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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. Hydrological control of rock carbon fluxes from shale weathering

Author: Wan, Jiamin, Tokunaga, Tetsu K, Beutler, Curtis A, Newman, Alexander W, Dong, Wenming, Bill, Markus, Brown, Wendy S, Henderson, Amanda N, Tran, Anh Phuong, and Williams, Kenneth H
Subjects: Hydrology, Earth Sciences, Geology
Published: 2024

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

Author: Collaboration, DESI, Adame, AG, Aguilar, J, Ahlen, S, Alam, S, Aldering, G, Alexander, DM, 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, SF, BenZvi, S, Silva, L Beraldo E, Bermejo-Climent, JR, Berti, A, Besuner, R, Beutler, F, Bianchi, D, Blake, C, Blum, R, Bolton, AS, 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, FJ, Cervantes-Cota, JL, Chabanier, S, Chaussidon, E, Chaves-Montero, J, Chen, S, Chen, X, Chuang, C, Claybaugh, T, Cole, S, Cooper, AP, Cuceu, A, Davis, TM, 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, DJ, Elliott, A, Ereza, J, Escoffier, S, Fagrelius, P, Fan, X, Fanning, K, Fawcett, VA, Ferraro, S, Flaugher, B, Font-Ribera, A, Forero-Romero, JE, Forero-Sánchez, D, Frenk, CS, Gänsicke, BT, García, LÁ, García-Bellido, J, Garcia-Quintero, C, Garrison, LH, Gil-Marín, H, Golden-Marx, J, and Gontcho, S Gontcho A
Subjects: Astronomical Sciences, Physical Sciences, Astronomical and Space Sciences, Astronomy & Astrophysics, Astronomical sciences, Particle and high energy physics
Abstract: The Dark Energy Spectroscopic Instrument (DESI) completed its 5 month Survey Validation in 2021 May. 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.
Published: 2024

8. 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

9. 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

10. 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

11. 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

12. 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

13. 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

14. Shifting groundwater fluxes in bedrock fractures: Evidence from stream water radon and water isotopes

Author: Johnson, Keira, Christensen, John N, Gardner, W Payton, Sprenger, Matthias, Li, Li, Williams, Kenneth H, Carroll, Rosemary WH, Thiros, Nicholas, Brown, Wendy, Beutler, Curtis, Newman, Alexander, and Sullivan, Pamela L
Subjects: Hydrology, Earth Sciences, Geology, Groundwater surface water interactions, Tracer hydrology, Groundwater modeling, Groundwater discharge, Montane catchment, Environmental Engineering
Abstract: Geologic features (e.g., fractures and alluvial fans) can play an important role in the locations and volumes of groundwater discharge and degree of groundwater-surface water (GW-SW) interactions. However, the role of these features in controlling GW-SW dynamics and streamflow generation processes are not well constrained. GW-SW interactions and streamflow generation processes are further complicated by variability in precipitation inputs from summer and fall monsoon rains, as well as declines in snowpack and changing melt dynamics driven by warming temperatures. Using high spatial and temporal resolution radon and water stable isotope sampling and a 1D groundwater flux model, we evaluated how groundwater contributions and GW-SW interactions varied along a stream reach impacted by fractures (fractured-zone) and downstream of the fractured hillslope (non-fractured zone) in Coal Creek, a Colorado River headwater stream affected by summer monsoons. During early summer, groundwater contributions from the fractured zone were high, but declined throughout the summer. Groundwater contributions from the non-fractured zone were constant throughout the summer and became proportionally more important later in the summer. We hypothesize that groundwater in the non-fractured zone is dominantly sourced from a high-storage alluvial fan at the base of a tributary that is connected to Coal Creek throughout the summer and provides consistent groundwater influx. Water isotope data revealed that Coal Creek responds quickly to incoming precipitation early in the summer, and summer precipitation becomes more important for streamflow generation later in the summer. We quantified the change in catchment dynamic storage and found it negatively related to stream water isotope values, and positively related to modeled groundwater discharge and the ratio of fractured zone to non-fractured zone groundwater. We interpret these relationships as declining hydrologic connectivity throughout the summer leading to late summer streamflow supported predominantly by shallow flow paths, with variable response to drying from geologic features based on their storage. As groundwater becomes more important for sustaining summer flows, quantifying local geologic controls on groundwater inputs and their response to variable moisture conditions may become critical for accurate predictions of streamflow.
Published: 2024

