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Euclid preparation: Testing multi-field inflation with galaxy power spectrum and bispectrum

T0 review · 2 major / 3 minor · reviewed 2026-05-21 · grok-4.3

Pith's one-line read Joint power spectrum and bispectrum analysis on Euclid-like mocks recovers unbiased f_NL with 29-46 percent tighter errors.

desk verdict Joint P+B pipeline on Abacus-PNG mocks recovers unbiased f_NL with 29-46% tightening from the bispectrum, but tree-level modeling at the chosen cuts is the part to watch. read the letter →

arxiv 2605.21436 v1 pith:C46IP6BT submitted 2026-05-20 astro-ph.CO

Euclid Collaboration: D. Linde , A. Moradinezhad Dizgah , G. Parimbelli , K. Pardede , E. Sefusatti , M. S. Cagliari , G. D'Amico , V. Desjacques
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A. Eggemeier M. Biagetti A. Veropalumbo B. Camacho Quevedo A. Chudaykin M. Crocce L. Castiblanco E. Castorina A. Farina M. Guidi M. Karcher A. Pezzotta A. Pugno B. Altieri S. Andreon N. Auricchio C. Baccigalupi M. Baldi S. Bardelli P. Battaglia A. Biviano E. Branchini M. Brescia S. Camera G. Canas-Herrera V. Capobianco C. Carbone J. Carretero S. Casas M. Castellano G. Castignani S. Cavuoti K. C. Chambers A. Cimatti C. Colodro-Conde G. Congedo L. Conversi Y. Copin F. Courbin H. M. Courtois H. Degaudenzi S. de la Torre G. De Lucia H. Dole M. Douspis F. Dubath X. Dupac S. Escoffier M. Farina R. Farinelli S. Ferriol F. Finelli P. Fosalba S. Fotopoulou M. Frailis M. Fumana S. Galeotta K. George B. Gillis C. Giocoli J. Gracia-Carpio A. Grazian F. Grupp S. V. H. Haugan W. Holmes F. Hormuth A. Hornstrup K. Jahnke B. Joachimi S. Kermiche A. Kiessling B. Kubik M. Kunz H. Kurki-Suonio A. M. C. Le Brun S. Ligori P. B. Lilje V. Lindholm I. Lloro G. Mainetti O. Mansutti O. Marggraf M. Martinelli N. Martinet F. Marulli R. J. Massey E. Medinaceli S. Mei M. Meneghetti E. Merlin G. Meylan A. Mora M. Moresco L. Moscardini C. Neissner S.-M. Niemi J. W. Nightingale C. Padilla S. Paltani F. Pasian K. Pedersen W. J. Percival V. Pettorino S. Pires G. Polenta M. Poncet L. A. Popa F. Raison A. Renzi J. Rhodes G. Riccio E. Romelli M. Roncarelli R. Saglia Z. Sakr A. G. Sanchez D. Sapone B. Sartoris A. Secroun G. Seidel E. Sihvola P. Simon C. Sirignano G. Sirri A. Spurio Mancini L. Stanco P. Tallada-Crespi A. N. Taylor I. Tereno N. Tessore S. Toft R. Toledo-Moreo F. Torradeflot I. Tutusaus L. Valenziano J. Valiviita T. Vassallo G. Verdoes Kleijn Y. Wang J. Weller G. Zamorani F. M. Zerbi E. Zucca M. Ballardini E. Bozzo C. Burigana R. Cabanac M. Calabrese T. Castro J. A. Escartin Vigo J. Garcia-Bellido J. Macias-Perez R. Maoli J. Martin-Fleitas N. Mauri R. B. Metcalf P. Monaco M. Pontinen I. Risso V. Scottez M. Sereno M. Tenti M. Tucci M. Viel M. Wiesmann Y. Akrami I. T. Andika G. Angora M. Archidiacono F. Atrio-Barandela S. Avila L. Bazzanini J. Bel D. Bertacca M. Bethermin F. Beutler A. Blanchard L. Blot H. Bohringer M. Bonici S. Borgani M. L. Brown S. Bruton A. Calabro F. Caro C. S. Carvalho F. Cogato A. R. Cooray S. Davini G. Desprez A. Diaz-Sanchez S. Di Domizio J. M. Diego V. Duret M. Y. Elkhashab A. Enia Y. Fang A. Finoguenov A. Franco K. Ganga T. Gasparetto F. Giacomini F. Gianotti G. Gozaliasl A. Gruppuso C. M. Gutierrez A. Hall C. Hernandez-Monteagudo H. Hildebrandt J. Hjorth J. J. E. Kajava Y. Kang V. Kansal D. Karagiannis K. Kiiveri J. Kim C. C. Kirkpatrick S. Kruk M. Lattanzi L. Legrand M. Lembo F. Lepori G. Leroy G. F. Lesci J. Lesgourgues T. I. Liaudat S. J. Liu G. Maggio M. Magliocchetti A. Manjon-Garcia F. Mannucci C. J. A. P. Martins L. Maurin C. Moretti G. Morgante S. Nadathur K. Naidoo A. Navarro-Alsina S. Nesseris L. Pagano D. Paoletti F. Passalacqua K. Paterson L. Patrizii C. Pattison A. Pisani D. Potter G. W. Pratt S. Quai M. Radovich K. Rojas W. Roster S. Sacquegna M. Sahlen D. B. Sanders E. Sarpa A. Schneider M. Schultheis D. Sciotti E. Sellentin L. C. Smith K. Tanidis F. Tarsitano G. Testera R. Teyssier S. Tosi A. Troja A. Venhola D. Vergani F. Vernizzi G. Verza S. Vinciguerra N. A. Walton A. H. Wright H. W. Yeung
This is my paper · ORCID
classification astro-ph.CO
keywords primordialnon-Gaussianityf_NLgalaxypowerspectrumbispectrumEuclidsurveyredshift-spacedistortionsmulti-fieldinflationhalooccupationdistribution
verification ladder T0 review T1 audit T2 compute T3 formal

The pith

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

The reading

This paper validates a pipeline that extracts primordial non-Gaussianity from galaxy clustering using both the power spectrum and bispectrum measured in redshift space. The authors run likelihood analyses on mocks built from Abacus-PNG simulations populated according to a halo occupation distribution tuned to Euclid Flagship 2. They show that the bispectrum alone improves the precision on the local PNG parameter f_NL by 29 to 46 percent compared with the power spectrum, while the joint analysis adds another 8 to 13 percent tightening. Across an effective volume of 16 cubic gigaparsecs spanning redshifts 0.8 to 1.7 the recovered values of f_NL and standard cosmological parameters remain unbiased at the sub-sigma level. The work therefore demonstrates a practical route to testing multi-field inflation scenarios with the upcoming Euclid spectroscopic sample.

What carries the argument

Joint likelihood of one-loop power-spectrum multipoles and tree-level bispectrum multipoles that isolates the dominant local PNG term proportional to f_NL times b_phi while marginalizing over bias and cosmological parameters.

What would settle it

Repeating the identical likelihood pipeline on an independent set of mocks or on actual Euclid data and finding biases in f_NL larger than one sigma would falsify the claim of unbiased recovery.

Watch

Extended reading notes

Core claim

Likelihood analyses of one-loop redshift-space power spectrum multipoles and tree-level bispectrum multipoles applied to Abacus-PNG simulations recover f_NL and Lambda-CDM parameters with less than one-sigma bias when the effective volume reaches 16 h^{-3} Gpc^3 across four snapshots from z=0.8 to 1.7. The bispectrum alone reduces the uncertainty on f_NL by 29-46 percent relative to the power spectrum at fixed scale cuts; the joint analysis supplies a further 8-13 percent gain. The strongest individual-bin results appear at z=1.7, where a physically motivated prior on the PNG bias parameter b_phi yields a 2.35-sigma detection of f_NL while the prior-agnostic setup reaches 1.9 sigma on the f_

Load-bearing premise

The halo occupation distribution tuned to Euclid Flagship 2 accurately populates halos in the Abacus-PNG simulations and the one-loop power spectrum plus tree-level bispectrum models remain sufficient without higher-order corrections or additional PNG bias terms for the chosen scale cuts.

Editorial extensions

If this is right

  • B_ℓ alone reduces σ(f_NL) by ∼29–46% relative to P_ℓ at fixed cuts.
  • Joint power spectrum-bispectrum analysis tightens constraints a further ∼8–13%.
  • Cumulative gain across the four redshift snapshots is a factor of ∼2.3 for the joint case.
  • A physically motivated prior on b_φ produces unbiased f_NL while incorporating theory uncertainty.
  • The bispectrum quadrupole supplies a substantial fraction of the extra constraining power.

Reading between the lines

Editorial extensions of the paper, not claims the author makes directly.

  • Extending the same pipeline to higher-order perturbation theory or wider scale ranges could further tighten f_NL bounds once real Euclid systematics are controlled.
  • Joint power-spectrum-bispectrum constraints on local PNG may be combined with CMB bispectrum measurements to break remaining degeneracies in multi-field inflation models.
  • The demonstrated volume scaling suggests that full-sky Euclid data could reach several-sigma detections of f_NL if the simulation-validated precision carries over.
  • Similar joint analyses could be applied to other large-scale structure surveys to cross-check PNG signals.
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Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit.

Referee Report

2 major / 3 minor

Summary. The manuscript validates a joint redshift-space power spectrum and bispectrum pipeline for constraining local primordial non-Gaussianity (f_NL) using Euclid-like mocks from Abacus-PNG N-body simulations populated with an HOD tuned to Euclid Flagship 2. It employs one-loop P_ℓ and tree-level B_ℓ models, stress-tests PNG-bias parametrization, priors, and scale cuts, introduces a physically motivated prior on b_φ to account for theory uncertainty, performs null tests, and reports unbiased recovery of f_NL and ΛCDM parameters with V_eff = 16 h^{-3} Gpc^3 across four snapshots (0.8 ≤ z ≤ 1.7). The bispectrum alone reduces σ(f_NL) by 29–46% relative to the power spectrum, with joint analysis providing an additional 8–13% tightening and a cumulative gain of ~2.3; the bispectrum quadrupole is highlighted as key, yielding up to 2.35σ for f_NL at z=1.7 under the prior-based setup.

Significance. If the adopted perturbative models and scale cuts prove sufficient, the work quantifies concrete gains from including the bispectrum (particularly the quadrupole) for multi-field inflation tests with Euclid and supplies a practical framework for handling degeneracies and theory uncertainties via a motivated prior on b_φ. The simulation-based recovery of injected f_NL with <1σ bias, combined with explicit stress-tests on Abacus-PNG mocks and null tests without PNG, provides a reproducible benchmark that strengthens prospects for Stage-IV PNG constraints. The reported improvement factors and strongest signals at z=1.7 constitute useful quantitative guidance for survey planning.

major comments (2)
  1. [§5] §5 (scale cuts and model validation): The central claim of <1σ bias in f_NL recovery and the 29–46% improvement from B_ℓ rests on the sufficiency of tree-level bispectrum plus one-loop power spectrum up to the chosen k-cuts. At z=1.7, where the bispectrum quadrupole drives the strongest results, an explicit test or estimate of the size of neglected two-loop corrections and additional PNG-induced bias operators (beyond the dominant f_NL b_φ term) within those cuts is needed; without it, the joint multi-redshift constraints and cumulative gain of ~2.3 could be compromised.
  2. [§4.2, §6.1] §4.2 and §6.1 (PNG-bias parametrization and prior on b_φ): The physically motivated prior on b_φ is presented as accounting for theory uncertainty while yielding unbiased f_NL. The manuscript should specify the exact functional form of this prior (including any dependence on the HOD or simulation parameters) and demonstrate that it does not inadvertently incorporate information from the same Abacus-PNG mocks used for the likelihood analyses, to ensure the 1.9σ (prior-agnostic) and 2.35σ (prior-based) detections at z=1.7 remain robust.
minor comments (3)
  1. [Figure 4] Figure 4 (or equivalent results figure): Axis labels and error-bar styles for the different redshift bins and analysis combinations (P_ℓ only, B_ℓ only, joint) could be made more distinct to improve readability of the σ(f_NL) comparisons.
  2. [Abstract, §3] Abstract and §3: The effective volume V_eff=16 h^{-3} Gpc^3 is stated without an explicit breakdown of the contribution per snapshot or per survey geometry; adding this would clarify how the four snapshots combine.
  3. [§2.2] §2.2: The HOD parameters tuned to Euclid Flagship 2 are summarized but lack a table of best-fit values or a brief discussion of how PNG-induced changes in halo properties are (or are not) propagated.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for their careful reading of the manuscript and constructive comments. We address each major comment below and have incorporated revisions to strengthen the presentation of our model validation and prior specification.

read point-by-point responses
  1. Referee: [§5] §5 (scale cuts and model validation): The central claim of <1σ bias in f_NL recovery and the 29–46% improvement from B_ℓ rests on the sufficiency of tree-level bispectrum plus one-loop power spectrum up to the chosen k-cuts. At z=1.7, where the bispectrum quadrupole drives the strongest results, an explicit test or estimate of the size of neglected two-loop corrections and additional PNG-induced bias operators (beyond the dominant f_NL b_φ term) within those cuts is needed; without it, the joint multi-redshift constraints and cumulative gain of ~2.3 could be compromised.

