Author: "Beutler A" / Publication Type: Reports - Searchworks@Jio Institute Digital Library Search Results

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1. Window convolution of the galaxy clustering bispectrum

Author: Wang, Mike Shengbo, Beutler, Florian, Aguilar, J., Ahlen, S., Bianchi, D., Brooks, D., Claybaugh, T., de la Macorra, A., Doel, P., Font-Ribera, A., Gaztañaga, E., Gutierrez, G., Honscheid, K., Howlett, C., Kirkby, D., Lambert, A., Landriau, M., Miquel, R., Niz, G., Prada, F., Pérez-Ràfols, I., Rossi, G., Sanchez, E., Schlegel, D., Schubnell, M., Sprayberry, D., Tarlé, G., and Weaver, B. A.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: In galaxy survey analysis, the observed clustering statistics do not directly match theoretical predictions but rather have been processed by a window function that arises from the survey geometry including the sky footprint, redshift-dependent background number density and systematic weights. While window convolution of the power spectrum is well studied, for the bispectrum with a larger number of degrees of freedom, it poses a significant numerical and computational challenge. In this work, we consider the effect of the survey window in the tripolar spherical harmonic decomposition of the bispectrum and lay down a formal procedure for their convolution via a series expansion of configuration-space three-point correlation functions, which was first proposed by Sugiyama et al. (2019). We then provide a linear algebra formulation of the full window convolution, where an unwindowed bispectrum model vector can be directly premultiplied by a window matrix specific to each survey geometry. To validate the pipeline, we focus on the Dark Energy Spectroscopic Instrument (DESI) Data Release 1 (DR1) luminous red galaxy (LRG) sample in the South Galactic Cap (SGC) in the redshift bin $0.4 \leqslant z \leqslant 0.6$. We first perform convergence checks on the measurement of the window function from discrete random catalogues, and then investigate the convergence of the window convolution series expansion truncated at a finite of number of terms as well as the performance of the window matrix. This work highlights the differences in window convolution between the power spectrum and bispectrum, and provides a streamlined pipeline for the latter for current surveys such as DESI and the Euclid mission., Comment: 30 pages, 12 figures, for submission to JCAP
Published: 2024

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

Author: 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., and Zou, H.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: 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 (FS) modeling of the power spectrum, including the effects of redshift-space distortions, in an analysis which has been validated in a series of supporting papers. In the flat $\Lambda$CDM cosmological model, DESI (FS+BAO), combined with a baryon density prior from Big Bang Nucleosynthesis and a weak prior on the scalar spectral index, determines matter density to $\Omega_\mathrm{m}=0.2962\pm 0.0095$, and the amplitude of mass fluctuations to $\sigma_8=0.842\pm 0.034$. The addition of the cosmic microwave background (CMB) data tightens these constraints to $\Omega_\mathrm{m}=0.3056\pm 0.0049$ and $\sigma_8=0.8121\pm 0.0053$, while further addition of the the joint clustering and lensing analysis from the Dark Energy Survey Year-3 (DESY3) data leads to a 0.4% determination of the Hubble constant, $H_0 = (68.40\pm 0.27)\,{\rm km\,s^{-1}\,Mpc^{-1}}$. In models with a time-varying dark energy equation of state, combinations of DESI (FS+BAO) with CMB and type Ia supernovae continue to show the preference, previously found in the DESI DR1 BAO analysis, for $w_0>-1$ and $w_a<0$ with similar levels of significance. DESI data, in combination with the CMB, impose the upper limits on the sum of the neutrino masses of $\sum m_\nu < 0.071\,{\rm eV}$ at 95% confidence. DESI data alone measure the modified-gravity parameter that controls the clustering of massive particles, $\mu_0=0.11^{+0.45}_{-0.54}$, while the combination of DESI with the CMB and the clustering and lensing analysis from DESY3 constrains both modified-gravity parameters, giving $\mu_0 = 0.04\pm 0.22$ and $\Sigma_0 = 0.044\pm 0.047$, in agreement with general relativity. [Abridged.], Comment: This DESI Collaboration Key Publication is part of the 2024 publication series using the first year of observations (see https://data.desi.lbl.gov/doc/papers/). 55 pages, 10 figures
Published: 2024

3. DESI 2024 II: Sample Definitions, Characteristics, and Two-point Clustering Statistics

Author: 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., Brown, Z., 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., Demina, R., Dey, A., Dey, B., Ding, Z., Doel, P., Edelstein, J., Eftekharzadeh, S., Eisenstein, D. J., Elliott, A., Fagrelius, P., Fanning, K., Ferraro, S., Ereza, J., Findlay, N., Flaugher, B., Font-Ribera, A., Forero-Sánchez, D., Forero-Romero, J. E., Frenk, C. S., Garcia-Quintero, C., Gaztañaga, E., Gil-Marín, H., Gontcho, S. Gontcho A, Gonzalez-Morales, A. X., Gonzalez-Perez, V., Gordon, C., Green, D., Gruen, D., Gsponer, R., Gutierrez, G., Guy, J., Hadzhiyska, B., Hahn, C., Hanif, M. M. S, Herrera-Alcantar, H. K., Honscheid, K., Hou, J., Howlett, C., Huterer, D., Iršič, V., Ishak, M., Juneau, S., Karaçaylı, N. G., Kehoe, R., Kent, S., Kirkby, D., Kitaura, F. -S., Kong, H., 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., 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., Scholte, 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., and Zou, H.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: We present the samples of galaxies and quasars used for DESI 2024 cosmological analyses, drawn from the DESI Data Release 1 (DR1). We describe the construction of large-scale structure (LSS) catalogs from these samples, which include matched sets of synthetic reference `randoms' and weights that account for variations in the observed density of the samples due to experimental design and varying instrument performance. We detail how we correct for variations in observational completeness, the input `target' densities due to imaging systematics, and the ability to confidently measure redshifts from DESI spectra. We then summarize how remaining uncertainties in the corrections can be translated to systematic uncertainties for particular analyses. We describe the weights added to maximize the signal-to-noise of DESI DR1 2-point clustering measurements. We detail measurement pipelines applied to the LSS catalogs that obtain 2-point clustering measurements in configuration and Fourier space. The resulting 2-point measurements depend on window functions and normalization constraints particular to each sample, and we present the corrections required to match models to the data. We compare the configuration- and Fourier-space 2-point clustering of the data samples to that recovered from simulations of DESI DR1 and find they are, generally, in statistical agreement to within 2\% in the inferred real-space over-density field. The LSS catalogs, 2-point measurements, and their covariance matrices will be released publicly with DESI DR1., Comment: This DESI Collaboration Key Publication is part of the 2024 publication series using the first year of observations (see https://data.desi.lbl.gov/doc/papers/)
Published: 2024

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

Author: 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., and Zou, H.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: 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
Published: 2024

5. GPT-4o System Card

Author: OpenAI, Hurst, Aaron, Lerer, Adam, Goucher, Adam P., Perelman, Adam, Ramesh, Aditya, Clark, Aidan, Ostrow, AJ, Welihinda, Akila, Hayes, Alan, Radford, Alec, Mądry, Aleksander, Baker-Whitcomb, Alex, Beutel, Alex, Borzunov, Alex, Carney, Alex, Chow, Alex, Kirillov, Alex, Nichol, Alex, Paino, Alex, Renzin, Alex, Passos, Alex Tachard, Kirillov, Alexander, Christakis, Alexi, Conneau, Alexis, Kamali, Ali, Jabri, Allan, Moyer, Allison, Tam, Allison, Crookes, Amadou, Tootoochian, Amin, Tootoonchian, Amin, Kumar, Ananya, Vallone, Andrea, Karpathy, Andrej, Braunstein, Andrew, Cann, Andrew, Codispoti, Andrew, Galu, Andrew, Kondrich, Andrew, Tulloch, Andrew, Mishchenko, Andrey, Baek, Angela, Jiang, Angela, Pelisse, Antoine, Woodford, Antonia, Gosalia, Anuj, Dhar, Arka, Pantuliano, Ashley, Nayak, Avi, Oliver, Avital, Zoph, Barret, Ghorbani, Behrooz, Leimberger, Ben, Rossen, Ben, Sokolowsky, Ben, Wang, Ben, Zweig, Benjamin, Hoover, Beth, Samic, Blake, McGrew, Bob, Spero, Bobby, Giertler, Bogo, Cheng, Bowen, Lightcap, Brad, Walkin, Brandon, Quinn, Brendan, Guarraci, Brian, Hsu, Brian, Kellogg, Bright, Eastman, Brydon, Lugaresi, Camillo, Wainwright, Carroll, Bassin, Cary, Hudson, Cary, Chu, Casey, Nelson, Chad, Li, Chak, Shern, Chan Jun, Conger, Channing, Barette, Charlotte, Voss, Chelsea, Ding, Chen, Lu, Cheng, Zhang, Chong, Beaumont, Chris, Hallacy, Chris, Koch, Chris, Gibson, Christian, Kim, Christina, Choi, Christine, McLeavey, Christine, Hesse, Christopher, Fischer, Claudia, Winter, Clemens, Czarnecki, Coley, Jarvis, Colin, Wei, Colin, Koumouzelis, Constantin, Sherburn, Dane, Kappler, Daniel, Levin, Daniel, Levy, Daniel, Carr, David, Farhi, David, Mely, David, Robinson, David, Sasaki, David, Jin, Denny, Valladares, Dev, Tsipras, Dimitris, Li, Doug, Nguyen, Duc Phong, Findlay, Duncan, Oiwoh, Edede, Wong, Edmund, Asdar, Ehsan, Proehl, Elizabeth, Yang, Elizabeth, Antonow, Eric, Kramer, Eric, Peterson, Eric, Sigler, Eric, Wallace, Eric, Brevdo, Eugene, Mays, Evan, Khorasani, Farzad, Such, Felipe Petroski, Raso, Filippo, Zhang, Francis, von Lohmann, Fred, Sulit, Freddie, Goh, Gabriel, Oden, Gene, Salmon, Geoff, Starace, Giulio, Brockman, Greg, Salman, Hadi, Bao, Haiming, Hu, Haitang, Wong, Hannah, Wang, Haoyu, Schmidt, Heather, Whitney, Heather, Jun, Heewoo, Kirchner, Hendrik, Pinto, Henrique Ponde de Oliveira, Ren, Hongyu, Chang, Huiwen, Chung, Hyung Won, Kivlichan, Ian, O'Connell, Ian, Osband, Ian, Silber, Ian, Sohl, Ian, Okuyucu, Ibrahim, Lan, Ikai, Kostrikov, Ilya, Sutskever, Ilya, Kanitscheider, Ingmar, Gulrajani, Ishaan, Coxon, Jacob, Menick, Jacob, Pachocki, Jakub, Aung, James, Betker, James, Crooks, James, Lennon, James, Kiros, Jamie, Leike, Jan, Park, Jane, Kwon, Jason, Phang, Jason, Teplitz, Jason, Wei, Jason, Wolfe, Jason, Chen, Jay, Harris, Jeff, Varavva, Jenia, Lee, Jessica Gan, Shieh, Jessica, Lin, Ji, Yu, Jiahui, Weng, Jiayi, Tang, Jie, Yu, Jieqi, Jang, Joanne, Candela, Joaquin Quinonero, Beutler, Joe, Landers, Joe, Parish, Joel, Heidecke, Johannes, Schulman, John, Lachman, Jonathan, McKay, Jonathan, Uesato, Jonathan, Ward, Jonathan, Kim, Jong Wook, Huizinga, Joost, Sitkin, Jordan, Kraaijeveld, Jos, Gross, Josh, Kaplan, Josh, Snyder, Josh, Achiam, Joshua, Jiao, Joy, Lee, Joyce, Zhuang, Juntang, Harriman, Justyn, Fricke, Kai, Hayashi, Kai, Singhal, Karan, Shi, Katy, Karthik, Kavin, Wood, Kayla, Rimbach, Kendra, Hsu, Kenny, Nguyen, Kenny, Gu-Lemberg, Keren, Button, Kevin, Liu, Kevin, Howe, Kiel, Muthukumar, Krithika, Luther, Kyle, Ahmad, Lama, Kai, Larry, Itow, Lauren, Workman, Lauren, Pathak, Leher, Chen, Leo, Jing, Li, Guy, Lia, Fedus, Liam, Zhou, Liang, Mamitsuka, Lien, Weng, Lilian, McCallum, Lindsay, Held, Lindsey, Ouyang, Long, Feuvrier, Louis, Zhang, Lu, Kondraciuk, Lukas, Kaiser, Lukasz, Hewitt, Luke, Metz, Luke, Doshi, Lyric, Aflak, Mada, Simens, Maddie, Boyd, Madelaine, Thompson, Madeleine, Dukhan, Marat, Chen, Mark, Gray, Mark, Hudnall, Mark, Zhang, Marvin, Aljubeh, Marwan, Litwin, Mateusz, Zeng, Matthew, Johnson, Max, Shetty, Maya, Gupta, Mayank, Shah, Meghan, Yatbaz, Mehmet, Yang, Meng Jia, Zhong, Mengchao, Glaese, Mia, Chen, Mianna, Janner, Michael, Lampe, Michael, Petrov, Michael, Wu, Michael, Wang, Michele, Fradin, Michelle, Pokrass, Michelle, Castro, Miguel, de Castro, Miguel Oom Temudo, Pavlov, Mikhail, Brundage, Miles, Wang, Miles, Khan, Minal, Murati, Mira, Bavarian, Mo, Lin, Molly, Yesildal, Murat, Soto, Nacho, Gimelshein, Natalia, Cone, Natalie, Staudacher, Natalie, Summers, Natalie, LaFontaine, Natan, Chowdhury, Neil, Ryder, Nick, Stathas, Nick, Turley, Nick, Tezak, Nik, Felix, Niko, Kudige, Nithanth, Keskar, Nitish, Deutsch, Noah, Bundick, Noel, Puckett, Nora, Nachum, Ofir, Okelola, Ola, Boiko, Oleg, Murk, Oleg, Jaffe, Oliver, Watkins, Olivia, Godement, Olivier, Campbell-Moore, Owen, Chao, Patrick, McMillan, Paul, Belov, Pavel, Su, Peng, Bak, Peter, Bakkum, Peter, Deng, Peter, Dolan, Peter, Hoeschele, Peter, Welinder, Peter, Tillet, Phil, Pronin, Philip, Tillet, Philippe, Dhariwal, Prafulla, Yuan, Qiming, Dias, Rachel, Lim, Rachel, Arora, Rahul, Troll, Rajan, Lin, Randall, Lopes, Rapha Gontijo, Puri, Raul, Miyara, Reah, Leike, Reimar, Gaubert, Renaud, Zamani, Reza, Wang, Ricky, Donnelly, Rob, Honsby, Rob, Smith, Rocky, Sahai, Rohan, Ramchandani, Rohit, Huet, Romain, Carmichael, Rory, Zellers, Rowan, Chen, Roy, Chen, Ruby, Nigmatullin, Ruslan, Cheu, Ryan, Jain, Saachi, Altman, Sam, Schoenholz, Sam, Toizer, Sam, Miserendino, Samuel, Agarwal, Sandhini, Culver, Sara, Ethersmith, Scott, Gray, Scott, Grove, Sean, Metzger, Sean, Hermani, Shamez, Jain, Shantanu, Zhao, Shengjia, Wu, Sherwin, Jomoto, Shino, Wu, Shirong, Shuaiqi, Xia, Phene, Sonia, Papay, Spencer, Narayanan, Srinivas, Coffey, Steve, Lee, Steve, Hall, Stewart, Balaji, Suchir, Broda, Tal, Stramer, Tal, Xu, Tao, Gogineni, Tarun, Christianson, Taya, Sanders, Ted, Patwardhan, Tejal, Cunninghman, Thomas, Degry, Thomas, Dimson, Thomas, Raoux, Thomas, Shadwell, Thomas, Zheng, Tianhao, Underwood, Todd, Markov, Todor, Sherbakov, Toki, Rubin, Tom, Stasi, Tom, Kaftan, Tomer, Heywood, Tristan, Peterson, Troy, Walters, Tyce, Eloundou, Tyna, Qi, Valerie, Moeller, Veit, Monaco, Vinnie, Kuo, Vishal, Fomenko, Vlad, Chang, Wayne, Zheng, Weiyi, Zhou, Wenda, Manassra, Wesam, Sheu, Will, Zaremba, Wojciech, Patil, Yash, Qian, Yilei, Kim, Yongjik, Cheng, Youlong, Zhang, Yu, He, Yuchen, Zhang, Yuchen, Jin, Yujia, Dai, Yunxing, and Malkov, Yury
Subjects: Computer Science - Computation and Language, Computer Science - Artificial Intelligence, Computer Science - Computer Vision and Pattern Recognition, Computer Science - Computers and Society, Computer Science - Machine Learning, Computer Science - Sound, Electrical Engineering and Systems Science - Audio and Speech Processing
Abstract: GPT-4o is an autoregressive omni model that accepts as input any combination of text, audio, image, and video, and generates any combination of text, audio, and image outputs. It's trained end-to-end across text, vision, and audio, meaning all inputs and outputs are processed by the same neural network. GPT-4o can respond to audio inputs in as little as 232 milliseconds, with an average of 320 milliseconds, which is similar to human response time in conversation. It matches GPT-4 Turbo performance on text in English and code, with significant improvement on text in non-English languages, while also being much faster and 50\% cheaper in the API. GPT-4o is especially better at vision and audio understanding compared to existing models. In line with our commitment to building AI safely and consistent with our voluntary commitments to the White House, we are sharing the GPT-4o System Card, which includes our Preparedness Framework evaluations. In this System Card, we provide a detailed look at GPT-4o's capabilities, limitations, and safety evaluations across multiple categories, focusing on speech-to-speech while also evaluating text and image capabilities, and measures we've implemented to ensure the model is safe and aligned. We also include third-party assessments on dangerous capabilities, as well as discussion of potential societal impacts of GPT-4o's text and vision capabilities.
Published: 2024

