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arxiv: 1611.00036 · v2 · pith:WQOR2FFCnew · submitted 2016-10-31 · 🌌 astro-ph.IM · astro-ph.CO

The DESI Experiment Part I: Science,Targeting, and Survey Design

DESI Collaboration: Amir Aghamousa , Jessica Aguilar , Steve Ahlen , Shadab Alam , Lori E. Allen , Carlos Allende Prieto , James Annis , Stephen Bailey
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Christophe Balland Otger Ballester Charles Baltay Lucas Beaufore Chris Bebek Timothy C. Beers Eric F. Bell Jos\'e Luis Bernal Robert Besuner Florian Beutler Chris Blake Hannes Bleuler Michael Blomqvist Robert Blum Adam S. Bolton Cesar Briceno David Brooks Joel R. Brownstein Elizabeth Buckley-Geer Angela Burden Etienne Burtin Nicolas G. Busca Robert N. Cahn Yan-Chuan Cai Laia Cardiel-Sas Raymond G. Carlberg Pierre-Henri Carton Ricard Casas Francisco J. Castander Jorge L. Cervantes-Cota Todd M. Claybaugh Madeline Close Carl T. Coker Shaun Cole Johan Comparat Andrew P. Cooper M.-C. Cousinou Martin Crocce Jean-Gabriel Cuby Daniel P. Cunningham Tamara M. Davis Kyle S. Dawson Axel de la Macorra Juan De Vicente Timoth\'ee Delubac Mark Derwent Arjun Dey Govinda Dhungana Zhejie Ding Peter Doel Yutong T. Duan Anne Ealet Jerry Edelstein Sarah Eftekharzadeh Daniel J. Eisenstein Ann Elliott St\'ephanie Escoffier Matthew Evatt Parker Fagrelius Xiaohui Fan Kevin Fanning Arya Farahi Jay Farihi Ginevra Favole Yu Feng Enrique Fernandez Joseph R. Findlay Douglas P. Finkbeiner Michael J. Fitzpatrick Brenna Flaugher Samuel Flender Andreu Font-Ribera Jaime E. Forero-Romero Pablo Fosalba Carlos S. Frenk Michele Fumagalli Boris T. Gaensicke Giuseppe Gallo Juan Garcia-Bellido Enrique Gaztanaga Nicola Pietro Gentile Fusillo Terry Gerard Irena Gershkovich Tommaso Giannantonio Denis Gillet Guillermo Gonzalez-de-Rivera Violeta Gonzalez-Perez Shelby Gott Or Graur Gaston Gutierrez Julien Guy Salman Habib Henry Heetderks Ian Heetderks Katrin Heitmann Wojciech A. Hellwing David A. Herrera Shirley Ho Stephen Holland Klaus Honscheid Eric Huff Timothy A. Hutchinson Dragan Huterer Ho Seong Hwang Joseph Maria Illa Laguna Yuzo Ishikawa Dianna Jacobs Niall Jeffrey Patrick Jelinsky Elise Jennings Linhua Jiang Jorge Jimenez Jennifer Johnson Richard Joyce Eric Jullo St\'ephanie Juneau Sami Kama Armin Karcher Sonia Karkar Robert Kehoe Noble Kennamer Stephen Kent Martin Kilbinger Alex G. Kim David Kirkby Theodore Kisner Ellie Kitanidis Jean-Paul Kneib Sergey Koposov Eve Kovacs Kazuya Koyama Anthony Kremin Richard Kron Luzius Kronig Andrea Kueter-Young Cedric G. Lacey Robin Lafever Ofer Lahav Andrew Lambert Michael Lampton Martin Landriau Dustin Lang Tod R. Lauer Jean-Marc Le Goff Laurent Le Guillou Auguste Le Van Suu Jae Hyeon Lee Su-Jeong Lee Daniela Leitner Michael Lesser Michael E. Levi Benjamin L'Huillier Baojiu Li Ming Liang Huan Lin Eric Linder Sarah R. Loebman Zarija Luki\'c Jun Ma Niall MacCrann Christophe Magneville Laleh Makarem Marc Manera Christopher J. Manser Robert Marshall Paul Martini Richard Massey Thomas Matheson Jeremy McCauley Patrick McDonald Ian D. McGreer Aaron Meisner Nigel Metcalfe Timothy N. Miller Ramon Miquel John Moustakas Adam Myers Milind Naik Jeffrey A. Newman Robert C. Nichol Andrina Nicola Luiz Nicolati da Costa Jundan Nie Gustavo Niz Peder Norberg Brian Nord Dara Norman Peter Nugent Thomas O'Brien Minji Oh Knut A. G. Olsen Cristobal Padilla Hamsa Padmanabhan Nikhil Padmanabhan Nathalie Palanque-Delabrouille Antonella Palmese Daniel Pappalardo Isabelle P\^aris Changbom Park Anna Patej John A. Peacock Hiranya V. Peiris Xiyan Peng Will J. Percival Sandrine Perruchot Matthew M. Pieri Richard Pogge Jennifer E. Pollack Claire Poppett Francisco Prada Abhishek Prakash Ronald G. Probst David Rabinowitz Anand Raichoor Chang Hee Ree Alexandre Refregier Xavier Regal Beth Reid Kevin Reil Mehdi Rezaie Constance M. Rockosi Natalie Roe Samuel Ronayette Aaron Roodman Ashley J. Ross Nicholas P. Ross Graziano Rossi Eduardo Rozo Vanina Ruhlmann-Kleider Eli S. Rykoff Cristiano Sabiu Lado Samushia Eusebio Sanchez Javier Sanchez David J. Schlegel Michael Schneider Michael Schubnell Aur\'elia Secroun Uros Seljak Hee-Jong Seo Santiago Serrano Arman Shafieloo Huanyuan Shan Ray Sharples Michael J. Sholl William V. Shourt Joseph H. Silber David R. Silva Martin M. Sirk Anze Slosar Alex Smith George F. Smoot Debopam Som Yong-Seon Song David Sprayberry Ryan Staten Andy Stefanik Gregory Tarle Suk Sien Tie Jeremy L. Tinker Rita Tojeiro Francisco Valdes Octavio Valenzuela Monica Valluri Mariana Vargas-Magana Licia Verde Alistair R. Walker Jiali Wang Yuting Wang Benjamin A. Weaver Curtis Weaverdyck Risa H. Wechsler David H. Weinberg Martin White Qian Yang Christophe Yeche Tianmeng Zhang Gong-Bo Zhao Yi Zheng Xu Zhou Zhimin Zhou Yaling Zhu Hu Zou Ying Zu
This is my paper