    Authors: We agree that an explicit estimate of higher-order terms would further bolster the validation. The scale cuts in the manuscript were chosen precisely because they yield unbiased recovery of both f_NL and ΛCDM parameters across the mocks, providing implicit evidence that neglected contributions remain subdominant. In the revised manuscript we have added a paragraph in §5 that estimates the magnitude of two-loop corrections using standard perturbation-theory scaling relations from the literature, confirming they lie below the statistical errors for our adopted k_max at z=1.7. We also briefly discuss additional PNG bias operators, noting that they are either suppressed by extra powers of f_NL or enter at higher order in the bias expansion; their expected impact is therefore smaller than the dominant f_NL b_φ term already included. These additions clarify the robustness of the reported gains without changing the conclusions. revision: yes

  2. Referee: [§4.2, §6.1] §4.2 and §6.1 (PNG-bias parametrization and prior on b_φ): The physically motivated prior on b_φ is presented as accounting for theory uncertainty while yielding unbiased f_NL. The manuscript should specify the exact functional form of this prior (including any dependence on the HOD or simulation parameters) and demonstrate that it does not inadvertently incorporate information from the same Abacus-PNG mocks used for the likelihood analyses, to ensure the 1.9σ (prior-agnostic) and 2.35σ (prior-based) detections at z=1.7 remain robust.

    Authors: We thank the referee for requesting this clarification. The prior is constructed from the theoretical peak-background-split expectation for the PNG bias parameter and is assigned a finite width to marginalize over residual theoretical uncertainties in the bias expansion. Its functional form and width are determined from general considerations in the literature and do not depend on the specific HOD parameters or outputs of the Abacus-PNG mocks employed in the likelihood analyses. In the revised version we have expanded §4.2 to state the functional form explicitly and added a sentence in §6.1 confirming that the prior parameters were fixed independently of the present mock likelihoods. This ensures the quoted significances remain unaffected by any circularity. revision: yes

Circularity Check

0 steps flagged · score 0.0 of 10

No significant circularity; validation is externally benchmarked

full rationale

The paper validates a one-loop power spectrum plus tree-level bispectrum pipeline on independent Abacus-PNG N-body simulations that inject known f_NL values (Gaussian and local-PNG initial conditions). The HOD is tuned to the separate Euclid Flagship 2 simulation. Likelihood analyses recover the injected signals with <1σ bias, and the reported 29–46% improvement from B_ℓ (plus further 8–13% from joint analysis) are direct numerical outcomes measured on these mocks. The proposed prior on b_φ is described as physically motivated to account for theory uncertainty rather than being fitted to the analysis data. No load-bearing step reduces by construction to a fitted parameter renamed as prediction, a self-definition, or a self-citation chain. The central claims rest on external simulation benchmarks and are therefore self-contained.

Assumptions & free parameters 2 free parameters · 2 assumptions · 0 invented entities

The central claim rests on the accuracy of the chosen perturbation theory order, the representativeness of the HOD, and the validity of the proposed b_φ prior; these are standard domain assumptions rather than new postulates.

free parameters (2)
  • prior on b_φ
    Physically motivated prior introduced to produce unbiased f_NL while incorporating theory uncertainty
  • scale cuts
    Chosen to ensure unbiased recovery of both ΛCDM and f_NL parameters
assumptions (2)
  • domain assumption HOD tuned to Euclid Flagship 2 accurately represents galaxy population in Abacus-PNG mocks
    Used to generate realistic galaxy catalogs from halo catalogs
  • domain assumption One-loop P_ℓ and tree-level B_ℓ capture the relevant clustering signal including PNG effects
    Pipeline choice stated for redshift-space distortions and bispectrum modeling

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Cite this review

Pith. "Pith review of Euclid preparation: Testing multi-field inflation with galaxy power spectrum and bispectrum." pith.science (2026). https://pith.science/paper/C46IP6BT

@misc{pith2026260521436,
  author       = {Pith},
  title        = {Pith review of: Euclid preparation: Testing multi-field inflation with galaxy power spectrum and bispectrum},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/C46IP6BT}},
  note         = {Machine review of arXiv:2605.21436}
}
abstract

Primordial non-Gaussianity (PNG) is a powerful probe of the origin of cosmic structure. Stage-IV surveys like \Euclid will measure galaxy $2$- and $3$-point clustering at high signal-to-noise, whose exploitation requires robust joint analysis. We prepare for Euclid's spectroscopic sample by validating a redshift-space power-spectrum and bispectrum pipeline (one-loop $P_\ell$, tree-level $B_\ell$) on Euclid-like mocks from Abacus-PNG $N$-body simulations with Gaussian and local-PNG initial conditions, using a halo occupation distribution (HOD) tuned to Euclid Flagship 2. We stress-test analysis choices -- PNG-bias parametrisation, priors, and scale cuts -- and perform null tests without PNG. In a `prior-agnostic setup', detection of the dominant PNG term $\propto f_{\rm NL} \, b_\phi$ in single redshift bins is difficult; nevertheless, the bispectrum provides constraints on other PNG combinations that partially lift degeneracies. We propose a physically motivated prior on $b_\phi$ that yields unbiased $f_{\rm NL}$ while accounting for theory uncertainty, and determine scale cuts that give unbiased $\Lambda$CDM and $f_{\rm NL}$. With $V_{\rm eff}=16\,h^{-3}\,{\rm Gpc}^3$ across four snapshots ($0.8\le z\le1.7$), our likelihood analyses recover $<1\sigma$ bias in $f_{\rm NL}$ and $\Lambda$CDM. At fixed cuts, $B_\ell$ alone reduces $\sigma({f_{\rm NL}})$ by $\sim29$--$46\%$ relative to $P_\ell$, and joint power spectrum-bispectrum analysis tightens a further $\sim8$--$13\%$; the cumulative gain from $z=0.8$ to $1.7$ is $\sim2.3$ for the joint case. The bispectrum quadrupole is key. Our strongest results are at $z=1.7$: $1.9\sigma$ for $f_{\rm NL} \, b_\phi$ (prior-agnostic) and $2.35\sigma$ for $f_{\rm NL}$ (prior-based). Joint analyses thus offer strong prospects for testing multi-field inflation, pending end-to-end validation in the full Euclid geometry with observational systematics.

Figures

Figures reproduced from arXiv: 2605.21436 by the authors.

Figure 2
Figure 2. Abundance matching applied to the AbacusSummit halo mass function at z = 0.8. The top panel shows the FS2 halo mass function (solid dark blue) and the AbacusSummit ΛCDM mass function (dashed orange). The bottom panel presents their ratio relative to FS2, illustrat￾ing differences of up to ∼ 20%. Applying AM (dot-dashed green) brings the AbacusSummit mass function into excellent agreement with FS2. selected galaxies … view at source ↗
Figure 3
Figure 3. Posterior of the prior-agnostic analysis. Marginalised posterior distributions from the power spectrum (blue), bispectrum (green), and their combination (red) at the stated redshift and scale cuts. Shaded re￾gions denote 68% and 95% credible intervals. Nuisance parameters are marginalised. Dashed lines mark the simulation fiducial values. and the bispectrum alone. Finally, by progressively adding mul￾tipoles, we qua… view at source ↗
Figure 4
Figure 4. Impact of prior choice on power spectrum analysis. The plot shows the parameter posteriors from the power spectrum under different treatments of the PNG-bias intercept pbϕ : we either fix it to the UHMF or GFM value, or fit it with a Gaussian prior (mean and width shown in the legend). Blue contours use a Gaussian prior centred on the UHMF value; orange contours are centred on the GFM value; green contours are centr… view at source ↗
Figures from the paper (13 more)
Figure 5
Figure 5. Figure 5: Same as [PITH_FULL_IMAGE:figures/full_fig_p012_5.png]
Figure 6
Figure 6. Figure 6: Same as [PITH_FULL_IMAGE:figures/full_fig_p013_6.png]
Figure 7
Figure 7. Figure 7: Measured versus assumed prior of bϕ. We compare the di￾rectly measured values of bϕ using SU simulations at four redshift bins (crosses) with UHMF (dashed blue line) and GFM (dashed orange line) predictions. Values of bϕ corresponding to our prior centre (converted usi…
Figure 8
Figure 8. Figure 8: Null test on simulations with Gaussian initial conditions (fNL = 0). Parameter posterior distributions from power spectrum (blue), bispec￾trum (green), and their combination (red). Left: constraints form the model with PNG. Right: constraints from the model without PNG…
Figure 9
Figure 9. Figure 9: Best-fit galaxy biases and the corresponding 1σ error bars from joint power spectrum-bispectrum fit to simulations with Gaussian ini￾tial conditions. To make the figure clearer, we have slightly shifted the data points horizontally within each redshift to avoid overlap…
Figure 10
Figure 10. Figure 10: Marginalised 1-dimensional posterior distributions in the four redshift bins and for five choices of scale cuts (for monopole and quadrupole). The violin errors represent the real posterior distribution for each parameter, with the blue and magenta error bars represen…
Figure 11
Figure 11. Figure 11: Marginalised 1-dimensional posterior distributions in the four redshift bins and for five choices of scale cuts (for monopole and quadrupole). The hexadecapole is discarded due to noisy measurements. The rest of the plot styling matches [PITH_FULL_IMAGE:figures/full_…
Figure 12
Figure 12. Figure 12: Validity of perturbative model and information content. The plots illustrate the accuracy in terms of FoB (Eq. 47) and the precision in terms of FoM (Eq. 48) of various scale cuts across all redshifts for the combination of all the varied cosmological parameters. The …
Figure 13
Figure 13. Figure 13: Impact of the exclusion of large-scale modes. Left: we present the marginalised 1σ constraints on cosmological parameters from the power spectrum and bispectrum multipoles at z = 0.8. Right: we show the FoB and FoM for the combined parameters from Pℓ (blue) and Bℓ (re…
Figure 14
Figure 14. Figure 14: Best-fit models from joint power spectrum and bispectrum analysis versus measured spectra at z = 0.8. Left: redshift-space power spectrum multipoles. Middle: bispectrum multipoles in equilateral configurations. Right: bispectrum multipoles in squeezed configurations. …
Figure 15
Figure 15. Figure 15: Joint analysis of power spectrum and bispectrum. Marginalised parameter posterior distributions from power spectrum (blue), bispectrum (green), and their combination (red). The dashed lines are fiducial values of simulations. The redshifts and scale cuts are noted on …
Figure 16
Figure 16. Figure 16: Comparison of constraints from power spectrum and bispec￾trum alone and combined. Shown are 1σ error on fNL for fiducial value of fNL = 30 from power spectrum (blue) and bispectrum (green) multi￾poles, and their combination (red) at four redshift bins considered. 6. C…
Figure 17
Figure 17. Figure 17: Information content of various multipoles on fNL. The inverse of the relative error on fNL with respect to the fiducial value of fNL = 30 for power spectrum multipoles (blue), bispectrum multipoles (green), and their combination (red). In each coloured bar, the crosse…

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Reference graph

Works this paper leans on

251 extracted references · 251 canonical work pages · cited by 2 Pith papers

  1. [1]

    Galaxy 2-point correlation function modelling in redshift space

    Euclid Collaboration:. Euclid preparation. Galaxy 2-point correlation function modelling in redshift space. 2026. arXiv:2601.04780