15. Vision Transformer Model for Automated End-to-End Radiographic Assessment of Joint Damage in Psoriatic Arthritis

Author: Govind, Darshana, Gao, Zijun, Parmar, Chaitanya, Broos, Kenneth, Fountoulakis, Nicholas, Noonan, Lenore, Yamamoto, Shinobu, Zemlianskaia, Natalia, Meyer, Craig S., Scherer, Emily, Deman, Michael, Damasceno, Pablo, Murphy, Philip S., Rooney, Terence, Hsia, Elizabeth, Beutler, Anna, Janiczek, Robert, Yip, Stephen S. F., Standish, Kristopher, Goos, Gerhard, Series Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Xu, Xuanang, editor, Cui, Zhiming, editor, Rekik, Islem, editor, Ouyang, Xi, editor, and Sun, Kaicong, editor
Published: 2025
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16. Ultrasound innovations in abdominal radiology: multiparametic imaging in liver transplantation

Author: Chau, Samantha S., Beutler, Bryce D., Grant, Edward G., and Tchelepi, Hisham
Published: 2024
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17. Lrp10 suppresses IL7R limiting CD8 T cell homeostatic expansion and anti-tumor immunity

Author: Russell, Jamie, Chen, Luming, Liu, Aijie, Wang, Jianhui, Ghosh, Subarna, Zhong, Xue, Shi, Hexin, Beutler, Bruce, and Nair-Gill, Evan
Published: 2024
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18. A Tale of Two Catchments: Causality Analysis and Isotope Systematics Reveal Mountainous Watershed Traits That Regulate the Retention and Release of Nitrogen

Author: Bouskill, NJ, Newcomer, M, Carroll, RWH, Beutler, C, Bill, M, Brown, WS, Conrad, M, Dong, WS, Falco, N, Maavara, T, Newman, A, Sorensen, PO, Tokunaga, TK, Wan, J, Wainwright, H, Zhu, Q, Brodie, EL, and Williams, KH
Subjects: Earth Sciences, Geophysics, catchment science, nitrogen cycling, causality analysis, nitrate isotopes, cQ analysis, mountainous ecosystem
Abstract: Mountainous watersheds are characterized by variability in functional traits, including vegetation, topography, geology, and geomorphology, which determine nitrogen (N) retention, and release. Coal Creek and East River are two contrasting catchments within the Upper Colorado River Basin that differ markedly in total nitrate (NO3−) export. The East River has a diverse vegetation cover, and sinuous floodplains, and is underlain by N-rich marine shale. At 0.21 ± 0.14 kg ha−1 yr−1, the East River exports ∼3.5 times more NO3− relative to the conifer-dominated Coal Creek (0.06 ± 0.02 kg ha−1 yr−1). While this can partly be explained by the larger size of the East River, the distinct watershed traits of these two catchments imply different mechanisms controlling the aggregate N-export signal. A causality analysis shows physical and biogenic processes were critical in determining NO3− export from the East River catchment. Stable isotope ratios of NO3− (δ15NNO3 and δ18ONO3) show the East River catchment is a strong hotspot for biogeochemical processing of NO3− at the hillslope soil-saprolite. By contrast, the conifer-dominated Coal Creek retained nearly all atmospherically deposited NO3−, and its export was controlled by catchment hydrological traits (i.e., snowmelt periods and water table depth). The conservative N-cycle within Coal Creek is likely due to the abundance of conifer trees, and smaller riparian regions, retaining more NO3− overall and reduced processing prior to export. This study highlights the value of integrating isotope systematics to link watershed functional traits to mechanisms of watershed element retention and release.
Published: 2024

