Data Release 1 of the Dark Energy Spectroscopic Instrument

This paper presents DESI Data Release 1, the largest sample of extragalactic redshifts ever assembled, comprising 18.7 million objects from the first 13 months of the survey to enable precise cosmological constraints and diverse astrophysical discoveries.

DESI Collaboration, M. Abdul Karim, A. G. Adame, D. Aguado, J. Aguilar, S. Ahlen, S. Alam, G. Aldering, D. M. Alexander, R. Alfarsy, L. Allen, C. Allende Prieto, O. Alves, A. Anand, U. Andrade, E. Armengaud, S. Avila, A. Aviles, H. Awan, S. Bailey, A. Baleato Lizancos, O. Ballester, A. Bault, J. Bautista, R. Bean, J. Behera, S. BenZvi, L. Beraldo e Silva, J. R. Bermejo-Climent, F. Beutler, D. Bianchi, C. Blake, R. Blum, A. S. Bolton, M. Bonici, S. Brieden, A. Brodzeller, D. Brooks, E. Buckley-Geer, E. Burtin, A. Byström, R. Canning, A. Carnero Rosell, A. Carr, P. Carrilho, L. Casas, F. J. Castander, R. Cereskaite, J. L. Cervantes-Cota, E. Chaussidon, J. Chaves-Montero, S. Chen, X. Chen, C. Circosta, T. Claybaugh, S. Cole, A. P. Cooper, M. -C. Cousinou, A. Cuceu, T. M. Davis, K. S. Dawson, R. de Belsunce, R. de la Cruz, A. de la Macorra, A. de Mattia, N. Deiosso, J. Della Costa, R. Demina, U. Demirbozan, J. DeRose, A. Dey, B. Dey, J. Ding, Z. Ding, P. Doel, K. Douglass, M. Dowicz, H. Ebina, J. Edelstein, D. J. Eisenstein, W. Elbers, N. Emas, S. Escoffier, P. Fagrelius, X. Fan, K. Fanning, G. Favole, V. A. Fawcett, E. Fernández-García, S. Ferraro, N. Findlay, A. Font-Ribera, J. E. Forero-Romero, D. Forero-Sánchez, C. S. Frenk, B. T. Gänsicke, L. Galbany, J. García-Bellido, C. Garcia-Quintero, L. H. Garrison, E. Gaztañaga, H. Gil-Marín, A. Gloudemans, O. Y. Gnedin, S. Gontcho A Gontcho, D. Gonzalez, A. X. Gonzalez-Morales, V. Gonzalez-Perez, C. Gordon, O. Graur, D. Green, D. Gruen, R. Gsponer, C. Guandalin, G. Gutierrez, J. Guy, C. Hahn, J. J. Han, J. Han, S. He, H. K. Herrera-Alcantar, S. Heydenreich, K. Honscheid, J. Hou, C. Howlett, D. Huterer, V. Iršič, M. Ishak, A. Jacques, L. Jiang, J. Jimenez, Y. P. Jing, B. Joachimi, S. Joudaki, R. Joyce, E. Jullo, S. Juneau, N. G. Karaçaylı, T. Karim, R. Kehoe, S. Kent, A. Khederlarian, D. Kirkby, T. Kisner, F. -S. Kitaura, N. Kizhuprakkat, H. Kong, S. E. Koposov, A. Kremin, A. Krolewski, O. Lahav, Y. Lai, C. Lamman, T. -W. Lan, M. Landriau, D. Lang, J. U. Lange, J. Lasker, J. M. Le Goff, L. Le Guillou, A. Leauthaud, M. E. Levi, S. Li, T. S. Li, W. Liu, K. Lodha, M. Lokken, Y. Luo, Y. Luo, C. Magneville, M. Manera, C. J. Manser, D. Margala, P. Martini, M. Maus, J. McCullough, P. McDonald, G. E. Medina, L. Medina-Varela, A. Meisner, J. Mena-Fernández, A. Menegas, J. Meneses-Rizo, M. Mezcua, R. Miquel, P. Montero-Camacho, J. Moon, J. Moustakas, A. Muñoz-Gutiérrez, D. Muñoz-Santos, A. D. Myers, J. Myles, S. Nadathur, J. Najita, L. Napolitano, J. A. Newman, F. Nikakhtar, R. Nikutta, G. Niz, H. E. Noriega, P. Nugent, N. Padmanabhan, E. Paillas, N. Palanque-Delabrouille, A. Palmese, J. Pan, Z. Pan, D. Parkinson, J. A. Peacock, M. P. Ibanez, W. J. Percival, A. Pérez-Fernández, I. Pérez-Ràfols, P. Peterson, J. Piat, M. M. Pieri, M. Pinon, C. Poppett, A. Porredon, F. Prada, R. Pucha, F. Qin, D. Rabinowitz, A. Raichoor, C. Ramírez-Pérez, S. Ramirez-Solano, M. Rashkovetskyi, C. Ravoux, B. Ried Guachalla, A. H. Riley, A. Rocher, C. Rockosi, J. Rohlf, A. J. Rosado-Marín, A. J. Ross, C. Ross, G. Rossi, R. Ruggeri, V. Ruhlmann-Kleider, C. G. Sabiu, K. Said, N. Sailer, A. Saintonge, Y. Salcedo Hernandez, L. Samushia, E. Sanchez, N. Sanders, N. Sandford, S. Satyavolu, C. Saulder, A. K. Saydjari, E. F. Schlafly, D. Schlegel, D. Scholte, M. Schubnell, A. Semenaite, H. Seo, A. Shafieloo, R. Sharples, J. Silber, F. Sinigaglia, M. Siudek, Z. Slepian, A. Smith, M. Soumagnac, D. Sprayberry, J. Suárez-Pérez, J. Swanson, T. Tan, G. Tarlé, P. Taylor, G. Thomas, R. Tojeiro, R. J. Turner, W. Turner, L. A. Ureña-López, R. Vaisakh, M. Valluri, G. Valogiannis, M. Vargas-Magaña, L. Verde, P. Vielzeuf, M. Walther, B. Wang, M. S. Wang, W. Wang, B. A. Weaver, N. Weaverdyck, R. H. Wechsler, D. H. Weinberg, M. White, A. Whitford, M. Wolfson, J. Yang, C. Yèche, S. Youles, J. Yu, S. Yuan, E. A. Zaborowski, P. Zarrouk, H. Zhang, C. Zhao, R. Zhao, Z. Zheng, C. Zhou, R. Zhou, Y. Zhou, H. Zou, S. Zou, Y. Zu

