, the two youngest of which are centrally concentrated and surrounded by thermal radio emission (the `radio nebula'). To investigate the role of these clusters in the starburst energetics, we combine new and archival Hubble Space Telescope images of NGC5253 with wavelength coverage from 1500 Ang to 1.9 micron in 13 filters. These include H-alpha, P-beta, and P-alpha, and the imaging from the Hubble Treasury Program LEGUS (Legacy Extragalactic UV Survey). The extraordinarily well-sampled spectral energy distributions enable modeling with unprecedented accuracy the ages, masses, and extinctions of the 9 optically brightest clusters (M_V < -8.8) and the two young radio nebula clusters. The clusters have ages ~1-15 Myr and masses ~1x10^4 - 2.5x10^5 M_sun. The clusters' spatial location and ages indicate that star formation has become more concentrated towards the radio nebula over the last ~15 Myr. The most massive cluster is in the radio nebula; with a mass 2.5x10^5 M_sun and an age ~1 Myr, it is 2-4 times less massive and younger than previously estimated. It is within a dust cloud with A_V~50 mag, and shows a clear nearIR excess, likely from hot dust. The second radio nebula cluster is also ~1 Myr old, confirming the extreme youth of the starburst region. These two clusters account for about half of the ionizing photon rate in the radio nebula, and will eventually supply about 2/3 of the mechanical energy in present-day shocks. Additional sources are required to supply the remaining ionizing radiation, and may include very massive stars., 67 pages; 11 figures; 7 tables. Accepted for publication in the Astrophysical Journal
Published: 2015

3. Synthetic photometry of OB star clusters with stochastically sampled IMFs: analysis of models and HST observations

Author: Eva K. Grebel, Timothy Wofford, Mark R. Krumholz, Gustavo Bruzual, Linda J. Smith, David O. Cook, Rogelio Orozco-Duarte, Michele Fumagalli, Stephen Hannon, M. Messa, Aida Wofford, Stéphane Charlot, Janice C. Lee, Alba Vidal-García, Daniel A. Dale, Kathryn Grasha, Orozco-Duarte, R, Wofford, A, Vidal-Garcia, A, Bruzual, G, Charlot, S, Krumholz, M, Hannon, S, Lee, J, Wofford, T, Fumagalli, M, Dale, D, Messa, M, Grebel, E, Smith, L, Grasha, K, and Cook, D
Subjects: Extinction (astronomy), FOS: Physical sciences, Magnitude (mathematics), Astrophysics, stellar content, 01 natural sciences, Photometry (optics), Methods statistical, star, 0103 physical sciences, Emission spectrum, 010303 astronomy & astrophysics, ISM, Physics, OB star, 010308 nuclear & particles physics, galaxie, luminosity function, mass function, Astronomy and Astrophysics, Astrophysics - Astrophysics of Galaxies, Stars, Star cluster, Space and Planetary Science, Astrophysics of Galaxies (astro-ph.GA), method, (ISM) HII region, data analysi
Abstract: We present a pilot library of synthetic NUV, U, B, V, and I photometry of star clusters with stochastically sampled IMFs and ionized gas for initial masses, Mi = 103, 104, and 105 M⊙; t = 1, 3, 4, and 8 Myr; Z = 0.014 and Z = 0.002; and log(US) = −2 and −3. We compare the library with predictions from deterministic models and observations of isolated low-mass (1.0 mag more luminous than the median stochastic magnitude without gas; and (b) nebular emission lines can contribute with $\gt 50{{\ \rm per\ cent}}$ and $\gt 30{{\ \rm per\ cent}}$ to the total emission in the V and I bands, respectively. (3) Age-dating OB-star clusters via deterministic tracks in the U-B versus V-I plane is highly uncertain at Z = 0.014 for Mi ∼ 103 M⊙ and Z = 0.002 for Mi ∼ 103–105 M⊙. (4) For low-mass clusters, the V-band extinction derived with stochastic models significantly depends on the value of log(US). (5) The youngest clusters tend to have higher extinction. (6) The majority of clusters have multi-peaked age PDFs. (7) Finally, we discuss the importance of characterizing the true variance in the number of stars per mass bin in nature.
Published: 2021