6. Euclid. I. Overview of the Euclid mission

Author: Euclid Collaboration, Mellier, Y., Abdurro'uf, Barroso, J. A. Acevedo, Achúcarro, A., Adamek, J., Adam, R., Addison, G. E., Aghanim, N., Aguena, M., Ajani, V., Akrami, Y., Al-Bahlawan, A., Alavi, A., Albuquerque, I. S., Alestas, G., Alguero, G., Allaoui, A., Allen, S. W., Allevato, V., Alonso-Tetilla, A. V., Altieri, B., Alvarez-Candal, A., Alvi, S., Amara, A., Amendola, L., Amiaux, J., Andika, I. T., Andreon, S., Andrews, A., Angora, G., Angulo, R. E., Annibali, F., Anselmi, A., Anselmi, S., Arcari, S., Archidiacono, M., Aricò, G., Arnaud, M., Arnouts, S., Asgari, M., Asorey, J., Atayde, L., Atek, H., Atrio-Barandela, F., Aubert, M., Aubourg, E., Auphan, T., Auricchio, N., Aussel, B., Aussel, H., Avelino, P. P., Avgoustidis, A., Avila, S., Awan, S., Azzollini, R., Baccigalupi, C., Bachelet, E., Bacon, D., Baes, M., Bagley, M. B., Bahr-Kalus, B., Balaguera-Antolinez, A., Balbinot, E., Balcells, M., Baldi, M., Baldry, I., Balestra, A., Ballardini, M., Ballester, O., Balogh, M., Bañados, E., Barbier, R., Bardelli, S., Baron, M., Barreiro, T., Barrena, R., Barriere, J. -C., Barros, B. J., Barthelemy, A., Bartolo, N., Basset, A., Battaglia, P., Battisti, A. J., Baugh, C. M., Baumont, L., Bazzanini, L., Beaulieu, J. -P., Beckmann, V., Belikov, A. N., Bel, J., Bellagamba, F., Bella, M., Bellini, E., Benabed, K., Bender, R., Benevento, G., Bennett, C. L., Benson, K., Bergamini, P., Bermejo-Climent, J. R., Bernardeau, F., Bertacca, D., Berthe, M., Berthier, J., Bethermin, M., Beutler, F., Bevillon, C., Bhargava, S., Bhatawdekar, R., Bianchi, D., Bisigello, L., Biviano, A., Blake, R. P., Blanchard, A., Blazek, J., Blot, L., Bosco, A., Bodendorf, C., Boenke, T., Böhringer, H., Boldrini, P., Bolzonella, M., Bonchi, A., Bonici, M., Bonino, D., Bonino, L., Bonvin, C., Bon, W., Booth, J. T., Borgani, S., Borlaff, A. S., Borsato, E., Bose, B., Botticella, M. T., Boucaud, A., Bouche, F., Boucher, J. S., Boutigny, D., Bouvard, T., Bouwens, R., Bouy, H., Bowler, R. A. A., Bozza, V., Bozzo, E., Branchini, E., Brando, G., Brau-Nogue, S., Brekke, P., Bremer, M. N., Brescia, M., Breton, M. -A., Brinchmann, J., Brinckmann, T., Brockley-Blatt, C., Brodwin, M., Brouard, L., Brown, M. L., Bruton, S., Bucko, J., Buddelmeijer, H., Buenadicha, G., Buitrago, F., Burger, P., Burigana, C., Busillo, V., Busonero, D., Cabanac, R., Cabayol-Garcia, L., Cagliari, M. S., Caillat, A., Caillat, L., Calabrese, M., Calabro, A., Calderone, G., Calura, F., Quevedo, B. Camacho, Camera, S., Campos, L., Canas-Herrera, G., Candini, G. P., Cantiello, M., Capobianco, V., Cappellaro, E., Cappelluti, N., Cappi, A., Caputi, K. I., Cara, C., Carbone, C., Cardone, V. F., Carella, E., Carlberg, R. G., Carle, M., Carminati, L., Caro, F., Carrasco, J. M., Carretero, J., Carrilho, P., Duque, J. Carron, Carry, B., Carvalho, A., Carvalho, C. S., Casas, R., Casas, S., Casenove, P., Casey, C. M., Cassata, P., Castander, F. J., Castelao, D., Castellano, M., Castiblanco, L., Castignani, G., Castro, T., Cavet, C., Cavuoti, S., Chabaud, P. -Y., Chambers, K. C., Charles, Y., Charlot, S., Chartab, N., Chary, R., Chaumeil, F., Cho, H., Chon, G., Ciancetta, E., Ciliegi, P., Cimatti, A., Cimino, M., Cioni, M. -R. L., Claydon, R., Cleland, C., Clément, B., Clements, D. L., Clerc, N., Clesse, S., Codis, S., Cogato, F., Colbert, J., Cole, R. E., Coles, P., Collett, T. E., Collins, R. S., Colodro-Conde, C., Colombo, C., Combes, F., Conforti, V., Congedo, G., Conseil, S., Conselice, C. J., Contarini, S., Contini, T., Conversi, L., Cooray, A. R., Copin, Y., Corasaniti, P. -S., Corcho-Caballero, P., Corcione, L., Cordes, O., Corpace, O., Correnti, M., Costanzi, M., Costille, A., Courbin, F., Mifsud, L. Courcoult, Courtois, H. M., Cousinou, M. -C., Covone, G., Cowell, T., Cragg, C., Cresci, G., Cristiani, S., Crocce, M., Cropper, M., Crouzet, P. E, Csizi, B., Cuby, J. -G., Cucchetti, E., Cucciati, O., Cuillandre, J. -C., Cunha, P. A. C., Cuozzo, V., Daddi, E., D'Addona, M., Dafonte, C., Dagoneau, N., Dalessandro, E., Dalton, G. B., D'Amico, G., Dannerbauer, H., Danto, P., Das, I., Da Silva, A., da Silva, R., Doumerg, W. d'Assignies, Daste, G., Davies, J. E., Davini, S., Dayal, P., de Boer, T., Decarli, R., De Caro, B., Degaudenzi, H., Degni, G., de Jong, J. T. A., de la Bella, L. F., de la Torre, S., Delhaise, F., Delley, D., Delucchi, G., De Lucia, G., Denniston, J., De Paolis, F., De Petris, M., Derosa, A., Desai, S., Desjacques, V., Despali, G., Desprez, G., De Vicente-Albendea, J., Deville, Y., Dias, J. D. F., Díaz-Sánchez, A., Diaz, J. J., Di Domizio, S., Diego, J. M., Di Ferdinando, D., Di Giorgio, A. M., Dimauro, P., Dinis, J., Dolag, K., Dolding, C., Dole, H., Sánchez, H. Domínguez, Doré, O., Dournac, F., Douspis, M., Dreihahn, H., Droge, B., Dryer, B., Dubath, F., Duc, P. -A., Ducret, F., Duffy, C., Dufresne, F., Duncan, C. A. J., Dupac, X., Duret, V., Durrer, R., Durret, F., Dusini, S., Ealet, A., Eggemeier, A., Eisenhardt, P. R. M., Elbaz, D., Elkhashab, M. Y., Ellien, A., Endicott, J., Enia, A., Erben, T., Vigo, J. A. Escartin, Escoffier, S., Sanz, I. Escudero, Essert, J., Ettori, S., Ezziati, M., Fabbian, G., Fabricius, M., Fang, Y., Farina, A., Farina, M., Farinelli, R., Farrens, S., Faustini, F., Feltre, A., Ferguson, A. M. N., Ferrando, P., Ferrari, A. G., Ferré-Mateu, A., Ferreira, P. G., Ferreras, I., Ferrero, I., Ferriol, S., Ferruit, P., Filleul, D., Finelli, F., Finkelstein, S. L., Finoguenov, A., Fiorini, B., Flentge, F., Focardi, P., Fonseca, J., Fontana, A., Fontanot, F., Fornari, F., Fosalba, P., Fossati, M., Fotopoulou, S., Fouchez, D., Fourmanoit, N., Frailis, M., Fraix-Burnet, D., Franceschi, E., Franco, A., Franzetti, P., Freihoefer, J., Frenk, C. . S., Frittoli, G., Frugier, P. -A., Frusciante, N., Fumagalli, A., Fumagalli, M., Fumana, M., Fu, Y., Gabarra, L., Galeotta, S., Galluccio, L., Ganga, K., Gao, H., García-Bellido, J., Garcia, K., Gardner, J. P., Garilli, B., Gaspar-Venancio, L. -M., Gasparetto, T., Gautard, V., Gavazzi, R., Gaztanaga, E., Genolet, L., Santos, R. Genova, Gentile, F., George, K., Gerbino, M., Ghaffari, Z., Giacomini, F., Gianotti, F., Gibb, G. P. S., Gillard, W., Gillis, B., Ginolfi, M., Giocoli, C., Girardi, M., Giri, S. K., Goh, L. W. K., Gómez-Alvarez, P., Gonzalez-Perez, V., Gonzalez, A. H., Gonzalez, E. J., Gonzalez, J. C., Beauchamps, S. Gouyou, Gozaliasl, G., Gracia-Carpio, J., Grandis, S., Granett, B. R., Granvik, M., Grazian, A., Gregorio, A., Grenet, C., Grillo, C., Grupp, F., Gruppioni, C., Gruppuso, A., Guerbuez, C., Guerrini, S., Guidi, M., Guillard, P., Gutierrez, C. M., Guttridge, P., Guzzo, L., Gwyn, S., Haapala, J., Haase, J., Haddow, C. R., Hailey, M., Hall, A., Hall, D., Hamaus, N., Haridasu, B. S., Harnois-Déraps, J., Harper, C., Hartley, W. G., Hasinger, G., Hassani, F., Hatch, N. A., Haugan, S. V. H., Häußler, B., Heavens, A., Heisenberg, L., Helmi, A., Helou, G., Hemmati, S., Henares, K., Herent, O., Hernández-Monteagudo, C., Heuberger, T., Hewett, P. C., Heydenreich, S., Hildebrandt, H., Hirschmann, M., Hjorth, J., Hoar, J., Hoekstra, H., Holland, A. D., Holliman, M. S., Holmes, W., Hook, I., Horeau, B., Hormuth, F., Hornstrup, A., Hosseini, S., Hu, D., Hudelot, P., Hudson, M. J., Huertas-Company, M., Huff, E. M., Hughes, A. C. N., Humphrey, A., Hunt, L. K., Huynh, D. D., Ibata, R., Ichikawa, K., Iglesias-Groth, S., Ilbert, O., Ilić, S., Ingoglia, L., Iodice, E., Israel, H., Israelsson, U. E., Izzo, L., Jablonka, P., Jackson, N., Jacobson, J., Jafariyazani, M., Jahnke, K., Jain, B., Jansen, H., Jarvis, M. J., Jasche, J., Jauzac, M., Jeffrey, N., Jhabvala, M., Jimenez-Teja, Y., Muñoz, A. Jimenez, Joachimi, B., Johansson, P. H., Joudaki, S., Jullo, E., Kajava, J. J. E., Kang, Y., Kannawadi, A., Kansal, V., Karagiannis, D., Kärcher, M., Kashlinsky, A., Kazandjian, M. V., Keck, F., Keihänen, E., Kerins, E., Kermiche, S., Khalil, A., Kiessling, A., Kiiveri, K., Kilbinger, M., Kim, J., King, R., Kirkpatrick, C. C., Kitching, T., Kluge, M., Knabenhans, M., Knapen, J. H., Knebe, A., Kneib, J. -P., Kohley, R., Koopmans, L. V. E., Koskinen, H., Koulouridis, E., Kou, R., Kovács, A., Kovačić, I., Kowalczyk, A., Koyama, K., Kraljic, K., Krause, O., Kruk, S., Kubik, B., Kuchner, U., Kuijken, K., Kümmel, M., Kunz, M., Kurki-Suonio, H., Lacasa, F., Lacey, C. G., La Franca, F., Lagarde, N., Lahav, O., Laigle, C., La Marca, A., La Marle, O., Lamine, B., Lam, M. C., Lançon, A., Landt, H., Langer, M., Lapi, A., Larcheveque, C., Larsen, S. S., Lattanzi, M., Laudisio, F., Laugier, D., Laureijs, R., Laurent, V., Lavaux, G., Lawrenson, A., Lazanu, A., Lazeyras, T., Boulc'h, Q. Le, Brun, A. M. C. Le, Brun, V. Le, Leclercq, F., Lee, S., Graet, J. Le, Legrand, L., Leirvik, K. N., Jeune, M. Le, Lembo, M., Mignant, D. Le, Lepinzan, M. D., Lepori, F., Reun, A. Le, Leroy, G., Lesci, G. F., Lesgourgues, J., Leuzzi, L., Levi, M. E., Liaudat, T. I., Libet, G., Liebing, P., Ligori, S., Lilje, P. B., Lin, C. -C., Linde, D., Linder, E., Lindholm, V., Linke, L., Li, S. -S., Liu, S. J., Lloro, I., Lobo, F. S. N., Lodieu, N., Lombardi, M., Lombriser, L., Lonare, P., Longo, G., López-Caniego, M., Lopez, X. Lopez, Alvarez, J. Lorenzo, Loureiro, A., Loveday, J., Lusso, E., Macias-Perez, J., Maciaszek, T., Maggio, G., Magliocchetti, M., Magnard, F., Magnier, E. A., Magro, A., Mahler, G., Mainetti, G., Maino, D., Maiorano, E., Malavasi, N., Mamon, G. A., Mancini, C., Mandelbaum, R., Manera, M., Manjón-García, A., Mannucci, F., Mansutti, O., Outeiro, M. Manteiga, Maoli, R., Maraston, C., Marcin, S., Marcos-Arenal, P., Margalef-Bentabol, B., Marggraf, O., Marinucci, D., Marinucci, M., Markovic, K., Marleau, F. R., Marpaud, J., Martignac, J., Martín-Fleitas, J., Martin-Moruno, P., Martin, E. L., Martinelli, M., Martinet, N., Martin, H., Martins, C. J. A. P., Marulli, F., Massari, D., Massey, R., Masters, D. C., Matarrese, S., Matsuoka, Y., Matthew, S., Maughan, B. J., Mauri, N., Maurin, L., Maurogordato, S., McCarthy, K., McConnachie, A. W., McCracken, H. J., McDonald, I., McEwen, J. D., McPartland, C. J. R., Medinaceli, E., Mehta, V., Mei, S., Melchior, M., Melin, J. -B., Ménard, B., Mendes, J., Mendez-Abreu, J., Meneghetti, M., Mercurio, A., Merlin, E., Metcalf, R. B., Meylan, G., Migliaccio, M., Mignoli, M., Miller, L., Miluzio, M., Milvang-Jensen, B., Mimoso, J. P., Miquel, R., Miyatake, H., Mobasher, B., Mohr, J. J., Monaco, P., Monguió, M., Montoro, A., Mora, A., Dizgah, A. Moradinezhad, Moresco, M., Moretti, C., Morgante, G., Morisset, N., Moriya, T. J., Morris, P. W., Mortlock, D. J., Moscardini, L., Mota, D. F., Mottet, S., Moustakas, L. A., Moutard, T., Müller, T., Munari, E., Murphree, G., Murray, C., Murray, N., Musi, P., Nadathur, S., Nagam, B. C., Nagao, T., Naidoo, K., Nakajima, R., Nally, C., Natoli, P., Navarro-Alsina, A., Girones, D. Navarro, Neissner, C., Nersesian, A., Nesseris, S., Nguyen-Kim, H. N., Nicastro, L., Nichol, R. C., Nielbock, M., Niemi, S. -M., Nieto, S., Nilsson, K., Noller, J., Norberg, P., Nouri-Zonoz, A., Ntelis, P., Nucita, A. A., Nugent, P., Nunes, N. J., Nutma, T., Ocampo, I., Odier, J., Oesch, P. A., Oguri, M., Oliveira, D. Magalhaes, Onoue, M., Oosterbroek, T., Oppizzi, F., Ordenovic, C., Osato, K., Pacaud, F., Pace, F., Padilla, C., Paech, K., Pagano, L., Page, M. J., Palazzi, E., Paltani, S., Pamuk, S., Pandolfi, S., Paoletti, D., Paolillo, M., Papaderos, P., Pardede, K., Parimbelli, G., Parmar, A., Partmann, C., Pasian, F., Passalacqua, F., Paterson, K., Patrizii, L., Pattison, C., Paulino-Afonso, A., Paviot, R., Peacock, J. A., Pearce, F. R., Pedersen, K., Peel, A., Peletier, R. F., Ibanez, M. Pellejero, Pello, R., Penny, M. T., Percival, W. J., Perez-Garrido, A., Perotto, L., Pettorino, V., Pezzotta, A., Pezzuto, S., Philippon, A., Pierre, M., Piersanti, O., Pietroni, M., Piga, L., Pilo, L., Pires, S., Pisani, A., Pizzella, A., Pizzuti, L., Plana, C., Polenta, G., Pollack, J. E., Poncet, M., Pöntinen, M., Pool, P., Popa, L. A., Popa, V., Popp, J., Porciani, C., Porth, L., Potter, D., Poulain, M., Pourtsidou, A., Pozzetti, L., Prandoni, I., Pratt, G. W., Prezelus, S., Prieto, E., Pugno, A., Quai, S., Quilley, L., Racca, G. D., Raccanelli, A., Rácz, G., Radinović, S., Radovich, M., Ragagnin, A., Ragnit, U., Raison, F., Ramos-Chernenko, N., Ranc, C., Rasera, Y., Raylet, N., Rebolo, R., Refregier, A., Reimberg, P., Reiprich, T. H., Renk, F., Renzi, A., Retre, J., Revaz, Y., Reylé, C., Reynolds, L., Rhodes, J., Ricci, F., Ricci, M., Riccio, G., Ricken, S. O., Rissanen, S., Risso, I., Rix, H. -W., Robin, A. C., Rocca-Volmerange, B., Rocci, P. -F., Rodenhuis, M., Rodighiero, G., Monroy, M. Rodriguez, Rollins, R. P., Romanello, M., Roman, J., Romelli, E., Romero-Gomez, M., Roncarelli, M., Rosati, P., Rosset, C., Rossetti, E., Roster, W., Rottgering, H. J. A., Rozas-Fernández, A., Ruane, K., Rubino-Martin, J. A., Rudolph, A., Ruppin, F., Rusholme, B., Sacquegna, S., Sáez-Casares, I., Saga, S., Saglia, R., Sahlén, M., Saifollahi, T., Sakr, Z., Salvalaggio, J., Salvaterra, R., Salvati, L., Salvato, M., Salvignol, J. -C., Sánchez, A. G., Sanchez, E., Sanders, D. B., Sapone, D., Saponara, M., Sarpa, E., Sarron, F., Sartori, S., Sartoris, B., Sassolas, B., Sauniere, L., Sauvage, M., Sawicki, M., Scaramella, R., Scarlata, C., Scharré, L., Schaye, J., Schewtschenko, J. A., Schindler, J. -T., Schinnerer, E., Schirmer, M., Schmidt, F., Schmidt, M., Schneider, A., Schneider, M., Schneider, P., Schöneberg, N., Schrabback, T., Schultheis, M., Schulz, S., Schuster, N., Schwartz, J., Sciotti, D., Scodeggio, M., Scognamiglio, D., Scott, D., Scottez, V., Secroun, A., Sefusatti, E., Seidel, G., Seiffert, M., Sellentin, E., Selwood, M., Semboloni, E., Sereno, M., Serjeant, S., Serrano, S., Setnikar, G., Shankar, F., Sharples, R. M., Short, A., Shulevski, A., Shuntov, M., Sias, M., Sikkema, G., Silvestri, A., Simon, P., Sirignano, C., Sirri, G., Skottfelt, J., Slezak, E., Sluse, D., Smith, G. P., Smith, L. C., Smith, R. E., Smit, S. J. A., Soldano, F., Solheim, B. G. B., Sorce, J. G., Sorrenti, F., Soubrie, E., Spinoglio, L., Mancini, A. Spurio, Stadel, J., Stagnaro, L., Stanco, L., Stanford, S. A., Starck, J. -L., Stassi, P., Steinwagner, J., Stern, D., Stone, C., Strada, P., Strafella, F., Stramaccioni, D., Surace, C., Sureau, F., Suyu, S. H., Swindells, I., Szafraniec, M., Szapudi, I., Taamoli, S., Talia, M., Tallada-Crespí, P., Tanidis, K., Tao, C., Tarrío, P., Tavagnacco, D., Taylor, A. N., Taylor, J. E., Taylor, P. L., Teixeira, E. M., Tenti, M., Idiago, P. Teodoro, Teplitz, H. I., Tereno, I., Tessore, N., Testa, V., Testera, G., Tewes, M., Teyssier, R., Theret, N., Thizy, C., Thomas, P. D., Toba, Y., Toft, S., Toledo-Moreo, R., Tolstoy, E., Tommasi, E., Torbaniuk, O., Torradeflot, F., Tortora, C., Tosi, S., Tosti, S., Trifoglio, M., Troja, A., Trombetti, T., Tronconi, A., Tsedrik, M., Tsyganov, A., Tucci, M., Tutusaus, I., Uhlemann, C., Ulivi, L., Urbano, M., Vacher, L., Vaillon, L., Valageas, P., Valdes, I., Valentijn, E. A., Valenziano, L., Valieri, C., Valiviita, J., Broeck, M. Van den, Vassallo, T., Vavrek, R., Vega-Ferrero, J., Venemans, B., Venhola, A., Ventura, S., Kleijn, G. Verdoes, Vergani, D., Verma, A., Vernizzi, F., Veropalumbo, A., Verza, G., Vescovi, C., Vibert, D., Viel, M., Vielzeuf, P., Viglione, C., Viitanen, A., Villaescusa-Navarro, F., Vinciguerra, S., Visticot, F., Voggel, K., von Wietersheim-Kramsta, M., Vriend, W. J., Wachter, S., Walmsley, M., Walth, G., Walton, D. M., Walton, N. A., Wander, M., Wang, L., Wang, Y., Weaver, J. R., Weller, J., Wetzstein, M., Whalen, D. J., Whittam, I. H., Widmer, A., Wiesmann, M., Wilde, J., Williams, O. R., Winther, H. -A., Wittje, A., Wong, J. H. W., Wright, A. H., Yankelevich, V., Yeung, H. W., Yoon, M., Youles, S., Yung, L. Y. A., Zacchei, A., Zalesky, L., Zamorani, G., Vitorelli, A. Zamorano, Marc, M. Zanoni, Zennaro, M., Zerbi, F. M., Zinchenko, I. A., Zoubian, J., Zucca, E., and Zumalacarregui, M.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics, Astrophysics - Astrophysics of Galaxies, Astrophysics - Instrumentation and Methods for Astrophysics
Abstract: The current standard model of cosmology successfully describes a variety of measurements, but the nature of its main ingredients, dark matter and dark energy, remains unknown. Euclid is a medium-class mission in the Cosmic Vision 2015-2025 programme of the European Space Agency (ESA) that will provide high-resolution optical imaging, as well as near-infrared imaging and spectroscopy, over about 14,000 deg^2 of extragalactic sky. In addition to accurate weak lensing and clustering measurements that probe structure formation over half of the age of the Universe, its primary probes for cosmology, these exquisite data will enable a wide range of science. This paper provides a high-level overview of the mission, summarising the survey characteristics, the various data-processing steps, and data products. We also highlight the main science objectives and expected performance., Comment: Accepted for publication in the A&A special issue`Euclid on Sky'
Published: 2024