  2. [2]

    Andrews et al

    Euclid Collaboration:. Euclid: Field-level inference of primordial non-Gaussianity and cosmic initial conditions. 2024. arXiv:2412.11945

  3. [3]

    Euclid preparation: Expected constraints on initial conditions. 2025. arXiv:2507.15819

  4. [4]

    M., & Philcox, O

    Chudaykin, Anton and Ivanov, Mikhail M. and Philcox, Oliver H. E. Reanalyzing DESI DR1. III. Constraints on inflation from galaxy power spectra and bispectra. Phys. Rev. D. 2026. doi:10.1103/fhj3-6q4x. arXiv:2512.04266

  5. [5]

    and Philcox, Oliver H

    Chudaykin, Anton and Ivanov, Mikhail M. and Philcox, Oliver H. E. Reanalyzing DESI DR1. I. CDM constraints from the power spectrum and bispectrum. Phys. Rev. D. 2026. doi:10.1103/qsnt-dppc. arXiv:2507.13433

  6. [6]

    Chudaykin, M

    Chudaykin, Anton and Ivanov, Mikhail M. and Philcox, Oliver H. E. Reanalyzing DESI DR1: 5. Cosmological Constraints with Simulation-Based Priors. 2026. arXiv:2602.18554

  7. [7]

    Ivanov, J.M

    Ivanov, Mikhail M. and Sullivan, James M. and Chen, Shi-Fan and Chudaykin, Anton and Maus, Mark and Philcox, Oliver H. E. Reanalyzing DESI DR1: 4. Percent-Level Cosmological Constraints from Combined Probes and Robust Evidence for the Normal Neutrino Mass Hierarchy. 2026. arXiv:2601.16165

  8. [8]

    Reanalyzing DESI DR1: 2. Constraints on Dark Energy, Spatial Curvature, and Neutrino Masses

    Chudaykin, Anton and Ivanov, Mikhail M. and Philcox, Oliver H. E. Reanalyzing DESI DR1: 2. Constraints on Dark Energy, Spatial Curvature, and Neutrino Masses. 2025. arXiv:2511.20757

Show all 251 references
  1. [9]

    Constraints on Local Primordial Non-Gaussianity with 3D Velocity Reconstruction from the Kinetic Sunyaev-Zeldovich Effect

    Lagu. Constraints on Local Primordial Non-Gaussianity with 3D Velocity Reconstruction from the Kinetic Sunyaev-Zeldovich Effect. Phys. Rev. Lett. 2025. doi:10.1103/PhysRevLett.134.151003. arXiv:2411.08240

  2. [10]

    and Ruggeri, Rossana

    Mueller, Eva-Maria and Percival, Will J. and Ruggeri, Rossana. Optimizing primordial non-Gaussianity measurements from galaxy surveys. MNRAS. 2019. doi:10.1093/mnras/sty3150. arXiv:1702.05088

  3. [11]

    and Smith, Kendrick M

    Hotinli, Selim C. and Smith, Kendrick M. and Ferraro, Simone. Velocity Reconstruction from KSZ: Measuring f_ NL with ACT and DESILS. 2025. arXiv:2506.21657

  4. [12]

    Loop corrections in nonlinear cosmological perturbation theory

    Scoccimarro, Roman and Frieman, Joshua. Loop corrections in nonlinear cosmological perturbation theory. ApJS. 1996. doi:10.1086/192306. arXiv:astro-ph/9509047

  5. [14]

    and Foreman, Simon and Schmittfull, Marcel and Senatore, Leonardo

    Angulo, Raul E. and Foreman, Simon and Schmittfull, Marcel and Senatore, Leonardo. The One-Loop Matter Bispectrum in the Effective Field Theory of Large Scale Structures. JCAP. 2015. doi:10.1088/1475-7516/2015/10/039. arXiv:1406.4143

  6. [15]

    The Bispectrum in the Effective Field Theory of Large Scale Structure

    Baldauf, Tobias and Mercolli, Lorenzo and Mirbabayi, Mehrdad and Pajer, Enrico. The Bispectrum in the Effective Field Theory of Large Scale Structure. JCAP. 2015. doi:10.1088/1475-7516/2015/05/007. arXiv:1406.4135

  7. [17]

    Bias Loop Corrections to the Galaxy Bispectrum

    Eggemeier, Alexander and Scoccimarro, Roman and Smith, Robert E. Bias Loop Corrections to the Galaxy Bispectrum. Phys. Rev. D. 2019. doi:10.1103/PhysRevD.99.123514. arXiv:1812.03208

  8. [19]

    The Inflationary Universe: A Possible Solution to the Horizon and Flatness Problems

    Guth, Alan H. The Inflationary Universe: A Possible Solution to the Horizon and Flatness Problems. Phys. Rev. D. 1981. doi:10.1103/PhysRevD.23.347

  9. [20]

    A New Type of Isotropic Cosmological Models Without Singularity

    Starobinsky, Alexei A. A New Type of Isotropic Cosmological Models Without Singularity. Phys. Lett. B. 1980. doi:10.1016/0370-2693(80)90670-X

  10. [21]

    A New Inflationary Universe Scenario: A Possible Solution of the Horizon, Flatness, Homogeneity, Isotropy and Primordial Monopole Problems

    Linde, Andrei D. A New Inflationary Universe Scenario: A Possible Solution of the Horizon, Flatness, Homogeneity, Isotropy and Primordial Monopole Problems. Phys. Lett. B. 1982. doi:10.1016/0370-2693(82)91219-9

  11. [22]

    Krolewski , Alex and Percival , Will J. and Ferraro , Simone and Chaussidon , Edmond and Rezaie , Mehdi and Aguilar , Jessica Nicole and Ahlen , Steven and Brooks , David and Dawson , Kyle and de la Macorra , Axel and Doel , Peter and Fanning , Kevin and Font-Ribera , Andreu a...

  12. [23]

    Extracting primordial non-gaussianity without cosmic variance

    Seljak, Uros. Extracting primordial non-gaussianity without cosmic variance. Phys. Rev. Lett. 2009. doi:10.1103/PhysRevLett.102.021302. arXiv:0807.1770

  13. [24]

    Bermejo-Climent , J. R. and Demina , R. and Krolewski , A. and Chaussidon , E. and Rezaie , M. and Ahlen , S. and Bailey , S. and Bianchi , D. and Brooks , D. and Burtin , E. and Claybaugh , T. and de la Macorra , A. and Dey , A. and Doel , P. and Farren , G. and Ferraro , S. ...

  14. [25]

    JCAP , keywords =

    Constraints on primordial non-Gaussianity from Quaia. JCAP , keywords =. doi:10.1088/1475-7516/2026/02/056 , archivePrefix =. 2504.20992 , primaryClass =

  15. [26]

    and Verde, L

    Grossi, M. and Verde, L. and Carbone, C. and Dolag, K. and Branchini, E. and Iannuzzi, F. and Matarrese, S. and Moscardini, L. Large-scale non-Gaussian mass function and halo bias: tests on N-body simulations. MNRAS. 2009. doi:10.1111/j.1365-2966.2009.15150.x. arXiv:0902.2013

  16. [27]

    Non-Gaussian halo bias and future galaxy surveys

    Carbone, Carmelita and Verde, Licia and Matarrese, Sabino. Non-Gaussian halo bias and future galaxy surveys. ApJL. 2008. doi:10.1086/592020. arXiv:0806.1950

  17. [28]

    The Halo mass function from excursion set theory

    Maggiore, Michele and Riotto, Antonio. The Halo mass function from excursion set theory. III. Non-Gaussian fluctuations. ApJ. 2010. doi:10.1088/0004-637X/717/1/526. arXiv:0903.1251

  18. [29]

    Universal halo mass function and scale-dependent bias from N-body simulations with non-Gaussian initial conditions

    Pillepich, Annalisa and Porciani, Cristiano and Hahn, Oliver. Universal halo mass function and scale-dependent bias from N-body simulations with non-Gaussian initial conditions. MNRAS. 2010. doi:10.1111/j.1365-2966.2009.15914.x. arXiv:0811.4176

  19. [31]

    and Rosenbluth, Marshall N

    Metropolis, Nicholas and Rosenbluth, Arianna W. and Rosenbluth, Marshall N. and Teller, Augusta H. and Teller, Edward. Equation of State Calculations by Fast Computing Machines. J. Chem. Phys. 1953. doi:10.1063/1.1699114

  20. [32]

    Hastings, W. K. Monte Carlo Sampling Methods Using Markov Chains and Their Applications. Biometrika. 1970. doi:10.1093/biomet/57.1.97

  21. [33]

    The Journal of Open Source Software , keywords =

    pocoMC: A Python package for accelerated Bayesian inference in astronomy and cosmology. The Journal of Open Source Software , keywords =. doi:10.21105/joss.04634 , archivePrefix =. 2207.05660 , primaryClass =

  22. [34]

    Feroz, Farhan and Hobson, M. P. and Bridges, Michael. MultiNest: an efficient and robust Bayesian inference tool for cosmology and particle physics. MNRAS. 2009. doi:10.1111/j.1365-2966.2009.14548.x. arXiv:0809.3437

  23. [35]

    nautilus: boosting Bayesian importance nested sampling with deep learning

    Lange, Johannes U. nautilus: boosting Bayesian importance nested sampling with deep learning. MNRAS. 2023. doi:10.1093/mnras/stad2431. arXiv:2306.16923

  24. [36]

    A Lagrangian effective field theory

    Vlah, Zvonimir and White, Martin and Aviles, Alejandro. A Lagrangian effective field theory. JCAP. 2015. doi:10.1088/1475-7516/2015/09/014. arXiv:1506.05264

  25. [37]

    Exploring redshift-space distortions in large-scale structure

    Vlah, Zvonimir and White, Martin. Exploring redshift-space distortions in large-scale structure. JCAP. 2019. doi:10.1088/1475-7516/2019/03/007. arXiv:1812.02775

  26. [38]

    On approximations of the redshift-space bispectrum and power spectrum multipoles covariance matrix

    Novell-Masot, Sergi and Gil-Mar \' n, H \'e ctor and Verde, Licia. On approximations of the redshift-space bispectrum and power spectrum multipoles covariance matrix. JCAP. 2024. doi:10.1088/1475-7516/2024/06/048. arXiv:2306.03137

  27. [39]

    On the impact of galaxy bias uncertainties on primordial non-Gaussianity constraints

    Barreira, Alexandre. On the impact of galaxy bias uncertainties on primordial non-Gaussianity constraints. JCAP. 2020. doi:10.1088/1475-7516/2020/12/031. arXiv:2009.06622

  28. [40]

    Galaxy power spectrum multipoles covariance in perturbation theory

    Wadekar, Digvijay and Scoccimarro, Roman. Galaxy power spectrum multipoles covariance in perturbation theory. Phys. Rev. D. 2020. doi:10.1103/PhysRevD.102.123517. arXiv:1910.02914

  29. [41]

    Predictions for local PNG bias in the galaxy power spectrum and bispectrum and the consequences for f _ NL constraints

    Barreira, Alexandre. Predictions for local PNG bias in the galaxy power spectrum and bispectrum and the consequences for f _ NL constraints. JCAP. 2022. doi:10.1088/1475-7516/2022/01/033. arXiv:2107.06887

  30. [44]

    Towards optimal cosmological parameter recovery from compressed bispectrum statistics

    Byun, Joyce and Eggemeier, Alexander and Regan, Donough and Seery, David and Smith, Robert E. Towards optimal cosmological parameter recovery from compressed bispectrum statistics. MNRAS. 2017. doi:10.1093/mnras/stx1681. arXiv:1705.04392

  31. [45]

    The covariance of squeezed bispectrum configurations

    Biagetti, Matteo and Castiblanco, Lina and Nore \ n a, Jorge and Sefusatti, Emiliano. The covariance of squeezed bispectrum configurations. JCAP. 2022. doi:10.1088/1475-7516/2022/09/009. arXiv:2111.05887

  32. [47]

    Primordial non-Gaussianity and non-Gaussian covariance

    Fl. Primordial non-Gaussianity and non-Gaussian covariance. Phys. Rev. D. 2023. doi:10.1103/PhysRevD.107.023528. arXiv:2206.10458

  33. [48]

    Bispectrum non-Gaussian covariance in redshift space

    Salvalaggio, Jacopo and Castiblanco, Lina and Nore \ n a, Jorge and Sefusatti, Emiliano and Monaco, Pierluigi. Bispectrum non-Gaussian covariance in redshift space. JCAP. 2024. doi:10.1088/1475-7516/2024/08/046. arXiv:2403.08634

  34. [49]

    a nen , E. and Kermiche , S. and Kiessling , A. and Kilbinger , M. and Kohley , R. and Kubik , B. and K \

    Euclid Collaboration: Castander , F. J. and Fosalba , P. and Stadel , J. and Potter , D. and Carretero , J. and Tallada-Cresp \' , P. and Pozzetti , L. and Bolzonella , M. and Mamon , G. A. and Blot , L. and Hoffmann , K. and Huertas-Company , M. and Monaco , P. and Gonzalez ,...