19. Validation of the Scientific Program for the Dark Energy Spectroscopic Instrument

Author: Collaboration, DESI, Adame, AG, Aguilar, J, Ahlen, S, Alam, S, Aldering, G, Alexander, DM, 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, SF, BenZvi, S, Silva, L Beraldo E, Bermejo-Climent, JR, Berti, A, Besuner, R, Beutler, F, Bianchi, D, Blake, C, Blum, R, Bolton, AS, 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, FJ, Cervantes-Cota, JL, Chabanier, S, Chaussidon, E, Chaves-Montero, J, Chen, S, Chen, X, Chuang, C, Claybaugh, T, Cole, S, Cooper, AP, Cuceu, A, Davis, TM, 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, DJ, Elliott, A, Escoffier, S, Fagrelius, P, Fan, X, Fanning, K, Fawcett, VA, Ferraro, S, Ereza, J, Flaugher, B, Font-Ribera, A, Forero-Sánchez, D, Forero-Romero, JE, Frenk, CS, Gänsicke, BT, García, LÁ, García-Bellido, J, Garcia-Quintero, C, Garrison, LH, Gil-Marín, H, Golden-Marx, J, Gontcho, S Gontcho A, and Gonzalez-Morales, AX
Subjects: Astronomical Sciences, Physical Sciences, Astronomical and Space Sciences, Astronomy & Astrophysics, Astronomical sciences, Particle and high energy physics
Abstract: The Dark Energy Spectroscopic Instrument (DESI) was designed to conduct a survey covering 14,000 deg2 over 5 yr to constrain the cosmic expansion history through precise measurements of baryon acoustic oscillations (BAO). The scientific program for DESI was evaluated during a 5 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 Milky Way Survey (MWS), Bright Galaxy Survey (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 5 yr 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 SV covering 140 deg2 using the final target selection algorithms with exposures of a depth typical of the main survey. The SV indicates that DESI will be able to complete the full 14,000 deg2 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 < z < 1.9, and 0.46% over the redshift interval 1.9 < z < 3.5.
Published: 2024

20. Stream water sourcing from high-elevation snowpack inferred from stable isotopes of water: a novel application of d-excess values

Author: Sprenger, Matthias, Carroll, Rosemary WH, Marchetti, David, Bern, Carleton, Beria, Harsh, Brown, Wendy, Newman, Alexander, Beutler, Curtis, and Williams, Kenneth H
Subjects: Hydrology, Atmospheric Sciences, Physical Geography and Environmental Geoscience, Earth Sciences, Civil Engineering, Environmental Engineering, Physical geography and environmental geoscience, Geomatic engineering
Abstract: About 80 % of the precipitation at the Colorado River s headwaters is snow, and the resulting snowmeltdriven hydrograph is a crucial water source for about 40 million people. Snowmelt from alpine and subalpine snowpack contributes substantially to groundwater recharge and river flow. However, the dynamics of snowmelt progression are not well understood because observations of the highelevation snowpack are difficult due to challenging access in complex mountainous terrain as well as the cost and labor intensity of currently available methods. We present a novel approach to infer the processes and dynamics of highelevation snowmelt contributions predicated upon stable hydrogen and oxygen isotope ratios observed in streamflow. We show that deuterium-excess (d-excess) values of stream water could serve as a comparatively cost-effective proxy for a catchment-integrated signal of high-elevation snowmelt contributions to catchment runoff. We sampled stable hydrogen and oxygen isotope ratios of the precipitation, snowpack, and stream water in the East River, a headwater catchment of the Colorado River, and the stream water of larger catchments at sites on the Gunnison River and Colorado River. The d-excess of snowpack increased with elevation; the upper subalpine and alpine snowpack (> 3200 m) had substantially higher d-excess compared to lower elevations (< 3200 m) in the study area. The d-excess values of stream water reflected this because d-excess values increased as the higher-elevation snowpack contributed more to stream water generation later in the snowmelt/runoff season. End-member mixing analyses based on the d-excess data showed that the share of high-elevation snowmelt contributions within the snowmelt hydrograph was on average 44 % and generally increased during melt period progression, up to 70 %. The observed pattern was consistent during 6 years for the East River, and a similar relation was found for the larger catchments on the Gunnison and Colorado rivers. High-elevation snowpack contributions were found to be higher for years with lower snowpack and warmer spring temperatures. Thus, we conclude that the d-excess of stream water is a viable proxy to observe changes in high-elevation snowmelt contributions in catchments at various scales. Inter-catchment comparisons and temporal trends of the d-excess of stream water could therefore serve as a catchment-integrated measure to monitor if mountain systems rely on high-elevation water inputs more during snow drought compared to years of average snowpack depths.
Published: 2024

21. E3 ubiquitin ligase Herc3 deficiency leads to accumulation of subretinal microglia and retinal neurodegeneration

Author: Zegeye, Yeshumenesh, Aredo, Bogale, Yuksel, Seher, Kirman, Dogan Can, Kumar, Ashwani, Chen, Bo, Turpin, Emily, Shresta, Sangita, He, Yu-Guang, Gautron, Laurent, Tang, Miao, Li, Xiaohong, DiCesare, Sophia M., Hulleman, John D., Xing, Chao, Ludwig, Sara, Moresco, Eva Marie Y., Beutler, Bruce A., and Ufret-Vincenty, Rafael L.
Published: 2024
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22. 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