4. 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

5. Star Cluster Catalogs for the LEGUS Dwarf Galaxies

Author: David Schiminovich, Robert C. Kennicutt, Aida Wofford, Linda J. Smith, R. da Silva, L. Kahre, S. N. Bright, Anne Pellerin, Ryan Parziale, G. Ashworth, Göran Östlin, Rupali Chandar, Michael W. Regan, A. Herrero, S. Taibi, F. Shabani, Eva K. Grebel, N. J. Lee, Alessandra Aloisi, J. C. Lee, Angela Adamo, Monica Tosi, Carol Christian, Rene A. M. Walterbos, Geoffrey C. Clayton, S. E. de Mink, Elena Sabbi, Jordan A. Turner, Leonardo Ubeda, I. C. de la Torre, Crystal L. Martin, Aaron S. Evans, David O. Cook, Frederick A. Slane, D. J. Lennon, Bruce G. Elmegreen, S. D. Van Dyk, John S. Gallagher, Daniel A. Dale, David A. Thilker, J. Small, Angus Mok, Thomas M. Brown, Matteo Messa, K. E. Johnson, J. E. Ryon, Michele Cignoni, Hwihyun Kim, Antonella Nota, Kathryn Grasha, Mark R. Krumholz, Elena Sacchi, Clare Dobbs, Michele Fumagalli, B. C. Whitmore, Emily I. Jensen, Jennifer E. Andrews, D. Calzetti, Daniel Schaerer, Deidre A. Hunter, Debra Meloy Elmegreen, C. L. Smith, Dimitrios A. Gouliermis, Sean T. Linden, P. Nair, Faculty of Science, Low Energy Astrophysics (API, FNWI), High Energy Astrophys. & Astropart. Phys (API, FNWI), Kennicutt, Robert [0000-0001-5448-1821], Apollo - University of Cambridge Repository, Cook, D, Lee, J, Adamo, A, Kim, H, Chandar, R, Whitmore, B, Mok, A, Ryon, J, Dale, D, Calzetti, D, Andrews, J, Aloisi, A, Ashworth, G, Bright, S, Brown, T, Christian, C, Cignoni, M, Clayton, G, Da Silva, R, De Mink, S, Dobbs, C, Elmegreen, B, Elmegreen, D, Evans, A, Fumagalli, M, Gallagher, J, Gouliermis, D, Grasha, K, Grebel, E, Herrero, A, Hunter, D, Jensen, E, Johnson, K, Kahre, L, Kennicutt, R, Krumholz, M, Lee, N, Lennon, D, Linden, S, Martin, C, Messa, M, Nair, P, Nota, A, Ostlin, G, Parziale, R, Pellerin, A, Regan, M, Sabbi, E, Sacchi, E, Schaerer, D, Schiminovich, D, Shabani, F, Slane, F, Small, J, Smith, C, Smith, L, Taibi, S, Thilker, D, De La Torre, I, Tosi, M, Turner, J, Ubeda, L, Van Dyk, S, Walterbos, R, and Wofford, A
Subjects: galaxies: spiral, FOS: Physical sciences, Astrophysics, Astrophysics::Cosmology and Extragalactic Astrophysics, 01 natural sciences, Photometry (optics), 0103 physical sciences, Cluster (physics), 010303 astronomy & astrophysics, galaxies: irregular, Astrophysics::Galaxy Astrophysics, Dwarf galaxy, Physics, 010308 nuclear & particles physics, Star formation, Local Group, Astronomy and Astrophysics, galaxies: dwarf, Astrophysics - Astrophysics of Galaxies, Galaxy, galaxies: photometry, Star cluster, Space and Planetary Science, Astrophysics of Galaxies (astro-ph.GA), galaxies: star clusters: general, Irregular galaxy
Abstract: We present the star cluster catalogs for 17 dwarf and irregular galaxies in the $HST$ Treasury Program "Legacy ExtraGalactic UV Survey" (LEGUS). Cluster identification and photometry in this subsample are similar to that of the entire LEGUS sample, but special methods were developed to provide robust catalogs with accurate fluxes due to low cluster statistics. The colors and ages are largely consistent for two widely used aperture corrections, but a significant fraction of the clusters are more compact than the average training cluster. However, the ensemble luminosity, mass, and age distributions are consistent suggesting that the systematics between the two methods are less than the random errors. When compared with the clusters from previous dwarf galaxy samples, we find that the LEGUS catalogs are more complete and provide more accurate total fluxes. Combining all clusters into a composite dwarf galaxy, we find that the luminosity and mass functions can be described by a power law with the canonical index of $-2$ independent of age and global SFR binning. The age distribution declines as a power law, with an index of $\approx-0.80\pm0.15$, independent of cluster mass and global SFR binning. This decline of clusters is dominated by cluster disruption since the combined star formation histories and integrated-light SFRs are both approximately constant over the last few hundred Myr. Finally, we find little evidence for an upper-mass cutoff ($, Comment: 25 pages; 28 figures (Accepted to MNRAS)
Published: 2019
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6. 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

7. 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

8. The Resolved Stellar Populations in the LEGUS Galaxies1

Author: D. M. Elmegreen, Elena Sabbi, A. Dolphin, Geoffrey C. Clayton, Eva K. Grebel, Linda J. Smith, T. M. Brown, G. Ashworth, R. Walterbos, Matteo Messa, Lauren Kahre, J. Prieto, Alessandra Aloisi, Rupali Chandar, C. D. Martin, Mark R. Krumholz, M. W. Regan, Daniel A. Dale, Bruce G. Elmegreen, Hwihyun Kim, Kathryn Grasha, Elena Sacchi, F. Shabani, A. Herrero, R. C. Kennicutt, David O. Cook, J. E. Ryon, A. Nota, B. C. Whitmore, L. Ubeda, D. Schaerer, D. Schiminovich, Jennifer E. Andrews, J. C. Lee, Stacey N. Bright, Dimitrios A. Gouliermis, John S. Gallagher, D. J. Lennon, Michele Fumagalli, Daniela Calzetti, Kelsey E. Johnson, Michele Cignoni, S. D. Van Dyk, C. Christian, P. Nair, Clare Dobbs, Aaron S. Evans, Monica Tosi, G. Ostlin, Anne Pellerin, Deidre A. Hunter, David A. Thilker, Angela Adamo, S. E. de Mink, Aida Wofford, Sabbi, E, Calzetti, D, Ubeda, L, Adamo, A, Cignoni, M, Thilker, D, Aloisi, A, Elmegreen, B, Elmegreen, D, Gouliermis, D, Grebel, E, Messa, M, Smith, L, Tosi, M, Dolphin, A, Andrews, J, Ashworth, G, Bright, S, Brown, T, Chandar, R, Christian, C, Clayton, G, Cook, D, Dale, D, De Mink, S, Dobbs, C, Evans, A, Fumagalli, M, Gallagher, J, Grasha, K, Herrero, A, Hunter, D, Johnson, K, Kahre, L, Kennicutt, R, Kim, H, Krumholz, M, Lee, J, Lennon, D, Martin, C, Nair, P, Nota, A, Ostlin, G, Pellerin, A, Prieto, J, Regan, M, Ryon, J, Sacchi, E, Schaerer, D, Schiminovich, D, Shabani, F, Van Dyk, S, Walterbos, R, Whitmore, B, Wofford, A, Sabbi, E [0000-0003-2954-7643], Calzetti, D [0000-0002-5189-8004], Adamo, A [0000-0002-8192-8091], Cignoni, M [0000-0001-6291-6813], Thilker, D [0000-0002-8528-7340], Aloisi, A [0000-0003-4137-882X], Elmegreen, BG [0000-0002-1723-6330], Elmegreen, DM [0000-0002-1392-3520], Gouliermis, DA [0000-0002-2763-0075], Grebel, EK [0000-0002-1891-3794], Smith, LJ [0000-0002-0806-168X], Tosi, M [0000-0002-0986-4759], Dolphin, A [0000-0001-8416-4093], Chandar, R [0000-0003-0085-4623], Clayton, GC [0000-0002-0141-7436], Dale, DA [0000-0002-5782-9093], Grasha, K [0000-0002-3247-5321], Hunter, DA [0000-0002-3322-9798], Johnson, KE [0000-0001-8348-2671], Kahre, L [0000-0002-2037-3096], Pellerin, A [0000-0003-1887-1966], Prieto, J [0000-0003-0943-0026], Sacchi, E [0000-0001-5618-0109], Schaerer, D [0000-0001-7144-7182], Shabani, F [0000-0002-5266-1260], Walterbos, R [0000-0002-0782-3064], Apollo - University of Cambridge Repository, and Low Energy Astrophysics (API, FNWI)
Subjects: Hertzsprung–Russell diagram, Russell and C-M diagram, Astrophysics, Astrophysics::Cosmology and Extragalactic Astrophysics, 01 natural sciences, Advanced Camera for Surveys, symbols.namesake, galaxies: star clusters: general, galaxies: star formation, galaxies: stellar content, Hertzsprung, Russell and C-M diagrams, stars: formation, Astronomy and Astrophysics, Space and Planetary Science, 0103 physical sciences, Astrophysics::Solar and Stellar Astrophysics, 010303 astronomy & astrophysics, Astrophysics::Galaxy Astrophysics, Physics, 010308 nuclear & particles physics, Star formation, Galaxy, Red-giant branch, Stars, Star cluster, symbols, Hertzsprung-Russell and C-M diagrams, Astrophysics::Earth and Planetary Astrophysics, Wide Field Camera 3
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 5 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 M ☉, 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 timescale 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. Based on observations with the NASA/ESA Hubble Space Telescope, obtained at the Space Telescope Science Institute, which is operated by AURA Inc., under NASA contract NAS 5-26555.
Published: 2018