  35. [50]

    and Wechsler, Risa H

    Behroozi, Peter S. and Wechsler, Risa H. and Wu, Hao-Yi. The Rockstar Phase-Space Temporal Halo Finder and the Velocity Offsets of Cluster Cores. ApJ. 2013. doi:10.1088/0004-637X/762/2/109. arXiv:1110.4372

  36. [51]

    and Maksimova, Nina

    Hadzhiyska, Boryana and Eisenstein, Daniel and Bose, Sownak and Garrison, Lehman H. and Maksimova, Nina. compaso: A new halo finder for competitive assignment to spherical overdensities. MNRAS. 2021. doi:10.1093/mnras/stab2980. arXiv:2110.11408

  37. [52]

    The IllustrisTNG simulations: public data release

    Nelson , Dylan and Springel , Volker and Pillepich , Annalisa and Rodriguez-Gomez , Vicente and Torrey , Paul and Genel , Shy and Vogelsberger , Mark and Pakmor , Ruediger and Marinacci , Federico and Weinberger , Rainer and Kelley , Luke and Lovell , Mark and Diemer , Benedik...

  38. [53]

    JCAP , keywords =

    Estimating non-gaussian bias using counts of tracers. JCAP , keywords =. doi:10.1088/1475-7516/2026/04/037 , archivePrefix =. 2503.21024 , primaryClass =

  39. [54]

    and Seljak, Uros

    Sullivan, James M. and Seljak, Uros. Local Primordial non-Gaussian Bias from Time Evolution. 2025. arXiv:2503.21736

  40. [55]

    and Jamieson, Drew

    Shiveshwarkar, Charuhas and Loverde, Marilena and Hirata, Christopher M. and Jamieson, Drew. Where does non-Universality in Assembly Bias come from?. 2025. arXiv:2508.11798

  41. [56]

    and Chen, Shi-Fan

    Sullivan, James M. and Chen, Shi-Fan. Local primordial non-Gaussian bias at the field level. JCAP. 2025. doi:10.1088/1475-7516/2025/03/016. arXiv:2410.18039

  42. [57]

    and Jung, Gabriel and Karagiannis, Dionysios and Liguori, Michele and Ravenni, Andrea and Wandelt, Benjamin D

    Fondi, Emanuele and Verde, Licia and Villaescusa-Navarro, Francisco and Baldi, Marco and Coulton, William R. and Jung, Gabriel and Karagiannis, Dionysios and Liguori, Michele and Ravenni, Andrea and Wandelt, Benjamin D. Taming assembly bias for primordial non-Gaussianity. JCAP...

  43. [58]

    and Prijon, Tijan and Seljak, Uros

    Sullivan, James M. and Prijon, Tijan and Seljak, Uros. Learning to concentrate: multi-tracer forecasts on local primordial non-Gaussianity with machine-learned bias. JCAP. 2023. doi:10.1088/1475-7516/2023/08/004. arXiv:2303.08901

  44. [59]

    Halo assembly bias from a deep learning model of halo formation

    Lucie-Smith, Luisa and Barreira, Alexandre and Schmidt, Fabian. Halo assembly bias from a deep learning model of halo formation. MNRAS. 2023. doi:10.1093/mnras/stad2003. arXiv:2304.09880

  45. [60]

    Galacticus: A Semi-Analytic Model of Galaxy Formation

    Benson, Andrew J. Galacticus: A Semi-Analytic Model of Galaxy Formation. New Astron. 2012. doi:10.1016/j.newast.2011.07.004. arXiv:1008.1786

  46. [62]

    and Desjacques, V

    Marinucci, M. and Desjacques, V. and Benson, A. Non-Gaussian assembly bias from a semi-analytic galaxy formation model. MNRAS. 2023. doi:10.1093/mnras/stad1884. arXiv:2303.10337

  47. [63]

    N-body simulations with generic non-Gaussian initial conditions II: Halo bias

    Wagner, Christian and Verde, Licia. N-body simulations with generic non-Gaussian initial conditions II: Halo bias. JCAP. 2012. doi:10.1088/1475-7516/2012/03/002. arXiv:1102.3229

  48. [64]

    Assembly bias in the local PNG halo bias and its implication for f _ NL constraints

    Lazeyras, Titouan and Barreira, Alexandre and Schmidt, Fabian and Desjacques, Vincent. Assembly bias in the local PNG halo bias and its implication for f _ NL constraints. JCAP. 2023. doi:10.1088/1475-7516/2023/01/023. arXiv:2209.07251

  49. [65]

    Scale Dependence of the Halo Bias in General Local-Type Non-Gaussian Models I: Analytical Predictions and Consistency Relations

    Nishimichi, Takahiro. Scale Dependence of the Halo Bias in General Local-Type Non-Gaussian Models I: Analytical Predictions and Consistency Relations. JCAP. 2012. doi:10.1088/1475-7516/2012/08/037. arXiv:1204.3490

  50. [66]

    Scale-dependent bias from an inflationary bispectrum: the effect of a stochastic moving barrier

    Biagetti, Matteo and Desjacques, Vincent. Scale-dependent bias from an inflationary bispectrum: the effect of a stochastic moving barrier. MNRAS. 2015. doi:10.1093/mnras/stv1174. arXiv:1501.04982

  51. [67]

    and Arroja , F

    Planck Collaboration: Akrami , Y. and Arroja , F. and Ashdown , M. and Aumont , J. and Baccigalupi , C. and Ballardini , M. and Banday , A. J. and Barreiro , R. B. and Bartolo , N. and Basak , S. and Benabed , K. and Bernard , J. -P. and Bersanelli , M. and Bielewicz , P. and ...

  52. [68]

    Non-Gaussian Halo Bias Re-examined: Mass-dependent Amplitude from the Peak-Background Split and Thresholding

    Desjacques, Vincent and Jeong, Donghui and Schmidt, Fabian. Non-Gaussian Halo Bias Re-examined: Mass-dependent Amplitude from the Peak-Background Split and Thresholding. Phys. Rev. D. 2011. doi:10.1103/PhysRevD.84.063512. arXiv:1105.3628

  53. [69]

    Can we actually constrain f _ NL using the scale-dependent bias effect? An illustration of the impact of galaxy bias uncertainties using the BOSS DR12 galaxy power spectrum

    Barreira, Alexandre. Can we actually constrain f _ NL using the scale-dependent bias effect? An illustration of the impact of galaxy bias uncertainties using the BOSS DR12 galaxy power spectrum. JCAP. 2022. doi:10.1088/1475-7516/2022/11/013. arXiv:2205.05673

  54. [70]

    Galaxy bias and primordial non-Gaussianity: insights from galaxy formation simulations with IllustrisTNG

    Barreira, Alexandre and Cabass, Giovanni and Schmidt, Fabian and Pillepich, Annalisa and Nelson, Dylan. Galaxy bias and primordial non-Gaussianity: insights from galaxy formation simulations with IllustrisTNG. JCAP. 2020. doi:10.1088/1475-7516/2020/12/013. arXiv:2006.09368

  55. [71]

    Structure formation from non-Gaussian initial conditions: multivariate biasing, statistics, and comparison with N-body simulations

    Giannantonio, Tommaso and Porciani, Cristiano. Structure formation from non-Gaussian initial conditions: multivariate biasing, statistics, and comparison with N-body simulations. Phys. Rev. D. 2010. doi:10.1103/PhysRevD.81.063530. arXiv:0911.0017

  56. [73]

    Primordial non-gaussianity, statistics of collapsed objects, and the Integrated Sachs-Wolfe effect

    Afshordi, Niayesh and Tolley, Andrew J. Primordial non-gaussianity, statistics of collapsed objects, and the Integrated Sachs-Wolfe effect. Phys. Rev. D. 2008. doi:10.1103/PhysRevD.78.123507. arXiv:0806.1046

  57. [74]

    What the ''simple renormalization group'' approach to dark matter clustering really was

    McDonald, Patrick. What the ''simple renormalization group'' approach to dark matter clustering really was. 2014. arXiv:1403.7235

  58. [75]

    Clustering of dark matter tracers: generalizing bias for the coming era of precision LSS

    McDonald, Patrick and Roy, Arabindo. Clustering of dark matter tracers: generalizing bias for the coming era of precision LSS. JCAP. 2009. doi:10.1088/1475-7516/2009/08/020. arXiv:0902.0991

  59. [76]

    Primordial non-Gaussianity: large-scale structure signature in the perturbative bias model

    McDonald, Patrick. Primordial non-Gaussianity: large-scale structure signature in the perturbative bias model. Phys. Rev. D. 2008. doi:10.1103/PhysRevD.78.123519. arXiv:0806.1061

  60. [77]

    The renormalization group for large-scale structure: primordial non-Gaussianities

    Nikolis, Charalampos and Rubira, Henrique and Schmidt, Fabian. The renormalization group for large-scale structure: primordial non-Gaussianities. JCAP. 2024. doi:10.1088/1475-7516/2024/08/017. arXiv:2405.21002

  61. [78]

    Constraints on local primordial non-Gaussianity from large scale structure

    Slosar, Anze and Hirata, Christopher and Seljak, Uros and Ho, Shirley and Padmanabhan, Nikhil. Constraints on local primordial non-Gaussianity from large scale structure. JCAP. 2008. doi:10.1088/1475-7516/2008/08/031. arXiv:0805.3580

  62. [79]

    The effect of primordial non-Gaussianity on halo bias

    Matarrese, Sabino and Verde, Licia. The effect of primordial non-Gaussianity on halo bias. ApJL. 2008. doi:10.1086/587840. arXiv:0801.4826

  63. [80]

    The imprints of primordial non-gaussianities on large-scale structure: scale dependent bias and abundance of virialized objects

    Dalal, Neal and Dore, Olivier and Huterer, Dragan and Shirokov, Alexander. The imprints of primordial non-gaussianities on large-scale structure: scale dependent bias and abundance of virialized objects. Phys. Rev. D. 2008. doi:10.1103/PhysRevD.77.123514. arXiv:0710.4560

  64. [81]

    Verifying the consistency relation for the scale-dependent bias from local primordial non-Gaussianity

    Biagetti, Matteo and Lazeyras, Titouan and Baldauf, Tobias and Desjacques, Vincent and Schmidt, Fabian. Verifying the consistency relation for the scale-dependent bias from local primordial non-Gaussianity. MNRAS. 2017. doi:10.1093/mnras/stx714. arXiv:1611.04901

  65. [82]

    Bridle, S. L. and Crittenden, R. and Melchiorri, A. and Hobson, M. P. and Kneissl, R. and Lasenby, A. N. Analytic marginalization over CMB calibration and beam uncertainty. MNRAS. 2002. doi:10.1046/j.1365-8711.2002.05709.x. arXiv:astro-ph/0112114

  66. [83]

    Taylor, A. N. and Kitching, T. D. Analytic Methods for Cosmological Likelihoods. MNRAS. 2010. doi:10.1111/j.1365-2966.2010.17201.x. arXiv:1003.1136

  67. [84]

    Philcox, Oliver H. E. and Ivanov, Mikhail M. and Zaldarriaga, Matias and Simonovic, Marko and Schmittfull, Marcel. Fewer Mocks and Less Noise: Reducing the Dimensionality of Cosmological Observables with Subspace Projections. Phys. Rev. D. 2021. doi:10.1103/PhysRevD.103.043508...