23. 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

24. 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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25. 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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26. 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

27. 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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28. 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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29. 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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30. 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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31. First test of the consistency relation for the large-scale structure using the anisotropic three-point correlation function 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: Particle and High Energy Physics, Physical Sciences, large-scale structure of Universe, dark matter, cosmology: observations, cosmology: theory, Astronomical and Space Sciences, Astronomy & Astrophysics, Astronomical sciences, Particle and high energy physics, Space sciences
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 parameterize the breakdown of the LSS consistency relation in the squeezed limit by Es, which represents the ratio of the coefficients of the shift terms in the second-order density and velocity fluctuations. Es ≠ 1 is a sufficient condition under which the LSS consistency relation is violated. A novel aspect of this work is that we constrain Es by obtaining information about the non-linear 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, indicating that there is no violation of the LSS consistency relation in our analysis within the statistical errors. Our parameterization 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.
Published: 2023

32. 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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33. 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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34. Beyond traditional screening: Unveiling antibiotic potentials of actinomycetes in extreme environments

Author: Lyudmila P. Trenozhnikova, Gul B. Baimakhanova, Baiken B. Baimakhanova, Assya S. Balgimbayeva, Saule T. Daugaliyeva, Elmira R. Faizulina, Larisa G. Tatarkina, Gulzhan A. Spankulova, Dmitriy A. Berillo, and John A. Beutler
Subjects: Extreme habitats, Novel screening approach, Actinomycetes, Adaptability, Antibiotics, Science (General), Q1-390, Social sciences (General), H1-99
Abstract: Extreme ecosystems are a rich source of specialized metabolites that can overcome multidrug resistance. However, the low efficiency of traditional exploratory research in discovering new antibiotics remains a major limitation. We hypothesized that actinomycetes may have the ability to produce antibiotics in the extremes of a changing natural environment. This study introduces a novel approach to screening natural antibiotic producers from extreme habitats based on the relationship between organisms' adaptive traits and their metabolic activities. The antibacterial and antifungal properties of 667 actinomycete isolates, obtained from 160 samples of Kazakhstan's diverse extreme habitats, were studied under neutral, saline, and alkaline conditions against MRSA, E. coli, C. albicans, and A. niger. Among these isolates, 113 exhibited antibacterial properties, and 109 demonstrated antifungal properties. Notably, one-fifth of the antagonist isolates could produce active substances solely under extreme growth conditions. Fifty-three antagonistic actinomycetes, possessing these characteristics, have been categorized into groups and warrant further investigation as potential producers of new natural antibiotics. Molecular genetic analysis of the selected isolates revealed a high prevalence of Streptomyces and Nocardiopsis strains. Furthermore, 83.4 % of obtained isolates demonstrated the ability to thrive in all studied habitats—neutral, saline, and alkaline. 96.3 % of actinomycetes isolated from extreme environments exhibited adaptation to neutral conditions, highlighting their inherent versatility. Our findings underscore the nearly complete potential (99.7 %) of isolates to overcome the salinity barrier of 3.5 % NaCl, indicating their capacity to inhabit oceanic environments. We assert that actinomycetes should be perceived as a cohesive, globally adaptive group, capable of migrating between changing conditions or remaining stable within them. These studies lay the groundwork for the development of a new platform for screening natural antibiotics.
Published: 2024
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35. Vision Transformer Model for Automated End-to-End Radiographic Assessment of Joint Damage in Psoriatic Arthritis.

Author: Darshana Govind, Zijun Gao, Chaitanya Parmar, Kenneth Broos, Nicholas Fountoulakis, Lenore Noonan, Shinobu Yamamoto, Natalia Zemlianskaia, Craig S. Meyer, Emily Scherer, Michael Deman, Pablo F. Damasceno, Philip S. Murphy, Terence Rooney, Elizabeth Hsia, Anna Beutler, Robert L. Janiczek, Stephen S. F. Yip, and Kristopher Standish
Published: 2024
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36. 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: Particle and High Energy Physics, Physical Sciences, dark matter, large-scale structure of Universe, cosmology: observations, cosmology: theory, Astronomical and Space Sciences, Astronomy & Astrophysics, Astronomical sciences, Particle and high energy physics, Space sciences
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 non-linear 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 < ζt and -0.504 < ζs at the confidence level on the parameters characterizing the time evolution of the tidal and shift terms of the second-order velocity field. These constraints are consistent with GR predictions of ζt = 15/1144 and ζs = 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 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 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.
Published: 2023