9. Extinction Maps and Dust-to-gas Ratios in Nearby Galaxies with LEGUS

Author: Leonardo Ubeda, Aaron S. Evans, Debra Meloy Elmegreen, Brad Whitmore, Daniel A. Dale, Janice C. Lee, Rene A. M. Walterbos, Carol Christian, Linda J. Smith, Rupali Chandar, Hwihyun Kim, R. C. Kennicutt, F. Shabani, Kathryn Grasha, Clare Dobbs, Dimitrios A. Gouliermis, Jennifer E. Andrews, Bruce G. Elmegreen, Alessandra Aloisi, Daniela Calzetti, J. E. Ryon, Michele Cignoni, Aida Wofford, Deidre A. Hunter, Michele Fumagalli, S. E. de Mink, John S. Gallagher, Elena Sabbi, David A. Thilker, Stacey N. Bright, Daniel Schaerer, S. D. Van Dyk, Preethi Nair, Kelsey E. Johnson, Matteo Messa, Antonella Nota, A. Herrero, Mark R. Krumholz, Elena Sacchi, Thomas M. Brown, Angela Adamo, L. Kahre, G. Ashworth, Eva K. Grebel, Monica Tosi, David O. Cook, Anne Pellerin, Low Energy Astrophysics (API, FNWI), Kahre, L [0000-0002-2037-3096], Walterbos, RA [0000-0002-0782-3064], Kim, H [0000-0003-4770-688X], Thilker, D [0000-0002-8528-7340], Calzetti, D [0000-0002-5189-8004], Lee, JC [0000-0002-2278-9407], Sabbi, E [0000-0003-2954-7643], Aloisi, A [0000-0003-4137-882X], Cignoni, M [0000-0001-6291-6813], Cook, DO [0000-0002-6877-7655], Dale, DA [0000-0002-5782-9093], Elmegreen, BG [0000-0002-1723-6330], Elmegreen, DM [0000-0002-1392-3520], Fumagalli, M [0000-0001-6676-3842], Gallagher, JS [0000-0001-8608-0408], Gouliermis, DA [0000-0002-2763-0075], Grasha, K [0000-0002-3247-5321], Grebel, EK [0000-0002-1891-3794], Hunter, DA [0000-0002-3322-9798], Sacchi, E [0000-0001-5618-0109], Smith, LJ [0000-0002-0806-168X], Tosi, M [0000-0002-0986-4759], Adamo, A [0000-0002-8192-8091], Brown, TM [0000-0002-1793-9968], Chandar, R [0000-0003-0085-4623], Christian, C [0000-0002-2179-3308], De Mink, SE [0000-0001-9336-2825], Herrero, A [0000-0001-8768-2179], Johnson, KE [0000-0001-8348-2671], Krumholz, MR [0000-0003-3893-854X], Pellerin, A [0000-0003-1887-1966], Schaerer, D [0000-0001-7144-7182], Shabani, F [0000-0002-5266-1260], Van Dyk, SD [0000-0001-9038-9950], Apollo - University of Cambridge Repository, Kahre, L, Walterbos, R, Kim, H, Thilker, D, Calzetti, D, Lee, J, Sabbi, E, Ubeda, L, Aloisi, A, Cignoni, M, Cook, D, Dale, D, Elmegreen, B, Elmegreen, D, Fumagalli, M, Gallagher, J, Gouliermis, D, Grasha, K, Grebel, E, Hunter, D, Sacchi, E, Smith, L, Tosi, M, Adamo, A, Andrews, J, Ashworth, G, Bright, S, Brown, T, Chandar, R, Christian, C, De Mink, S, Dobbs, C, Evans, A, Herrero, A, Johnson, K, Kennicutt, R, Krumholz, M, Messa, M, Nair, P, Nota, A, Pellerin, A, Ryon, J, Schaerer, D, Shabani, F, Van Dyk, S, Whitmore, B, and Wofford, A
Subjects: galaxies: spiral, Metallicity, FOS: Physical sciences, Astrophysics, Astrophysics::Cosmology and Extragalactic Astrophysics, 01 natural sciences, Power law, Hubble space telescope, 0103 physical sciences, Astrophysics::Solar and Stellar Astrophysics, 010303 astronomy & astrophysics, Astrophysics::Galaxy Astrophysics, ISM: general, Physics, Extinction, 010308 nuclear & particles physics, extinction, Astronomy and Astrophysics, HERA, galaxies: dwarf, Astrophysics - Astrophysics of Galaxies, Galaxy, Stars, dust, galaxies: ISM, galaxies: photometry, Space and Planetary Science, Astrophysics of Galaxies (astro-ph.GA), Spectral energy distribution, dust, extinction, Astrophysics::Earth and Planetary Astrophysics
Abstract: We present a study of the dust-to-gas ratios in five nearby galaxies NGC 628 (M74), NGC 6503, NGC 7793, UGC 5139 (Holmberg I), and UGC 4305 (Holmberg II). Using Hubble Space Telescope broad band WFC3/UVIS UV and optical images from the Treasury program LEGUS (Legacy ExtraGalactic UV Survey) combined with archival HST/ACS data, we correct thousands of individual stars for extinction across these five galaxies using an isochrone-matching (reddening-free Q) method. We generate extinction maps for each galaxy from the individual stellar extinctions using both adaptive and fixed resolution techniques, and correlate these maps with neutral HI and CO gas maps from literature, including The HI Nearby Galaxy Survey (THINGS) and the HERA CO-Line Extragalactic Survey (HERACLES). We calculate dust-to-gas ratios and investigate variations in the dust-to-gas ratio with galaxy metallicity. We find a power law relationship between dust-to-gas ratio and metallicity, consistent with other studies of dust-to-gas ratio compared to metallicity. We find a change in the relation when H$_2$ is not included. This implies that underestimation of $N_{H_2}$ in low-metallicity dwarfs from a too-low CO-to-H$_2$ conversion factor $X_{CO}$ could have produced too low a slope in the derived relationship between dust-to-gas ratio and metallicity. We also compare our extinctions to those derived from fitting the spectral energy distribution (SED) using the Bayesian Extinction and Stellar Tool (BEAST) for NGC 7793 and find systematically lower extinctions from SED-fitting as compared to isochrone matching., Comment: 22 pages, 14 figures, accepted by ApJ
Published: 2018

