ICML Topological Deep Learning Challenge 2024: Beyond the Graph Domain

Autor: Bernárdez, Guillermo, Telyatnikov, Lev, Montagna, Marco, Baccini, Federica, Papillon, Mathilde, Ferriol-Galmés, Miquel, Hajij, Mustafa, Papamarkou, Theodore, Bucarelli, Maria Sofia, Zaghen, Olga, Mathe, Johan, Myers, Audun, Mahan, Scott, Lillemark, Hansen, Vadgama, Sharvaree, Bekkers, Erik, Doster, Tim, Emerson, Tegan, Kvinge, Henry, Agate, Katrina, Ahmed, Nesreen K, Bai, Pengfei, Banf, Michael, Battiloro, Claudio, Beketov, Maxim, Bogdan, Paul, Carrasco, Martin, Cavallo, Andrea, Choi, Yun Young, Dasoulas, George, Elphick, Matouš, Escalona, Giordan, Filipiak, Dominik, Fritze, Halley, Gebhart, Thomas, Gil-Sorribes, Manel, Goomanee, Salvish, Guallar, Victor, Imasheva, Liliya, Irimia, Andrei, Jin, Hongwei, Johnson, Graham, Kanakaris, Nikos, Koloski, Boshko, Kovač, Veljko, Lecha, Manuel, Lee, Minho, Leroy, Pierrick, Long, Theodore, Magai, German, Martinez, Alvaro, Masden, Marissa, Mežnar, Sebastian, Miquel-Oliver, Bertran, Molina, Alexis, Nikitin, Alexander, Nurisso, Marco, Piekenbrock, Matt, Qin, Yu, Rygiel, Patryk, Salatiello, Alessandro, Schattauer, Max, Snopov, Pavel, Suk, Julian, Sánchez, Valentina, Tec, Mauricio, Vaccarino, Francesco, Verhellen, Jonas, Wantiez, Frederic, Weers, Alexander, Zajec, Patrik, Škrlj, Blaž, Miolane, Nina

This paper describes the 2nd edition of the ICML Topological Deep Learning Challenge that was hosted within the ICML 2024 ELLIS Workshop on Geometry-grounded Representation Learning and Generative Modeling (GRaM). The challenge focused on the problem

Externí odkaz: http://arxiv.org/abs/2409.05211

Analytical and EZmock covariance validation for the DESI 2024 results

Autor: Forero-Sánchez, Daniel, Rashkovetskyi, Michael, Alves, Otávio, de Mattia, Arnaud, Nadathur, Seshadri, Zarrouk, Pauline, Gil-Marín, Héctor, Ding, Zhejie, Yu, Jiaxi, Andrade, Uendert, Chen, Xinyi, Garcia-Quintero, Cristhian, Mena-Fernández, Juan, Ahlen, Steven, Bianchi, Davide, Brooks, David, Burtin, Etienne, Chaussidon, Edmond, Claybaugh, Todd, Cole, Shaun, de la Macorra, Axel, Vargas, Miguel Enriquez, Gaztañaga, Enrique, Gutierrez, Gaston, Honscheid, Klaus, Howlett, Cullan, Kisner, Theodore, Landriau, Martin, Guillou, Laurent Le, Levi, Michael, Miquel, Ramon, Moustakas, John, Palanque-Delabrouille, Nathalie, Percival, Will, Pérez-Ràfols, Ignasi, Ross, Ashley J., Rossi, Graziano, Sanchez, Eusebio, Schlegel, David, Schubnell, Michael, Seo, Hee-Jong, Sprayberry, David, Tarlé, Gregory, Magana, Mariana Vargas, Weaver, Benjamin Alan, Zou, Hu

The estimation of uncertainties in cosmological parameters is an important challenge in Large-Scale-Structure (LSS) analyses. For standard analyses such as Baryon Acoustic Oscillations (BAO) and Full Shape, two approaches are usually considered. Firs

Externí odkaz: http://arxiv.org/abs/2411.12027

Characterization of DESI fiber assignment incompleteness effect on 2-point clustering and mitigation methods for DR1 analysis

Autor: Bianchi, D., Hanif, M. M. S, Rosell, A. Carnero, Lasker, J., Ross, A. J., Pinon, M., de Mattia, A., White, M., Ahlen, S., Bailey, S., Brooks, D., Burtin, E., Chaussidon, E., Claybaugh, T., Cole, S., de la Macorra, A., Ferraro, S., Font-Ribera, A., Forero-Romero, J. E., Gaztañaga, E., Gontcho, S. Gontcho A, Gutierrez, G., Guy, J., Hahn, C., Honscheid, K., Howlett, C., Juneau, S., Kirkby, D., Kisner, T., Kremin, A., Landriau, M., Guillou, L. Le, Levi, M. E., McDonald, P., Meisner, A., Miquel, R., Moustakas, J., Palanque-Delabrouille, N., Percival, W. J., Prada, F., Pérez-Ràfols, I., Raichoor, A., Rossi, G., Sanchez, E., Schlegel, D., Schubnell, M., Sharples, R., Silber, J., Sprayberry, D., Tarlé, G., Vargas-Magaña, M., Weaver, B. A., Zarrouk, P., Zhou, R., Zou, H.