7. DESI 2024 VI: Cosmological Constraints from the Measurements of Baryon Acoustic Oscillations

Author: DESI Collaboration, Adame, A. G., Aguilar, J., Ahlen, S., Alam, S., Alexander, D. M., Alvarez, M., Alves, O., Anand, A., Andrade, U., Armengaud, E., Avila, S., Aviles, A., Awan, H., Bahr-Kalus, B., Bailey, S., Baltay, C., Bault, A., Behera, J., BenZvi, S., Bera, A., Beutler, F., Bianchi, D., Blake, C., Blum, R., Brieden, S., Brodzeller, A., Brooks, D., Buckley-Geer, E., Burtin, E., Calderon, R., Canning, R., Rosell, A. Carnero, Cereskaite, R., Cervantes-Cota, J. L., Chabanier, S., Chaussidon, E., Chaves-Montero, J., Chen, S., Chen, X., Claybaugh, T., Cole, S., Cuceu, A., Davis, T. M., Dawson, K., de la Macorra, A., de Mattia, A., Deiosso, N., Dey, A., Dey, B., Ding, Z., Doel, P., Edelstein, J., Eftekharzadeh, S., Eisenstein, D. J., Elliott, A., Fagrelius, P., Fanning, K., Ferraro, S., Ereza, J., Findlay, N., Flaugher, B., Font-Ribera, A., Forero-Sánchez, D., Forero-Romero, J. E., Frenk, C. S., Garcia-Quintero, C., Gaztañaga, E., Gil-Marín, H., Gontcho, S. Gontcho A, Gonzalez-Morales, A. X., Gonzalez-Perez, V., Gordon, C., Green, D., Gruen, D., Gsponer, R., Gutierrez, G., Guy, J., Hadzhiyska, B., Hahn, C., Hanif, M. M. S, Herrera-Alcantar, H. K., Honscheid, K., Howlett, C., Huterer, D., Iršič, V., Ishak, M., Juneau, S., Karaçaylı, N. G., Kehoe, R., Kent, S., Kirkby, D., Kremin, A., Krolewski, A., Lai, Y., Lan, T. -W., Landriau, M., Lang, D., Lasker, J., Goff, J. M. Le, Guillou, L. Le, Leauthaud, A., Levi, M. E., Li, T. S., Linder, E., Lodha, K., Magneville, C., Manera, M., Margala, D., Martini, P., Maus, M., McDonald, P., Medina-Varela, L., Meisner, A., Mena-Fernández, J., Miquel, R., Moon, J., Moore, S., Moustakas, J., Mudur, N., Mueller, E., Muñoz-Gutiérrez, A., Myers, A. D., Nadathur, S., Napolitano, L., Neveux, R., Newman, J. A., Nguyen, N. M., Nie, J., Niz, G., Noriega, H. E., Padmanabhan, N., Paillas, E., Palanque-Delabrouille, N., Pan, J., Penmetsa, S., Percival, W. J., Pieri, M. M., Pinon, M., Poppett, C., Porredon, A., Prada, F., Pérez-Fernández, A., Pérez-Ràfols, I., Rabinowitz, D., Raichoor, A., Ramírez-Pérez, C., Ramirez-Solano, S., Ravoux, C., Rashkovetskyi, M., Rezaie, M., Rich, J., Rocher, A., Rockosi, C., Roe, N. A., Rosado-Marin, A., Ross, A. J., Rossi, G., Ruggeri, R., Ruhlmann-Kleider, V., Samushia, L., Sanchez, E., Saulder, C., Schlafly, E. F., Schlegel, D., Schubnell, M., Seo, H., Shafieloo, A., Sharples, R., Silber, J., Slosar, A., Smith, A., Sprayberry, D., Tan, T., Tarlé, G., Taylor, P., Trusov, S., Ureña-López, L. A., Vaisakh, R., Valcin, D., Valdes, F., Vargas-Magaña, M., Verde, L., Walther, M., Wang, B., Wang, M. S., Weaver, B. A., Weaverdyck, N., Wechsler, R. H., Weinberg, D. H., White, M., Yu, J., Yu, Y., Yuan, S., Yèche, C., Zaborowski, E. A., Zarrouk, P., Zhang, H., Zhao, C., Zhao, R., Zhou, R., Zhuang, T., and Zou, H.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: We present cosmological results from the measurement of baryon acoustic oscillations (BAO) in galaxy, quasar and Lyman-$\alpha$ forest tracers from the first year of observations from the Dark Energy Spectroscopic Instrument (DESI), to be released in the DESI Data Release 1. DESI BAO provide robust measurements of the transverse comoving distance and Hubble rate, or their combination, relative to the sound horizon, in seven redshift bins from over 6 million extragalactic objects in the redshift range $0.1-1$ and $w_a<0$. This preference is 2.6$\sigma$ for the DESI+CMB combination, and persists or grows when SN~Ia are added in, giving results discrepant with the $\Lambda$CDM model at the $2.5\sigma$, $3.5\sigma$ or $3.9\sigma$ levels for the addition of Pantheon+, Union3, or DES-SN5YR datasets respectively. For the flat $\Lambda$CDM model with the sum of neutrino mass $\sum m_\nu$ free, combining the DESI and CMB data yields an upper limit $\sum m_\nu < 0.072$ $(0.113)$ eV at 95% confidence for a $\sum m_\nu>0$ $(\sum m_\nu>0.059)$ eV prior. These neutrino-mass constraints are substantially relaxed in models beyond $\Lambda$CDM. [Abridged.], Comment: This DESI Collaboration Key Publication is part of the 2024 publication series using the first year of observations (see https://data.desi.lbl.gov/doc/papers). 68 pages, 15 figures. Version accepted for publication in JCAP
Published: 2024

8. DESI 2024 IV: Baryon Acoustic Oscillations from the Lyman Alpha Forest

Author: DESI Collaboration, Adame, A. G., Aguilar, J., Ahlen, S., Alam, S., Alexander, D. M., Alvarez, M., Alves, O., Anand, A., Andrade, U., Armengaud, E., Avila, S., Aviles, A., Awan, H., Bailey, S., Baltay, C., Bault, A., Bautista, J., Behera, J., BenZvi, S., Beutler, F., Bianchi, D., Blake, C., Blum, R., Brieden, S., Brodzeller, A., Brooks, D., Buckley-Geer, E., Burtin, E., Calderon, R., Canning, R., Rosell, A. Carnero, Cereskaite, R., Cervantes-Cota, J. L., Chabanier, S., Chaussidon, E., Chaves-Montero, J., Chen, S., Chen, X., Claybaugh, T., Cole, S., Cuceu, A., Davis, T. M., Dawson, K., de la Cruz, R., de la Macorra, A., de Mattia, A., Deiosso, N., Dey, A., Dey, B., Ding, J., Ding, Z., Doel, P., Edelstein, J., Eftekharzadeh, S., Eisenstein, D. J., Elliott, A., Fagrelius, P., Fanning, K., Ferraro, S., Ereza, J., Findlay, N., Flaugher, B., Font-Ribera, A., Forero-Sánchez, D., Forero-Romero, J. E., Garcia-Quintero, C., Gaztañaga, E., Gil-Marín, H., Gontcho, S. Gontcho A, Gonzalez-Morales, A. X., Gonzalez-Perez, V., Gordon, C., Green, D., Gruen, D., Gsponer, R., Gutierrez, G., Guy, J., Hadzhiyska, B., Hahn, C., Hanif, M. M. S, Herrera-Alcantar, H. K., Honscheid, K., Howlett, C., Huterer, D., Iršič, V., Ishak, M., Juneau, S., Karaçayli, N. G., Kehoe, R., Kent, S., Kirkby, D., Kremin, A., Krolewski, A., Lai, Y., Lan, T. -W., Landriau, M., Lang, D., Lasker, J., Goff, J. M. Le, Guillou, L. Le, Leauthaud, A., Levi, M. E., Li, T. S., Linder, E., Lodha, K., Magneville, C., Manera, M., Margala, D., Martini, P., Maus, M., McDonald, P., Medina-Varela, L., Meisner, A., Mena-Fernández, J., Miquel, R., Moon, J., Moore, S., Moustakas, J., Mueller, E., Muñoz-Gutiérrez, A., Myers, A. D., Nadathur, S., Napolitano, L., Neveux, R., Newman, J. A., Nguyen, N. M., Nie, J., Niz, G., Noriega, H. E., Padmanabhan, N., Paillas, E., Palanque-Delabrouille, N., Pan, J., Penmetsa, S., Percival, W. J., Pieri, M. M., Pinon, M., Poppett, C., Porredon, A., Prada, F., Pérez-Fernández, A., Pérez-Ràfols, I., Rabinowitz, D., Raichoor, A., Ramírez-Pérez, C., Ramirez-Solano, S., Rashkovetskyi, M., Ravoux, C., Rezaie, M., Rich, J., Rocher, A., Rockosi, C., Roe, N. A., Rosado-Marin, A., Ross, A. J., Rossi, G., Ruggeri, R., Ruhlmann-Kleider, V., Samushia, L., Sanchez, E., Saulder, C., Schlafly, E. F., Schlegel, D., Schubnell, M., Seo, H., Sharples, R., Silber, J., Sinigaglia, F., Slosar, A., Smith, A., Sprayberry, D., Tan, T., Tarlé, G., Trusov, S., Vaisakh, R., Valcin, D., Valdes, F., Vargas-Magaña, M., Verde, L., Walther, M., Wang, B., Wang, M. S., Weaver, B. A., Weaverdyck, N., Wechsler, R. H., Weinberg, D. H., White, M., Yu, J., Yu, Y., Yuan, S., Yèche, C., Zaborowski, E. A., Zarrouk, P., Zhang, H., Zhao, C., Zhao, R., Zhou, R., and Zou, H.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: We present the measurement of Baryon Acoustic Oscillations (BAO) from the Lyman-$\alpha$ (Ly$\alpha$) forest of high-redshift quasars with the first-year dataset of the Dark Energy Spectroscopic Instrument (DESI). Our analysis uses over $420\,000$ Ly$\alpha$ forest spectra and their correlation with the spatial distribution of more than $700\,000$ quasars. An essential facet of this work is the development of a new analysis methodology on a blinded dataset. We conducted rigorous tests using synthetic data to ensure the reliability of our methodology and findings before unblinding. Additionally, we conducted multiple data splits to assess the consistency of the results and scrutinized various analysis approaches to confirm their robustness. For a given value of the sound horizon ($r_d$), we measure the expansion at $z_{\rm eff}=2.33$ with 2\% precision, $H(z_{\rm eff}) = (239.2 \pm 4.8) (147.09~{\rm Mpc} /r_d)$ km/s/Mpc. Similarly, we present a 2.4\% measurement of the transverse comoving distance to the same redshift, $D_M(z_{\rm eff}) = (5.84 \pm 0.14) (r_d/147.09~{\rm Mpc})$ Gpc. Together with other DESI BAO measurements at lower redshifts, these results are used in a companion paper to constrain cosmological parameters., Comment: This DESI Collaboration Key Publication is part of the 2024 publication series using the first year of observations (see https://data.desi.lbl.gov/doc/papers). Minor changes in v4, version accepted for publication in JCAP
Published: 2024

9. DESI 2024 III: Baryon Acoustic Oscillations from Galaxies and Quasars

Author: DESI Collaboration, Adame, A. G., Aguilar, J., Ahlen, S., Alam, S., Alexander, D. M., Alvarez, M., Alves, O., Anand, A., Andrade, U., Armengaud, E., Avila, S., Aviles, A., Awan, H., Bailey, S., Baltay, C., Bault, A., Behera, J., BenZvi, S., Beutler, F., Bianchi, D., Blake, C., Blum, R., Brieden, S., Brodzeller, A., Brooks, D., Buckley-Geer, E., Burtin, E., Calderon, R., Canning, R., Rosell, A. Carnero, Cereskaite, R., Cervantes-Cota, J. L., Chabanier, S., Chaussidon, E., Chaves-Montero, J., Chen, S., Chen, X., Claybaugh, T., Cole, S., Cuceu, A., Davis, T. M., Dawson, K., de la Macorra, A., de Mattia, A., Deiosso, N., Dey, A., Dey, B., Ding, Z., Doel, P., Edelstein, J., Eftekharzadeh, S., Eisenstein, D. J., Elliott, A., Fagrelius, P., Fanning, K., Ferraro, S., Ereza, J., Findlay, N., Flaugher, B., Font-Ribera, A., Forero-Sánchez, D., Forero-Romero, J. E., Garcia-Quintero, C., Gaztañaga, E., Gil-Marín, H., Gontcho, S. Gontcho A, Gonzalez-Morales, A. X., Gonzalez-Perez, V., Gordon, C., Green, D., Gruen, D., Gsponer, R., Gutierrez, G., Guy, J., Hadzhiyska, B., Hahn, C., Hanif, M. M. S, Herrera-Alcantar, H. K., Honscheid, K., Howlett, C., Huterer, D., Iršič, V., Ishak, M., Juneau, S., Karaçaylı, N. G., Kehoe, R., Kent, S., Kirkby, D., Kremin, A., Krolewski, A., Lai, Y., Lan, T. -W., Landriau, M., Lang, D., Lasker, J., Goff, J. M. Le, Guillou, L. Le, Leauthaud, A., Levi, M. E., Li, T. S., Linder, E., Lodha, K., Magneville, C., Manera, M., Margala, D., Martini, P., Maus, M., McDonald, P., Medina-Varela, L., Meisner, A., Mena-Fernández, J., Miquel, R., Moon, J., Moore, S., Moustakas, J., Mudur, N., Mueller, E., Muñoz-Gutiérrez, A., Myers, A. D., Nadathur, S., Napolitano, L., Neveux, R., Newman, J. A., Nguyen, N. M., Nie, J., Niz, G., Noriega, H. E., Padmanabhan, N., Paillas, E., Palanque-Delabrouille, N., Pan, J., Penmetsa, S., Percival, W. J., Pieri, M., Pinon, M., Poppett, C., Porredon, A., Prada, F., Pérez-Fernández, A., Pérez-Ràfols, I., Rabinowitz, D., Raichoor, A., Ramírez-Pérez, C., Ramirez-Solano, S., Rashkovetskyi, M., Rezaie, M., Rich, J., Rocher, A., Rockosi, C., Roe, N. A., Rosado-Marin, A., Ross, A. J., Rossi, G., Ruggeri, R., Ruhlmann-Kleider, V., Samushia, L., Sanchez, E., Saulder, C., Schlafly, E. F., Schlegel, D., Schubnell, M., Seo, H., Sharples, R., Silber, J., Slosar, A., Smith, A., Sprayberry, D., Swanson, J., Tan, T., Tarlé, G., Trusov, S., Vaisakh, R., Valcin, D., Valdes, F., Vargas-Magaña, M., Verde, L., Walther, M., Wang, B., Wang, M. S., Weaver, B. A., Weaverdyck, N., Wechsler, R. H., Weinberg, D. H., White, M., Yu, J., Yu, Y., Yuan, S., Yèche, C., Zaborowski, E. A., Zarrouk, P., Zhang, H., Zhao, C., Zhao, R., Zhou, R., and Zou, H.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: We present the DESI 2024 galaxy and quasar baryon acoustic oscillations (BAO) measurements using over 5.7 million unique galaxy and quasar redshifts in the range 0.1
Published: 2024

10. A comparison of shrinkage estimators of the cosmological precision matrix

Author: Looijmans, Marnix J., Wang, Mike Shengbo, and Beutler, Florian
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics, Astrophysics - Instrumentation and Methods for Astrophysics
Abstract: The determination of the covariance matrix and its inverse, the precision matrix, is critical in the statistical analysis of cosmological measurements. The covariance matrix is typically estimated with a limited number of simulations at great computational cost before inversion into the precision matrix; therefore, it can be ill-conditioned and overly noisy when the sample size $n$ used for estimation is not much larger than the data vector dimension. In this work, we consider a class of methods known as shrinkage estimation for the precision matrix, which combines an empirical estimate with a target that is either analytical or stochastic. These methods include linear and non-linear shrinkage applied to the covariance matrix (the latter represented by the so-called NERCOME estimator), and the direct linear shrinkage estimation of the precision matrix which we introduce in a cosmological setting. Using Bayesian parameter inference as well as metrics like matrix loss functions and the eigenvalue spectrum, we compare their performance against the standard sample estimator with varying sample size $n$. We have found the shrinkage estimators to significantly improve the posterior distribution at low $n$, especially for the linear shrinkage estimators either inverted from the covariance matrix or applied directly to the precision matrix, with an empirical target constructed from the sample estimate. Our results should be particularly relevant to the analyses of Stage-IV spectroscopic galaxy surveys such as the Dark Energy Spectroscopic Instrument (DESI) and Euclid, whose statistical power can be limited by the computational cost of obtaining an accurate precision matrix estimate., Comment: 12 pages, 10 figures, for submission to MNRAS
Published: 2024

11. Active Axial Motion Compensation in Multiphoton-Excited Fluorescence Microscopy

Author: Kunisch, Manuel, Beutler, Sascha, Pilger, Christian, Kiefer, Friedemann, Huser, Thomas, and Wirth, Benedikt
Subjects: Physics - Optics, Electrical Engineering and Systems Science - Image and Video Processing, Physics - Biological Physics
Abstract: In living organisms, the natural motion caused by the heartbeat, breathing, or muscle movements leads to the deformation of tissue caused by translation and stretching of the tissue structure. This effect results in the displacement or deformation of the plane of observation for intravital microscopy and causes motion-induced aberrations of the resulting image data. This, in turn, places severe limitations on the time during which specific events can be observed in intravital imaging experiments. These limitations can be overcome if the tissue motion can be compensated such that the plane of observation remains steady. We have developed a mathematical shape space model that can predict the periodic motion of a cylindrical tissue phantom resembling blood vessels. This model is then used to rapidly calculate the future position of the plane of observation of a confocal multiphoton fluorescence microscope. The focal plane is continuously adjusted to the calculated position with a piezo-actuated objective lens holder. We demonstrate active motion compensation for non-harmonic axial displacements of the vessel phantom with a field of view up to 400 $\mu$m $\times$ 400 $\mu$m, vertical amplitudes of more than 100 $\mu$m, and at a rate of 0.5 Hz., Comment: 16 pages, 6 figures
Published: 2024

12. SUNBIRD: A simulation-based model for full-shape density-split clustering

Author: Cuesta-Lazaro, Carolina, Paillas, Enrique, Yuan, Sihan, Cai, Yan-Chuan, Nadathur, Seshadri, Percival, Will J., Beutler, Florian, de Mattia, Arnaud, Eisenstein, Daniel, Forero-Sanchez, Daniel, Padilla, Nelson, Pinon, Mathilde, Ruhlmann-Kleider, Vanina, Sánchez, Ariel G., Valogiannis, Georgios, and Zarrouk, Pauline
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: Combining galaxy clustering information from regions of different environmental densities can help break cosmological parameter degeneracies and access non-Gaussian information from the density field that is not readily captured by the standard two-point correlation function (2PCF) analyses. However, modelling these density-dependent statistics down to the non-linear regime has so far remained challenging. We present a simulation-based model that is able to capture the cosmological dependence of the full shape of the density-split clustering (DSC) statistics down to intra-halo scales. Our models are based on neural-network emulators that are trained on high-fidelity mock galaxy catalogues within an extended-$\Lambda$CDM framework, incorporating the effects of redshift-space, Alcock-Paczynski distortions and models of the halo-galaxy connection. Our models reach sub-percent level accuracy down to $1\,h^{-1}{\rm Mpc}$ and are robust against different choices of galaxy-halo connection modelling. When combined with the galaxy 2PCF, DSC can tighten the constraints on $\omega_{\rm cdm}$, $\sigma_8$, and $n_s$ by factors of 2.9, 1.9, and 2.1, respectively, compared to a 2PCF-only analysis. DSC additionally puts strong constraints on environment-based assembly bias parameters. Our code is made publicly available on Github., Comment: Submitted to MNRAS. Source code to generate the figures available in the captions. Updated to add missing references
Published: 2023