10. Theoretical predictions for IMF diagnostics in UV spectroscopy of star clusters

Author: Michele Fumagalli, Mark R. Krumholz, Greg Ashworth, Angela Adamo, Ashworth, G, Fumagalli, M, Adamo, A, and Krumholz, M
Subjects: Physics, Initial mass function, 010308 nuclear & particles physics, FOS: Physical sciences, Astronomy and Astrophysics, Astrophysics, Stars: luminosity function, Astrophysics::Cosmology and Extragalactic Astrophysics, Bayesian inference, 01 natural sciences, Astrophysics - Astrophysics of Galaxies, Galaxy, 3. Good health, Photometry (optics), Ultraviolet visible spectroscopy, Star cluster, Space and Planetary Science, Astrophysics of Galaxies (astro-ph.GA), Mass function, 0103 physical sciences, Cluster (physics), Galaxies: clusters: general, 010303 astronomy & astrophysics, Equivalent width, Methods: statistical
Abstract: We explore the possibility of using UV spectroscopy in combination with broad-band photometry as diagnostic tools for understanding the shape of the Initial Mass Function (IMF) in unresolved stellar populations. Building on our previous work, we extend the Stochastically Lighting Up Galaxies code (slug) to include a high-resolution UV spectral synthesiser and equivalent width calculation capabilities. We first gain a qualitative understanding of how UV spectral features behave as the parameters that define a star cluster in slug (mass, age, extinction, and IMF slope alpha) are changed. We then exploit Bayesian inference techniques to recover the alpha values for clusters simulated with slug, using mock observations of these clusters comprised of broad-band photometry and equivalent width measurements of a selection of UV spectral features. We find some improvement when compared to attempts using broad-band photometry alone (with the interquartile range of the alpha posterior PDF shrinking by 32%), although we still do not yet fully break the known degeneracy between the cluster mass and alpha. Finally, we make predictions about how effective real observations will be by quantifying our ability to constrain alpha as a function of limiting equivalent width. We find that observations sensitive to a modest equivalent width of 9 A are sufficient to improve the recovery of the IMF slope parameter by 32% (interquartile range of posterior PDF median residuals), moving to 39% when we include all the significant spectral features in the wavelength range 900-3000 A., 18 pages, 7 figures. MNRAS in press. Includes online appendix
Published: 2018
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11. Connecting young star clusters to CO molecular gas in NGC 7793 with ALMA-LEGUS

Author: Alessandra Aloisi, D. Calzetti, Rene A. M. Walterbos, Linda J. Smith, Bruce G. Elmegreen, Aida Wofford, John S. Gallagher, David A. Thilker, Daniel A. Dale, David O. Cook, Eva K. Grebel, Robert C. Kennicutt, Matteo Messa, K. E. Johnson, Angela Adamo, Dimitrios A. Gouliermis, Mark R. Krumholz, Elena Sacchi, Kathryn Grasha, Michele Fumagalli, J. Donovan Meyer, Lauren Bittle, Sean T. Linden, Kennicutt, Robert [0000-0001-5448-1821], Apollo - University of Cambridge Repository, Grasha, K, Calzetti, D, Bittle, L, Johnson, K, Donovan Meyer, J, Kennicutt, R, Elmegreen, B, Adamo, A, Krumholz, M, Fumagalli, M, Grebel, E, Gouliermis, D, Cook, D, Gallagher, J, Aloisi, A, Dale, D, Linden, S, Sacchi, E, Thilker, D, Walterbos, R, Messa, M, Wofford, A, and Smith, L
Subjects: ISM: structure, FOS: Physical sciences, Astrophysics, Astrophysics::Cosmology and Extragalactic Astrophysics, 01 natural sciences, ISM: clouds, ISM: cloud, Young star, 0103 physical sciences, Astrophysics::Solar and Stellar Astrophysics, 010303 astronomy & astrophysics, Astrophysics::Galaxy Astrophysics, Physics, 010308 nuclear & particles physics, Star formation, Molecular cloud, galaxies: individual: NGC 7793, Astronomy and Astrophysics, Astrophysics - Astrophysics of Galaxies, Galaxy, Star cluster, Space and Planetary Science, Astrophysics of Galaxies (astro-ph.GA), galaxies: star clusters: general, Spatial clustering, galaxies: stellar content, galaxies: structure, Age distribution, Astrophysics::Earth and Planetary Astrophysics
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 catalog from the HST LEGUS (Legacy ExtraGalactic UV Survey) program with the 15 parsec 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 timescale 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 $-0.35 \pm 0.03$, significantly more clustered than the molecular cloud hierarchy with slope of $-0.18 \pm 0.04$ 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 $-0.44\pm0.03$ and $-0.45\pm0.06$ respectively, when we compare massive ($>$10$^5$ M$_{\odot}$) 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 percent., 12 page, 8 figures. Accepted for publication in MNRAS
Published: 2018