Published 2026-03-06
📖 5 min read🧠 Deep dive

Imagine the universe as a giant, three-dimensional city that is constantly expanding. For decades, astronomers have been trying to map this city, but they've mostly been looking at it from a distance, seeing only the streetlights (galaxies) and guessing where the buildings are.

DESI (Dark Energy Spectroscopic Instrument) is like a massive, high-tech drone swarm that flies into this cosmic city to take a selfie of every single building, street, and alleyway, measuring exactly how far away they are and how fast they are moving away from us.

This paper is the first major report card (Data Release 1, or DR1) from DESI after its first year of flying. Here is what they found, explained simply:

1. The Mission: Why Are We Doing This?

The universe isn't just expanding; it's expanding faster every day. Something invisible is pushing it apart, and scientists call this "Dark Energy." It's like an invisible wind blowing the city apart.

DESI's job is to measure this wind. By mapping millions of galaxies and quasars (super-bright black holes), they want to answer three big questions:

  • How strong is the "Dark Energy" wind?
  • How is the "gravity" of the universe trying to hold the city together?
  • How heavy are the ghostly particles called neutrinos that float through everything?

2. The Tool: A Robot Swarm

DESI sits on top of a giant telescope in Arizona. It has 5,000 tiny robotic arms (fibers). Think of these like 5,000 vacuum cleaner hoses.

  • Every night, the telescope points at a patch of sky.
  • The robotic arms instantly move to point at 5,000 specific stars or galaxies.
  • They suck up the light from those objects and send it to 10 cameras.
  • This happens every night, creating a massive library of light spectra (rainbows) for millions of objects.

3. The Result: The Biggest Map Ever

In just 13 months (May 2021 to June 2022), DESI did something incredible. It measured the distance and speed of 18.7 million objects.

  • 13.1 million galaxies: The "buildings" of the universe.
  • 1.6 million quasars: The "super-bright lighthouses" at the centers of galaxies.
  • 4 million stars: Our own "neighbors" in the Milky Way.

To put this in perspective: All the previous major surveys combined (like the famous Sloan Digital Sky Survey, which ran for 25 years) only mapped about 4 million objects. DESI did it in one year and has four times more data than everything before it combined. It's like going from a sketch of a city to a high-definition 3D model.

4. The "Three Programs" (Day, Night, and Twilight)

Just like a city has different activities at different times, DESI has three modes:

  • The Dark Program (Night): When the moon is hidden, they look at faint, distant galaxies and quasars to map the deep universe.
  • The Bright Program (Day/Twilight): When the moon is bright, they look at closer, brighter galaxies and stars in our own neighborhood.
  • The Backup Program: If the weather is bad or the moon is too bright, they still work on specific stars to keep the robot arms busy.

5. The "Iron" Production

The paper mentions something called the "Iron" production. Think of this as the "Gold Standard" version of the data.

  • Earlier, they released a smaller "Early Data Release" (EDR) which was like a beta test.
  • Now, they have re-processed all that old data plus the new year of data using a better, more uniform software recipe called "Iron."
  • This ensures that every single measurement is consistent, like making sure every brick in the city map is the exact same size and shape.

6. What's in the Box? (The Data Release)

This paper isn't just about the numbers; it's a user manual for the data.

  • The Catalogs: They have organized the 18.7 million objects into neat lists (catalogs) so other scientists can download them.
  • The "Value-Added" Catalogs: These are special reports created by different teams within the collaboration. For example:
    • The "Milky Way Survey" team mapped the shape of our own galaxy's halo (the outer shell).
    • The "Quasar" team found hidden black holes.
    • The "Cosmology" team started measuring the expansion rate of the universe.

7. Why This Matters

Imagine you are trying to figure out why a car is speeding up. You need a map of the road, the speed of the car at different points, and the wind speed.

  • Before DESI: We had a blurry map and a few speed readings.
  • With DESI DR1: We have a crystal-clear, 3D map of the entire highway system with millions of speed readings.

This data allows scientists to test theories about the universe with a precision never seen before. It helps us understand if "Dark Energy" is a constant force or if it changes over time, which could tell us the ultimate fate of the universe (will it keep expanding forever, or will it eventually rip apart?).

Summary

This paper is the announcement that DESI has successfully launched its first major data dump. It is the largest collection of cosmic distances ever assembled, offering a detailed, 3D map of the universe that will fuel scientific discoveries for decades. It's not just a list of numbers; it's the foundation for the next generation of understanding how our universe works.