We present an in-depth analysis of the fiber assignment incompleteness in the Dark Energy Spectroscopic Instrument (DESI) Data Release 1 (DR1). This incompleteness is caused by the restricted mobility of the robotic fiber positioner in the DESI focal

Externí odkaz: http://arxiv.org/abs/2411.12025

DESI 2024 VII: Cosmological Constraints from the Full-Shape Modeling of Clustering Measurements

Autor: DESI Collaboration, Adame, A. G., Aguilar, J., Ahlen, S., Alam, S., Alexander, D. M., Prieto, C. Allende, Alvarez, M., Alves, O., Anand, A., Andrade, U., Armengaud, E., Avila, S., Aviles, A., Awan, H., Bahr-Kalus, B., Bailey, S., Baltay, C., Bault, A., Behera, J., BenZvi, S., Beutler, F., Bianchi, D., Blake, C., Blum, R., Bonici, M., Brieden, S., Brodzeller, A., Brooks, D., Buckley-Geer, E., Burtin, E., Calderon, R., Canning, R., Rosell, A. Carnero, Cereskaite, R., Cervantes-Cota, J. L., Chabanier, S., Chaussidon, E., Chaves-Montero, J., Chebat, D., Chen, S., Chen, X., Claybaugh, T., Cole, S., Cuceu, A., Davis, T. M., Dawson, K., de la Macorra, A., de Mattia, A., Deiosso, N., Dey, A., Dey, B., Ding, Z., Doel, P., Edelstein, J., Eftekharzadeh, S., Eisenstein, D. J., Elbers, W., Elliott, A., Fagrelius, P., Fanning, K., Ferraro, S., Ereza, J., Findlay, N., Flaugher, B., Font-Ribera, A., Forero-Sánchez, D., Forero-Romero, J. E., Frenk, C. S., Garcia-Quintero, C., Garrison, L. H., Gaztañaga, E., Gil-Marín, H., Gontcho, S. Gontcho A, Gonzalez-Morales, A. X., Gonzalez-Perez, V., Gordon, C., Green, D., Gruen, D., Gsponer, R., Gutierrez, G., Guy, J., Hadzhiyska, B., Hahn, C., Hanif, M. M. S, Herrera-Alcantar, H. K., Honscheid, K., Howlett, C., Huterer, D., Iršič, V., Ishak, M., Joyce, R., Juneau, S., Karaçaylı, N. G., Kehoe, R., Kent, S., Kirkby, D., Kong, H., Koposov, S. E., Kremin, A., Krolewski, A., Lahav, O., Lai, Y., Lan, T. -W., Landriau, M., Lang, D., Lasker, J., Goff, J. M. Le, Guillou, L. Le, Leauthaud, A., Levi, M. E., Li, T. S., Lodha, K., Magneville, C., Manera, M., Margala, D., Martini, P., Matthewson, W., Maus, M., McDonald, P., Medina-Varela, L., Meisner, A., Mena-Fernández, J., Miquel, R., Moon, J., Moore, S., Moustakas, J., Mudur, N., Mueller, E., Muñoz-Gutiérrez, A., Myers, A. D., Nadathur, S., Napolitano, L., Neveux, R., Newman, J. A., Nguyen, N. M., Nie, J., Niz, G., Noriega, H. E., Padmanabhan, N., Paillas, E., Palanque-Delabrouille, N., Pan, J., Penmetsa, S., Percival, W. J., Pieri, M. M., Pinon, M., Poppett, C., Porredon, A., Prada, F., Pérez-Fernández, A., Pérez-Ràfols, I., Rabinowitz, D., Raichoor, A., Ramírez-Pérez, C., Ramirez-Solano, S., Rashkovetskyi, M., Ravoux, C., Rezaie, M., Rich, J., Rocher, A., Rockosi, C., Roe, N. A., Rosado-Marin, A., Ross, A. J., Rossi, G., Ruggeri, R., Ruhlmann-Kleider, V., Samushia, L., Sanchez, E., Saulder, C., Schlafly, E. F., Schlegel, D., Schubnell, M., Seo, H., Shafieloo, A., Sharples, R., Silber, J., Slosar, A., Smith, A., Sprayberry, D., Tan, T., Tarlé, G., Taylor, P., Trusov, S., Vaisakh, R., Valcin, D., Valdes, F., Valogiannis, G., Vargas-Magaña, M., Verde, L., Walther, M., Wang, B., Wang, M. S., Weaver, B. A., Weaverdyck, N., Wechsler, R. H., Weinberg, D. H., White, M., Wilson, M. J., Yi, L., Yu, J., Yu, Y., Yuan, S., Yèche, C., Zaborowski, E. A., Zarrouk, P., Zhang, H., Zhao, C., Zhao, R., Zhou, R., Zhuang, T., Zou, H.