13. Cosmological constraints from density-split clustering in the BOSS CMASS galaxy sample

Author: Paillas, Enrique, Cuesta-Lazaro, Carolina, Percival, Will J., Nadathur, Seshadri, Cai, Yan-Chuan, Yuan, Sihan, Beutler, Florian, de Mattia, Arnaud, Eisenstein, Daniel, Forero-Sanchez, Daniel, Padilla, Nelson, Pinon, Mathilde, Ruhlmann-Kleider, Vanina, Sánchez, Ariel G., Valogiannis, Georgios, and Zarrouk, Pauline
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: We present a clustering analysis of the BOSS DR12 CMASS galaxy sample, combining measurements of the galaxy two-point correlation function and density-split clustering down to a scale of $1\,h^{-1}{\rm Mpc}$. Our theoretical framework is based on emulators trained on high-fidelity mock galaxy catalogues that forward model the cosmological dependence of the clustering statistics within an extended-$\Lambda$CDM framework, including redshift-space and Alcock-Paczynski distortions. Our base-$\Lambda$CDM analysis finds $\omega_{\rm cdm} = 0.1201\pm 0.0022$, $\sigma_8 = 0.792\pm 0.034$, and $n_s = 0.970\pm 0.018$, corresponding to $f\sigma_8 = 0.462\pm 0.020$ at $z \approx 0.525$, which is in agreement with Planck 2018 predictions and various clustering studies in the literature. We test single-parameter extensions to base-$\Lambda$CDM, varying the running of the spectral index, the dark energy equation of state, and the density of massless relic neutrinos, finding no compelling evidence for deviations from the base model. We model the galaxy-halo connection using a halo occupation distribution framework, finding signatures of environment-based assembly bias in the data. We validate our pipeline against mock catalogues that match the clustering and selection properties of CMASS, showing that we can recover unbiased cosmological constraints even with a volume 84 times larger than the one used in this study., Comment: Submitted to MNRAS. Source code to generate the figures available in the captions. Updated to add missing references and fix legend of Fig. 6
Published: 2023

14. Analysis of Unified Galaxy Power Spectrum Multipole Measurements

Author: Donald-McCann, Jamie, Gsponer, Rafaela, Zhao, Ruiyang, Koyama, Kazuya, and Beutler, Florian
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: We present a series of full-shape analyses of galaxy power spectrum multipole measurements from the 6dFGS, BOSS, and eBOSS galaxy surveys. We use an emulated effective field theory of large-scale structure (EFTofLSS) model to conduct these analyses. We exploit the accelerated prediction speed of the neural-network-based emulator to explore various analysis setups for our cosmological inference pipeline. Via a set of mock full-shape analyses of synthetic power spectrum multipoles, designed to approximate measurements from the surveys above, we demonstrate that the use of alternative priors on nuisance parameters and restricted model complexity reduces many of the biases previously observed in marginalised cosmological constraints coming from EFTofLSS analyses. The alternative priors take the form of a Jeffreys prior; a non-informative prior that can mitigate against biases induced by marginalising over poorly constrained nuisance parameters. When performing a joint analysis of all synthetic multipoles, we see an improvement in the level of agreement between the marginalised $\ln{\left(10^{10}A_s\right)}$ constraints and the truth; from $\sim2.0\sigma$ to $\sim0.42\sigma$. Using our pipeline to analyse the measured multipoles, we find an improvement in the level of agreement with cosmic microwave background (CMB) results; from $\sim2.4\sigma$ to $\sim0.5\sigma$. Therefore, we conclude that the spectroscopic galaxy survey datasets listed above are consistent with constraints obtained from the CMB., Comment: 22 pages, 17 figures, 8 tables. MNRAS accepted version
Published: 2023
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15. Local primordial non-Gaussianity from the large-scale clustering of photometric DESI luminous red galaxies

Author: Rezaie, Mehdi, Ross, Ashley J., Seo, Hee-Jong, Kong, Hui, Porredon, Anna, Samushia, Lado, Chaussidon, Edmond, Krolewski, Alex, de Mattia, Arnaud, Beutler, Florian, Aguilar, Jessica Nicole, Ahlen, Steven, Alam, Shadab, Avila, Santiago, Bahr-Kalus, Benedict, Bermejo-Climent, Jose, Brooks, David, Claybaugh, Todd, Cole, Shaun, Dawson, Kyle, de la Macorra, Axel, Doel, Peter, Font-Ribera, Andreu, Forero-Romero, Jaime E., Gontcho, Satya Gontcho A, Guy, Julien, Honscheid, Klaus, Huterer, Dragan, Kisner, Theodore, Landriau, Martin, Levi, Michael, Manera, Marc, Meisner, Aaron, Miquel, Ramon, Mueller, Eva-Maria, Myers, Adam, Newman, Jeffrey A., Nie, Jundan, Palanque-Delabrouille, Nathalie, Percival, Will, Poppett, Claire, Rossi, Graziano, Sanchez, Eusebio, Schubnell, Michael, Tarlé, Gregory, Weaver, Benjamin Alan, Yèche, Christophe, Zhou, Zhimin, and Zou, Hu
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics, Computer Science - Machine Learning, Physics - Computational Physics, Physics - Data Analysis, Statistics and Probability
Abstract: We use angular clustering of luminous red galaxies from the Dark Energy Spectroscopic Instrument (DESI) imaging surveys to constrain the local primordial non-Gaussianity parameter $\fnl$. Our sample comprises over 12 million targets, covering 14,000 square degrees of the sky, with redshifts in the range $0.2< z < 1.35$. We identify Galactic extinction, survey depth, and astronomical seeing as the primary sources of systematic error, and employ linear regression and artificial neural networks to alleviate non-cosmological excess clustering on large scales. Our methods are tested against simulations with and without $\fnl$ and systematics, showing superior performance of the neural network treatment. The neural network with a set of nine imaging property maps passes our systematic null test criteria, and is chosen as the fiducial treatment. Assuming the universality relation, we find $\fnl = 34^{+24(+50)}_{-44(-73)}$ at 68\%(95\%) confidence. We apply a series of robustness tests (e.g., cuts on imaging, declination, or scales used) that show consistency in the obtained constraints. We study how the regression method biases the measured angular power-spectrum and degrades the $\fnl$ constraining power. The use of the nine maps more than doubles the uncertainty compared to using only the three primary maps in the regression. Our results thus motivate the development of more efficient methods that avoid over-correction, protect large-scale clustering information, and preserve constraining power. Additionally, our results encourage further studies of $\fnl$ with DESI spectroscopic samples, where the inclusion of 3D clustering modes should help separate imaging systematics and lessen the degradation in the $\fnl$ uncertainty., Comment: 21 pages, 17 figures, 7 tables (Appendix excluded). Published in MNRAS
Published: 2023
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16. The DESI One-Percent Survey: Modelling the clustering and halo occupation of all four DESI tracers with Uchuu

Author: Prada, F., Ereza, J., Smith, A., Lasker, J., Vaisakh, R., Kehoe, R., Dong-Páez, C. A., Siudek, M., Wang, M. S., Alam, S., Beutler, F., Bianchi, D., Cole, S., Dey, B., Kirkby, D., Norberg, P., Aguilar, J., Ahlen, S., Brooks, D., Claybaugh, T., Dawson, K., de la Macorra, A., Fanning, K., Forero-Romero, J. E., Gontcho, S. Gontcho A, Hahn, C., Honscheid, K., Ishak, M., Kisner, T., Landriau, M., Manera, M., Meisner, A., Miquel, R., Moustakas, J., Mueller, E., Nie, J., Percival, W. J., Poppett, C., Rezaie, M., Rossi, G., Sanchez, E., Schubnell, M., Tarlé, G., Vargas-Magaña, M., Weaver, B. A., Yuan, S., and Zhou, Z.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: We present results from a set of mock lightcones for the DESI One-Percent Survey, created from the Uchuu simulation. This This 8 (Gpc/h)^3 N-body simulation comprises 2.1 trillion particles and provides high-resolution dark matter (sub)haloes in the framework of the Planck base-LCDM cosmology. Employing the subhalo abundance matching (SHAM) technique, we populate the Uchuu (sub)haloes with all four DESI tracers (BGS, LRG, ELG and QSO) to z = 2.1. Our method accounts for redshift evolution as well as the clustering dependence on luminosity and stellar mass. The two-point clustering statistics of the DESI One-Percent Survey generally agree with predictions from Uchuu across scales ranging from 0.3 Mpc/h to 100 Mpc/h for the BGS and across scales ranging from 5 Mpc/h to 100 Mpc/h for the other tracers. We observe some differences in clustering statistics that can be attributed to incompleteness of the massive end of the stellar mass function of LRGs, our use of a simplified galaxy-halo connection model for ELGs and QSOs, and cosmic variance. We find that at the high precision of Uchuu, the shape of the halo occupation distribution (HOD) of the BGS and LRG samples are not fully captured by the standard 5-parameter HOD model. However, the ELGs and QSOs show agreement with an adopted Gaussian distribution for central haloes with a power law for satellites. We observe fair agreement in the large-scale bias measurements between data and mock samples, although the BGS data exhibits smaller bias values, likely due to cosmic variance. The bias dependence on absolute magnitude, stellar mass and redshift aligns with that of previous surveys. These results provide DESI with tools to generate high-fidelity lightcones for the remainder of the survey and enhance our understanding of the galaxy-halo connection., Comment: 24 pages, 16 figures, 5 tables, accepted for publication in A&A. The Uchuu-DESI lightcones are available at https://data.desi.lbl.gov
Published: 2023

17. The Early Data Release of the Dark Energy Spectroscopic Instrument

Author: DESI Collaboration, Adame, A. G., Aguilar, J., Ahlen, S., Alam, S., Aldering, G., Alexander, D. M., Alfarsy, R., Prieto, C. Allende, Alvarez, M., Alves, O., Anand, A., Andrade-Oliveira, F., Armengaud, E., Asorey, J., Avila, S., Aviles, A., Bailey, S., Balaguera-Antolínez, A., Ballester, O., Baltay, C., Bault, A., Bautista, J., Behera, J., Beltran, S. F., BenZvi, S., Silva, L. Beraldo e, Bermejo-Climent, J. R., Berti, A., Besuner, R., Beutler, F., Bianchi, D., Blake, C., Blum, R., Bolton, A. S., Brieden, S., Brodzeller, A., Brooks, D., Brown, Z., Buckley-Geer, E., Burtin, E., Cabayol-Garcia, L., Cai, Z., Canning, R., Cardiel-Sas, L., Rosell, A. Carnero, Castander, F. J., Cervantes-Cota, J. L., Chabanier, S., Chaussidon, E., Chaves-Montero, J., Chen, S., Chen, X., Chuang, C., Claybaugh, T., Cole, S., Cooper, A. P., Cuceu, A., Davis, T. M., Dawson, K., de Belsunce, R., de la Cruz, R., de la Macorra, A., Della Costa, J., de Mattia, A., Demina, R., Demirbozan, U., DeRose, J., Dey, A., Dey, B., Dhungana, G., Ding, J., Ding, Z., Doel, P., Doshi, R., Douglass, K., Edge, A., Eftekharzadeh, S., Eisenstein, D. J., Elliott, A., Escoffier, S., Fagrelius, P., Fan, X., Fanning, K., Fawcett, V. A., Ferraro, S., Ereza, J., Flaugher, B., Font-Ribera, A., Forero-Sánchez, D., Forero-Romero, J. E., Frenk, C. S., Gänsicke, B. T., García, L. Á., García-Bellido, J., Garcia-Quintero, C., Garrison, L. H., Gil-Marín, H., Golden-Marx, J., Gontcho, S. Gontcho A, Gonzalez-Morales, A. X., Gonzalez-Perez, V., Gordon, C., Graur, O., Green, D., Gruen, D., Guy, J., Hadzhiyska, B., Hahn, C., Han, J. J., Hanif, M. M. S, Herrera-Alcantar, H. K., Honscheid, K., Hou, J., Howlett, C., Huterer, D., Iršič, V., Ishak, M., Jacques, A., Jana, A., Jiang, L., Jimenez, J., Jing, Y. P., Joudaki, S., Jullo, E., Juneau, S., Kizhuprakkat, N., Karaçaylı, N. G., Karim, T., Kehoe, R., Kent, S., Khederlarian, A., Kim, S., Kirkby, D., Kisner, T., Kitaura, F., Kneib, J., Koposov, S. E., Kovács, A., Kremin, A., Krolewski, A., L'Huillier, B., Lahav, O., Lambert, A., Lamman, C., Lan, T. -W., Landriau, M., Lang, D., Lange, J. U., Lasker, J., Leauthaud, A., Guillou, L. Le, Levi, M. E., Li, T. S., Linder, E., Lyons, A., Magneville, C., Manera, M., Manser, C. J., Margala, D., Martini, P., McDonald, P., Medina, G. E., Medina-Varela, L., Meisner, A., Mena-Fernández, J., Meneses-Rizo, J., Mezcua, M., Miquel, R., Montero-Camacho, P., Moon, J., Moore, S., Moustakas, J., Mueller, E., Mundet, J., Muñoz-Gutiérrez, A., Myers, A. D., Nadathur, S., Napolitano, L., Neveux, R., Newman, J. A., Nie, J., Nikutta, R., Niz, G., Norberg, P., Noriega, H. E., Paillas, E., Palanque-Delabrouille, N., Palmese, A., Zhiwei, P., Parkinson, D., Penmetsa, S., Percival, W. J., Pérez-Fernández, A., Pérez-Ràfols, I., Pieri, M., Poppett, C., Porredon, A., Pothier, S., Prada, F., Pucha, R., Raichoor, A., Ramírez-Pérez, C., Ramirez-Solano, S., Rashkovetskyi, M., Ravoux, C., Rocher, A., Rockosi, C., Ross, A. J., Rossi, G., Ruggeri, R., Ruhlmann-Kleider, V., Sabiu, C. G., Said, K., Saintonge, A., Samushia, L., Sanchez, E., Saulder, C., Schaan, E., Schlafly, E. F., Schlegel, D., Scholte, D., Schubnell, M., Seo, H., Shafieloo, A., Sharples, R., Sheu, W., Silber, J., Sinigaglia, F., Siudek, M., Slepian, Z., Smith, A., Soumagnac, M. T., Sprayberry, D., Stephey, L., Suárez-Pérez, J., Sun, Z., Tan, T., Tarlé, G., Tojeiro, R., Ureña-López, L. A., Vaisakh, R., Valcin, D., Valdes, F., Valluri, M., Vargas-Magaña, M., Variu, A., Verde, L., Walther, M., Wang, B., Wang, M. S., Weaver, B. A., Weaverdyck, N., Wechsler, R. H., White, M., Xie, Y., Yang, J., Yèche, C., Yu, J., Yuan, S., Zhang, H., Zhang, Z., Zhao, C., Zheng, Z., Zhou, R., Zhou, Z., Zou, H., Zou, S., and Zu, Y.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: The Dark Energy Spectroscopic Instrument (DESI) completed its five-month Survey Validation in May 2021. Spectra of stellar and extragalactic targets from Survey Validation constitute the first major data sample from the DESI survey. This paper describes the public release of those spectra, the catalogs of derived properties, and the intermediate data products. In total, the public release includes good-quality spectral information from 466,447 objects targeted as part of the Milky Way Survey, 428,758 as part of the Bright Galaxy Survey, 227,318 as part of the Luminous Red Galaxy sample, 437,664 as part of the Emission Line Galaxy sample, and 76,079 as part of the Quasar sample. In addition, the release includes spectral information from 137,148 objects that expand the scope beyond the primary samples as part of a series of secondary programs. Here, we describe the spectral data, data quality, data products, Large-Scale Structure science catalogs, access to the data, and references that provide relevant background to using these spectra., Comment: 43 pages, 7 figures, 17 tables, accepted for publication in the Astronomical Journal
Published: 2023
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18. Validation of the Scientific Program for the Dark Energy Spectroscopic Instrument

Author: DESI Collaboration, Adame, A. G., Aguilar, J., Ahlen, S., Alam, S., Aldering, G., Alexander, D. M., Alfarsy, R., Prieto, C. Allende, Alvarez, M., Alves, O., Anand, A., Andrade-Oliveira, F., Armengaud, E., Asorey, J., Avila, S., Aviles, A., Bailey, S., Balaguera-Antolínez, A., Ballester, O., Baltay, C., Bault, A., Bautista, J., Behera, J., Beltran, S. F., BenZvi, S., Silva, L. Beraldo e, Bermejo-Climent, J. R., Berti, A., Besuner, R., Beutler, F., Bianchi, D., Blake, C., Blum, R., Bolton, A. S., Brieden, S., Brodzeller, A., Brooks, D., Brown, Z., Buckley-Geer, E., Burtin, E., Cabayol-Garcia, L., Cai, Z., Canning, R., Cardiel-Sas, L., Rosell, A. Carnero, Castander, F. J., Cervantes-Cota, J. L., Chabanier, S., Chaussidon, E., Chaves-Montero, J., Chen, S., Chuang, C., Claybaugh, T., Cole, S., Cooper, A. P., Cuceu, A., Davis, T. M., Dawson, K., de Belsunce, R., de la Cruz, R., de la Macorra, A., de Mattia, A., Demina, R., Demirbozan, U., DeRose, J., Dey, A., Dey, B., Dhungana, G., Ding, J., Ding, Z., Doel, P., Doshi, R., Douglass, K., Edge, A., Eftekharzadeh, S., Eisenstein, D. J., Elliott, A., Escoffier, S., Fagrelius, P., Fan, X., Fanning, K., Fawcett, V. A., Ferraro, S., Ereza, J., Flaugher, B., Font-Ribera, A., Forero-Sánchez, D., Forero-Romero, J. E., Frenk, C. S., Gänsicke, B. T., García, L. Á., García-Bellido, J., Garcia-Quintero, C., Garrison, L. H., Gil-Marín, H., Golden-Marx, J., Gontcho, S. Gontcho A, Gonzalez-Morales, A. X., Gonzalez-Perez, V., Gordon, C., Graur, O., Green, D., Gruen, D., Guy, J., Hadzhiyska, B., Hahn, C., Han, J. J., Hanif, M. M. S, Herrera-Alcantar, H. K., Honscheid, K., Hou, J., Howlett, C., Huterer, D., Iršič, V., Ishak, M., Jana, A., Jiang, L., Jimenez, J., Jing, Y. P., Joudaki, S., Joyce, R., Jullo, E., Juneau, S., Kizhuprakkat, N., Karaçaylı, N. G., Karim, T., Kehoe, R., Kent, S., Khederlarian, A., Kim, S., Kirkby, D., Kisner, T., Kitaura, F., Kneib, J., Koposov, S. E., Kovács, A., Kremin, A., Krolewski, A., L'Huillier, B., Lahav, O., Lambert, A., Lamman, C., Lan, T. -W., Landriau, M., Lang, D., Lange, J. U., Lasker, J., Guillou, L. Le, Leauthaud, A., Levi, M. E., Li, T. S., Linder, E., Lyons, A., Magneville, C., Manera, M., Manser, C. J., Margala, D., Martini, P., McDonald, P., Medina, G. E., Medina-Varela, L., Meisner, A., Mena-Fernández, J., Meneses-Rizo, J., Mezcua, M., Miquel, R., Montero-Camacho, P., Moon, J., Moore, S., Moustakas, J., Mueller, E., Mundet, J., Muñoz-Gutiérrez, A., Myers, A. D., Nadathur, S., Napolitano, L., Neveux, R., Newman, J. A., Nie, J., Niz, G., Norberg, P., Noriega, H. E., Paillas, E., Palanque-Delabrouille, N., Palmese, A., Zhiwei, P., Parkinson, D., Penmetsa, S., Percival, W. J., Pérez-Fernández, A., Pérez-Ràfols, I., Pieri, M., Poppett, C., Porredon, A., Prada, F., Pucha, R., Raichoor, A., Ramírez-Pérez, C., Ramirez-Solano, S., Rashkovetskyi, M., Ravoux, C., Rocher, A., Rockosi, C., Ross, A. J., Rossi, G., Ruggeri, R., Ruhlmann-Kleider, V., Sabiu, C. G., Said, K., Saintonge, A., Samushia, L., Sanchez, E., Saulder, C., Schaan, E., Schlafly, E. F., Schlegel, D., Scholte, D., Schubnell, M., Seo, H., Shafieloo, A., Sharples, R., Sheu, W., Silber, J., Sinigaglia, F., Siudek, M., Slepian, Z., Smith, A., Sprayberry, D., Stephey, L., Suárez-Pérez, J., Sun, Z., Tan, T., Tarlé, G., Tojeiro, R., Ureña-López, L. A., Vaisakh, R., Valcin, D., Valdes, F., Valluri, M., Vargas-Magaña, M., Variu, A., Verde, L., Walther, M., Wang, B., Wang, M. S., Weaver, B. A., Weaverdyck, N., Wechsler, R. H., White, M., Xie, Y., Yang, J., Yèche, C., Yu, J., Yuan, S., Zhang, H., Zhang, Z., Zhao, C., Zheng, Z., Zhou, R., Zhou, Z., Zou, H., Zou, S., and Zu, Y.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: The Dark Energy Spectroscopic Instrument (DESI) was designed to conduct a survey covering 14,000 deg$^2$ over five years to constrain the cosmic expansion history through precise measurements of Baryon Acoustic Oscillations (BAO). The scientific program for DESI was evaluated during a five month Survey Validation (SV) campaign before beginning full operations. This program produced deep spectra of tens of thousands of objects from each of the stellar (MWS), bright galaxy (BGS), luminous red galaxy (LRG), emission line galaxy (ELG), and quasar target classes. These SV spectra were used to optimize redshift distributions, characterize exposure times, determine calibration procedures, and assess observational overheads for the five-year program. In this paper, we present the final target selection algorithms, redshift distributions, and projected cosmology constraints resulting from those studies. We also present a `One-Percent survey' conducted at the conclusion of Survey Validation covering 140 deg$^2$ using the final target selection algorithms with exposures of a depth typical of the main survey. The Survey Validation indicates that DESI will be able to complete the full 14,000 deg$^2$ program with spectroscopically-confirmed targets from the MWS, BGS, LRG, ELG, and quasar programs with total sample sizes of 7.2, 13.8, 7.46, 15.7, and 2.87 million, respectively. These samples will allow exploration of the Milky Way halo, clustering on all scales, and BAO measurements with a statistical precision of 0.28% over the redshift interval $z<1.1$, 0.39% over the redshift interval $1.1
Published: 2023
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19. First test of the consistency relation for the large-scale structure using the anisotropic three-point correlation function of BOSS DR12 galaxies (An explanatory video is available at https://youtu.be/Zi36ooLPhss.)