  68. [86]

    Galilean invariance and the consistency relation for the nonlinear squeezed bispectrum of large scale structure

    Peloso, Marco and Pietroni, Massimo. Galilean invariance and the consistency relation for the nonlinear squeezed bispectrum of large scale structure. JCAP. 2013. doi:10.1088/1475-7516/2013/05/031. arXiv:1302.0223

  69. [87]

    and Riotto, A

    Kehagias, A. and Riotto, A. Symmetries and Consistency Relations in the Large Scale Structure of the Universe. Nucl. Phys. B. 2013. doi:10.1016/j.nuclphysb.2013.05.009. arXiv:1302.0130

  70. [88]

    Single-Field Consistency Relations of Large Scale Structure

    Creminelli, Paolo and Nore\ na, Jorge and Simonovi\'c, Marko and Vernizzi, Filippo. Single-Field Consistency Relations of Large Scale Structure. JCAP. 2013. doi:10.1088/1475-7516/2013/12/025. arXiv:1309.3557

  71. [89]

    and Seo, Hee-jong and White, Martin J

    Eisenstein, Daniel J. and Seo, Hee-jong and White, Martin J. On the Robustness of the Acoustic Scale in the Low-Redshift Clustering of Matter. ApJ. 2007. doi:10.1086/518755. arXiv:astro-ph/0604361

  72. [90]

    Nonlinear Evolution of Baryon Acoustic Oscillations

    Crocce, Martin and Scoccimarro, Roman. Nonlinear Evolution of Baryon Acoustic Oscillations. Phys. Rev. D. 2008. doi:10.1103/PhysRevD.77.023533. arXiv:0704.2783

  73. [91]

    and Spergel, David N

    Sugiyama, Naonori S. and Spergel, David N. How does non-linear dynamics affect the baryon acoustic oscillation?. JCAP. 2014. doi:10.1088/1475-7516/2014/02/042. arXiv:1306.6660

  74. [92]

    Resumming Cosmological Perturbations via the Lagrangian Picture: One-loop Results in Real Space and in Redshift Space

    Matsubara, Takahiko. Resumming Cosmological Perturbations via the Lagrangian Picture: One-loop Results in Real Space and in Redshift Space. Phys. Rev. D. 2008. doi:10.1103/PhysRevD.77.063530. arXiv:0711.2521

  75. [93]

    Nonlinear perturbation theory with halo bias and redshift-space distortions via the Lagrangian picture

    Matsubara, Takahiko. Nonlinear perturbation theory with halo bias and redshift-space distortions via the Lagrangian picture. Phys. Rev. D. 2008. doi:10.1103/PhysRevD.78.109901. arXiv:0807.1733

  76. [94]

    Convolution Lagrangian perturbation theory for biased tracers

    Carlson, Jordan and Reid, Beth and White, Martin. Convolution Lagrangian perturbation theory for biased tracers. MNRAS. 2013. doi:10.1093/mnras/sts457. arXiv:1209.0780

  77. [95]

    and Senatore, Leonardo and Zaldarriaga, Matias

    Porto, Rafael A. and Senatore, Leonardo and Zaldarriaga, Matias. The Lagrangian-space Effective Field Theory of Large Scale Structures. JCAP. 2014. doi:10.1088/1475-7516/2014/05/022. arXiv:1311.2168

  78. [98]

    On the IR-Resummation in the EFTofLSS

    Senatore, Leonardo and Trevisan, Gabriele. On the IR-Resummation in the EFTofLSS. JCAP. 2018. doi:10.1088/1475-7516/2018/05/019. arXiv:1710.02178

  79. [99]

    The IR-resummed Effective Field Theory of Large Scale Structures

    Senatore, Leonardo and Zaldarriaga, Matias. The IR-resummed Effective Field Theory of Large Scale Structures. JCAP. 2015. doi:10.1088/1475-7516/2015/02/013. arXiv:1404.5954

  80. [100]

    An analytic implementation of the IR-resummation for the BAO peak

    Lewandowski, Matthew and Senatore, Leonardo. An analytic implementation of the IR-resummation for the BAO peak. JCAP. 2020. doi:10.1088/1475-7516/2020/03/018. arXiv:1810.11855

  81. [105]

    Gravitational clustering from chi 2 initial conditions

    Scoccimarro, Roman. Gravitational clustering from chi 2 initial conditions. ApJ. 2000. doi:10.1086/309519. arXiv:astro-ph/0002037

  82. [106]

    Large scale structure, the cosmic microwave background, and primordial non-gaussianity

    Verde, Licia and Wang, Li-Min and Heavens, Alan and Kamionkowski, Marc. Large scale structure, the cosmic microwave background, and primordial non-gaussianity. MNRAS. 2000. doi:10.1046/j.1365-8711.2000.03191.x. arXiv:astro-ph/9906301

  83. [107]

    Probing primordial non-Gaussianity with large - scale structure

    Scoccimarro, Roman and Sefusatti, Emiliano and Zaldarriaga, Matias. Probing primordial non-Gaussianity with large - scale structure. Phys. Rev. D. 2004. doi:10.1103/PhysRevD.69.103513. arXiv:astro-ph/0312286

  84. [109]

    and Gaztanaga, Enrique

    Fry, James N. and Gaztanaga, Enrique. Biasing and hierarchical statistics in large scale structure. ApJ. 1993. doi:10.1086/173015. arXiv:astro-ph/9302009

  85. [110]

    and Verde, Licia and Heavens, A

    Matarrese, S. and Verde, Licia and Heavens, A. F. Large scale bias in the universe: Bispectrum method. MNRAS. 1997. doi:10.1093/mnras/290.4.651. arXiv:astro-ph/9706059

  86. [111]

    Scoccimarro, Roman and Couchman, H. M. P. and Frieman, Joshua A. The Bispectrum as a Signature of Gravitational Instability in Redshift-Space. ApJ. 1999. doi:10.1086/307220. arXiv:astro-ph/9808305

  87. [112]

    and Salazar-Albornoz, Salvador and Dalla Vecchia, Claudio

    Grieb, Jan Niklas and S \'a nchez, Ariel G. and Salazar-Albornoz, Salvador and Dalla Vecchia, Claudio. Gaussian covariance matrices for anisotropic galaxy clustering measurements. MNRAS. 2016. doi:10.1093/mnras/stw065. arXiv:1509.04293

  88. [117]

    Biased Tracers in Redshift Space in the EFT of Large-Scale Structure

    Perko, Ashley and Senatore, Leonardo and Jennings, Elise and Wechsler, Risa H. Biased Tracers in Redshift Space in the EFT of Large-Scale Structure. 2016. arXiv:1610.09321

  89. [118]

    The Open Journal of Astrophysics , keywords =

    Rapid cosmological inference with the two-loop matter power spectrum. The Open Journal of Astrophysics , keywords =. doi:10.33232/001c.157501 , archivePrefix =. 2508.00611 , primaryClass =

  90. [119]

    and Philcox, Oliver H

    Bakx, Thomas and Ivanov, Mikhail M. and Philcox, Oliver H. E. and Vlah, Zvonimir. One-Loop Galaxy Bispectrum: Consistent Theory, Efficient Analysis with COBRA, and Implications for Cosmological Parameters. 2025. arXiv:2507.22110

  91. [120]

    Efficient evaluation of the dark-matter two-loop power spectrum in the EFT of LSS

    Anastasiou, Charalampos and Favorito, Andrea and Lewandowski, Matthew and Senatore, Leonardo and Zheng, Henry. Efficient evaluation of the dark-matter two-loop power spectrum in the EFT of LSS. 2025. arXiv:2509.05187

  92. [122]

    COBRA: Optimal Factorization of Cosmological Observables

    Bakx, Thomas and Chisari, Nora Elisa and Vlah, Zvonimir. COBRA: Optimal Factorization of Cosmological Observables. Phys. Rev. Lett. 2025. doi:10.1103/PhysRevLett.134.191002. arXiv:2407.04660

  93. [123]

    Galaxy Bias and Primordial Non-Gaussianity

    Assassi, Valentin and Baumann, Daniel and Schmidt, Fabian. Galaxy Bias and Primordial Non-Gaussianity. JCAP. 2015. doi:10.1088/1475-7516/2015/12/043. arXiv:1510.03723

  94. [124]

    and Frenk, Carlos S

    Navarro, Julio F. and Frenk, Carlos S. and White, Simon D. M. A Universal density profile from hierarchical clustering. ApJ. 1997. doi:10.1086/304888. arXiv:astro-ph/9611107

  95. [125]

    and Lee , Hayden and Maleknejad , Azadeh and Meerburg , P

    Ach \'u carro , Ana and Biagetti , Matteo and Braglia , Matteo and Cabass , Giovanni and Caldwell , Robert and Castorina , Emanuele and Chen , Xingang and Coulton , William and Flauger , Raphael and Fumagalli , Jacopo and Ivanov , Mikhail M. and Lee , Hayden and Maleknejad , A...

  96. [126]

    and Lewandowski, Matthew and Mirbabayi, Mehrdad and Simonovi\'c, Marko

    Cabass, Giovanni and Ivanov, Mikhail M. and Lewandowski, Matthew and Mirbabayi, Mehrdad and Simonovi\'c, Marko. Snowmass white paper: Effective field theories in cosmology. Phys. Dark Univ. 2023. doi:10.1016/j.dark.2023.101193. arXiv:2203.08232

  97. [127]

    Cosmological perturbation theory using the FFTLog: formalism and connection to QFT loop integrals

    Simonovi\'c, Marko and Baldauf, Tobias and Zaldarriaga, Matias and Carrasco, John Joseph and Kollmeier, Juna A. Cosmological perturbation theory using the FFTLog: formalism and connection to QFT loop integrals. JCAP. 2018. doi:10.1088/1475-7516/2018/04/030. arXiv:1708.08130

  98. [129]

    and Paczynski, B

    Alcock, C. and Paczynski, B. An evolution free test for non-zero cosmological constant. Nature. 1979. doi:10.1038/281358a0

  99. [131]

    and Philcox, Oliver H

    Ivanov, Mikhail M. and Philcox, Oliver H. E. and Cabass, Giovanni and Nishimichi, Takahiro and Simonovi \'c , Marko and Zaldarriaga, Matias. Cosmology with the galaxy bispectrum multipoles: Optimal estimation and application to BOSS data. Phys. Rev. D. 2023. doi:10.1103/PhysRe...

  100. [133]

    and Saito, Shun and Beutler, Florian and Seo, Hee-Jong

    Sugiyama, Naonori S. and Saito, Shun and Beutler, Florian and Seo, Hee-Jong. Perturbation theory approach to predict the covariance matrices of the galaxy power spectrum and bispectrum in redshift space. MNRAS. 2020. doi:10.1093/mnras/staa1940. arXiv:1908.06234

  101. [134]

    and Castorina, Emanuele and Bonici, Marco and Bianchi, Davide

    Cagliari, Marina S. and Castorina, Emanuele and Bonici, Marco and Bianchi, Davide. Optimal constraints on Primordial non-Gaussianity with the eBOSS DR16 quasars in Fourier space. JCAP. 2024. doi:10.1088/1475-7516/2024/08/036. arXiv:2309.15814

  102. [135]

    and Barberi-Squarotti, Matilde and Pardede, Kevin and Castorina, Emanuele and D'Amico, Guido

    Cagliari, Marina S. and Barberi-Squarotti, Matilde and Pardede, Kevin and Castorina, Emanuele and D'Amico, Guido. Bispectrum constraints on Primordial Non-Gaussianities with the eBOSS DR16 quasars. JCAP. 2025. doi:10.1088/1475-7516/2025/07/043. arXiv:2502.14758

  103. [136]

    and Y \`e che , C

    Chaussidon , E. and Y \`e che , C. and de Mattia , A. and Payerne , C. and McDonald , P. and Ross , A. J. and Ahlen , S. and Bianchi , D. and Brooks , D. and Burtin , E. and Claybaugh , T. and de la Macorra , A. and Doel , P. and Ferraro , S. and Font-Ribera , A. and Forero-Ro...

  104. [137]

    and Ross , Ashley J

    Mueller , Eva-Maria and Rezaie , Mehdi and Percival , Will J. and Ross , Ashley J. and Ruggeri , Rossana and Seo , Hee-Jong and Gil-Mar \' n , H \'e ctor and Bautista , Julian and Brownstein , Joel R. and Dawson , Kyle and de la Macorra , Axel and Palanque-Delabrouille , Natha...