37. 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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38. Dynamic molecular architecture and substrate recruitment of cullin3–RING E3 ligase CRL3KBTBD2

Author: Hu, Yuxia, Zhang, Zhao, Mao, Qiyu, Zhang, Xiang, Hao, Aihua, Xun, Yu, Wang, Yeda, Han, Lin, Zhan, Wuqiang, Liu, Qianying, Yin, Yue, Peng, Chao, Moresco, Eva Marie Y., Chen, Zhenguo, Beutler, Bruce, and Sun, Lei
Published: 2024
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39. Stream water sourcing from high-elevation snowpack inferred from stable isotopes of water: a novel application of d-excess values

Author: M. Sprenger, R. W. H. Carroll, D. Marchetti, C. Bern, H. Beria, W. Brown, A. Newman, C. Beutler, and K. H. Williams
Subjects: Technology, Environmental technology. Sanitary engineering, TD1-1066, Geography. Anthropology. Recreation, Environmental sciences, GE1-350
Abstract: About 80 % of the precipitation at the Colorado River's headwaters is snow, and the resulting snowmelt-driven hydrograph is a crucial water source for about 40 million people. Snowmelt from alpine and subalpine snowpack contributes substantially to groundwater recharge and river flow. However, the dynamics of snowmelt progression are not well understood because observations of the high-elevation snowpack are difficult due to challenging access in complex mountainous terrain as well as the cost and labor intensity of currently available methods. We present a novel approach to infer the processes and dynamics of high-elevation snowmelt contributions predicated upon stable hydrogen and oxygen isotope ratios observed in streamflow. We show that deuterium-excess (d-excess) values of stream water could serve as a comparatively cost-effective proxy for a catchment-integrated signal of high-elevation snowmelt contributions to catchment runoff. We sampled stable hydrogen and oxygen isotope ratios of the precipitation, snowpack, and stream water in the East River, a headwater catchment of the Colorado River, and the stream water of larger catchments at sites on the Gunnison River and Colorado River. The d-excess of snowpack increased with elevation; the upper subalpine and alpine snowpack (> 3200 m) had substantially higher d-excess compared to lower elevations (< 3200 m) in the study area. The d-excess values of stream water reflected this because d-excess values increased as the higher-elevation snowpack contributed more to stream water generation later in the snowmelt/runoff season. End-member mixing analyses based on the d-excess data showed that the share of high-elevation snowmelt contributions within the snowmelt hydrograph was on average 44 % and generally increased during melt period progression, up to 70 %. The observed pattern was consistent during 6 years for the East River, and a similar relation was found for the larger catchments on the Gunnison and Colorado rivers. High-elevation snowpack contributions were found to be higher for years with lower snowpack and warmer spring temperatures. Thus, we conclude that the d-excess of stream water is a viable proxy to observe changes in high-elevation snowmelt contributions in catchments at various scales. Inter-catchment comparisons and temporal trends of the d-excess of stream water could therefore serve as a catchment-integrated measure to monitor if mountain systems rely on high-elevation water inputs more during snow drought compared to years of average snowpack depths.
Published: 2024
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40. 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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41. 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

42. 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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43. Soil compaction and fertilization in soybean productivity

Author: Beutler Amauri Nelson and Centurion José Frederico
Subjects: bulk density, penetration resistance, fertilizer, yield, Agriculture (General), S1-972
Abstract: Soil compaction and fertilization affect soybean development. This study evaluated the effects of soil compaction and fertilization on soybean (Glycine max cv. Embrapa 48) productivity in a Typic Haplustox under field conditions in Jaboticabal, SP, Brazil. A completely randomized design with a 5 x 2 factorial layout (compaction vs. fertilization), with four replications in each treatment, was employed. Each experimental unit (replicate) consisted of a 3.6 m² useful area. After the soil was prepared by cultivation, an 11 Mg tractor passed over it a variable number of times to create five levels of compaction. Treatments were: T0= no compaction, T1= one tractor pass, T2= two, T4= four, and T6= six passes, and no fertilizer and fertilizer to give soybean yields of 2.5 to 2.9 Mg ha-1. Soil was sampled at depths of 0.02-0.05, 0.07-0.10, and 0.15-0.18 m to determine macro and microporosity, penetration resistance (PR), and bulk density (Db). After 120 days growing under these conditions, the plants were analyzed in terms of development (plant height, number of pods, shoot dry matter per plant and weight of 100 seeds) and seed productivity per hectare. Soil compaction decreased soybean development and productivity, but this effect was decreased by soil fertilization, showing that such fertilization increased soybean tolerance to soil compaction.
Published: 2004