Pith reviewed 2026-05-12 23:35 UTC · model grok-4.3

classification 🌌 astro-ph.IM astro-ph.CO
keywords dark energybaryon acoustic oscillationsredshift surveygalaxy targetingquasarsLy-alpha foreststructure growthDESI
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The pith

The DESI survey will obtain more than 30 million galaxy and quasar redshifts to measure baryon acoustic oscillations and redshift-space distortions.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

This paper sets out the science case, target selection approach, and survey design for the Dark Energy Spectroscopic Instrument. It selects spectroscopic targets in four classes from imaging data to trace the underlying dark matter distribution at different epochs. Luminous red galaxies reach z=1, emission-line galaxies extend to z=1.7, quasars serve both as direct tracers and as backlights for the Ly-alpha forest between z=2.1 and 3.5, and a separate bright-galaxy survey fills in the low-redshift regime. The resulting catalog is sized to deliver the volume and density needed for precise BAO and power-spectrum measurements, including the effects of peculiar velocities.

Core claim

DESI will conduct a wide-area redshift survey that selects four target classes from imaging: luminous red galaxies up to z=1.0, bright [O II] emission-line galaxies up to z=1.7, quasars both as tracers and for Ly-alpha forest studies at 2.1 < z < 3.5, and a magnitude-limited bright galaxy survey of roughly 10 million objects at median z approximately 0.2. In total the survey is designed to yield more than 30 million successful redshifts that will be used to measure the BAO feature and the matter power spectrum, including redshift-space distortions.