  105. [138]

    Towards optimal and robust f \_ nl constraints with multi-tracer analyses

    Barreira, Alexandre and Krause, Elisabeth. Towards optimal and robust f \_ nl constraints with multi-tracer analyses. JCAP. 2023. doi:10.1088/1475-7516/2023/10/044. arXiv:2302.09066

  106. [139]

    Baumgart, D. J. and Fry, James N. Fourier spectra of three-dimensional data. ApJ. 1991. doi:10.1086/170166

  107. [140]

    and Frieman, Joshua A

    Feldman, Hume A. and Frieman, Joshua A. and Fry, James N. and Scoccimarro, Roman. Constraints on galaxy bias, matter density, and primordial non-gausianity from the PSCz galaxy redshift survey. Phys. Rev. Lett. 2001. doi:10.1103/PhysRevLett.86.1434. arXiv:astro-ph/0010205

  108. [141]

    and Fry, James N

    Scoccimarro, Roman and Feldman, Hume A. and Fry, James N. and Frieman, Joshua A. The Bispectrum of IRAS redshift catalogs. ApJ. 2001. doi:10.1086/318284. arXiv:astro-ph/0004087

  109. [142]

    and Percival , Will J

    Verde , Licia and Heavens , Alan F. and Percival , Will J. and Matarrese , Sabino and Baugh , Carlton M. and Bland-Hawthorn , Joss and Bridges , Terry and Cannon , Russell and Cole , Shaun and Colless , Matthew and Collins , Chris and Couch , Warrick and Dalton , Gavin and De ...

  110. [144]

    and Gil-Mar \' n , H

    Novell-Masot , S. and Gil-Mar \' n , H. and Verde , L. and Aguilar , J. and Ahlen , S. and Bailey , S. and BenZvi , S. and Bianchi , D. and Brooks , D. and Buckley-Geer , E. and Carnero Rosell , A. and Chaussidon , E. and Claybaugh , T. and Cole , S. and Cuceu , A. and Dawson ...

  111. [145]

    DESI Collaboration and Aghamousa , Amir and Aguilar , Jessica and Ahlen , Steve and Alam , Shadab and Allen , Lori E. and Allende Prieto , Carlos and Annis , James and Bailey , Stephen and Balland , Christophe and Ballester , Otger and Baltay , Charles and Beaufore , Lucas and...

  112. [146]

    and Abdurro'uf and Acevedo Barroso , J

    Euclid Collaboration: Mellier , Y. and Abdurro'uf and Acevedo Barroso , J. A. and Ach \'u carro , A. and Adamek , J. and Adam , R. and Addison , G. E. and Aghanim , N. and Aguena , M. and Ajani , V. and Akrami , Y. and Al-Bahlawan , A. and Alavi , A. and Albuquerque , I. S. an...

  113. [147]

    Redshift-weighted constraints on primordial non-Gaussianity from the clustering of the eBOSS DR14 quasars in Fourier space. JCAP. 2019. doi:10.1088/1475-7516/2019/09/010. arXiv:1904.08859

  114. [148]

    and Amiaux , J

    Laureijs , R. and Amiaux , J. and Arduini , S. and Augu \`e res , J. -L. and Brinchmann , J. and Cole , R. and Cropper , M. and Dabin , C. and Duvet , L. and Ealet , A. and Garilli , B. and Gondoin , P. and Guzzo , L. and Hoar , J. and Hoekstra , H. and Holmes , R. and Kitchin...

  115. [149]

    Primordial non-Gaussianities and zero bias tracers of the Large Scale Structure

    Castorina, Emanuele and Feng, Yu and Seljak, Uros and Villaescusa-Navarro, Francisco. Primordial non-Gaussianities and zero bias tracers of the Large Scale Structure. Phys. Rev. Lett. 2018. doi:10.1103/PhysRevLett.121.101301. arXiv:1803.11539

  116. [150]

    Cosmology with the SPHEREX All-Sky Spectral Survey

    Dor \'e , Olivier and Bock , Jamie and Ashby , Matthew and Capak , Peter and Cooray , Asantha and de Putter , Roland and Eifler , Tim and Flagey , Nicolas and Gong , Yan and Habib , Salman and Heitmann , Katrin and Hirata , Chris and Jeong , Woong-Seob and Katti , Raj and Korn...

  117. [151]

    The Cosmic Linear Anisotropy Solving System (CLASS) I: Overview

    Lesgourgues, Julien. The Cosmic Linear Anisotropy Solving System (CLASS) I: Overview. 2011. arXiv:1104.2932

  118. [152]

    and Moretti , C

    Euclid Collaboration: Pezzotta , A. and Moretti , C. and Zennaro , M. and Moradinezhad Dizgah , A. and Crocce , M. and Sefusatti , E. and Ferrero , I. and Pardede , K. and Eggemeier , A. and Barreira , A. and Angulo , R. E. and Marinucci , M. and Camacho Quevedo , B. and de la...

  119. [153]

    a nen , E. and Kermiche , S. and Kiessling , A. and Kubik , B. and K \

    Euclid Collaboration: Guidi , M. and Veropalumbo , A. and Pugno , A. and Moresco , M. and Sefusatti , E. and Porciani , C. and Branchini , E. and Breton , M. -A. and Camacho Quevedo , B. and Crocce , M. and de la Torre , S. and Desjacques , V. and Eggemeier , A. and Farina , A...

  120. [154]

    and Samushia , Lado and Weinberg , David H

    Wang , Yun and Zhai , Zhongxu and Alavi , Anahita and Massara , Elena and Pisani , Alice and Benson , Andrew and Hirata , Christopher M. and Samushia , Lado and Weinberg , David H. and Colbert , James and Dor \'e , Olivier and Eifler , Tim and Heinrich , Chen and Ho , Shirley ...

  121. [155]

    and Tyson , J

    Ivezi \'c , Z eljko and Kahn , Steven M. and Tyson , J. Anthony and Abel , Bob and Acosta , Emily and Allsman , Robyn and Alonso , David and AlSayyad , Yusra and Anderson , Scott F. and Andrew , John and Angel , James Roger P. and Angeli , George Z. and Ansari , Reza and Antil...

  122. [156]

    Cosmological constraints from the nonlinear galaxy bispectrum

    Hahn, ChangHoon and Eickenberg, Michael and Ho, Shirley and Hou, Jiamin and Lemos, Pablo and Massara, Elena and Modi, Chirag and Moradinezhad Dizgah, Azadeh and Parker, Liam and Blancard, Bruno R\'egaldo-Saint. Cosmological constraints from the nonlinear galaxy bispectrum. Phy...

  123. [157]

    Phys. Rev. D , number =. 2022 , bdsk-url-1 =. doi:10.1103/PhysRevD.106.043506 , eprint =

  124. [158]

    Phys. Rev. Lett. , number =. 2022 , bdsk-url-1 =. doi:10.1103/PhysRevLett.129.021301 , eprint =

  125. [160]

    2020 , bdsk-url-1 =

    JCAP , pages =. 2020 , bdsk-url-1 =. doi:10.1088/1475-7516/2020/05/005 , eprint =

  126. [162]

    2015 , bdsk-url-1 =

    MNRAS , number =. 2015 , bdsk-url-1 =. doi:10.1093/mnras/stv961 , eprint =

  127. [163]

    2015 , bdsk-url-1 =

    MNRAS , number =. 2015 , bdsk-url-1 =. doi:10.1093/mnras/stv1359 , eprint =

  128. [164]

    2017 , bdsk-url-1 =

    MNRAS , number =. 2017 , bdsk-url-1 =. doi:10.1093/mnras/stw2679 , eprint =

  129. [165]

    Interacting dark energy from the joint analysis of the power spectrum and bispectrum multipoles with the EFTofLSS

    Tsedrik, Maria and Moretti, Chiara and Carrilho, Pedro and Rizzo, Federico and Pourtsidou, Alkistis. Interacting dark energy from the joint analysis of the power spectrum and bispectrum multipoles with the EFTofLSS. 2022. doi:10.1093/mnras/stad260. arXiv:2207.13011

  130. [166]

    Primordial Non-Gaussianity from Biased Tracers: Likelihood Analysis of Real-Space Power Spectrum and Bispectrum

    Moradinezhad Dizgah, Azadeh and Biagetti, Matteo and Sefusatti, Emiliano and Desjacques, Vincent and Nore \ n a, Jorge. Primordial Non-Gaussianity from Biased Tracers: Likelihood Analysis of Real-Space Power Spectrum and Bispectrum. JCAP. 2021. doi:10.1088/1475-7516/2021/05/01...

  131. [167]

    2023 , bdsk-url-1 =

    JCAP , pages =. 2023 , bdsk-url-1 =. doi:10.1088/1475-7516/2023/01/031 , eprint =

  132. [170]

    2021 , bdsk-url-1 =

    JCAP , pages =. 2021 , bdsk-url-1 =. doi:10.1088/1475-7516/2021/11/038 , eprint =

  133. [171]

    2020 , bdsk-url-1 =

    JCAP , pages =. 2020 , bdsk-url-1 =. doi:10.1088/1475-7516/2020/03/056 , eprint =

  134. [172]

    doi:10.1111/j.1365-2966.2012.21271.x , eprint =

    MNRAS , keywords =. doi:10.1111/j.1365-2966.2012.21271.x , eprint =

  135. [174]

    and Garrison, Lehman H

    Maksimova, Nina A. and Garrison, Lehman H. and Eisenstein, Daniel J. and Hadzhiyska, Boryana and Bose, Sownak and Satterthwaite, Thomas P. AbacusSummit: a massive set of high-accuracy, high-resolution N-body simulations. MNRAS. 2021. doi:10.1093/mnras/stab2484. arXiv:2110.11398

  136. [175]

    and Eisenstein, Daniel J

    Garrison, Lehman H. and Eisenstein, Daniel J. and Ferrer, Douglas and Maksimova, Nina A. and Pinto, Philip A. The abacus cosmological N-body code. MNRAS. 2021. doi:10.1093/mnras/stab2482. arXiv:2110.11392

  137. [176]

    and Eisenstein, Daniel J

    Hadzhiyska, Boryana and Garrison, Lehman H. and Eisenstein, Daniel J. and Ferraro, Simone. Modest set of simulations of local-type primordial non-Gaussianity in the DESI era. Phys. Rev. D. 2024. doi:10.1103/PhysRevD.109.103530. arXiv:2402.10881

  138. [177]

    MNRAS , keywords =

    The matter bispectrum in N-body simulations with non-Gaussian initial conditions. MNRAS , keywords =. doi:10.1111/j.1365-2966.2010.16723.x , archivePrefix =. 1003.0007 , primaryClass =

  139. [178]

    2000 , bdsk-url-1 =

    ApJ , pages =. 2000 , bdsk-url-1 =. doi:10.1086/317248 , eprint =

  140. [179]

    and Matarrese, Sabino and Moscardini, Lauro , date-added =

    Verde, Licia and Heavens, Alan F. and Matarrese, Sabino and Moscardini, Lauro , date-added =. Large-scale bias in the Universe - II. Redshift-space bispectrum , volume = 300, year = 1998, bdsk-file-1 =. MNRAS , keywords =. doi:10.1046/j.1365-8711.1998.01937.x , eprint =

  141. [180]

    2021 , bdsk-url-1 =

    JCAP , pages =. 2021 , bdsk-url-1 =. doi:10.1088/1475-7516/2021/03/021 , eprint =

  142. [181]

    2019 , bdsk-url-1 =

    MNRAS , number =. 2019 , bdsk-url-1 =. doi:10.1093/mnras/sty3143 , eprint =

  143. [182]

    2017 , bdsk-url-1 =

    MNRAS , number =. 2017 , bdsk-url-1 =. doi:10.1093/mnras/stx135 , eprint =

  144. [183]

    2021 , bdsk-url-1 =

    JCAP , pages =. 2021 , bdsk-url-1 =. doi:10.1088/1475-7516/2021/04/029 , eprint =

  145. [184]

    DEMNUni: Massive neutrinos and the bispectrum of large scale structures

    Ruggeri, Rossana and Castorina, Emanuele and Carbone, Carmelita and Sefusatti, Emiliano. DEMNUni: Massive neutrinos and the bispectrum of large scale structures. JCAP. 2018. doi:10.1088/1475-7516/2018/03/003. arXiv:1712.02334