Author: Sugiyama, Naonori S., Yamauchi, Daisuke, Kobayashi, Tsutomu, Fujita, Tomohiro, Arai, Shun, Hirano, Shin'ichi, Saito, Shun, Beutler, Florian, and Seo, Hee-Jong
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics, General Relativity and Quantum Cosmology
Abstract: We present, for the first time, an observational test of the consistency relation for the large-scale structure (LSS) of the Universe through a joint analysis of the anisotropic two- and three-point correlation functions (2PCF and 3PCF) of galaxies. We parameterise the breakdown of the LSS consistency relation in the squeezed limit by $E_{\rm s}$, which represents the ratio of the coefficients of the shift terms in the second-order density and velocity fluctuations. $E_{\rm s}\neq1$ is a sufficient condition under which the LSS consistency relation is violated. A novel aspect of this work is that we constrain $E_{\rm s}$ by obtaining information about the nonlinear velocity field from the quadrupole component of the 3PCF without taking the squeezed limit. Using the galaxy catalogues in the Baryon Oscillation Spectroscopic Survey (BOSS) Data Release 12, we obtain $E_{\rm s} = -0.92_{-3.26}^{+3.13}$, indicating that there is no violation of the LSS consistency relation in our analysis within the statistical errors. Our parameterisation is general enough that our constraint can be applied to a wide range of theories, such as multicomponent fluids, modified gravity theories, and their associated galaxy bias effects. Our analysis opens a new observational window to test the fundamental physics using the anisotropic higher-order correlation functions of galaxy clustering., Comment: 17 pages, 6 figures. Explanatory videos are available in several languages: https://youtu.be/Zi36ooLPhss (English), https://youtu.be/d2ZamcDt6hs (French), https://youtu.be/iSm5yPWmZ9c (Spanish), https://youtu.be/Go7ox-ciHIc (German), https://youtu.be/6Ith7cE723o (Chinese), and https://youtu.be/rH9-C3eKoYc (English with my voice)
Published: 2023
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20. Triumvirate: A Python/C++ package for three-point clustering measurements

Author: Wang, Mike Shengbo, Beutler, Florian, and Sugiyama, Naonori S.
Subjects: Astrophysics - Instrumentation and Methods for Astrophysics, Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: Triumvirate is a Python/C++ package for measuring the three-point clustering statistics in large-scale structure (LSS) cosmological analyses. Given a catalogue of discrete particles (such as galaxies) with their spatial coordinates, it computes estimators of the multipoles of the three-point correlation function, also known as the bispectrum in Fourier space, in the tri-polar spherical harmonic (TripoSH) decomposition proposed by Sugiyama et al. (2019). The objective of Triumvirate is to provide efficient end-to-end measurement of clustering statistics which can be fed into downstream galaxy survey analyses to constrain and test cosmological models. To this end, it builds upon the original algorithms in the hitomi code developed by Sugiyama et al. (2018, 2019), and supplies a user-friendly interface with flexible input/output (I/O) of catalogue data and measurement results, with the built program configurable through external parameter files and tracked through enhanced logging and warning/exception handling. For completeness and complementarity, methods for measuring two-point clustering statistics are also included in the package., Comment: 6 pages, 1 table. Accepted by JOSS: added references and performance details; new code release v0.3.0. Code available at https://github.com/MikeSWang/Triumvirate
Published: 2023
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21. Primordial feature constraints from BOSS+eBOSS

Author: Mergulhão, Thiago, Beutler, Florian, and Peacock, John A.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics, General Relativity and Quantum Cosmology, High Energy Physics - Phenomenology
Abstract: Understanding the universe in its pristine epoch is crucial in order to obtain a concise comprehension of the late-time universe. Although current data in cosmology are compatible with Gaussian primordial perturbations whose power spectrum follows a nearly scale-invariant power law, this need not be the case when a fundamental theoretical construction is assumed. These extended models lead to sharp features in the primordial power spectrum, breaking its scale invariance. In this work, we obtain combined constraints on four primordial feature models by using the final data release of the BOSS galaxies and eBOSS quasars. By pushing towards the fundamental mode of these surveys and using the larger eBOSS volume, we were able to extend the feature parameter space (i.e. the feature frequency $\omega$) by a factor of four compared to previous analyses using BOSS. While we did not detect any significant features, previous work showed that next-generation galaxy surveys such as DESI will improve the sensitivity to features by a factor of 7, and will also extend the parameter space by a factor of 2.5., Comment: Published by JCAP, 28 + 4 pages, 16 figures; changes made after peer review
Published: 2023
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22. New constraints on cosmological modified gravity theories from anisotropic three-point correlation functions of BOSS DR12 galaxies

Author: Sugiyama, Naonori S., Yamauchi, Daisuke, Kobayashi, Tsutomu, Fujita, Tomohiro, Arai, Shun, Hirano, Shin'ichi, Saito, Shun, Beutler, Florian, and Seo, Hee-Jong
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: We report a new test of modified gravity theories using the large-scale structure of the Universe. This paper is the first attempt to (1) apply a joint analysis of the anisotropic components of galaxy two- and three-point correlation functions (2 and 3PCFs) to actual galaxy data and (2) constrain the nonlinear effects of degenerate higher-order scalar-tensor (DHOST) theories on cosmological scales. Applying this analysis to the Baryon Oscillation Spectroscopic Survey (BOSS) data release 12, we obtain the lower bounds of $-1.655 < \xi_{\rm t}$ and $-0.504 < \xi_{\rm s}$ at the $95\%$ confidence level on the parameters characterising the time evolution of the tidal and shift terms of the second-order velocity field. These constraints are consistent with GR predictions of $\xi_{\rm t}=15/1144$ and $\xi_{\rm s}=0$. Moreover, they represent a $35$-fold and $20$-fold improvement, respectively, over the joint analysis with only the isotropic 3PCF. We ensure the validity of our results by investigating various quantities, including theoretical models of the 3PCF, window function corrections, cumulative ${\rm S/N}$, Fisher matrices, and statistical scattering effects of mock simulation data. We also find statistically significant discrepancies between the BOSS data and the Patchy mocks for the 3PCF measurement. Finally, we package all of our 3PCF analysis codes under the name \textsc{HITOMI} and make them publicly available so that readers can reproduce all the results of this paper and easily apply them to ongoing future galaxy surveys., Comment: 60 pages, 21 figures, 22 tables; a set of codes for data analysis is publicly available at https://github.com/naonori/hitomi.git
Published: 2023
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23. Lagrangian displacement field estimators in cosmology

Author: Ota, Atsuhisa, Seo, Hee-Jong, Saito, Shun, and Beutler, Florian
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics, Astrophysics - Instrumentation and Methods for Astrophysics
Abstract: The late-time nonlinear Lagrangian displacement field is highly correlated with the initial field, so reconstructing it could enable us to extract primordial cosmological information. Our previous work [1] carefully studied the displacement field reconstructed from the late time density field using the iterative method proposed by Ref. [2] and found that it does not fully converge to the true, underlying displacement field (e.g., $\sim 8\%$ offset at $k\sim 0.2 \ihMpc$ at $z=0.6$). We also constructed the Lagrangian perturbation theory model for the reconstructed field, but the model could not explain the discrepancy between the true and the reconstructed fields in the previous work. The main sources of the discrepancy were speculated to be a numerical artifact in the displacement estimator due to the discreteness of the sample. In this paper, we develop two new estimators of the displacement fields to reduce such numerical discreteness effect, the normalized momentum estimator~(NME) and the rescaled resumed estimator~(RRE). We show that the discrepancy Ref. [1] reported is not due to the numerical artifacts. We conclude that the method from Ref. [2] cannot fully reconstruct the shape of the nonlinear displacement field at the redshift we studied, while it is still an efficient BAO reconstruction method. In parallel, by properly accounting for the UV-sensitive term in a reconstruction procedure with an effective field theory approach, we improve the theoretical model for the reconstructed displacement field, by almost five times, from $\sim 15\%$ to the level of a few \% at $k\sim 0.2\ihMpc$ at the redshift $z=0.6$., Comment: 16 pages, 6 figures, published version
Published: 2022
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24. Constraining {\nu}{\Lambda}CDM with density-split clustering

Author: Paillas, Enrique, Cuesta-Lazaro, Carolina, Zarrouk, Pauline, Cai, Yan-Chuan, Percival, Will J., Nadathur, Seshadri, Pinon, Mathilde, de Mattia, Arnaud, and Beutler, Florian
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: The dependence of galaxy clustering on local density provides an effective method for extracting non-Gaussian information from galaxy surveys. The two-point correlation function (2PCF) provides a complete statistical description of a Gaussian density field. However, the late-time density field becomes non-Gaussian due to non-linear gravitational evolution and higher-order summary statistics are required to capture all of its cosmological information. Using a Fisher formalism based on halo catalogues from the Quijote simulations, we explore the possibility of retrieving this information using the density-split clustering (DS) method, which combines clustering statistics from regions of different environmental density. We show that DS provides more precise constraints on the parameters of the $\nu \Lambda$CDM model compared to the 2PCF, and we provide suggestions for where the extra information may come from. DS improves the constraints on the sum of neutrino masses by a factor of $7$ and by factors of 4, 3, 3, 6, and 5 for $\Omega_{\rm m}$, $\Omega_{\rm b}$, $h$, $n_s$, and $\sigma_8$, respectively. We compare DS statistics when the local density environment is estimated from the real or redshift-space positions of haloes. The inclusion of DS autocorrelation functions, in addition to the cross-correlation functions between DS environments and haloes, recovers most of the information that is lost when using the redshift-space halo positions to estimate the environment. We discuss the possibility of constructing simulation-based methods to model DS clustering statistics in different scenarios., Comment: Author's accepted manuscript
Published: 2022
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25. pocoMC: A Python package for accelerated Bayesian inference in astronomy and cosmology

Author: Karamanis, Minas, Nabergoj, David, Beutler, Florian, Peacock, John A., and Seljak, Uros
Subjects: Astrophysics - Instrumentation and Methods for Astrophysics, Astrophysics - Cosmology and Nongalactic Astrophysics, Physics - Computational Physics
Abstract: pocoMC is a Python package for accelerated Bayesian inference in astronomy and cosmology. The code is designed to sample efficiently from posterior distributions with non-trivial geometry, including strong multimodality and non-linearity. To this end, pocoMC relies on the Preconditioned Monte Carlo algorithm which utilises a Normalising Flow in order to decorrelate the parameters of the posterior. It facilitates both tasks of parameter estimation and model comparison, focusing especially on computationally expensive applications. It allows fitting arbitrary models defined as a log-likelihood function and a log-prior probability density function in Python. Compared to popular alternatives (e.g. nested sampling) pocoMC can speed up the sampling procedure by orders of magnitude, cutting down the computational cost substantially. Finally, parallelisation to computing clusters manifests linear scaling., Comment: 6 pages, 1 figure. Submitted to JOSS. Code available at https://github.com/minaskar/pocomc
Published: 2022

26. Accelerating astronomical and cosmological inference with Preconditioned Monte Carlo

Author: Karamanis, Minas, Beutler, Florian, Peacock, John A., Nabergoj, David, and Seljak, Uros
Subjects: Astrophysics - Instrumentation and Methods for Astrophysics, Astrophysics - Cosmology and Nongalactic Astrophysics, Physics - Computational Physics
Abstract: We introduce Preconditioned Monte Carlo (PMC), a novel Monte Carlo method for Bayesian inference that facilitates efficient sampling of probability distributions with non-trivial geometry. PMC utilises a Normalising Flow (NF) in order to decorrelate the parameters of the distribution and then proceeds by sampling from the preconditioned target distribution using an adaptive Sequential Monte Carlo (SMC) scheme. The results produced by PMC include samples from the posterior distribution and an estimate of the model evidence that can be used for parameter inference and model comparison respectively. The aforementioned framework has been thoroughly tested in a variety of challenging target distributions achieving state-of-the-art sampling performance. In the cases of primordial feature analysis and gravitational wave inference, PMC is approximately 50 and 25 times faster respectively than Nested Sampling (NS). We found that in higher dimensional applications the acceleration is even greater. Finally, PMC is directly parallelisable, manifesting linear scaling up to thousands of CPUs., Comment: 10 pages, 9 figures. Submitted to MNRAS. Code available at https://github.com/minaskar/pocomc
Published: 2022
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27. Overview of the Instrumentation for the Dark Energy Spectroscopic Instrument

Author: Abareshi, B., Aguilar, J., Ahlen, S., Alam, Shadab, Alexander, David M., Alfarsy, R., Allen, L., Prieto, C. Allende, Alves, O., Ameel, J., Armengaud, E., Asorey, J., Aviles, Alejandro, Bailey, S., Balaguera-Antolínez, A., Ballester, O., Baltay, C., Bault, A., Beltran, S. F., Benavides, B., BenZvi, S., Berti, A., Besuner, R., Beutler, Florian, Bianchi, D., Blake, C., Blanc, P., Blum, R., Bolton, A., Bose, S., Bramall, D., Brieden, S., Brodzeller, A., Brooks, D., Brownewell, C., Buckley-Geer, E., Cahn, R. N., Cai, Z., Canning, R., Rosell, A. Carnero, Carton, P., Casas, R., Castander, F. J., Cervantes-Cota, J. L., Chabanier, S., Chaussidon, E., Chuang, C., Circosta, C., Cole, S., Cooper, A. P., da Costa, L., Cousinou, M. -C., Cuceu, A., Davis, T. M., Dawson, K., de la Cruz-Noriega, R., de la Macorra, A., de Mattia, A., Della Costa, J., Demmer, P., Derwent, M., Dey, A., Dey, B., Dhungana, G., Ding, Z., Dobson, C., Doel, P., Donald-McCann, J., Donaldson, J., Douglass, K., Duan, Y., Dunlop, P., Edelstein, J., Eftekharzadeh, S., Eisenstein, D. J., Enriquez-Vargas, M., Escoffier, S., Evatt, M., Fagrelius, P., Fan, X., Fanning, K., Fawcett, V. A., Ferraro, S., Ereza, J., Flaugher, B., Font-Ribera, A., Forero-Romero, J. E., Frenk, C. S., Fromenteau, S., Gänsicke, B. T., Garcia-Quintero, C., Garrison, L., Gaztañaga, E., Gerardi, F., Gil-Marín, H., Gontcho, S. Gontcho A, Gonzalez-Morales, Alma X., Gonzalez-de-Rivera, G., Gonzalez-Perez, V., Gordon, C., Graur, O., Green, D., Grove, C., Gruen, D., Gutierrez, G., Guy, J., Hahn, C., Harris, S., Herrera, D., Herrera-Alcantar, Hiram K., Honscheid, K., Howlett, C., Huterer, D., Iršič, V., Ishak, M., Jelinsky, P., Jiang, L., Jimenez, J., Jing, Y. P., Joyce, R., Jullo, E., Juneau, S., Karaçaylı, N. G., Karamanis, M., Karcher, A., Karim, T., Kehoe, R., Kent, S., Kirkby, D., Kisner, T., Kitaura, F., Koposov, S. E., Kovács, A., Kremin, A., Krolewski, Alex, L'Huillier, B., Lahav, O., Lambert, A., Lamman, C., Lan, Ting-Wen, Landriau, M., Lane, S., Lang, D., Lange, J. U., Lasker, J., Guillou, L. Le, Leauthaud, A., Van Suu, A. Le, Levi, Michael E., Li, T. S., Magneville, C., Manera, M., Manser, Christopher J., Marshall, B., McCollam, W., McDonald, P., Meisner, Aaron M., Mezcua, J. Mena-Fernández M., Miller, T., Miquel, R., Montero-Camacho, P., Moon, J., Martini, J. Paul, Meneses-Rizo, J., Moustakas, J., Mueller, E., Muñoz-Gutiérrez, Andrea, Myers, Adam D., Nadathur, S., Najita, J., Napolitano, L., Neilsen, E., Newman, Jeffrey A., Nie, J. D., Ning, Y., Niz, G., Norberg, P., Noriega, Hernán E., O'Brien, T., Obuljen, A., Palanque-Delabrouille, N., Palmese, A., Zhiwei, P., Pappalardo, D., Peng, X., Percival, W. J., Perruchot, S., Pogge, R., Poppett, C., Porredon, A., Prada, F., Prochaska, J., Pucha, R., Pérez-Fernández, A., Pérez-Ráfols, I., Rabinowitz, D., Raichoor, A., Ramirez-Solano, S., Ramírez-Pérez, César, Ravoux, C., Reil, K., Rezaie, M., Rocher, A., Rockosi, C., Roe, N. A., Roodman, A., Ross, A. J., Rossi, G., Ruggeri, R., Ruhlmann-Kleider, V., Sabiu, C. G., Safonova, S., Said, K., Saintonge, A., Catonga, Javier Salas, Samushia, L., Sanchez, E., Saulder, C., Schaan, E., Schlafly, E., Schlegel, D., Schmoll, J., Scholte, D., Schubnell, M., Secroun, A., Seo, H., Serrano, S., Sharples, Ray M., Sholl, Michael J., Silber, Joseph Harry, Silva, D. R., Sirk, M., Siudek, M., Smith, A., Sprayberry, D., Staten, R., Stupak, B., Tan, T., Tarlé, Gregory, Tie, Suk Sien, Tojeiro, R., Ureña-López, L. A., Valdes, F., Valenzuela, O., Valluri, M., Vargas-Magaña, M., Verde, L., Walther, M., Wang, B., Wang, M. S., Weaver, B. A., Weaverdyck, C., Wechsler, R., Wilson, Michael J., Yang, J., Yu, Y., Yuan, S., Yèche, Christophe, Zhang, H., Zhang, K., Zhao, Cheng, Zhou, Rongpu, Zhou, Zhimin, Zou, H., Zou, J., Zou, S., and Zu, Y.
Subjects: Astrophysics - Instrumentation and Methods for Astrophysics, Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: The Dark Energy Spectroscopic Instrument (DESI) has embarked on an ambitious five-year survey to explore the nature of dark energy with spectroscopy of 40 million galaxies and quasars. DESI will determine precise redshifts and employ the Baryon Acoustic Oscillation method to measure distances from the nearby universe to z > 3.5, as well as measure the growth of structure and probe potential modifications to general relativity. In this paper we describe the significant instrumentation we developed for the DESI survey. The new instrumentation includes a wide-field, 3.2-deg diameter prime-focus corrector that focuses the light onto 5020 robotic fiber positioners on the 0.812 m diameter, aspheric focal surface. The positioners and their fibers are divided among ten wedge-shaped petals. Each petal is connected to one of ten spectrographs via a contiguous, high-efficiency, nearly 50 m fiber cable bundle. The ten spectrographs each use a pair of dichroics to split the light into three channels that together record the light from 360 - 980 nm with a resolution of 2000 to 5000. We describe the science requirements, technical requirements on the instrumentation, and management of the project. DESI was installed at the 4-m Mayall telescope at Kitt Peak, and we also describe the facility upgrades to prepare for DESI and the installation and functional verification process. DESI has achieved all of its performance goals, and the DESI survey began in May 2021. Some performance highlights include RMS positioner accuracy better than 0.1", SNR per \sqrt{\AA} > 0.5 for a z > 2 quasar with flux 0.28e-17 erg/s/cm^2/A at 380 nm in 4000s, and median SNR = 7 of the [OII] doublet at 8e-17 erg/s/cm^2 in a 1000s exposure for emission line galaxies at z = 1.4 - 1.6. We conclude with highlights from the on-sky validation and commissioning of the instrument, key successes, and lessons learned. (abridged), Comment: 78 pages, 32 figures, submitted to AJ
Published: 2022
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28. $\texttt{matryoshka}$ II: Accelerating Effective Field Theory Analyses of the Galaxy Power Spectrum