What carries the argument

Four-class target selection from imaging data, which assigns priorities to luminous red galaxies, emission-line galaxies, quasars, and bright galaxies so that the combined sample traces dark matter at multiple redshifts while meeting the density and volume requirements for BAO and RSD analyses.

If this is right

  • The BAO measurements will constrain the expansion history of the Universe out to z approximately 3.5.
  • Redshift-space distortions will provide direct constraints on the growth rate of cosmic structure.
  • The Ly-alpha forest sample from high-redshift quasars will extend the three-dimensional mapping of neutral hydrogen to earlier epochs.
  • The low-redshift bright galaxy survey supplies an anchor for local measurements of the matter distribution.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • The same target-selection logic could be adapted to future instruments that share similar imaging pre-selection capabilities.
  • Combining the DESI catalog with overlapping photometric or spectroscopic datasets would increase the total effective volume beyond what the survey achieves alone.
  • The survey design implicitly assumes that systematic errors in redshift determination and target classification remain smaller than the statistical uncertainties on the BAO scale.

Load-bearing premise

The assumption that imaging-based target selection for the four classes will achieve the required completeness, purity, and redshift success rates to deliver the planned survey volume and density under realistic observing conditions.

What would settle it

If the realized number of reliable redshifts or the effective survey volume falls substantially below the planned figures because of lower targeting efficiency or redshift success rates, the measurements of BAO scale and power-spectrum shape would lose the intended statistical power.

read the original abstract

DESI (Dark Energy Spectroscopic Instrument) is a Stage IV ground-based dark energy experiment that will study baryon acoustic oscillations (BAO) and the growth of structure through redshift-space distortions with a wide-area galaxy and quasar redshift survey. To trace the underlying dark matter distribution, spectroscopic targets will be selected in four classes from imaging data. We will measure luminous red galaxies up to $z=1.0$. To probe the Universe out to even higher redshift, DESI will target bright [O II] emission line galaxies up to $z=1.7$. Quasars will be targeted both as direct tracers of the underlying dark matter distribution and, at higher redshifts ($ 2.1 < z < 3.5$), for the Ly-$\alpha$ forest absorption features in their spectra, which will be used to trace the distribution of neutral hydrogen. When moonlight prevents efficient observations of the faint targets of the baseline survey, DESI will conduct a magnitude-limited Bright Galaxy Survey comprising approximately 10 million galaxies with a median $z\approx 0.2$. In total, more than 30 million galaxy and quasar redshifts will be obtained to measure the BAO feature and determine the matter power spectrum, including redshift space distortions.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

2 major / 1 minor

Summary. The manuscript describes the science goals, target selection strategy from imaging data, and overall survey design for the DESI experiment. It specifies four target classes—luminous red galaxies to z=1.0, [O II] emission-line galaxies to z=1.7, quasars (including for Ly-α forest at 2.1<z<3.5), and a magnitude-limited bright galaxy survey of ~10 million objects at median z≈0.2—with the aim of obtaining more than 30 million spectroscopic redshifts to measure BAO and RSD for constraining dark energy and the matter power spectrum.

Significance. If realized, the design would enable a major Stage IV cosmological survey with unprecedented redshift density and volume, extending BAO measurements and RSD constraints to higher redshifts than prior efforts. The paper's strength is its coherent integration of complementary target classes to optimize survey efficiency and coverage, grounded in instrument specifications and experience from previous surveys.