44. Resistência à penetração em latossolos: valor limitante à produtividade de arroz de sequeiro

Author: Beutler Amauri Nelson and Centurion José Frederico
Subjects: Oryza sativa, compactação do solo, conteúdo de água, Agriculture, Agriculture (General), S1-972
Abstract: Este trabalho objetivou avaliar o valor de resistência à penetração limitante à produtividade de arroz de sequeiro (Oryza sativa cv. IAC 165) no conteúdo de água retida, na tensão de 0,05 e 0,01 MPa. Foram utilizadas amostras de Latossolo Vermelho, textura média (LVd) e, Latossolo Vermelho, textura argilosa (LVef), coletadas na profundidade de 0,00-0,20m, passadas em peneira de 0,004m e compactados em camadas de 0,03m, em vasos de 0,20m de altura e 0,25m de diâmetro (0,00982m³). Os valores de resistência à penetração foram determinados com o penetrômetro de anel dinamométrico. Utilizou-se o delineamento inteiramente casualizado, em esquema fatorial 4 x 2, com três repetições. No conteúdo de água retida, na tensão de 0,01MPa, o valor de resistência do solo à penetração limitante à produtividade de grãos de arroz de sequeiro foi de 2,38 e 2,07MPa, respectivamente, para o LVd e LVef. No conteúdo de água retida na tensão de 0,05MPa foram obtidas maiores produções no menor valor de resistência à penetração. O arroz de sequeiro foi menos produtivo no conteúdo de água retida na tensão de 0,05MPa.
Published: 2004

45. Targeted protein S-nitrosylation of ACE2 inhibits SARS-CoV-2 infection

Author: Oh, Chang-ki, Nakamura, Tomohiro, Beutler, Nathan, Zhang, Xu, Piña-Crespo, Juan, Talantova, Maria, Ghatak, Swagata, Trudler, Dorit, Carnevale, Lauren N, McKercher, Scott R, Bakowski, Malina A, Diedrich, Jolene K, Roberts, Amanda J, Woods, Ashley K, Chi, Victor, Gupta, Anil K, Rosenfeld, Mia A, Kearns, Fiona L, Casalino, Lorenzo, Shaabani, Namir, Liu, Hejun, Wilson, Ian A, Amaro, Rommie E, Burton, Dennis R, Yates, John R, Becker, Cyrus, Rogers, Thomas F, Chatterjee, Arnab K, and Lipton, Stuart A
Subjects: Vaccine Related, Emerging Infectious Diseases, Prevention, Pneumonia & Influenza, Biodefense, Pneumonia, Infectious Diseases, Lung, 5.1 Pharmaceuticals, Development of treatments and therapeutic interventions, Infection, Good Health and Well Being, Humans, COVID-19, SARS-CoV-2, Angiotensin-Converting Enzyme 2, Protein Binding, Peptidyl-Dipeptidase A, Medicinal and Biomolecular Chemistry, Biochemistry and Cell Biology, Biochemistry & Molecular Biology
Abstract: Prevention of infection and propagation of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a high priority in the Coronavirus Disease 2019 (COVID-19) pandemic. Here we describe S-nitrosylation of multiple proteins involved in SARS-CoV-2 infection, including angiotensin-converting enzyme 2 (ACE2), the receptor for viral entry. This reaction prevents binding of ACE2 to the SARS-CoV-2 spike protein, thereby inhibiting viral entry, infectivity and cytotoxicity. Aminoadamantane compounds also inhibit coronavirus ion channels formed by envelope (E) protein. Accordingly, we developed dual-mechanism aminoadamantane nitrate compounds that inhibit viral entry and, thus, the spread of infection by S-nitrosylating ACE2 via targeted delivery of the drug after E protein channel blockade. These non-toxic compounds are active in vitro and in vivo in the Syrian hamster COVID-19 model and, thus, provide a novel avenue to pursue therapy.
Published: 2023