12. Legacy extraGalactic UV survey with the Hubble space telescope : stellar cluster catalogs and first insights into cluster formation and evolution in NGC 628

Author: A. Adamo, J. E. Ryon, M. Messa, H. Kim, K. Grasha, D. O. Cook, D. Calzetti, J. C. Lee, B. C. Whitmore, B. G. Elmegreen, L. Ubeda, L. J. Smith, S. N. Bright, A. Runnholm, J. E. Andrews, M. Fumagalli, D. A. Gouliermis, L. Kahre, P. Nair, D. Thilker, R. Walterbos, A. Wofford, A. Aloisi, G. Ashworth, T. M. Brown, R. Chandar, C. Christian, M. Cignoni, G. C. Clayton, D. A. Dale, S. E. de Mink, C. Dobbs, D. M. Elmegreen, A. S. Evans, J. S. Gallagher III, E. K. Grebel, A. Herrero, D. A. Hunter, K. E. Johnson, R. C. Kennicutt, M. R. Krumholz, D. Lennon, K. Levay, C. Martin, A. Nota, G. Östlin, A. Pellerin, J. Prieto, M. W. Regan, E. Sabbi, E. Sacchi, D. Schaerer, D. Schiminovich, F. Shabani, M. Tosi, S. D. Van Dyk, E. Zackrisson, Adamo, A, Ryon, J, Messa, M, Kim, H, Grasha, K, Cook, D, Calzetti, D, Lee, J, Whitmore, B, Elmegreen, B, Ubeda, L, Smith, L, Bright, S, Runnholm, A, Andrews, J, Fumagalli, M, Gouliermis, D, Kahre, L, Nair, P, Thilker, D, Walterbos, R, Wofford, A, Aloisi, A, Ashworth, G, Brown, T, Chandar, R, Christian, C, Cignoni, M, Clayton, G, Dale, D, De Mink, S, Dobbs, C, Elmegreen, D, Evans, A, Gallagher, J, Grebel, E, Herrero, A, Hunter, D, Johnson, K, Kennicutt, R, Krumholz, M, Lennon, D, Levay, K, Martin, C, Nota, A, Ostlin, G, Pellerin, A, Prieto, J, Regan, M, Sabbi, E, Sacchi, E, Schaerer, D, Schiminovich, D, Shabani, F, Tosi, M, Van Dyk, S, Zackrisson, E, and Low Energy Astrophysics (API, FNWI)
Subjects: Astrophysics::High Energy Astrophysical Phenomena, FOS: Physical sciences, Astrophysics, Astrophysics::Cosmology and Extragalactic Astrophysics, 01 natural sciences, Photometry (optics), galaxies: individual (NGC 628, M74), Hubble space telescope, 0103 physical sciences, Cluster (physics), Astrophysics::Solar and Stellar Astrophysics, 010303 astronomy & astrophysics, Astrophysics::Galaxy Astrophysics, Luminosity function (astronomy), Physics, Spiral galaxy, stars: formation, 010308 nuclear & particles physics, Astronomy and Astrophysics, Astrophysics - Astrophysics of Galaxies, Galaxy, galaxies: star clusters: general, galaxies: star formation, Space and Planetary Science, Astrophysics of Galaxies (astro-ph.GA), galaxies: individual (NGC 628, Spectral energy distribution, Low Mass, M74)
Abstract: We report the large effort which is producing comprehensive high-level young star cluster (YSC) catalogues for a significant fraction of galaxies observed with the Legacy ExtraGalactic UV Survey (LEGUS) Hubble treasury program. We present the methodology developed to extract cluster positions, verify their genuine nature, produce multiband photometry (from NUV to NIR), and derive their physical properties via spectral energy distribution fitting analyses. We use the nearby spiral galaxy NGC628 as a test case for demonstrating the impact that LEGUS will have on our understanding of the formation and evolution of YSCs and compact stellar associations within their host galaxy. Our analysis of the cluster luminosity function from the UV to the NIR finds a steepening at the bright end and at all wavelengths suggesting a dearth of luminous clusters. The cluster mass function of NGC628 is consistent with a power-law distribution of slopes $\sim -2$ and a truncation of a few times $10^5$ M$_\odot$. After their formation YSCs and compact associations follow different evolutionary paths. YSCs survive for a longer timeframe, confirming their being potentially bound systems. Associations disappear on time scales comparable to hierarchically organized star-forming regions, suggesting that they are expanding systems. We find mass-independent cluster disruption in the inner region of NGC628, while in the outer part of the galaxy there is little or no disruption. We observe faster disruption rates for low mass ($\leq$ $10^4$ M$_\odot$) clusters suggesting that a mass-dependent component is necessary to fully describe the YSC disruption process in NGC628., accepted for publication in ApJ; 27 pages; complete stellar cluster catalogues will be released in June 2017 at https://legus.stsci.edu
Published: 2017