Author: Donald-McCann, Jamie, Koyama, Kazuya, and Beutler, Florian
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: In this paper we present an extension to the $\texttt{matryoshka}$ suite of neural-network-based emulators. The new editions have been developed to accelerate EFTofLSS analyses of galaxy power spectrum multipoles in redshift space. They are collectively referred to as the $\texttt{EFTEMU}$. We test the $\texttt{EFTEMU}$ at the power spectrum level and achieve a prediction accuracy of better than 1\% with BOSS-like bias parameters and counterterms on scales $0.001\ h\ \mathrm{Mpc}^{-1} \leq k \leq 0.19\ h\ \mathrm{Mpc}^{-1}$. We also run a series of mock full shape analyses to test the performance of the $\texttt{EFTEMU}$ when carrying out parameter inference. Through these mock analyses we verify that the $\texttt{EFTEMU}$ recovers the true cosmology within $1\sigma$ at several redshifts ($z=[0.38,0.51,0.61]$), and with several noise levels (the most stringent of which is Gaussian covariance associated with a volume of $5000^3 \ \mathrm{Mpc}^3 \ h^{-3}$). We compare the mock inference results from the $\texttt{EFTEMU}$ to those obtained with a fully analytic EFTofLSS model and again find no significant bias, whilst speeding up the inference by three orders of magnitude. The $\texttt{EFTEMU}$ is publicly available as part of the $\texttt{matryoshka}$ $\texttt{Python}$ package., Comment: MNRAS accepted version. 11 pages, 8 figures, 3 tables. Code available at https://github.com/JDonaldM/Matryoshka
Published: 2022
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29. The Seventeenth Data Release of the Sloan Digital Sky Surveys: Complete Release of MaNGA, MaStar and APOGEE-2 Data

Author: Abdurro'uf, Accetta, Katherine, Aerts, Conny, Aguirre, Victor Silva, Ahumada, Romina, Ajgaonkar, Nikhil, Ak, N. Filiz, Alam, Shadab, Prieto, Carlos Allende, Almeida, Andres, Anders, Friedrich, Anderson, Scott F., Andrews, Brett H., Anguiano, Borja, Aquino-Ortiz, Erik, Aragon-Salamanca, Alfonso, Argudo-Fernandez, Maria, Ata, Metin, Aubert, Marie, Avila-Reese, Vladimir, Badenes, Carles, Barba, Rodolfo H., Barger, Kat, Barrera-Ballesteros, Jorge K., Beaton, Rachael L., Beers, Timothy C., Belfiore, Francesco, Bender, Chad F., Bernardi, Mariangela, Bershady, Matthew A., Beutler, Florian, Bidin, Christian Moni, Bird, Jonathan C., Bizyaev, Dmitry, Blanc, Guillermo A., Blanton, Michael R., Boardman, Nicholas Fraser, Bolton, Adam S., Boquien, Mederic, Borissova, Jura, Bovy, Jo, Brandt, W. N., Brown, Jordan, Brownstein, Joel R., Brusa, Marcella, Buchner, Johannes, Bundy, Kevin, Burchett, Joseph N., Bureau, Martin, Burgasser, Adam, Cabang, Tuesday K., Campbell, Stephanie, Cappellari, Michele, Carlberg, Joleen K., Wanderley, Fabio Carneiro, Carrera, Ricardo, Cash, Jennifer, Chen, Yan-Ping, Chen, Wei-Huai, Cherinka, Brian, Chiappini, Cristina, Choi, Peter Doohyun, Chojnowski, S. Drew, Chung, Haeun, Clerc, Nicolas, Cohen, Roger E., Comerford, Julia M., Comparat, Johan, da Costa, Luiz, Covey, Kevin, Crane, Jeffrey D., Cruz-Gonzalez, Irene, Culhane, Connor, Cunha, Katia, Dai, Y. Sophia, Damke, Guillermo, Darling, Jeremy, Davidson Jr., James W., Davies, Roger, Dawson, Kyle, De Lee, Nathan, Diamond-Stanic, Aleksandar M., Cano-Diaz, Mariana, Sanchez, Helena Dominguez, Donor, John, Duckworth, Chris, Dwelly, Tom, Eisenstein, Daniel J., Elsworth, Yvonne P., Emsellem, Eric, Eracleous, Mike, Escoffier, Stephanie, Fan, Xiaohui, Farr, Emily, Feng, Shuai, Fernandez-Trincado, Jose G., Feuillet, Diane, Filipp, Andreas, Fillingham, Sean P, Frinchaboy, Peter M., Fromenteau, Sebastien, Galbany, Lluis, Garcia, Rafael A., Garcia-Hernandez, D. A., Ge, Junqiang, Geisler, Doug, Gelfand, Joseph, Geron, Tobias, Gibson, Benjamin J., Goddy, Julian, Godoy-Rivera, Diego, Grabowski, Kathleen, Green, Paul J., Greener, Michael, Grier, Catherine J., Griffith, Emily, Guo, Hong, Guy, Julien, Hadjara, Massinissa, Harding, Paul, Hasselquist, Sten, Hayes, Christian R., Hearty, Fred, Hernandez, Jesus, Hill, Lewis, Hogg, David W., Holtzman, Jon A., Horta, Danny, Hsieh, Bau-Ching, Hsu, Chin-Hao, Hsu, Yun-Hsin, Huber, Daniel, Huertas-Company, Marc, Hutchinson, Brian, Hwang, Ho Seong, Ibarra-Medel, Hector J., Chitham, Jacob Ider, Ilha, Gabriele S., Imig, Julie, Jaekle, Will, Jayasinghe, Tharindu, Ji, Xihan, Johnson, Jennifer A., Jones, Amy, Jonsson, Henrik, Katkov, Ivan, Khalatyan, Arman, Kinemuchi, Karen, Kisku, Shobhit, Knapen, Johan H., Kneib, Jean-Paul, Kollmeier, Juna A., Kong, Miranda, Kounkel, Marina, Kreckel, Kathryn, Krishnarao, Dhanesh, Lacerna, Ivan, Lane, Richard R., Langgin, Rachel, Lavender, Ramon, Law, David R., Lazarz, Daniel, Leung, Henry W., Leung, Ho-Hin, Lewis, Hannah M., Li, Cheng, Li, Ran, Lian, Jianhui, Liang, Fu-Heng, Lin, Lihwai, Lin, Yen-Ting, Lin, Sicheng, Lintott, Chris, Long, Dan, Longa-Pena, Penelope, Lopez-Coba, Carlos, Lu, Shengdong, Lundgren, Britt F., Luo, Yuanze, Mackereth, J. Ted, de la Macorra, Axel, Mahadevan, Suvrath, Majewski, Steven R., Manchado, Arturo, Mandeville, Travis, Maraston, Claudia, Margalef-Bentabol, Berta, Masseron, Thomas, Masters, Karen L., Mathur, Savita, McDermid, Richard M., Mckay, Myles, Merloni, Andrea, Merrifield, Michael, Meszaros, Szabolcs, Miglio, Andrea, Di Mille, Francesco, Minniti, Dante, Minsley, Rebecca, Monachesi, Antonela, Moon, Jeongin, Mosser, Benoit, Mulchaey, John, Muna, Demitri, Munoz, Ricardo R., Myers, Adam D., Myers, Natalie, Nadathur, Seshadri, Nair, Preethi, Nandra, Kirpal, Neumann, Justus, Newman, Jeffrey A., Nidever, David L., Nikakhtar, Farnik, Nitschelm, Christian, O'Connell, Julia E., Garma-Oehmichen, Luis, de Oliveira, Gabriel Luan Souza, Olney, Richard, Oravetz, Daniel, Ortigoza-Urdaneta, Mario, Osorio, Yeisson, Otter, Justin, Pace, Zachary J., Padilla, Nelson, Pan, Kaike, Pan, Hsi-An, Parikh, Taniya, Parker, James, Peirani, Sebastien, Ramirez, Karla Pena, Penny, Samantha, Percival, Will J., Perez-Fournon, Ismael, Pinsonneault, Marc, Poidevin, Frederick, Poovelil, Vijith Jacob, Price-Whelan, Adrian M., Queiroz, Anna Barbara de Andrade, Raddick, M. Jordan, Ray, Amy, Rembold, Sandro Barboza, Riddle, Nicole, Riffel, Rogemar A., Riffel, Rogerio, Rix, Hans-Walter, Robin, Annie C., Rodriguez-Puebla, Aldo, Roman-Lopes, Alexandre, Roman-Zuniga, Carlos, Rose, Benjamin, Ross, Ashley J., Rossi, Graziano, Rubin, Kate H. R., Salvato, Mara, Sanchez, Sebastian F., Sanchez-Gallego, Jose R., Sanderson, Robyn, Rojas, Felipe Antonio Santana, Sarceno, Edgar, Sarmiento, Regina, Sayres, Conor, Sazonova, Elizaveta, Schaefer, Adam L., Schiavon, Ricardo, Schlegel, David J, Schneider, Donald P., Schultheis, Mathias, Schwope, Axel, Serenelli, Aldo, Serna, Javier, Shao, Zhengyi, Shapiro, Griffin, Sharma, Anubhav, Shen, Yue, Shetrone, Matthew, Shu, Yiping, Simon, Joshua D., Skrutskie, M. F., Smethurst, Rebecca, Smith, Verne, Sobeck, Jennifer, Spoo, Taylor, Sprague, Dani, Stark, David V., Stassun, Keivan G., Steinmetz, Matthias, Stello, Dennis, Stone-Martinez, Alexander, Storchi-Bergmann, Thaisa, Stringfellow, Guy S., Stutz, Amelia, Su, Yung-Chau, Taghizadeh-Popp, Manuchehr, Talbot, Michael S., Tayar, Jamie, Telles, Eduardo, Teske, Johanna, Thakar, Ani, Theissen, Christopher, Thomas, Daniel, Tkachenko, Andrew, Tojeiro, Rita, Toledo, Hector Hernandez, Troup, Nicholas W., Trump, Jonathan R., Trussler, James, Turner, Jacqueline, Tuttle, Sarah, Unda-Sanzana, Eduardo, Vazquez-Mata, Jose Antonio, Valentini, Marica, Valenzuela, Octavio, Vargas-Gonzalez, Jaime, Vargas-Magana, Mariana, Alfaro, Pablo Vera, Villanova, Sandro, Vincenzo, Fiorenzo, Wake, David, Warfield, Jack T., Washington, Jessica Diane, Weaver, Benjamin Alan, Weijmans, Anne-Marie, Weinberg, David H., Weiss, Achim, Westfall, Kyle B., Wild, Vivienne, Wilde, Matthew C., Wilson, John C., Wilson, Robert F., Wilson, Mikayla, Wolf, Julien, Wood-Vasey, W. M., Yan, Renbin, Zamora, Olga, Zasowski, Gail, Zhang, Kai, Zhao, Cheng, Zheng, Zheng, and Zhu, Kai
Subjects: Astrophysics - Astrophysics of Galaxies, Astrophysics - Instrumentation and Methods for Astrophysics
Abstract: This paper documents the seventeenth data release (DR17) from the Sloan Digital Sky Surveys; the fifth and final release from the fourth phase (SDSS-IV). DR17 contains the complete release of the Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey, which reached its goal of surveying over 10,000 nearby galaxies. The complete release of the MaNGA Stellar Library (MaStar) accompanies this data, providing observations of almost 30,000 stars through the MaNGA instrument during bright time. DR17 also contains the complete release of the Apache Point Observatory Galactic Evolution Experiment 2 (APOGEE-2) survey which publicly releases infra-red spectra of over 650,000 stars. The main sample from the Extended Baryon Oscillation Spectroscopic Survey (eBOSS), as well as the sub-survey Time Domain Spectroscopic Survey (TDSS) data were fully released in DR16. New single-fiber optical spectroscopy released in DR17 is from the SPectroscipic IDentification of ERosita Survey (SPIDERS) sub-survey and the eBOSS-RM program. Along with the primary data sets, DR17 includes 25 new or updated Value Added Catalogs (VACs). This paper concludes the release of SDSS-IV survey data. SDSS continues into its fifth phase with observations already underway for the Milky Way Mapper (MWM), Local Volume Mapper (LVM) and Black Hole Mapper (BHM) surveys., Comment: 40 pages, 8 figures, 6 tables. In press at ApJSS (arxiv v2 corrects some minor typos and updates references)
Published: 2021
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30. $\texttt{matryoshka}$: Halo Model Emulator for the Galaxy Power Spectrum

Author: Donald-McCann, Jamie, Beutler, Florian, Koyama, Kazuya, and Karamanis, Minas
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: We present $\texttt{matryoshka}$, a suite of neural network based emulators and accompanying Python package that have been developed with the goal of producing fast and accurate predictions of the nonlinear galaxy power spectrum. The suite of emulators consists of four linear component emulators, from which fast linear predictions of the power spectrum can be made, allowing all nonlinearities to be included in predictions from a nonlinear boost component emulator. The linear component emulators includes an emulator for the matter transfer function that produces predictions in $\sim 0.0004 \ \mathrm{s}$, with an error of $<0.08\%$ (at $1\sigma$ level) on scales $10^{-4} \ h \ \mathrm{Mpc}^{-1}
Published: 2021
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31. hankl: A lightweight Python implementation of the FFTLog algorithm for Cosmology

Author: Karamanis, Minas and Beutler, Florian
Subjects: Astrophysics - Instrumentation and Methods for Astrophysics, Astrophysics - Cosmology and Nongalactic Astrophysics, Physics - Computational Physics
Abstract: We introduce hankl, a lightweight Python implementation of the FFTLog algorithm for Cosmology. The FFTLog algorithm is an extension of the Fast Fourier Transform (FFT) for logarithmically spaced periodic sequences. It can be used to efficiently compute Hankel transformations, which are paramount for many modern cosmological analyses that are based on the power spectrum or the 2-point correlation function multipoles. The code is well-tested, open source, and publicly available., Comment: 6 pages, 2 figures; Code available at https://github.com/minaskar/hankl
Published: 2021
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32. Unified galaxy power spectrum measurements from 6dFGS, BOSS, and eBOSS

Author: Beutler, Florian and McDonald, Patrick
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: We make use of recent developments in the analysis of galaxy redshift surveys to present an easy to use matrix-based analysis framework for the galaxy power spectrum multipoles, including wide-angle effects and the survey window function. We employ this framework to derive the deconvolved power spectrum multipoles of 6dFGS DR3, BOSS DR12 and the eBOSS DR16 quasar sample. As an alternative to the standard analysis, the deconvolved power spectrum multipoles can be used to perform a data analysis agnostic of survey specific aspects, like the window function. We show that in the case of the BOSS dataset, the Baryon Acoustic Oscillation (BAO) analysis using the deconvolved power spectra results in the same likelihood as the standard analysis. To facilitate the analysis based on both the convolved and deconvolved power spectrum measurements, we provide the window function matrices, wide-angle matrices, covariance matrices and the power spectrum multipole measurements for the datasets mentioned above. Together with this paper we publish a \code{Python}-based toolbox to calculate the different analysis components. The appendix contains a detailed user guide with examples for how a cosmological analysis of these datasets could be implemented. We hope that our work makes the analysis of galaxy survey datasets more accessible to the wider cosmology community., Comment: 39 pages, 16 figures, one table
Published: 2021
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33. Iterative reconstruction excursions for Baryon Acoustic Oscillations and beyond

Author: Seo, Hee-Jong, Ota, Atsuhisa, Schmittfull, Marcel, Saito, Shun, and Beutler, Florian
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: The density field reconstruction technique has been widely used for recovering the Baryon Acoustic Oscillation (BAO) feature in galaxy surveys that has been degraded due to nonlinearities. Recent studies advocated adopting iterative steps to improve the recovery much beyond that of the standard technique. In this paper, we investigate the performance of a few selected iterative reconstruction techniques focusing on the BAO and the broadband-shape of the two-point clustering. We include redshift-space distortions, halo bias, and shot noise and inspect the components of the reconstructed field in Fourier space and in configuration space using both density field-based reconstruction and displacement field-based reconstruction. We find that the displacement field reconstruction becomes quickly challenging in the presence of non-negligible shot noise and therefore present surrogate methods that can be practically applied to a much more sparse field such as galaxies. For a galaxy field, implementing a debiasing step to remove the Lagrangian bias appears crucial for the displacement field reconstruction. We show that the iterative reconstruction does not substantially improve the BAO feature beyond an aggressively optimized standard reconstruction with a small smoothing kernel. However, we find taking iterative steps allows us to use a small smoothing kernel more `stably', i.e., without causing a substantial deviation from the linear power spectrum on large scales. In one specific example we studied, we find that a deviation of 13\% in $P( k \sim 0.1h/Mpc)$ with an aggressive standard reconstruction can reduce to 3-4\% with iterative steps., Comment: 17 pages, 12 figures, 2 tables. Corrected for minor inconsistencies related to bias and RSD treatment during iterative reconstruction. All relevant figures are updated, while the results stay almost the same
Published: 2021
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34. Modeling iterative reconstruction and displacement field in the large scale structure

Author: Ota, Atsuhisa, Seo, Hee-Jong, Saito, Shun, and Beutler, Florian
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics, Astrophysics - Astrophysics of Galaxies, High Energy Physics - Theory
Abstract: The next generation of galaxy surveys like the Dark Energy Spectroscopic Instrument (DESI) and Euclid will provide datasets orders of magnitude larger than anything available to date. Our ability to model nonlinear effects in late time matter perturbations will be a key to unlock the full potential of these datasets, and the area of initial condition reconstruction is attracting growing attention. Iterative reconstruction developed in Ref. [1] is a technique designed to reconstruct the displacement field from the observed galaxy distribution. The nonlinear displacement field and initial linear density field are highly correlated. Therefore, reconstructing the nonlinear displacement field enables us to extract the primordial cosmological information better than from the late time density field at the level of the two-point statistics. This paper will test to what extent the iterative reconstruction can recover the true displacement field and construct a perturbation theory model for the postreconstructed field. We model the iterative reconstruction process with Lagrangian perturbation theory~(LPT) up to third order for dark matter in real space and compare it with $N$-body simulations. We find that the simulated iterative reconstruction does not converge to the nonlinear displacement field, and the discrepancy mainly appears in the shift term, i.e., the term correlated directly with the linear density field. On the contrary, our 3LPT model predicts that the iterative reconstruction should converge to the nonlinear displacement field. We discuss the sources of discrepancy, including numerical noise/artifacts on small scales, and present an ad hoc phenomenological model that improves the agreement., Comment: 19 pages, 11 figures, submitted to PRD
Published: 2021
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35. The clustering of the SDSS-IV extended Baryon Oscillation Spectroscopic Survey quasar sample: Testing observational systematics on the Baryon Acoustic Oscillation measurement