46. Broadly neutralizing anti-S2 antibodies protect against all three human betacoronaviruses that cause deadly disease

Author: Zhou, Panpan, Song, Ge, Liu, Hejun, Yuan, Meng, He, Wan-ting, Beutler, Nathan, Zhu, Xueyong, Tse, Longping V, Martinez, David R, Schäfer, Alexandra, Anzanello, Fabio, Yong, Peter, Peng, Linghang, Dueker, Katharina, Musharrafieh, Rami, Callaghan, Sean, Capozzola, Tazio, Limbo, Oliver, Parren, Mara, Garcia, Elijah, Rawlings, Stephen A, Smith, Davey M, Nemazee, David, Jardine, Joseph G, Safonova, Yana, Briney, Bryan, Rogers, Thomas F, Wilson, Ian A, Baric, Ralph S, Gralinski, Lisa E, Burton, Dennis R, and Andrabi, Raiees
Subjects: Medical Microbiology, Biomedical and Clinical Sciences, Immunology, Biodefense, Prevention, Vaccine Related, Emerging Infectious Diseases, Biotechnology, Pneumonia, Pneumonia & Influenza, Lung, Immunization, Infection, Good Health and Well Being, Humans, SARS-CoV-2, Broadly Neutralizing Antibodies, COVID-19, Antibodies, Neutralizing, Antibodies, Viral, S2 stem-helix site, SARS-CoV-2 variants of concern, broad coronavirus protection, broadly neutralizing antibodies, coronavirus spike, coronaviruses, pan-betacoronavirus vaccines
Abstract: Pan-betacoronavirus neutralizing antibodies may hold the key to developing broadly protective vaccines against novel pandemic coronaviruses and to more effectively respond to SARS-CoV-2 variants. The emergence of Omicron and subvariants of SARS-CoV-2 illustrates the limitations of solely targeting the receptor-binding domain (RBD) of the spike (S) protein. Here, we isolated a large panel of broadly neutralizing antibodies (bnAbs) from SARS-CoV-2 recovered-vaccinated donors, which targets a conserved S2 region in the betacoronavirus spike fusion machinery. Select bnAbs showed broad in vivo protection against all three deadly betacoronaviruses, SARS-CoV-1, SARS-CoV-2, and MERS-CoV, which have spilled over into humans in the past two decades. Structural studies of these bnAbs delineated the molecular basis for their broad reactivity and revealed common antibody features targetable by broad vaccination strategies. These bnAbs provide new insights and opportunities for antibody-based interventions and for developing pan-betacoronavirus vaccines.
Published: 2023

47. Atrial Fibrillation: Prevalence and Association With Outcome in Patients With Stroke Undergoing Mechanical Thrombectomy in the United States

Author: Fadar Oliver Otite, Smit D. Patel, Haydn Hoffman, Ehimen Aneni, Nnabuchi Anikpezie, Emmanuel Oladele Akano, Claribel Wee, Devin Burke, Karen Albright, Timothy Beutler, Julius Gene Latorre, Ashish Sonig, Amit Singla, Nicholas Morris, Seemant Chaturvedi, and Priyank Khandelwal
Subjects: atrial fibrillation, epidemiology, ischemic stroke, mortality, Neurology. Diseases of the nervous system, RC346-429, Diseases of the circulatory (Cardiovascular) system, RC666-701
Abstract: Background How the prevalence of atrial fibrillation (AF) has changed over time in various demographic subgroups of patients with acute ischemic stroke (AIS) undergoing mechanical thrombectomy (MT) in the United States is unknown. Whether in‐hospital outcomes differ between patients with AF versus patients without AF after MT remains uncertain. Methods We conducted a serial cross‐sectional study using all primary AIS discharges in the 2010 to 2020 National Inpatient Sample. Discharges with MT codes were identified (n = 155 277), and the proportion with AF in various age, sex, and racial subgroups were computed. We used multivariable‐adjusted negative binomial regression to compare AF prevalence between demographic subgroups and joinpoint regression to evaluate trends over time. Multivariable‐adjusted generalized linear models were used to evaluate the association of AF with in‐hospital outcomes. Results Across the study period, 45.0% of AIS discharges with MT had AF, but prevalence varied by age, sex, and race or ethnicity. After multivariable adjustment, AF prevalence was 4% higher in women versus men (prevalence rate ratio, 1.04 [95% CI, 1.01–1.07]) and was lower in Black versus White (prevalence rate ratio, 0.80 [95% CI, 0.77–0.84]) but higher in Asian compared with White discharges (prevalence rate ratio, 1.11 [95% CI, 1.05–1.18]). Prevalence increased with age (prevalence rate ratio for ≥80 years versus 18–39 years, 5.23 [95% CI, 4.28–6.39]). Following joinpoint regression, prevalence increased by 3.2% (95% CI, 1.3%–5.2%) annually across the period 2010 to 2015 but declined by −2.2% (95% CI −2.9% to −1.4%) from 2015 to 2020. AF was associated with 22% lower odds of in‐hospital death (odds ratio, 0.78 [95% CI, 0.71–0.85]) and 13% greater odds of routine home discharge (odds ratio, 1.13 95% CI, 1.04–1.22]) compared with no AF. Conclusion AF prevalence in patients undergoing MT in the United States is approximately twice that of the general AIS population. AF prevalence in MT increased from 2010 to 2015 but declined from 2015 to 2020. In the subset of patients with AIS undergoing MT, AF is associated with reduced in‐hospital death.
Published: 2024
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48. The role of diabetes on the development of abdominal aortic aneurysms (AAA)