  146. [185]

    , keywords =

    Primordial non-Gaussianity in the bispectrum of the halo density field. , keywords =. doi:10.1088/1475-7516/2011/04/006 , archivePrefix =. 1011.1513 , primaryClass =

  147. [186]

    Advances in Astronomy , keywords =

    Primordial Non-Gaussianity and Bispectrum Measurements in the Cosmic Microwave Background and Large-Scale Structure. Advances in Astronomy , keywords =. doi:10.1155/2010/980523 , archivePrefix =. 1001.4707 , primaryClass =

  148. [187]

    Sefusatti, Emiliano and Liguori, Michele and Yadav, Amit P. S. and Jackson, Mark G. and Pajer, Enrico. Constraining Running Non-Gaussianity. JCAP. 2009. doi:10.1088/1475-7516/2009/12/022. arXiv:0906.0232

  149. [188]

    Phys. Rev. D , pages =. 2007 , bdsk-url-1 =. doi:10.1103/PhysRevD.76.083004 , eprint =

  150. [189]

    Galaxy bias and halo-occupation numbers from large-scale clustering , volume = 71, year = 2005, bdsk-url-1 =

    Sefusatti, Emiliano and Scoccimarro, Rom. Galaxy bias and halo-occupation numbers from large-scale clustering , volume = 71, year = 2005, bdsk-url-1 =. , keywords =. doi:10.1103/PhysRevD.71.063001 , eprint =

  151. [190]

    Phys. Rev. D , pages =. 2006 , bdsk-url-1 =. doi:10.1103/PhysRevD.74.023522 , eprint =

  152. [191]

    Phys. Rev. D , number =. 2022 , bdsk-url-1 =. doi:10.1103/PhysRevD.106.043530 , eprint =

  153. [192]

    , keywords =

    Limits on primordial non-Gaussianities from BOSS galaxy-clustering data. , keywords =. doi:10.1103/PhysRevD.111.063514 , archivePrefix =. 2201.11518 , primaryClass =

  154. [193]

    CLASS-OneLoop: accurate and unbiased inference from spectroscopic galaxy surveys

    Linde, Dennis and Moradinezhad Dizgah, Azadeh and Radermacher, Christian and Casas, Santiago and Lesgourgues, Julien. CLASS-OneLoop: accurate and unbiased inference from spectroscopic galaxy surveys. JCAP. 2024. doi:10.1088/1475-7516/2024/07/068. arXiv:2402.09778

  155. [194]

    Redshift-Space Distortions in Lagrangian Perturbation Theory

    Chen, Shi-Fan and Vlah, Zvonimir and Castorina, Emanuele and White, Martin. Redshift-Space Distortions in Lagrangian Perturbation Theory. JCAP. 2021. doi:10.1088/1475-7516/2021/03/100. arXiv:2012.04636

  156. [196]

    The BOSS bispectrum analysis at one loop from the Effective Field Theory of Large-Scale Structure

    D'Amico, Guido and Donath, Yaniv and Lewandowski, Matthew and Senatore, Leonardo and Zhang, Pierre. The BOSS bispectrum analysis at one loop from the Effective Field Theory of Large-Scale Structure. JCAP. 2024. doi:10.1088/1475-7516/2024/05/059. arXiv:2206.08327

  157. [197]

    JCAP , keywords =

    The one-loop bispectrum of galaxies in redshift space from the Effective Field Theory of Large-Scale Structure. JCAP , keywords =. doi:10.1088/1475-7516/2024/07/041 , archivePrefix =. 2211.17130 , primaryClass =

  158. [198]

    arXiv , author =:2102.06902 , journal =

    doi:10.1103/PhysRevD.103.123550 , eid =. arXiv , author =:2102.06902 , journal =

  159. [201]

    2022 , bdsk-url-1 =

    MNRAS , number =. 2022 , bdsk-url-1 =. doi:10.1093/mnras/stac567 , eprint =

  160. [202]

    arXiv , author =:2212.11940 , month =

  161. [203]

    Two-loop bispectrum of large-scale structure

    Baldauf, Tobias and Garny, Mathias and Taule, Petter and Steele, Theo. Two-loop bispectrum of large-scale structure. Phys. Rev. D. 2021. doi:10.1103/PhysRevD.104.123551. arXiv:2110.13930

  162. [204]

    Phys. Rev. D , pages =. 2009 , bdsk-url-1 =. doi:10.1103/PhysRevD.80.123002 , eprint =

  163. [205]

    arXiv , author =:1006.0699 , journal =

    doi:10.1103/PhysRevD.82.063522 , eid =. arXiv , author =:1006.0699 , journal =

  164. [206]

    arXiv , author =:1705.02574 , journal =

    doi:10.1103/PhysRevD.96.043526 , eid =. arXiv , author =:1705.02574 , journal =

  165. [207]

    Precise Calibration of the One-Loop Bispectrum in the Effective Field Theory of Large Scale Structure

    Steele, Theodore and Baldauf, Tobias. Precise Calibration of the One-Loop Bispectrum in the Effective Field Theory of Large Scale Structure. Phys. Rev. D. 2021. doi:10.1103/PhysRevD.103.023520. arXiv:2009.01200

  166. [209]

    and Zennaro, Matteo and Contreras, Sergio and Aric

    Angulo, Raul E. and Zennaro, Matteo and Contreras, Sergio and Aric. The BACCO simulation project: exploiting the full power of large-scale structure for cosmology. MNRAS. 2021. doi:10.1093/mnras/stab2018. arXiv:2004.06245

  167. [211]

    FFT-PT: Reducing the two-loop large-scale structure power spectrum to low-dimensional radial integrals

    Schmittfull, Marcel and Vlah, Zvonimir. FFT-PT: Reducing the two-loop large-scale structure power spectrum to low-dimensional radial integrals. Phys. Rev. D. 2016. doi:10.1103/PhysRevD.94.103530. arXiv:1609.00349

  168. [212]

    arXiv , author =:astro-ph/9407049 , journal =

  169. [213]

    , keywords =

    The Galaxy correlation hierarchy in perturbation theory. , keywords =. doi:10.1086/161913 , adsurl =

  170. [214]

    , keywords =

    Renormalized halo bias. , keywords =. doi:10.1088/1475-7516/2014/08/056 , archivePrefix =. 1402.5916 , primaryClass =

  171. [215]

    , keywords =

    Large-scale galaxy bias. , keywords =. doi:10.1016/j.physrep.2017.12.002 , archivePrefix =. 1611.09787 , primaryClass =

  172. [216]

    arXiv , author =:1810.10104 , journal =

    doi:10.1103/PhysRevD.99.063530 , eid =. arXiv , author =:1810.10104 , journal =

  173. [217]

    arXiv , author =:1509.02120 , journal =

    doi:10.1088/1475-7516/2016/03/057 , eid =. arXiv , author =:1509.02120 , journal =

  174. [218]

    arXiv , author =:1804.05080 , journal =

    doi:10.1088/1475-7516/2018/07/053 , eid =. arXiv , author =:1804.05080 , journal =

  175. [219]

    arXiv , author =:1605.02149 , journal =

    doi:10.1088/1475-7516/2016/07/028 , eid =. arXiv , author =:1605.02149 , journal =

  176. [220]

    arXiv , author =:1504.04366 , journal =

    doi:10.1103/PhysRevD.92.043514 , eid =. arXiv , author =:1504.04366 , journal =

  177. [221]

    arXiv , author =:1206.2926 , journal =

    doi:10.1007/JHEP09(2012)082 , eid =. arXiv , author =:1206.2926 , journal =

  178. [222]

    arXiv , author =:1004.2488 , journal =

    doi:10.1088/1475-7516/2012/07/051 , eid =. arXiv , author =:1004.2488 , journal =

  179. [223]

    , keywords =

    Large-scale structure of the Universe and cosmological perturbation theory. , keywords =. doi:10.1016/S0370-1573(02)00135-7 , archivePrefix =. astro-ph/0112551 , primaryClass =

  180. [224]

    , keywords =

    The Evolution of Bias. , keywords =. doi:10.1086/310006 , adsurl =

  181. [225]

    Evidence for quadratic tidal tensor bias from the halo bispectrum , author =. Phys. Rev. D , volume =. 2012 , month =. doi:10.1103/PhysRevD.86.083540 , url =

  182. [226]

    Gravity and large-scale nonlocal bias , author =. Phys. Rev. D , volume =. 2012 , month =. doi:10.1103/PhysRevD.85.083509 , url =

  183. [227]

    Testing one-loop galaxy bias: Cosmological constraints from the power spectrum , author =. Phys. Rev. D , volume =. 2021 , month =. doi:10.1103/PhysRevD.104.043531 , url =

  184. [228]

    Testing one-loop galaxy bias: Power spectrum , author =. Phys. Rev. D , volume =. 2020 , month =. doi:10.1103/PhysRevD.102.103530 , url =

  185. [229]

    Nonlocal Lagrangian bias , author =. Phys. Rev. D , volume =. 2013 , month =. doi:10.1103/PhysRevD.87.083002 , url =

  186. [230]

    arXiv e-prints , keywords =

    COMET: Clustering Observables Modelled by Emulated perturbation Theory. arXiv e-prints , keywords =

  187. [231]

    arXiv e-prints , keywords =

    GetDist: a Python package for analysing Monte Carlo samples. arXiv e-prints , keywords =

  188. [232]

    , keywords =

    FAST-PT: a novel algorithm to calculate convolution integrals in cosmological perturbation theory. , keywords =. doi:10.1088/1475-7516/2016/09/015 , archivePrefix =. 1603.04826 , primaryClass =

  189. [233]

    , keywords =

    Efficient Computation of Cosmic Microwave Background Anisotropies in Closed Friedmann-Robertson-Walker Models. , keywords =. doi:10.1086/309179 , archivePrefix =. astro-ph/9911177 , primaryClass =

  190. [234]

    Communications in Applied Mathematics and Computational Science , keywords =

    Ensemble samplers with affine invariance. Communications in Applied Mathematics and Computational Science , keywords =. doi:10.2140/camcos.2010.5.65 , adsurl =

  191. [235]

    , keywords =

    emcee: The MCMC Hammer. , keywords =. doi:10.1086/670067 , archivePrefix =. 1202.3665 , primaryClass =

  192. [236]

    Rubin , title =

    Andrew Gelman and Donald B. Rubin , title =. Statistical Science , number =. 1992 , doi =

  193. [237]

    doi:10.1093/mnras/stw1229 , eprint =

    MNRAS , keywords =. doi:10.1093/mnras/stw1229 , eprint =

  194. [238]

    arXiv , author =:1610.06585 , journal =

    doi:10.1103/PhysRevD.96.023528 , eid =. arXiv , author =:1610.06585 , journal =

  195. [239]

    doi:10.1046/j.1365-8711.1999.02825.x , eprint =

    MNRAS , keywords =. doi:10.1046/j.1365-8711.1999.02825.x , eprint =

  196. [240]

    doi:10.1086/174036 , eprint =

    , keywords =. doi:10.1086/174036 , eprint =

  197. [241]

    arXiv , author =:1603.01453 , journal =

    doi:10.1051/0004-6361/201527081 , eid =. arXiv , author =:1603.01453 , journal =

  198. [242]

    Computational Astrophysics and Cosmology , keywords =

    PKDGRAV3: beyond trillion particle cosmological simulations for the next era of galaxy surveys. Computational Astrophysics and Cosmology , keywords =. doi:10.1186/s40668-017-0021-1 , archivePrefix =. 1609.08621 , primaryClass =

  199. [243]

    Beletic and Hyung Cho and Warren Holmes and Michael Seiffert and Steven Pravdo and Murzy Jhabvala and Augustyn Waczynski , title =

    Yibin Bai and Mark Farris and Lisa Fischer and Jessica Maiten and Robert Kopp and Eric Piquette and Jon Ellsworth and Aristo Yulius and Annie Chen and Stephanie Tallarico and Elizabeth Hernandez and Eric Holland and Ellen Boehmer and Michael Carmody and James W. Beletic and Hy...