Author: Merz, Grant, Rezaie, Mehdi, Seo, Hee-Jong, Neveux, Richard, Ross, Ashley J., Beutler, Florian, Percival, Will J., Mueller, Eva, Gil-Marín, Héctor, Rossi, Graziano, Dawson, Kyle, Brownstein, Joel R., Myers, Adam D., Schneider, Donald P., Chuang, Chia-Hsun, Zhao, Cheng, de la Macorra, Axel, and Nitschelm, Christian
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: Baryon Acoustic Oscillations are considered to be a very robust standard ruler against various systematics. This premise has been tested against observational systematics, but not to the level required for the next generation of galaxy surveys such as the Dark Energy Spectroscopic Instrument (DESI) and Euclid. In this paper, we investigate the effect of observational systematics on the BAO measurement of the final sample of quasars from the extended Baryon Oscillation Spectroscopic Survey Data Release 16 in order to prepare and hone a similar analysis for upcoming surveys. We employ catalogues with various treatments of imaging systematic effects using linear and neural network-based nonlinear approaches and consider how the BAO measurement changes. We also test how the variations to the BAO fitting model respond to the observational systematics. As expected, we confirm that the BAO measurements obtained from the DR16 quasar sample are robust against imaging systematics well within the statistical error, while reporting slightly modified constraints that shift the line-of-sight BAO signal by less than 1.1% . We use realistic simulations with similar redshift and angular distributions as the DR16 sample to conduct statistical tests for validating the pipeline, quantifying the significance of differences, and estimating the expected bias on the BAO scale in future high-precision data sets. Although we find a marginal impact for the eBOSS QSO data, the work presented here is of vital importance for constraining the nature of dark energy with the BAO feature in the new era of big data cosmology with DESI and Euclid., Comment: 14 pages and 16 figures, comments are welcome
Published: 2021
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36. zeus: A Python implementation of Ensemble Slice Sampling for efficient Bayesian parameter inference

Author: Karamanis, Minas, Beutler, Florian, and Peacock, John A.
Subjects: Astrophysics - Instrumentation and Methods for Astrophysics, Astrophysics - Cosmology and Nongalactic Astrophysics, Astrophysics - Earth and Planetary Astrophysics, Physics - Computational Physics
Abstract: We introduce zeus, a well-tested Python implementation of the Ensemble Slice Sampling (ESS) method for Bayesian parameter inference. ESS is a novel Markov chain Monte Carlo (MCMC) algorithm specifically designed to tackle the computational challenges posed by modern astronomical and cosmological analyses. In particular, the method requires only minimal hand--tuning of 1-2 hyper-parameters that are often trivial to set; its performance is insensitive to linear correlations and it can scale up to 1000s of CPUs without any extra effort. Furthermore, its locally adaptive nature allows to sample efficiently even when strong non-linear correlations are present. Lastly, the method achieves a high performance even in strongly multimodal distributions in high dimensions. Compared to emcee, a popular MCMC sampler, zeus performs 9 and 29 times better in a cosmological and an exoplanet application respectively., Comment: 15 pages, 17 figures, 2 tables, published in MNRAS; Code available at https://github.com/minaskar/zeus
Published: 2021
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37. Towards a self-consistent analysis of the anisotropic galaxy two- and three-point correlation functions on large scales: application to mock galaxy catalogues

Author: Sugiyama, Naonori S., Saito, Shun, Beutler, Florian, and Seo, Hee-Jong
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: We establish a practical method for the joint analysis of anisotropic galaxy two- and three-point correlation functions (2PCF and 3PCF) on the basis of the decomposition formalism of the 3PCF using tri-polar spherical harmonics. We perform such an analysis with MultiDark Patchy mock catalogues to demonstrate and understand the benefit of the anisotropic 3PCF. We focus on scales above $80 h^{-1}\,{\rm Mpc}$, and use information from the shape and the baryon acoustic oscillation (BAO) signals of the 2PCF and 3PCF. We also apply density field reconstruction to increase the signal-noise ratio of BAO in the 2PCF measurement, but not in the 3PCF measurement. In particular, we study in detail the constraints on the angular diameter distance and the Hubble parameter. We build a model of the bispectrum or 3PCF that includes the nonlinear damping of the BAO signal in redshift space. We carefully account for various uncertainties in our analysis including theoretical models of the 3PCF, window function corrections, biases in estimated parameters from the fiducial values, the number of mock realizations to estimate the covariance matrix, and bin size. The joint analysis of the 2PCF and 3PCF monopole and quadrupole components shows a $30\%$ a nd $20\%$ improvement in Hubble parameter constraints before and after reconstruction of the 2PCF measurements, respectively, compared to the 2PCF analysis alone. This study clearly shows that the anisotropic 3PCF increases cosmological information from galaxy surveys and encourages further development of the modeling of the 3PCF on smaller scales than we consider., Comment: 36 pages, 18 figures
Published: 2020
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38. The Completed SDSS-IV extended Baryon Oscillation Spectroscopic Survey: measurement of the BAO and growth rate of structure of the emission line galaxy sample from the anisotropic power spectrum between redshift 0.6 and 1.1

Author: de Mattia, Arnaud, Ruhlmann-Kleider, Vanina, Raichoor, Anand, Ross, Ashley J., Tamone, Amélie, Zhao, Cheng, Alam, Shadab, Avila, Santiago, Burtin, Etienne, Bautista, Julian, Beutler, Florian, Brinkmann, Jonathan, Brownstein, Joel R., Chapman, Michael J., Chuang, Chia-Hsun, Comparat, Johan, Bourboux, Hélion du Mas des, Dawson, Kyle S., de la Macorra, Axel, Gil-Marín, Héctor, Gonzalez-Perez, Violeta, Gorgoni, Claudio, Hou, Jiamin, Kong, Hui, Lin, Sicheng, Nadathur, Seshadri, Newman, Jeffrey A., Mueller, Eva-Maria, Percival, Will J., Rezaie, Mehdi, Rossi, Graziano, Schneider, Donald P., Tiwari, Prabhakar, Vivek, M., Wang, Yuting, and Zhao, Gong-Bo
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: We analyse the large-scale clustering in Fourier space of emission line galaxies (ELG) from the Data Release 16 of the Sloan Digital Sky Survey IV extended Baryon Oscillation Spectroscopic Survey. The ELG sample contains 173,736 galaxies covering 1,170 square degrees in the redshift range $0.6 < z < 1.1$. We perform a BAO measurement from the post-reconstruction power spectrum monopole, and study redshift space distortions (RSD) in the first three even multipoles. Photometric variations yield fluctuations of both the angular and radial survey selection functions. Those are directly inferred from data, imposing integral constraints which we model consistently. The full data set has only a weak preference for a BAO feature ($1.4\sigma$). At the effective redshift $z_{\rm eff} = 0.845$ we measure $D_{\rm V}(z_{\rm eff})/r_{\rm drag} = 18.33_{-0.62}^{+0.57}$, with $D_{\rm V}$ the volume-averaged distance and $r_{\rm drag}$ the comoving sound horizon at the drag epoch. In combination with the RSD measurement, at $z_{\rm eff} = 0.85$ we find $f\sigma_8(z_{\rm eff}) = 0.289_{-0.096}^{+0.085}$, with $f$ the growth rate of structure and $\sigma_8$ the normalisation of the linear power spectrum, $D_{\rm H}(z_{\rm eff})/r_{\rm drag} = 20.0_{-2.2}^{+2.4}$ and $D_{\rm M}(z_{\rm eff})/r_{\rm drag} = 19.17 \pm 0.99$ with $D_{\rm H}$ and $D_{\rm M}$ the Hubble and comoving angular distances, respectively. These results are in agreement with those obtained in configuration space, thus allowing a consensus measurement of $f\sigma_8(z_{\rm eff}) = 0.315 \pm 0.095$, $D_{\rm H}(z_{\rm eff})/r_{\rm drag} = 19.6_{-2.1}^{+2.2}$ and $D_{\rm M}(z_{\rm eff})/r_{\rm drag} = 19.5 \pm 1.0$. This measurement is consistent with a flat $\Lambda$CDM model with Planck parameters., Comment: 31 pages, 17 figures. A summary of all SDSS BAO and RSD measurements with accompanying legacy figures can be found here: https://sdss.org/science/final-bao-and-rsd-measurements. The full cosmological interpretation of these measurements can be found here: https://sdss.org/science/cosmology-results-from-eboss. Matches version accepted by MNRAS
Published: 2020
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39. Impact of Relativistic Effects on the Primordial Non-Gaussianity Signature in the Large-Scale Clustering of Quasars

Author: Wang, Mike Shengbo, Beutler, Florian, and Bacon, David
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: Relativistic effects in clustering observations have been shown to introduce scale-dependent corrections to the galaxy over-density field on large scales, which may hamper the detection of primordial non-Gaussianity $f_\textrm{NL}$ through the scale-dependent halo bias. The amplitude of relativistic corrections depends not only on the cosmological background expansion, but also on the redshift evolution and sensitivity to the luminosity threshold of the tracer population being examined, as parametrised by the evolution bias $b_\textrm{e}$ and magnification bias $s$. In this work, we propagate luminosity function measurements from the extended Baryon Oscillation Spectroscopic Survey (eBOSS) to $b_\textrm{e}$ and $s$ for the quasar (QSO) sample, and thereby derive constraints on relativistic corrections to its power spectrum multipoles. Although one could mitigate the impact on the $f_\textrm{NL}$ signature by adjusting the redshift range or the luminosity threshold of the tracer sample being considered, we suggest that, for future surveys probing large cosmic volumes, relativistic corrections should be forward modelled from the tracer luminosity function including its uncertainties. This will be important to quasar clustering measurements on scales $k \sim 10^{-3} h \, \textrm{Mpc}^{-1}$ in upcoming surveys such as the Dark Energy Spectroscopic Instrument (DESI), where relativistic corrections can overwhelm the expected $f_\textrm{NL}$ signature at low redshifts $z \lesssim 1$ and become comparable to $f_\textrm{NL} \simeq 1$ in the power spectrum quadrupole at redshifts $z \gtrsim 2.5$., Comment: Published by MNRAS, 7 figures and 1 table; changes made after peer review; public code HorizonGRound available at http://github.com/MikeSWang/HorizonGRound
Published: 2020
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40. Modeling relativistic contributions to the halo power spectrum dipole

Author: Beutler, Florian and Di Dio, Enea
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics, General Relativity and Quantum Cosmology
Abstract: We study the power spectrum dipole of an N-body simulation which includes relativistic effects through ray-tracing and covers the low redshift Universe up to $z_{\rm max} = 0.465$ (RayGalGroup simulation). We model relativistic corrections as well as wide-angle, evolution, window and lightcone effects. Our model includes all relativistic corrections up to third-order including third-order bias expansion. We consider all terms which depend linearly on $\mathcal{H}/k$ (weak field approximation). We also study the impact of 1-loop corrections to the matter power spectrum for the gravitational redshift and transverse Doppler effect. We found wide-angle and window function effects to significantly contribute to the dipole signal. When accounting for all contributions, our dipole model can accurately capture the gravitational redshift and Doppler terms up to the smallest scales included in our comparison ($k=0.48\,h{\rm Mpc}^{-1}$), while our model for the transverse Doppler term is less accurate. We find the Doppler term to be the dominant signal for this low redshift sample. We use Fisher matrix forecasts to study the potential for the future Dark Energy Spectroscopic Instrument (DESI) to detect relativistic contributions to the power spectrum dipole. A conservative estimate suggests that the DESI-BGS sample should be able to have a detection of at least $4.4\sigma$, while more optimistic estimates find detections of up to $10\sigma$. Detecting these effects in the galaxy distribution allows new tests of gravity on the largest scales, providing an interesting additional science case for galaxy survey experiments., Comment: 45 pages, 10 figures
Published: 2020
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41. The relativistic galaxy number counts in the weak field approximation

Author: Di Dio, Enea and Beutler, Florian
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics, General Relativity and Quantum Cosmology
Abstract: We present a novel approach to compute systematically the relativistic projection effects at any order in perturbation theory within the weak field approximation. In this derivation the galaxy number counts is written completely in terms of the redshift perturbation. The relativistic effects break the symmetry along the line-of-sight and they source, contrarily to the standard perturbation theory, the odd multipoles of the matter power spectrum or 2-point correlation function, providing a unique signature for their detection in Large Scale Structure surveys. We show that our approach agrees with previous derivations (up to third order) of relativistic effects and, for the first time, we derive a model for the transverse Doppler effect. Moreover, we show that in the Newtonian limit this approach is consistent with standard perturbation theory at any order., Comment: 17 pages, v2: minor modifications to match published version
Published: 2020
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42. Ensemble Slice Sampling: Parallel, black-box and gradient-free inference for correlated & multimodal distributions

Author: Karamanis, Minas and Beutler, Florian
Subjects: Statistics - Machine Learning, Astrophysics - Cosmology and Nongalactic Astrophysics, Astrophysics - Instrumentation and Methods for Astrophysics, Computer Science - Machine Learning, Statistics - Computation
Abstract: Slice Sampling has emerged as a powerful Markov Chain Monte Carlo algorithm that adapts to the characteristics of the target distribution with minimal hand-tuning. However, Slice Sampling's performance is highly sensitive to the user-specified initial length scale hyperparameter and the method generally struggles with poorly scaled or strongly correlated distributions. This paper introduces Ensemble Slice Sampling (ESS), a new class of algorithms that bypasses such difficulties by adaptively tuning the initial length scale and utilising an ensemble of parallel walkers in order to efficiently handle strong correlations between parameters. These affine-invariant algorithms are trivial to construct, require no hand-tuning, and can easily be implemented in parallel computing environments. Empirical tests show that Ensemble Slice Sampling can improve efficiency by more than an order of magnitude compared to conventional MCMC methods on a broad range of highly correlated target distributions. In cases of strongly multimodal target distributions, Ensemble Slice Sampling can sample efficiently even in high dimensions. We argue that the parallel, black-box and gradient-free nature of the method renders it ideal for use in scientific fields such as physics, astrophysics and cosmology which are dominated by a wide variety of computationally expensive and non-differentiable models., Comment: Published in Statistics & Computing; 18 pages, 11 figures, 2 tables; Code available https://github.com/minaskar/zeus
Published: 2020
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43. Testing Low-Redshift Cosmic Acceleration with Large-Scale Structure

Author: Nadathur, Seshadri, Percival, Will J., Beutler, Florian, and Winther, Hans
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: We examine the cosmological implications of measurements of the void-galaxy cross-correlation at redshift $z=0.57$ combined with baryon acoustic oscillation (BAO) data at $0.110\sigma$ significance from these data alone, independent of the cosmic microwave background and supernovae. Using a nucleosynthesis prior on $\Omega_bh^2$, we measure the Hubble constant to be $H_0=72.3\pm1.9\;{\rm km\,s}^{-1}{\rm Mpc}^{-1}$ from BAO+voids at $z<2$, and $H_0=69.0\pm1.2\;{\rm km\,s}^{-1}{\rm Mpc}^{-1}$ when adding Lyman-$\alpha$ BAO at $z=2.34$, both independent of the CMB. Adding voids to CMB, BAO and supernova data greatly improves measurement of the dark energy equation of state, increasing the figure of merit by >40%, but remaining consistent with flat flat $\Lambda$ cold dark matter., Comment: 7 pages, 5 figures. Accepted for publication in PRL. v2: minor edits to text in response to review
Published: 2020
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44. Prospects for Fundamental Physics with LISA

Author: Barausse, Enrico, Berti, Emanuele, Hertog, Thomas, Hughes, Scott A., Jetzer, Philippe, Pani, Paolo, Sotiriou, Thomas P., Tamanini, Nicola, Witek, Helvi, Yagi, Kent, Yunes, Nicolas, Abdelsalhin, T., Achucarro, A., Aelst, K. V., Afshordi, N., Akcay, S., Annulli, L., Arun, K. G., Ayuso, I., Baibhav, V., Baker, T., Bantilan, H., Barreiro, T., Barrera-Hinojosa, C., Bartolo, N., Baumann, D., Belgacem, E., Bellini, E., Bellomo, N., Ben-Dayan, I., Bena, I., Benkel, R., Bergshoefs, E., Bernard, L., Bernuzzi, S., Bertacca, D., Besancon, M., Beutler, F., Beyer, F., Bhagwat, S., Bicak, J., Biondini, S., Bize, S., Blas, D., Boehmer, C., Boller, K., Bonga, B., Bonvin, C., Bosso, P., Bozzola, G., Brax, P., Breitbach, M., Brito, R., Bruni, M., Brügmann, B., Bulten, H., Buonanno, A., Burke, A. O., Burko, L. M., Burrage, C., Cabral, F., Calcagni, G., Caprini, C., Cárdenas-Avendaño, A., Celoria, M., Chatziioannou, K., Chernoff, D., Clough, K., Coates, A., Comelli, D., Compère, G., Croon, D., Cruces, D., Cusin, G., Dalang, C., Danielsson, U., Das, S., Datta, S., de Boer, J., De Luca, V., De Rham, C., Desjacques, V., Destounis, K., Di Filippo, F., Dima, A., Dimastrogiovanni, E., Dolan, S., Doneva, D., Duque, F., Durrer, R., East, W., Easther, R., Elley, M., Ellis, J. R., Emparan, R., Ezquiaga, J. M., Fairbairn, M., Fairhurst, S., Farmer, H. F., Fasiello, M. R., Ferrari, V., Ferreira, P. G., Ficarra, G., Figueras, P., Fisenko, S., Foffa, S., Franchini, N., Franciolini, G., Fransen, K., Frauendiener, J., Frusciante, N., Fujita, R., Gair, J., Ganz, A., Garcia, P., Garcia-Bellido, J., Garriga, J., Geiger, R., Geng, C., Gergely, L. Á., Germani, C., Gerosa, D., Giddings, S. B., Gourgoulhon, E., Grandclement, P., Graziani, L., Gualtieri, L., Haggard, D., Haino, S., Halburd, R., Han, W. -B., Hawken, A. J., Hees, A., Heng, I. S., Hennig, J., Herdeiro, C., Hervik, S., Holten, J. v., Hoyle, C. J. D., Hu, Y., Hull, M., Ikeda, T., Isi, M., Jenkins, A., Julié, F., Kajfasz, E., Kalaghatgi, C., Kaloper, N., Kamionkowski, M., Karas, V., Kastha, S., Keresztes, Z., Kidder, L., Kimpson, T., Klein, A., Klioner, S., Kokkotas, K., Kolesova, H., Kolkowitz, S., Kopp, J., Koyama, K., Krishnendu, N. V., Kroon, J. A. V., Kunz, M., Lahav, O., Landragin, A., Lang, R. N., Poncin-Lafitte, C. Le, Lemos, J., Li, B., Liberati, S., Liguori, M., Lin, F., Liu, G., Lobo, F. S. N., Loll, R., Lombriser, L., Lovelace, G., Macedo, R. P., Madge, E., Maggio, E., Maggiore, M., Marassi, S., Marcoccia, P., Markakis, C., Martens, W., Martinovic, K., Martins, C. J. A. P., Maselli, A., Mastrogiovanni, S., Matarrese, S., Matas, A., Mavromatos, N. E., Mazumdar, A., Meerburg, P. D., Megias, E., Miller, J., Mimoso, J. P., Mittnacht, L., Montero, M. M., Moore, B., Martin-Moruno, P., Musco, I., Nakano, H., Nampalliwar, S., Nardini, G., Nielsen, A., Novák, J., Nunes, N. J., Okounkova, M., Oliveri, R., Oppizzi, F., Orlando, G., Oshita, N., Pappas, G., Paschalidis, V., Peiris, H., Peloso, M., Perkins, S., Pettorino, V., Pikovski, I., Pilo, L., Podolsky, J., Pontzen, A., Prabhat, S., Pratten, G., Prokopec, T., Prouza, M., Qi, H., Raccanelli, A., Rajantie, A., Randall, L., Raposo, G., Raymond, V., Renaux-Petel, S., Ricciardone, A., Riotto, A., Robson, T., Roest, D., Rollo, R., Rosofsky, S., Ruan, J. J., Rubiera-García, D., Ruiz, M., Rusu, M., Sabatie, F., Sago, N., Sakellariadou, M., Saltas, I. D., Sberna, L., Sathyaprakash, B., Scheel, M., Schmidt, P., Schutz, B., Schwaller, P., Shao, L., Shapiro, S. L., Shoemaker, D., Silva, A. d., Simpson, C., Sopuerta, C. F., Spallicci, A., Stefanek, B. A., Stein, L., Stergioulas, N., Stott, M., Sutton, P., Svarc, R., Tagoshi, H., Tahamtan, T., Takeda, H., Tanaka, T., Tantilian, G., Tasinato, G., Tattersall, O., Teukolsky, S., Tiec, A. L., Theureau, G., Trodden, M., Tolley, A., Toubiana, A., Traykova, D., Tsokaros, A., Unal, C., Unnikrishnan, C. S., Vagenas, E. C., Valageas, P., Vallisneri, M., Brand, J. Van den, Broeck, C. Van den, van de Meent, M., Vanhove, P., Varma, V., Veitch, J., Vercnocke, B., Verde, L., Vernieri, D., Vernizzi, F., Vicente, R., Vidotto, F., Visser, M., Vlah, Z., Vretinaris, S., Völkel, S., Wang, Q., Wang, Yu-Tong, Werner, M. C., Westernacher, J., Weygaert, R. v. d., Wiltshire, D., Wiseman, T., Wolf, P., Wu, K., Yamada, K., Yang, H., Yi, L., Yue, X., Yvon, D., Zilhão, M., Zimmerman, A., and Zumalacarregui, M.
Subjects: General Relativity and Quantum Cosmology
Abstract: In this paper, which is of programmatic rather than quantitative nature, we aim to further delineate and sharpen the future potential of the LISA mission in the area of fundamental physics. Given the very broad range of topics that might be relevant to LISA, we present here a sample of what we view as particularly promising directions, based in part on the current research interests of the LISA scientific community in the area of fundamental physics. We organize these directions through a "science-first" approach that allows us to classify how LISA data can inform theoretical physics in a variety of areas. For each of these theoretical physics classes, we identify the sources that are currently expected to provide the principal contribution to our knowledge, and the areas that need further development. The classification presented here should not be thought of as cast in stone, but rather as a fluid framework that is amenable to change with the flow of new insights in theoretical physics., Comment: 22 pages, 1 figure, to appear in General Relativity and Gravitation
Published: 2020
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45. The Sixteenth Data Release of the Sloan Digital Sky Surveys: First Release from the APOGEE-2 Southern Survey and Full Release of eBOSS Spectra