13. 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

14. 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

15. TESTING MODELS FOR MOLECULAR GAS FORMATION IN GALAXIES: HYDROSTATIC PRESSURE OR GAS AND DUST SHIELDING?

Author: Leslie K. Hunt, Mark R. Krumholz, Michele Fumagalli, Fumagalli, M, Krumholz, M, and Hunt, L
Subjects: Cosmology and Nongalactic Astrophysics (astro-ph.CO), Stars: formation, Metallicity, Hydrostatic pressure, FOS: Physical sciences, ISM: molecule, Astrophysics::Cosmology and Extragalactic Astrophysics, Astrophysics, 01 natural sciences, 0103 physical sciences, Disc, 010303 astronomy & astrophysics, Stellar density, Astrophysics::Galaxy Astrophysics, Dwarf galaxy, Physics, Galaxies: dwarf, 010308 nuclear & particles physics, Molecular cloud, Astronomy and Astrophysics, Galaxy, Interstellar medium, Galaxies: ISM, Space and Planetary Science, Astrophysics::Earth and Planetary Astrophysics, Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: Stars in galaxies form in giant molecular clouds that coalesce when the atomic hydrogen is converted into molecules. There are currently two dominant models for what property of the galactic disk determines its molecular fraction: either hydrostatic pressure driven by the gravity of gas and stars, or a combination of gas column density and metallicity. To assess the validity of these models, we compare theoretical predictions to the observed atomic gas content of low-metallicity dwarf galaxies with high stellar densities. The extreme conditions found in these systems are optimal to distinguish the two models, otherwise degenerate in nearby spirals. Locally, on scales, 20 pages, 12 figures. Accepted for publication in ApJ
Published: 2010

16. Star cluster properties in two LEGUS galaxies computed with stochastic stellar population synthesis models

Author: J. E. Ryon, David A. Thilker, Dimitrios A. Gouliermis, Stacey N. Bright, Erik Zackrisson, Angela Adamo, Michele Fumagalli, Daniela Calzetti, Mark R. Krumholz, Leonardo Ubeda, Linda J. Smith, P. Nair, Hwihyun Kim, Kathryn Grasha, Bradley C. Whitmore, Janice C. Lee, Aida Wofford, Krumholz, M, Adamo, A, Fumagalli, M, Wofford, A, Calzetti, D, Lee, J, Whitmore, B, Bright, S, Grasha, K, Gouliermis, D, Kim, H, Nair, P, Ryon, J, Smith, L, Thilker, D, Ubeda, L, and Zackrisson, E
Subjects: statistical [Methods], Initial mass function, Stellar population, Metallicity, Population, Posterior probability, star clusters: general [Galaxies], FOS: Physical sciences, Astrophysics, Astrophysics::Cosmology and Extragalactic Astrophysics, photometric. [Techniques], individual (NGC 628 [Galaxies], techniques: photometric, Prior probability, education, data analysis [Methods], Instrumentation and Methods for Astrophysics (astro-ph.IM), galaxies: individual (NGC 628, NGC 7793), Astrophysics::Galaxy Astrophysics, Physics, education.field_of_study, methods: statistical, Astronomy and Astrophysics, Astrophysics - Astrophysics of Galaxies, Galaxy, NGC 7793), Star cluster, Space and Planetary Science, Astrophysics of Galaxies (astro-ph.GA), galaxies: star clusters: general, Astrophysics - Instrumentation and Methods for Astrophysics, methods: data analysi
Abstract: We investigate a novel Bayesian analysis method, based on the Stochastically Lighting Up Galaxies (slug) code, to derive the masses, ages, and extinctions of star clusters from integrated light photometry. Unlike many analysis methods, slug correctly accounts for incomplete IMF sampling, and returns full posterior probability distributions rather than simply probability maxima. We apply our technique to 621 visually-confirmed clusters in two nearby galaxies, NGC 628 and NGC 7793, that are part of the Legacy Extragalactic UV Survey (LEGUS). LEGUS provides Hubble Space Telescope photometry in the NUV, U, B, V, and I bands. We analyze the sensitivity of the derived cluster properties to choices of prior probability distribution, evolutionary tracks, IMF, metallicity, treatment of nebular emission, and extinction curve. We find that slug's results for individual clusters are insensitive to most of these choices, but that the posterior probability distributions we derive are often quite broad, and sometimes multi-peaked and quite sensitive to the choice of priors. In contrast, the properties of the cluster population as a whole are relatively robust against all of these choices. We also compare our results from slug to those derived with a conventional non-stochastic fitting code, Yggdrasil. We show that slug's stochastic models are generally a better fit to the observations than the deterministic ones used by Yggdrasil. However, the overall properties of the cluster populations recovered by both codes are qualitatively similar., Accepted to ApJ; 25 pages, 17 figures, 3 tables; machine-readable versions of the tables are available at https://sites.google.com/a/ucsc.edu/krumholz/publications
Published: 2015

17. SLUG – stochastically lighting up galaxies – III. A suite of tools for simulated photometry, spectroscopy, and Bayesian inference with stochastic stellar populations