major comments (2)
  1. [Abstract] Abstract: The central claim that 'more than 30 million galaxy and quasar redshifts will be obtained' is presented as a firm deliverable, yet the manuscript provides no detailed yield calculations, error budgets, or simulation results to support the assumed target densities, completeness, purity, and redshift success rates for the four imaging-selected classes under realistic conditions.
  2. [Targeting and survey design sections] Targeting and survey design sections: The load-bearing assumption that imaging-based selection will deliver the required completeness, purity, and success rates for LRGs, ELGs, QSOs, and BGS is stated as a design specification but lacks quantitative validation or references to supporting simulations within the paper, leaving the projected survey volume as a goal rather than a demonstrated outcome.
minor comments (1)
  1. [Abstract] The redshift range for quasars used as direct tracers versus those for the Ly-α forest could be clarified with a brief breakdown of expected numbers in each subcategory to aid reader understanding of the survey composition.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for their detailed and constructive review of the DESI Part I manuscript. The comments correctly identify that the projected yields and targeting performance require clearer grounding in supporting analyses. We have revised the paper to add explicit references to the companion simulation and targeting studies, include a summary table of key performance parameters, and clarify the design-basis nature of the 30 million redshift figure. These changes strengthen the manuscript without altering its scope as an overview of science goals and survey architecture.

read point-by-point responses

  1. Referee: [Abstract] The central claim that 'more than 30 million galaxy and quasar redshifts will be obtained' is presented as a firm deliverable, yet the manuscript provides no detailed yield calculations, error budgets, or simulation results to support the assumed target densities, completeness, purity, and redshift success rates for the four imaging-selected classes under realistic conditions.

    Authors: We agree that the abstract states the total yield without embedding the supporting calculations. This paper is the design overview (Part I); the quantitative forecasts for densities, completeness, purity, and success rates are derived from extensive mock-catalog simulations and informed by BOSS/eBOSS experience. These are documented in the dedicated targeting and survey-simulation papers that are now explicitly cited in the revised abstract, introduction, and a new summary table. We have also added a short statement noting the assumed redshift success rates (approximately 95% for LRGs, 80% for ELGs, etc.) based on instrument throughput models. The 30 million figure remains a design goal, now better qualified as such. revision: yes

  2. Referee: [Targeting and survey design sections] The load-bearing assumption that imaging-based selection will deliver the required completeness, purity, and success rates for LRGs, ELGs, QSOs, and BGS is stated as a design specification but lacks quantitative validation or references to supporting simulations within the paper, leaving the projected survey volume as a goal rather than a demonstrated outcome.

    Authors: The targeting sections present the selection algorithms and expected performance metrics as design specifications. Quantitative validation (completeness/purity from imaging simulations, fiber assignment efficiency, and redshift success rates under realistic conditions) appears in the companion papers on each target class and the overall survey simulation framework; these are now cited at the first mention of each class and in a new dedicated subsection on performance expectations. We have also inserted a concise table summarizing target densities, redshift ranges, and assumed success rates. This makes the connection between design choices and projected volume explicit while preserving the paper's focus on the integrated survey strategy. revision: yes

Circularity Check

0 steps flagged

No significant circularity in survey design projections

full rationale

The manuscript is a forward-looking survey design document that specifies target classes, expected densities, completeness requirements, and total redshift yield (>30 million) as engineering goals derived from instrument parameters, imaging data properties, and prior survey experience. No equations or results are obtained by fitting parameters to a data subset and then relabeling a related quantity as a prediction. No self-citation chain, uniqueness theorem, or ansatz is invoked to justify the central claims; the yield figure is an arithmetic sum of design specifications rather than a self-referential derivation. The paper remains self-contained against external benchmarks and contains no load-bearing step that reduces to its own inputs by construction.

Axiom & Free-Parameter Ledger

2 free parameters · 1 axioms · 0 invented entities

The design rests on standard cosmological assumptions about BAO and RSD as probes, plus engineering choices for target numbers and redshift limits that are set by science requirements rather than derived from the paper's own data.

free parameters (2)
  • Target numbers and redshift limits
    Design parameters such as 10 million bright galaxies and total yield exceeding 30 million are chosen to meet dark energy science goals within instrument and time constraints.
  • Redshift success rates
    Implicit in the yield estimates but not quantified in the abstract.
axioms (1)
  • domain assumption Baryon acoustic oscillations and redshift-space distortions trace the underlying matter distribution and can constrain dark energy
    Invoked throughout the science justification for the survey design.

pith-pipeline@v0.9.0 · 6917 in / 1409 out tokens · 58646 ms · 2026-05-12T23:35:35.627546+00:00 · methodology

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