We present cosmological results from the measurement of clustering of galaxy, quasar and Lyman-$\alpha$ forest tracers from the first year of observations with the Dark Energy Spectroscopic Instrument (DESI Data Release 1). We adopt the full-shape (F

Externí odkaz: http://arxiv.org/abs/2411.12022

DESI 2024 V: Full-Shape Galaxy Clustering from Galaxies and Quasars

Autor: DESI Collaboration, Adame, A. G., Aguilar, J., Ahlen, S., Alam, S., Alexander, D. M., Alvarez, M., Alves, O., Anand, A., Andrade, U., Armengaud, E., Avila, S., Aviles, A., Awan, H., Bailey, S., Baltay, C., Bault, A., Behera, J., BenZvi, S., Beutler, F., Bianchi, D., Blake, C., Blum, R., Brieden, S., Brodzeller, A., Brooks, D., Buckley-Geer, E., Burtin, E., Calderon, R., Canning, R., Rosell, A. Carnero, Cereskaite, R., Cervantes-Cota, J. L., Chabanier, S., Chaussidon, E., Chaves-Montero, J., Chen, S., Chen, X., Claybaugh, T., Cole, S., Cuceu, A., Davis, T. M., Dawson, K., de la Macorra, A., de Mattia, A., Deiosso, N., Dey, A., Dey, B., Ding, Z., Doel, P., Edelstein, J., Eftekharzadeh, S., Eisenstein, D. J., Elliott, A., Fagrelius, P., Fanning, K., Ferraro, S., Ereza, J., Findlay, N., Flaugher, B., Font-Ribera, A., Forero-Sánchez, D., Forero-Romero, J. E., Garcia-Quintero, C., Garrison, L. H., Gaztañaga, E., Gil-Marín, H., Gontcho, S. Gontcho A, Gonzalez-Morales, A. X., Gonzalez-Perez, V., Gordon, C., Green, D., Gruen, D., Gsponer, R., Gutierrez, G., Guy, J., Hadzhiyska, B., Hahn, C., Hanif, M. M. S, Herrera-Alcantar, H. K., Honscheid, K., Howlett, C., Huterer, D., Iršič, V., Ishak, M., Juneau, S., Karaçaylı, N. G., Kehoe, R., Kent, S., Kirkby, D., Kong, H., Koposov, S. E., Kremin, A., Krolewski, A., Lai, Y., Lan, T. -W., Landriau, M., Lang, D., Lasker, J., Goff, J. M. Le, Guillou, L. Le, Leauthaud, A., Levi, M. E., Li, T. S., Lodha, K., Magneville, C., Manera, M., Margala, D., Martini, P., Maus, M., McDonald, P., Medina-Varela, L., Meisner, A., Mena-Fernández, J., Miquel, R., Moon, J., Moore, S., Moustakas, J., Mueller, E., Muñoz-Gutiérrez, A., Myers, A. D., Nadathur, S., Napolitano, L., Neveux, R., Newman, J. A., Nguyen, N. M., Nie, J., Niz, G., Noriega, H. E., Padmanabhan, N., Paillas, E., Palanque-Delabrouille, N., Pan, J., Penmetsa, S., Percival, W. J., Pieri, M. M., Pinon, M., Poppett, C., Porredon, A., Prada, F., Pérez-Fernández, A., Pérez-Ràfols, I., Rabinowitz, D., Raichoor, A., Ramírez-Pérez, C., Ramirez-Solano, S., Rashkovetskyi, M., Ravoux, C., Rezaie, M., Rich, J., Rocher, A., Rockosi, C., Rodríguez-Martínez, F., Roe, N. A., Rosado-Marin, A., Ross, A. J., Rossi, G., Ruggeri, R., Ruhlmann-Kleider, V., Samushia, L., Sanchez, E., Saulder, C., Schlafly, E. F., Schlegel, D., Schubnell, M., Seo, H., Sharples, R., Silber, J., Slosar, A., Smith, A., Sprayberry, D., Tan, T., Tarlé, G., Trusov, S., Vaisakh, R., Valcin, D., Valdes, F., Vargas-Magaña, M., Verde, L., Walther, M., Wang, B., Wang, M. S., Weaver, B. A., Weaverdyck, N., Wechsler, R. H., Weinberg, D. H., White, M., Wilson, M. J., Yu, J., Yu, Y., Yuan, S., Yèche, C., Zaborowski, E. A., Zarrouk, P., Zhang, H., Zhao, C., Zhao, R., Zhou, R., Zou, H.

We present the measurements and cosmological implications of the galaxy two-point clustering using over 4.7 million unique galaxy and quasar redshifts in the range $0.1