Author: Theodore Rendahl, Mark R. Krumholz, Robert L. da Silva, Michele Fumagalli, Jonathan Parra, Krumholz, M, Fumagalli, M, da Silva, R, Rendahl, T, and Parra, J
Subjects: statistical [Methods], Stellar population, Stars: formation, Population, star clusters: general [Galaxies], FOS: Physical sciences, Astrophysics, Astrophysics::Cosmology and Extragalactic Astrophysics, stellar content. [Galaxies], 01 natural sciences, Photometry (optics), 0103 physical sciences, Astrophysics::Solar and Stellar Astrophysics, education, 010303 astronomy & astrophysics, Solar and Stellar Astrophysics (astro-ph.SR), Galaxies: star clusters: general, Methods: statistical, Astrophysics::Galaxy Astrophysics, formation [Stars], Dwarf galaxy, Physics, education.field_of_study, Spiral galaxy, numerical [Methods], Methods: numerical, 010308 nuclear & particles physics, Star formation, photometric [Techniques], Astronomy, Astronomy and Astrophysics, Galaxies: stellar content, Astrophysics - Astrophysics of Galaxies, Galaxy, Star cluster, Astrophysics - Solar and Stellar Astrophysics, Space and Planetary Science, Astrophysics of Galaxies (astro-ph.GA), Astrophysics::Earth and Planetary Astrophysics, Techniques: photometric
Abstract: Stellar population synthesis techniques for predicting the observable light emitted by a stellar population have extensive applications in numerous areas of astronomy. However, accurate predictions for small populations of young stars, such as those found in individual star clusters, star-forming dwarf galaxies, and small segments of spiral galaxies, require that the population be treated stochastically. Conversely, accurate deductions of the properties of such objects also requires consideration of stochasticity. Here we describe a comprehensive suite of modular, open-source software tools for tackling these related problems. These include: a greatly-enhanced version of the slug code introduced by da Silva et al. (2012), which computes spectra and photometry for stochastically- or deterministically-sampled stellar populations with nearly-arbitrary star formation histories, clustering properties, and initial mass functions; cloudy_slug, a tool that automatically couples slug-computed spectra with the cloudy radiative transfer code in order to predict stochastic nebular emission; bayesphot, a general-purpose tool for performing Bayesian inference on the physical properties of stellar systems based on unresolved photometry; and cluster_slug and sfr_slug, a pair of tools that use bayesphot on a library of slug models to compute the mass, age, and extinction of mono-age star clusters, and the star formation rate of galaxies, respectively. The latter two tools make use of an extensive library of pre-computed stellar population models, which are included the software. The complete package is available at http://www.slugsps.com., Comment: 24 pages, 13 figures, accepted for publication in MNRAS; some additions to previous version; source code and model libraries are available at http://www.slugsps.com
Published: 2015
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18. Legacy ExtraGalactic UV Survey (LEGUS) with the Hubble Space Telescope. I. Survey description

Author: S. D. Van Dyk, Monica Tosi, Dimitrios A. Gouliermis, Daniel Schaerer, Crystal L. Martin, Alessandra Aloisi, Goeran Oestlin, Hwihyun Kim, A. Nota, Linda J. Smith, K. Levay, S. N. Bright, Rupali Chandar, B. C. Whitmore, Aida Wofford, Rene A. M. Walterbos, Mark R. Krumholz, Jiho Lee, Artemio Herrero, K. E. Johnson, Debra Meloy Elmegreen, J. E. Ryon, J. L. Prieto, Clare Dobbs, Elena Sabbi, Carol Christian, L. Ubeda, Geoffrey C. Clayton, Michael W. Regan, D. J. Lennon, David A. Thilker, Robert C. Kennicutt, Michele Fumagalli, Danny Hunter, Bruce G. Elmegreen, Aaron S. Evans, Michele Cignoni, S. E. de Mink, Thomas M. Brown, Jennifer E. Andrews, Daniela Calzetti, P. Nair, Eva K. Grebel, R. da Silva, J. S. Gallagher, Anne Pellerin, A. Adamo, David Schiminovich, Low Energy Astrophysics (API, FNWI), Calzetti, D, Lee, J, Sabbi, E, Adamo, A, Smith, L, Andrews, J, Ubeda, L, Bright, S, Thilker, D, Aloisi, A, Brown, T, Chandar, R, Christian, C, Cignoni, M, Clayton, G, Da Silva, R, De Mink, S, Dobbs, C, Elmegreen, B, Elmegreen, D, Evans, A, Fumagalli, M, Gallagher, J, Gouliermis, D, Grebel, E, Herrero, A, Hunter, D, Johnson, K, Kennicutt, R, Kim, H, Krumholz, M, Lennon, D, Levay, K, Martin, C, Nair, P, Nota, A, Ostlin, G, Pellerin, A, Prieto, J, Regan, M, Ryon, J, Schaerer, D, Schiminovich, D, Tosi, M, Van Dyk, S, Walterbos, R, Whitmore, B, and Wofford, A
Subjects: KILOPARSEC-SCALE CLUMPS, Cosmology and Nongalactic Astrophysics (astro-ph.CO), SIMILAR-TO 2, ULTRA DEEP FIELD, INITIAL MASS FUNCTION, star clusters: general [Galaxies], FOS: Physical sciences, Galaxies: Star formation, TULLY-FISHER, Astrophysics, Astrophysics::Cosmology and Extragalactic Astrophysics, Advanced Camera for Surveys, star formation [Galaxies], RELATION, COMPACT DWARF GALAXIES, Galaxy formation and evolution, STAR-FORMING GALAXIES, Astrophysics::Solar and Stellar Astrophysics, SMALL-MAGELLANIC-CLOUD, GIANT MOLECULAR CLOUDS, Astrophysics::Galaxy Astrophysics, ultraviolet: stars, Physics, Star formation, galaxies: general, galaxies: star clusters: general, galaxies: star, formation, galaxies: stellar content, ultraviolet: galaxies, COLOR-MAGNITUDE, DIAGRAMS, Astronomy and Astrophysics, general [Galaxies], Astrophysics - Astrophysics of Galaxies, Redshift, Galaxy, galaxies [Ultraviolet], Stars, Star cluster, Space and Planetary Science, Astrophysics of Galaxies (astro-ph.GA), stars. [Ultraviolet], stellar content [Galaxies], Astrophysics::Earth and Planetary Astrophysics, Wide Field Camera 3, Ultraviolet: Galaxie, Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: The Legacy ExtraGalactic UV Survey (LEGUS) is a Cycle 21 Treasury program on the Hubble Space Telescope, aimed at the investigation of star formation and its relation with galactic environment in nearby galaxies, from the scales of individual stars to those of ~kpc-size clustered structures. Five-band imaging, from the near-ultraviolet to the I-band, with the Wide Field Camera 3, plus parallel optical imaging with the Advanced Camera for Surveys, is being collected for selected pointings of 50 galaxies within the local 12 Mpc. The filters used for the observations with the Wide Field Camera 3 are: F275W(2,704 A), F336W(3,355 A), F438W(4,325 A), F555W(5,308 A), and F814W(8,024 A); the parallel observations with the Advanced Camera for Surveys use the filters: F435W(4,328 A), F606W(5,921 A), and F814W(8,057 A). The multi-band images are yielding accurate recent (, Comment: 67 pages, 9 figures; accepted for publication on the Astronomical Journal
Published: 2015