Author: Michal Siwek, Jacek Beutler, Katarzyna Beutler, and Jędrzej Lewandowski
Subjects: abdominal aortic aneurysms, diabetes, antidiabetic drugs, Education, Sports, GV557-1198.995, Medicine
Abstract: An abdominal aortic aneurysm (AAA) is a pathological local dilatation of the abdominal aorta that may develop from a variety of causes. With a 80% mortality rate, it is mainly linked to male gender, age above 65 years, smoking, and a family history of AAA. Ultrasonography is an effective method for screening males who are 65 or older for AAA. Endovascular aneurysm repair (EVAR) procedure reduces 30-day operative mortality and hospital stay, becoming a global standard. Both open and endovascular surgery aim to cut off the aneurysm's circulation, preventing it from rupturing. Diabetes mellitus (DM) may provide protection against regrowth and the need for additional intervention after endovascular AAA repair, thereby limiting the enlargement and rupture of AAAs. Hyperglycemia thickens the aortic walls and reduces wall stress in diabetic patients' abdominal aortas. It stabilizes collagen structure and promotes the synthesis of collagen type IV. Anti-diabetic drugs like metformin, thiazolidinedione, and dipeptidyl peptidase 4 inhibitors (DPP-4i) have been shown in both animal and human studies to protect against aortic aneurysms. In a dose-response pattern, these antidiabetic drugs may lower the prevalence, incidence, and enlargement rate of AAA.
Published: 2024
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49. 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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50. Quantifying Subsurface Flow and Solute Transport in a Snowmelt‐Recharged Hillslope With Multiyear Water Balance

Author: Tokunaga, Tetsu K, Tran, Anh Phuong, Wan, Jiamin, Dong, Wenming, Newman, Alexander W, Beutler, Curtis A, Brown, Wendy, Henderson, Amanda N, and Williams, Kenneth H
Subjects: Hydrology, Earth Sciences, Geology, hillslope hydrology, transmissivity feedback, subsurface flow, snow drought, evapotranspiration, Physical Geography and Environmental Geoscience, Civil Engineering, Environmental Engineering, Civil engineering, Environmental engineering
Abstract: Quantifying flow and transport from hillslopes is vital for understanding water quantity and quality in rivers, but remains obscure because of limited subsurface measurements. Using measured hydraulic conductivity K profiles and water balance over a single year to calibrate a transmissivity feedback model for a hillslope in the East River watershed (Colorado) proved unsatisfactory for predicting flow over the subsequent years. Well-constrained field-scale K were obtained by optimizing subsurface flux predictions over years having large differences in recharge, and by including estimates of interannual transfer of excess snowmelt recharge. Water and solute exports during high snowmelt recharge occur predominantly via shallow groundwater flow through weathered rock and soil because of their enlarged transmissivities under saturated conditions. Conversely, these shallow pathways are less active in snow drought years when the water table remains deeper within the weathering zone. Hillslope soil water monitoring showed that rainfall does not infiltrate deeply during summer and fall months, and revealed water losses consistent with model ET predictions. By combining water table-dependent fluxes with pore water chemistry in different zones, time-dependent rates of solute exports become predictable. As an example, calibrated K were combined with dissolved nitrogen concentrations in pore waters to show the snowmelt-dependence of reactive nitrogen exported from the hillslope, further supporting the recent finding that the weathering zone is the dominant source of reactive nitrogen at this site. Subsurface export predictions can now be obtained for wide ranges of recharge based on measurements of water table elevation and profiles of pore water chemistry.
Published: 2022

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