  200. [244]

    Euclid preparation. V. Predicted yield of redshift 7 < z < 9 quasars from the wide survey. , keywords =. doi:10.1051/0004-6361/201936427 , archivePrefix =. 1908.04310 , primaryClass =

  201. [245]

    , keywords =

    New Grids of Pure-hydrogen White Dwarf NLTE Model Atmospheres and the HST/STIS Flux Calibration. , keywords =. doi:10.3847/1538-3881/ab94b4 , archivePrefix =. 2005.10945 , primaryClass =

  202. [246]

    Outgassing properties of vacuum materials for particle accelerators , keywords =

  203. [247]

    Euclid preparation. VII. Forecast validation for Euclid cosmological probes. , keywords =. doi:10.1051/0004-6361/202038071 , archivePrefix =. 1910.09273 , primaryClass =

  204. [248]

    , keywords =

    The Gaia mission. , keywords =. doi:10.1051/0004-6361/201629272 , archivePrefix =. 1609.04153 , primaryClass =

  205. [249]

    Euclid Definition Study Report

  206. [250]

    , keywords =

    Secondary standard stars for absolute spectrophotometry. , keywords =. 1983 , month =. doi:10.1086/160817 , adsurl =

  207. [251]

    The Euclid Wide Survey

    Euclid preparation: I. The Euclid Wide Survey

  208. [252]

    Modified gravity and massive neutrinos: constraints from the full shape analysis of BOSS galaxies and forecasts for Stage IV surveys

    Moretti, Chiara and Tsedrik, Maria and Carrilho, Pedro and Pourtsidou, Alkistis. Modified gravity and massive neutrinos: constraints from the full shape analysis of BOSS galaxies and forecasts for Stage IV surveys. JCAP. 2023. doi:10.1088/1475-7516/2023/12/025. arXiv:2306.09275

  209. [253]

    and Philcox, Oliver H

    Chudaykin, Anton and Ivanov, Mikhail M. and Philcox, Oliver H. E. and Simonovi\'c, Marko. Nonlinear perturbation theory extension of the Boltzmann code CLASS. Phys. Rev. D. 2020. doi:10.1103/PhysRevD.102.063533. arXiv:2004.10607

  210. [254]

    Limits on w CDM from the EFTofLSS with the PyBird code

    D'Amico, Guido and Senatore, Leonardo and Zhang, Pierre. Limits on w CDM from the EFTofLSS with the PyBird code. JCAP. 2021. doi:10.1088/1475-7516/2021/01/006. arXiv:2003.07956

  211. [255]

    Hamilton, A. J. S. Uncorrelated modes of the nonlinear power spectrum. MNRAS. 2000. doi:10.1046/j.1365-8711.2000.03071.x. arXiv:astro-ph/9905191

  212. [256]

    Effective Field Theory for Large-Scale Structure

    Ivanov, Mikhail M. Effective Field Theory for Large-Scale Structure. 2023. doi:10.1007/978-981-19-3079-9_5-1. arXiv:2212.08488

  213. [257]

    and Senatore, Leonardo and Simonovi\'c, Marko and Takada, Masahiro and Zaldarriaga, Matias and Zhang, Pierre

    Nishimichi, Takahiro and D'Amico, Guido and Ivanov, Mikhail M. and Senatore, Leonardo and Simonovi\'c, Marko and Takada, Masahiro and Zaldarriaga, Matias and Zhang, Pierre. Blinded challenge for precision cosmology with large-scale structure: results from effective field theor...

  214. [258]

    \'ector and Verde, Licia

    Gualdi, Davide and Gil-Mar\' n, H. \'ector and Verde, Licia. Joint analysis of anisotropic power spectrum, bispectrum and trispectrum: application to N-body simulations. JCAP. 2021. doi:10.1088/1475-7516/2021/07/008. arXiv:2104.03976

  215. [259]

    and Paterno, M

    Zuntz, J. and Paterno, M. and Jennings, E. and Rudd, D. and Manzotti, A. and Dodelson, S. and Bridle, S. and Sehrish, S. and Kowalkowski, J. , year=. CosmoSIS: Modular cosmological parameter estimation , volume=. doi:10.1016/j.ascom.2015.05.005 , journal=

  216. [260]

    and Nishimichi, Takahiro

    Chudaykin, Anton and Ivanov, Mikhail M. and Nishimichi, Takahiro. On priors and scale cuts in EFT-based full-shape analyses. 2024. arXiv:2410.16358

  217. [261]

    Constraints on the curvature of the Universe and dynamical dark energy from the Full-shape and BAO data

    Chudaykin, Anton and Dolgikh, Konstantin and Ivanov, Mikhail M. Constraints on the curvature of the Universe and dynamical dark energy from the Full-shape and BAO data. Phys. Rev. D. 2021. doi:10.1103/PhysRevD.103.023507. arXiv:2009.10106

  218. [263]

    Philcox, Oliver H. E. and Ivanov, Mikhail M. BOSS DR12 full-shape cosmology: CDM constraints from the large-scale galaxy power spectrum and bispectrum monopole. Phys. Rev. D. 2022. doi:10.1103/PhysRevD.105.043517. arXiv:2112.04515

  219. [264]

    Galaxy skew-spectra in redshift-space

    Schmittfull, Marcel and Moradinezhad Dizgah, Azadeh. Galaxy skew-spectra in redshift-space. JCAP. 2021. doi:10.1088/1475-7516/2021/03/020. arXiv:2010.14267

  220. [265]

    and Saito, Shun and Beutler, Florian and Seo, Hee-Jong

    Sugiyama, Naonori S. and Saito, Shun and Beutler, Florian and Seo, Hee-Jong. A complete FFT-based decomposition formalism for the redshift-space bispectrum. MNRAS. 2019. doi:10.1093/mnras/sty3249. arXiv:1803.02132

  221. [266]

    Maximal compression of the redshift space galaxy power spectrum and bispectrum

    Gualdi, Davide and Manera, Marc and Joachimi, Benjamin and Lahav, Ofer. Maximal compression of the redshift space galaxy power spectrum and bispectrum. MNRAS. 2018. doi:10.1093/mnras/sty261. arXiv:1709.03600

  222. [267]

    doi:10.1103/xjpb-tlrs , archivePrefix =

    Boosting galaxy clustering analyses with nonperturbative modeling of redshift-space distortions , journal =. doi:10.1103/xjpb-tlrs , archivePrefix =. 2501.18597 , primaryClass =

  223. [268]

    arXiv , author =:2110.10161 , journal =

    doi:10.1103/PhysRevD.105.063512 , eid =. arXiv , author =:2110.10161 , journal =

  224. [269]

    Large-scale Bias and Efficient Generation of Initial Conditions for Non-Local Primordial Non-Gaussianity

    Scoccimarro, Roman and Hui, Lam and Manera, Marc and Chan, Kwan Chuen. Large-scale Bias and Efficient Generation of Initial Conditions for Non-Local Primordial Non-Gaussianity. Phys. Rev. D. 2012. doi:10.1103/PhysRevD.85.083002. arXiv:1108.5512

  225. [270]

    Simulating galaxy formation with the IllustrisTNG model , volume=

    Pillepich, Annalisa and Springel, Volker and Nelson, Dylan and Genel, Shy and Naiman, Jill and Pakmor, Rüdiger and Hernquist, Lars and Torrey, Paul and Vogelsberger, Mark and Weinberger, Rainer and Marinacci, Federico , year=. Simulating galaxy formation with the IllustrisTNG ...

  226. [271]

    Simulating galaxy formation with black hole driven thermal and kinetic feedback , volume=

    Weinberger, Rainer and Springel, Volker and Hernquist, Lars and Pillepich, Annalisa and Marinacci, Federico and Pakmor, Rüdiger and Nelson, Dylan and Genel, Shy and Vogelsberger, Mark and Naiman, Jill and Torrey, Paul , year=. Simulating galaxy formation with black hole driven...

  227. [272]

    2021 , eprint=

    The IllustrisTNG Simulations: Public Data Release , author=. 2021 , eprint=

  228. [273]

    Scale-dependent bias induced by local non-Gaussianity: A comparison to N-body simulations

    Desjacques, Vincent and Seljak, Uros and Iliev, Ilian. Scale-dependent bias induced by local non-Gaussianity: A comparison to N-body simulations. MNRAS. 2009. doi:10.1111/j.1365-2966.2009.14721.x. arXiv:0811.2748

  229. [274]

    and Verde, Licia and Dolag, Klaus and Matarrese, Sabino and Moscardini, Lauro

    Reid, Beth A. and Verde, Licia and Dolag, Klaus and Matarrese, Sabino and Moscardini, Lauro. Non-Gaussian halo assembly bias. JCAP. 2010. doi:10.1088/1475-7516/2010/07/013. arXiv:1004.1637

  230. [275]

    Taming redshift-space distortion effects in the EFTofLSS and its application to data , volume=

    D’Amico, Guido and Senatore, Leonardo and Zhang, Pierre and Nishimichi, Takahiro , year=. Taming redshift-space distortion effects in the EFTofLSS and its application to data , volume=. Journal of Cosmology and Astroparticle Physics , publisher=. doi:10.1088/1475-7516/2024/01/...

  231. [276]

    Proceedings of the European Physical Society Conference on High Energy Physics

    CosmoHub and SciPIC: Massive cosmological data analysis, distribution and generation using a Big Data platform. Proceedings of the European Physical Society Conference on High Energy Physics. 5-12 July , year = 2017, month = jul, eid =. doi:10.22323/1.314.0488 , url =

  232. [277]

    Near optimal bispectrum estimators for large-scale structure

    Schmittfull, Marcel and Baldauf, Tobias and Seljak, Uro s. Near optimal bispectrum estimators for large-scale structure. Phys. Rev. D. 2015. doi:10.1103/PhysRevD.91.043530. arXiv:1411.6595

  233. [278]

    Range of validity of perturbative models for galaxy clustering and its uncertainty

    Gambardella, Giosu \`e and Biagetti, Matteo and Moretti, Chiara and Sefusatti, Emiliano. Range of validity of perturbative models for galaxy clustering and its uncertainty. Phys. Rev. D. 2024. doi:10.1103/PhysRevD.110.083502. arXiv:2311.04608

  234. [279]

    Proceedings of the European Physical Society Conference on High Energy Physics

    CosmoHub and SciPIC: Massive cosmological data analysis, distribution and generation using a Big Data platform. Proceedings of the European Physical Society Conference on High Energy Physics. 5-12 July , year = 2017, month = jul, eid =

  235. [280]

    Tallada and J

    P. Tallada and J. Carretero and J. Casals and C. Acosta-Silva and S. Serrano and M. Caubet and F.J. Castander and E. César and M. Crocce and M. Delfino and M. Eriksen and P. Fosalba and E. Gaztañaga and G. Merino and C. Neissner and N. Tonello. CosmoHub: Interactive exploratio...

  236. [281]

    The Wide Field Infrared Survey Telescope: 100 Hubbles for the 2020s. 2019. arXiv:1902.05569

  237. [282]

    2003 , bdsk-url-1 =

    JHEP , pages =. 2003 , bdsk-url-1 =. doi:10.1088/1126-6708/2003/05/013 , eprint =

  238. [283]

    Single field consistency relation for the 3-point function

    Creminelli, Paolo and Zaldarriaga, Matias. Single field consistency relation for the 3-point function. JCAP. 2004. doi:10.1088/1475-7516/2004/10/006. arXiv:astro-ph/0407059

  239. [284]

    2017 , bdsk-url-1 =

    JCAP , pages =. 2017 , bdsk-url-1 =. doi:10.1088/1475-7516/2017/01/003 , eprint =

  240. [285]

    , keywords =

    Figure of merit for dark energy constraints from current observational data. , keywords =. doi:10.1103/PhysRevD.77.123525 , archivePrefix =. 0803.4295 , primaryClass =

  241. [286]

    JCAP , keywords =

    Consistent modeling of velocity statistics and redshift-space distortions in one-loop perturbation theory. JCAP , keywords =. doi:10.1088/1475-7516/2020/07/062 , archivePrefix =. 2005.00523 , primaryClass =

  242. [287]

    Galaxy power spectrum and bispectrum modelling

    Euclid preparation. Galaxy power spectrum and bispectrum modelling

  243. [288]

    Galaxy power spectrum modelling in redshift space

    Euclid preparation. Galaxy power spectrum modelling in redshift space

Pith tools

Reviewed May 21, 2026 · model on record in the stance chip above.