Author: Ahumada, Romina, Prieto, Carlos Allende, Almeida, Andres, Anders, Friedrich, Anderson, Scott F., Andrews, Brett H., Anguiano, Borja, Arcodia, Riccardo, Armengaud, Eric, Aubert, Marie, Avila, Santiago, Avila-Reese, Vladimir, Badenes, Carles, Balland, Christophe, Barger, Kat, Barrera-Ballesteros, Jorge K., Basu, Sarbani, Bautista, Julian, Beaton, Rachael L., Beers, Timothy C., Benavides, B. Izamar T., Bender, Chad F., Bernardi, Mariangela, Bershady, Matthew, Beutler, Florian, Bidin, Christian Moni, Bird, Jonathan, Bizyaev, Dmitry, Blanc, Guillermo A., Blanton, Michael R., Boquien, Mederic, Borissova, Jura, Bovy, Jo, Brandt, W. N., Brinkmann, Jonathan, Brownstein, Joel R., Bundy, Kevin, Bureau, Martin, Burgasser, Adam, Burtin, Etienne, Cano-Diaz, Mariana, Capasso, Raffaella, Cappellari, Michele, Carrera, Ricardo, Chabanier, Solene, Chaplin, William, Chapman, Michael, Cherinka, Brian, Chiappini, Cristina, Choi, Peter Doohyun, Chojnowski, S. Drew, Chung, Haeun, Clerc, Nicolas, Coffey, Damien, Comerford, Julia M., Comparat, Johan, da Costa, Luiz, Cousinou, Marie-Claude, Covey, Kevin, Crane, Jeffrey D., Cunha, Katia, Ilha, Gabriele da Silva, Dai, Yu Sophia, Damsted, Sanna B., Darling, Jeremy, Davidson Jr., James W., Davies, Roger, Dawson, Kyle, De, Nikhil, de la Macorra, Axel, De Lee, Nathan, Queiroz, Anna Barbara de Andrade, Machado, Alice Deconto, de la Torre, Sylvain, Dell'Agli, Flavia, Bourboux, Helion du Mas des, Diamond-Stanic, Aleksandar M., Dillon, Sean, Donor, John, Drory, Niv, Duckworth, Chris, Dwelly, Tom, Ebelke, Garrett, Eftekharzadeh, Sarah, Eigenbrot, Arthur Davis, Elsworth, Yvonne P., Eracleous, Mike, Erfanianfar, Ghazaleh, Escoffier, Stephanie, Fan, Xiaohui, Farr, Emily, Fernandez-Trincado, Jose G., Feuillet, Diane, Finoguenov, Alexis, Fofie, Patricia, Fraser-McKelvie, Amelia, Frinchaboy, Peter M., Fromenteau, Sebastien, Fu, Hai, Galbany, Lluis, Garcia, Rafael A., Garcia-Hernandez, D. A., Oehmichen, Luis Alberto Garma, Ge, Junqiang, Maia, Marcio Antonio Geimba, Geisler, Doug, Gelfand, Joseph, Goddy, Julian, Goff, Jean-Marc Le, Gonzalez-Perez, Violeta, Grabowski, Kathleen, Green, Paul, Grier, Catherine J., Guo, Hong, Guy, Julien, Harding, Paul, Hasselquist, Sten, Hawken, Adam James, Hayes, Christian R., Hearty, Fred, Hekker, S., Hogg, David W., Holtzman, Jon, Horta, Danny, Hou, Jiamin, Hsieh, Bau-Ching, Huber, Daniel, Hunt, Jason A. S., Chitham, J. Ider, Imig, Julie, Jaber, Mariana, Angel, Camilo Eduardo Jimenez, Johnson, Jennifer A., Jones, Amy M., Jonsson, Henrik, Jullo, Eric, Kim, Yerim, Kinemuchi, Karen, Kirkpatrick IV, Charles C., Kite, George W., Klaene, Mark, Kneib, Jean-Paul, Kollmeier, Juna A., Kong, Hui, Kounkel, Marina, Krishnarao, Dhanesh, Lacerna, Ivan, Lan, Ting-Wen, Lane, Richard R., Law, David R., Leung, Henry W., Lewis, Hannah, Li, Cheng, Lian, Jianhui, Lin, Lihwai, Long, Dan, Longa-Pena, Penelope, Lundgren, Britt, Lyke, Brad W., Mackereth, J. Ted, MacLeod, Chelsea L., Majewski, Steven R., Manchado, Arturo, Maraston, Claudia, Martini, Paul, Masseron, Thomas, Masters, Karen L., Mathur, Savita, McDermid, Richard M., Merloni, Andrea, Merrifield, Michael, Meszaros, Szabolcs, Miglio, Andrea, Minniti, Dante, Minsley, Rebecca, Miyaji, Takamitsu, Mohammad, Faizan Gohar, Mosser, Benoit, Mueller, Eva-Maria, Muna, Demitri, Munoz-Gutierrez, Andrea, Myers, Adam D., Nadathur, Seshadri, Nair, Preethi, Nandra, Kirpal, Nascimento, Janaina Correa do, Nevin, Rebecca Jean, Newman, Jeffrey A., Nidever, David L., Nitschelm, Christian, Noterdaeme, Pasquier, O'Connell, Julia E., Olmstead, Matthew D, Oravetz, Daniel, Oravetz, Audrey, Osorio, Yeisson, Pace, Zachary J., Padilla, Nelson, Palanque-Delabrouille, Nathalie, Palicio, Pedro A., Pan, Hsi-An, Pan, Kaike, Parker, James, Paviot, Romain, Peirani, Sebastien, Ramrez, Karla Pena, Penny, Samantha, Percival, Will J., Perez-Fournon, Ismael, Perez-Rafols, Ignasi, Petitjean, Patrick, Pieri, Matthew M., Pinsonneault, Marc, Poovelil, Vijith Jacob, Povick, Joshua Tyler, Prakash, Abhishek, Price-Whelan, Adrian M., Raddick, M. Jordan, Raichoor, Anand, Ray, Amy, Rembold, Sandro Barboza, Rezaie, Mehdi, Riffel, Rogemar A., Riffel, Rogerio, Rix, Hans-Walter, Robin, Annie C., Roman-Lopes, A., Roman-Zuniga, Carlos, Rose, Benjamin, Ross, Ashley J., Rossi, Graziano, Rowlands, Kate, Rubin, Kate H. R., Salvato, Mara, Sanchez, Ariel G., Sanchez-Menguiano, Laura, Sanchez-Gallego, Jose R., Sayres, Conor, Schaefer, Adam, Schiavon, Ricardo P., Schimoia, Jaderson S., Schlafly, Edward, Schlegel, David, Schneider, Donald P., Schultheis, Mathias, Schwope, Axel, Seo, Hee-Jong, Serenelli, Aldo, Shafieloo, Arman, Shamsi, Shoaib Jamal, Shao, Zhengyi, Shen, Shiyin, Shetrone, Matthew, Shirley, Raphael, Aguirre, Victor Silva, Simon, Joshua D., Skrutskie, M. F., Slosar, Anze, Smethurst, Rebecca, Sobeck, Jennifer, Sodi, Bernardo Cervantes, Souto, Diogo, Stark, David V., Stassun, Keivan G., Steinmetz, Matthias, Stello, Dennis, Stermer, Julianna, Storchi-Bergmann, Thaisa, Streblyanska, Alina, Stringfellow, Guy S., Stutz, Amelia, Suarez, Genaro, Sun, Jing, Taghizadeh-Popp, Manuchehr, Talbot, Michael S., Tayar, Jamie, Thakar, Aniruddha R., Theriault, Riley, Thomas, Daniel, Thomas, Zak C., Tinker, Jeremy, Tojeiro, Rita, Toledo, Hector Hernandez, Tremonti, Christy A., Troup, Nicholas W., Tuttle, Sarah, Unda-Sanzana, Eduardo, Valentini, Marica, Vargas-Gonzalez, Jaime, Vargas-Magana, Mariana, Vazquez-Mata, Jose Antonio, Vivek, M., Wake, David, Wang, Yuting, Weaver, Benjamin Alan, Weijmans, Anne-Marie, Wild, Vivienne, Wilson, John C., Wilson, Robert F., Wolthuis, Nathan, Wood-Vasey, W. M., Yan, Renbin, Yang, Meng, Yeche, Christophe, Zamora, Olga, Zarrouk, Pauline, Zasowski, Gail, Zhang, Kai, Zhao, Cheng, Zhao, Gongbo, Zheng, Zheng, Zhu, Guangtun, and Zou, Hu
Subjects: Astrophysics - Astrophysics of Galaxies, Astrophysics - Cosmology and Nongalactic Astrophysics, Astrophysics - Instrumentation and Methods for Astrophysics
Abstract: This paper documents the sixteenth data release (DR16) from the Sloan Digital Sky Surveys; the fourth and penultimate from the fourth phase (SDSS-IV). This is the first release of data from the southern hemisphere survey of the Apache Point Observatory Galactic Evolution Experiment 2 (APOGEE-2); new data from APOGEE-2 North are also included. DR16 is also notable as the final data release for the main cosmological program of the Extended Baryon Oscillation Spectroscopic Survey (eBOSS), and all raw and reduced spectra from that project are released here. DR16 also includes all the data from the Time Domain Spectroscopic Survey (TDSS) and new data from the SPectroscopic IDentification of ERosita Survey (SPIDERS) programs, both of which were co-observed on eBOSS plates. DR16 has no new data from the Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey (or the MaNGA Stellar Library "MaStar"). We also preview future SDSS-V operations (due to start in 2020), and summarize plans for the final SDSS-IV data release (DR17)., Comment: DR16 release: Monday Dec 9th 2019. This is the alphabetical order SDSS-IV collaboration data release paper. 25 pages, 6 figures, accepted by ApJS on 11th May 2020. Minor changes clarify or improve text and figures relative to v1
Published: 2019
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46. Efficient Cosmological Analysis of the SDSS/BOSS data from the Effective Field Theory of Large-Scale Structure

Author: Colas, Thomas, D'Amico, Guido, Senatore, Leonardo, Zhang, Pierre, and Beutler, Florian
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics, General Relativity and Quantum Cosmology, High Energy Physics - Phenomenology, High Energy Physics - Theory
Abstract: The precision of the cosmological data allows us to accurately approximate the predictions for cosmological observables by Taylor expanding up to a low order the dependence on the cosmological parameters around a reference cosmology. By applying this observation to the redshift-space one-loop galaxy power spectrum of the Effective Field Theory of Large-Scale Structure, we analyze the BOSS DR12 data by scanning over all the parameters of $\Lambda$CDM cosmology with massive neutrinos. We impose several sets of priors, the widest of which is just a Big Bang Nucleosynthesis prior on the current fractional energy density of baryons, $\Omega_b h^2$, and a bound on the sum of neutrino masses to be less than 0.9 eV. In this case we measure the primordial amplitude of the power spectrum, $A_s$, the abundance of matter, $\Omega_m$, the Hubble parameter, $H_0$, and the tilt of the primordial power spectrum, $n_s$, to about $19\%$, $5.7\%$, $2.2\%$ and $7.3\%$ respectively, obtaining $\ln ( 10^{10} A_s) =2.91\pm 0.19$, $\Omega_m=0.314\pm 0.018$, $H_0=68.7\pm 1.5$ km/(s Mpc) and $n_s=0.979\pm 0.071$ at $68\%$ confidence level. A public code is released with this preprint., Comment: 15 + 10 pages, 15 figures. Code publicly available. Removed prior on the tilt, improved presentation and accuracy
Published: 2019
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47. The Cosmological Analysis of the SDSS/BOSS data from the Effective Field Theory of Large-Scale Structure

Author: D'Amico, Guido, Gleyzes, Jérôme, Kokron, Nickolas, Markovic, Dida, Senatore, Leonardo, Zhang, Pierre, Beutler, Florian, and Gil-Marín, Héctor
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics, General Relativity and Quantum Cosmology, High Energy Physics - Phenomenology, High Energy Physics - Theory
Abstract: The Effective Field Theory of Large-Scale Structure (EFTofLSS) is a formalism that allows us to predict the clustering of Cosmological Large-Scale Structure in the mildly non-linear regime in an accurate and reliable way. After validating our technique against several sets of numerical simulations, we perform the analysis for the cosmological parameters of the DR12 BOSS data. We assume $\Lambda$CDM, a fixed value of the baryon/dark-matter ratio, $\Omega_b/\Omega_c$, and of the tilt of the primordial power spectrum, $n_s$, and no significant input from numerical simulations. By using the one-loop power spectrum multipoles, we measure the primordial amplitude of the power spectrum, $A_s$, the abundance of matter, $\Omega_m$, and the Hubble parameter, $H_0$, to about $13\%$, $3.2\%$ and $3.2\%$ respectively, obtaining $\ln(10^{10}As)=2.72\pm 0.13$, $\Omega_m=0.309\pm 0.010$, $H_0=68.5\pm 2.2$ km/(s Mpc) at 68\% confidence level. If we then add a CMB prior on the sound horizon, the error bar on $H_0$ is reduced to $1.6\%$. These results are a substantial qualitative and quantitative improvement with respect to former analyses, and suggest that the EFTofLSS is a powerful instrument to extract cosmological information from Large-Scale Structure., Comment: 78 pages, 27 figures
Published: 2019
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48. Perturbation theory approach to predict the covariance matrices of the galaxy power spectrum and bispectrum in redshift space

Author: Sugiyama, Naonori S., Saito, Shun, Beutler, Florian, and Seo, Hee-Jong
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: In this paper, we predict the covariance matrices of both the power spectrum and the bispectrum, including full non-Gaussian contributions, redshift space distortions, linear bias effects and shot-noise corrections, using perturbation theory (PT). To quantify the redshift-space distortion effect, we focus mainly on the monopole and quadrupole components of both the power and bispectra. We, for the first time, compute the 5- and 6-point spectra to predict the cross-covariance between the power and bispectra, and the auto-covariance of the bispectrum in redshift space. We test the validity of our calculations by comparing them with the covariance matrices measured from the MultiDark-Patchy mock catalogues that are designed to reproduce the galaxy clustering measured from the Baryon Oscillation Spectroscopic Survey Data Release 12. We argue that the simple, leading-order perturbation theory works because the shot-noise corrections for the Patchy mocks are more dominant than other higher-order terms we ignore. In the meantime, we confirm some discrepancies in the comparison, especially of the cross-covariance. We discuss potential sources of such discrepancies. We also show that our PT model reproduces well the cumulative signal-to-noise of the power spectrum and the bispectrum as a function of maximum wavenumber, implying that our PT model captures successfully essential contributions to the covariance matrices., Comment: 30 pages, 8 figures
Published: 2019
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49. The Dark Energy Spectroscopic Instrument (DESI)

Author: Levi, Michael E., Allen, Lori E., Raichoor, Anand, Baltay, Charles, BenZvi, Segev, Beutler, Florian, Bolton, Adam, Castander, Francisco J., Chuang, Chia-Hsun, Cooper, Andrew, Cuby, Jean-Gabriel, Dey, Arjun, Eisenstein, Daniel, Fan, Xiaohui, Flaugher, Brenna, Frenk, Carlos, Gonzalez-Morales, Alma X., Graur, Or, Guy, Julien, Habib, Salman, Honscheid, Klaus, Juneau, Stephanie, Kneib, Jean-Paul, Lahav, Ofer, Lang, Dustin, Leauthaud, Alexie, Lusso, Betta, de la Macorra, Axel, Manera, Marc, Martini, Paul, Mao, Shude, Newman, Jeffrey A., Palanque-Delabrouille, Nathalie, Percival, Will J., Prieto, Carlos Allende, Rockosi, Constance M., Ruhlmann-Kleider, Vanina, Schlegel, David, Seo, Hee-Jong, Song, Yong-Seon, Tarle, Greg, Wechsler, Risa, Weinberg, David, Yeche, Christophe, and Zu, Ying
Subjects: Astrophysics - Instrumentation and Methods for Astrophysics, Astrophysics - Cosmology and Nongalactic Astrophysics, Astrophysics - Astrophysics of Galaxies, Astrophysics - High Energy Astrophysical Phenomena, Astrophysics - Solar and Stellar Astrophysics
Abstract: We present the status of the Dark Energy Spectroscopic Instrument (DESI) and its plans and opportunities for the coming decade. DESI construction and its initial five years of operations are an approved experiment of the US Department of Energy and is summarized here as context for the Astro2020 panel. Beyond 2025, DESI will require new funding to continue operations. We expect that DESI will remain one of the world's best facilities for wide-field spectroscopy throughout the decade. More about the DESI instrument and survey can be found at https://www.desi.lbl.gov., Comment: 9-page APC White Paper submitted to the Astro2020 Decadal Survey. To be published in BAAS. More about the DESI instrument and survey can be found at https://www.desi.lbl.gov
Published: 2019

50. Primordial Features from Linear to Nonlinear Scales

Author: Beutler, Florian, Biagetti, Matteo, Green, Daniel, Slosar, Anže, and Wallisch, Benjamin
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics, High Energy Physics - Phenomenology, High Energy Physics - Theory
Abstract: Sharp features in the primordial power spectrum are a powerful window into the inflationary epoch. To date, the cosmic microwave background (CMB) has offered the most sensitive avenue to search for these signatures. In this paper, we demonstrate the power of large-scale structure observations to surpass the CMB as a probe of primordial features. We show that the signatures in galaxy surveys can be separated from the broadband power spectrum and are as robust to the nonlinear evolution of matter as the standard baryon acoustic oscillations. As a result, analyses can exploit a significant range of scales beyond the linear regime available in the datasets. We develop a feature search for large-scale structure, apply it to the final data release of the Baryon Oscillation Spectroscopic Survey and find new bounds on oscillatory features that exceed the sensitivity of Planck for a significant range of frequencies. Moreover, we forecast that the next generation of galaxy surveys, such as DESI and Euclid, will be able to improve current constraints by up to an order of magnitude over an expanded frequency range., Comment: 60 pages, 20 figures, 2 tables; v2: minor changes
Published: 2019
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