19. An analytic method to compute star cluster luminosity statistics

Author: Michele Fumagalli, Robert L. da Silva, Mark R. Krumholz, S. Michael Fall, Da Silva, R, Krumholz, M, Fumagalli, M, and Michael Fall, S
Subjects: statistical [Methods], Monte Carlo method, Population, star clusters: general [Galaxies], Astrophysics, Astrophysics::Cosmology and Extragalactic Astrophysics, Luminosity, symbols.namesake, Cluster (physics), Statistical physics, education, data analysis [Methods], Stellar evolution, Galaxies: star clusters: general, Methods: statistical, Astrophysics::Galaxy Astrophysics, Physics, education.field_of_study, numerical [Methods], Methods: numerical, photometric [Techniques], Astronomy and Astrophysics, Markov chain Monte Carlo, Galaxy, Star cluster, Space and Planetary Science, symbols, Techniques: photometric, Methods: data analysi
Abstract: The luminosity distribution of the brightest star clusters in a population of galaxies encodes critical pieces of information about how clusters form, evolve and disperse, and whether and how these processes depend on the large-scale galactic environment. However, extracting constraints on models from these data is challenging, in part because comparisons between theory and observation have traditionally required computationally intensive Monte Carlo methods to generate mock data that can be compared to observations. We introduce a new method that circumvents this limitation by allowing analytic computation of cluster order statistics, i.e. the luminosity distribution of the Nth most luminous cluster in a population. Our method is flexible and requires few assumptions, allowing for parametrized variations in the initial cluster mass function and its upper and lower cutoffs, variations in the cluster age distribution, stellar evolution and dust extinction, as well as observational uncertainties in both the properties of star clusters and their underlying host galaxies. The method is fast enough to make it feasible for the first time to use Markov chain Monte Carlo methods to search parameter space to find best-fitting values for the parameters describing cluster formation and disruption, and to obtain rigorous confidence intervals on the inferred values. We implement our method in a software package called the Cluster Luminosity Order-Statistic Code, which we have made publicly available. © 2013 The AuthorsPublished by Oxford University Press on behalf of the Royal Astronomical Society.
Published: 2014

20. 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

21. 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

22. Stochastic star formation and a (nearly) uniform stellar initial mass function

Author: Michele Fumagalli, Mark R. Krumholz, Robert L. da Silva, Fumagalli, M, Da Silva, R, and Krumholz, M
Subjects: Initial mass function, Cosmology and Nongalactic Astrophysics (astro-ph.CO), 010504 meteorology & atmospheric sciences, FOS: Physical sciences, Astrophysics, Astrophysics::Cosmology and Extragalactic Astrophysics, 01 natural sciences, Photometry (optics), 0103 physical sciences, Cluster (physics), Astrophysics::Solar and Stellar Astrophysics, stars: statistic, 010303 astronomy & astrophysics, Astrophysics::Galaxy Astrophysics, 0105 earth and related environmental sciences, Dwarf galaxy, Physics, Star formation, Sampling (statistics), Astronomy and Astrophysics, galaxies: dwarf, Galaxy, Star cluster, Space and Planetary Science, galaxies: star formation, galaxies: statistic, galaxies: stellar content, ultraviolet: galaxies, Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: Recent observations indicate a lower Halpha to FUV ratio in dwarf galaxies than in brighter systems, a trend that could be explained by a truncated and/or steeper IMF in small galaxies. However, at low star formation rates (SFRs), the Halpha to FUV ratio can vary due to stochastic sampling even for a universal IMF, a hypothesis that has, prior to this work, received limited investigation. Using SLUG, a fully stochastic code for synthetic photometry in star clusters and galaxies, we compare the Halpha and FUV luminosity in a sample of ~450 nearby galaxies with models drawn from a universal Kroupa IMF and a modified IMF, the integrated galactic initial mass function (IGIMF). Once random sampling and time evolution are included, a Kroupa IMF convolved with the cluster mass function reproduces the observed Halpha distribution at all FUV luminosities, while a truncated IMF as implemented in current IGIMF models underpredicts the Halpha luminosity by more than an order of magnitude at the lowest SFRs. We conclude that the observed luminosity is the result of the joint probability distribution function of the SFR, cluster mass function, and a universal IMF, consistent with parts of the IGIMF theory, but that a truncation in the IMF in clusters is inconsistent with the observations. Future work will examine stochastic star formation and its time dependence in detail to study whether random sampling can explain other observations that suggest a varying IMF., Comment: 6 pages, 3 figures. To appear in ApJL
Published: 2011
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23. 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

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23 results on '"Krumholz, M."'

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

2. The brightest young star clusters in NGC 5253

3. Synthetic photometry of OB star clusters with stochastically sampled IMFs: analysis of models and HST observations

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

5. Star Cluster Catalogs for the LEGUS Dwarf Galaxies

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

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

8. The Resolved Stellar Populations in the LEGUS Galaxies1

9. Extinction Maps and Dust-to-gas Ratios in Nearby Galaxies with LEGUS

10. Theoretical predictions for IMF diagnostics in UV spectroscopy of star clusters

11. Connecting young star clusters to CO molecular gas in NGC 7793 with ALMA-LEGUS

12. Legacy extraGalactic UV survey with the Hubble space telescope : stellar cluster catalogs and first insights into cluster formation and evolution in NGC 628

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

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

15. TESTING MODELS FOR MOLECULAR GAS FORMATION IN GALAXIES: HYDROSTATIC PRESSURE OR GAS AND DUST SHIELDING?

16. Star cluster properties in two LEGUS galaxies computed with stochastic stellar population synthesis models

17. SLUG – stochastically lighting up galaxies – III. A suite of tools for simulated photometry, spectroscopy, and Bayesian inference with stochastic stellar populations

18. Legacy ExtraGalactic UV Survey (LEGUS) with the Hubble Space Telescope. I. Survey description

19. An analytic method to compute star cluster luminosity statistics

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

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

22. Stochastic star formation and a (nearly) uniform stellar initial mass function

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

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23 results on '"Krumholz, M."'

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