{"paper":{"title":"Probing nonlinear structure formation beyond $\\Lambda$CDM with the LSS bootstrap: a joint power spectrum and bispectrum analysis","license":"http://creativecommons.org/licenses/by/4.0/","headline":"The LSS bootstrap yields first MCMC constraints on deviations from ΛCDM using power spectrum and bispectrum.","cross_cats":[],"primary_cat":"astro-ph.CO","authors_text":"Giorgia Biselli, Guido D'Amico, Marco Marinucci, Massimo Pietroni","submitted_at":"2026-05-13T10:12:06Z","abstract_excerpt":"We present the first MCMC-derived constraints on the parameters of the Large Scale Structure (LSS) bootstrap, a model-independent framework that captures deviations from $\\Lambda$CDM using symmetry arguments alone. Focusing on modifications to the linear growth rate and to the quadratic perturbation-theory kernel -- quantified by the fractional parameters $\\varepsilon_f$ and $\\varepsilon_{d_{\\gamma}}$, respectively -- we carry out a joint analysis of the one-loop galaxy power spectrum and the tree-level bispectrum multipoles within the EFTofLSS, employing the \\texttt{PyBird} code extended to i"},"claims":{"count":4,"items":[{"kind":"strongest_claim","text":"We present the first MCMC-derived constraints on the parameters of the Large Scale Structure (LSS) bootstrap... For BOSS, combining the power spectrum with the bispectrum monopole yields ∼7% constraints on ε_f and ∼57% constraints on ε_{d_γ}.","source":"verdict.strongest_claim","status":"machine_extracted","claim_id":"C1","attestation":"unclaimed"},{"kind":"weakest_assumption","text":"The LSS bootstrap parametrization, based on symmetry arguments alone, correctly captures all relevant deviations from ΛCDM in the linear growth rate and quadratic perturbation-theory kernel for the scales probed by BOSS and PT Challenge data.","source":"verdict.weakest_assumption","status":"machine_extracted","claim_id":"C2","attestation":"unclaimed"},{"kind":"one_line_summary","text":"First MCMC constraints on LSS bootstrap parameters yield ~7% precision on linear growth modifications and ~57% on quadratic kernel modifications from BOSS data, improving to 1% and 25% with larger simulations.","source":"verdict.one_line_summary","status":"machine_extracted","claim_id":"C3","attestation":"unclaimed"},{"kind":"headline","text":"The LSS bootstrap yields first MCMC constraints on deviations from ΛCDM using power spectrum and bispectrum.","source":"verdict.pith_extraction.headline","status":"machine_extracted","claim_id":"C4","attestation":"unclaimed"}],"snapshot_sha256":"1f00f1b131e31d8408ef4a58fc2d8075dc351f16c30bf280fa7888306d5bccb5"},"source":{"id":"2605.13298","kind":"arxiv","version":1},"verdict":{"id":"0ed59910-a490-4b1c-888e-d8775288dad2","model_set":{"reader":"grok-4.3"},"created_at":"2026-05-14T17:33:25.853949Z","strongest_claim":"We present the first MCMC-derived constraints on the parameters of the Large Scale Structure (LSS) bootstrap... For BOSS, combining the power spectrum with the bispectrum monopole yields ∼7% constraints on ε_f and ∼57% constraints on ε_{d_γ}.","one_line_summary":"First MCMC constraints on LSS bootstrap parameters yield ~7% precision on linear growth modifications and ~57% on quadratic kernel modifications from BOSS data, improving to 1% and 25% with larger simulations.","pipeline_version":"pith-pipeline@v0.9.0","weakest_assumption":"The LSS bootstrap parametrization, based on symmetry arguments alone, correctly captures all relevant deviations from ΛCDM in the linear growth rate and quadratic perturbation-theory kernel for the scales probed by BOSS and PT Challenge data.","pith_extraction_headline":"The LSS bootstrap yields first MCMC constraints on deviations from ΛCDM using power spectrum and bispectrum."},"references":{"count":72,"sample":[{"doi":"","year":2048,"title":"(see also [13]), which provided the initial Fisher-matrix forecasts for these parameters for a Euclid-like survey. Here, we perform a state-of-the-art combined analysis of the one-loop galaxy power sp","work_id":"f3159602-e0f9-481a-a887-b4f2655fc8a9","ref_index":1,"cited_arxiv_id":"","is_internal_anchor":false},{"doi":"","year":null,"title":"we leave it free (only for the BOSS analysis)","work_id":"e2d6b48b-2966-4e1f-a0de-b4b354ec347b","ref_index":2,"cited_arxiv_id":"","is_internal_anchor":false},{"doi":"","year":null,"title":"we fixln (1010As) = 3.0448, thePlanckbest-fit value [39], for the BOSS analysis, and to the true value used in the simulations for the PT Challenge","work_id":"34e70151-9fe2-4d26-bf53-5bf8d1f0fa71","ref_index":3,"cited_arxiv_id":"","is_internal_anchor":false},{"doi":"","year":2048,"title":"we instead adopt a Gaussian prior onAs with a width equal to3σof thePlanckuncertainty [ 39], following refs. [40, 41]. Given thatPlanck’s uncertainty onAs is extremely small, fixingAs or applying a3σG","work_id":"99b7eb15-1e65-4a53-84be-4d0be65f4296","ref_index":4,"cited_arxiv_id":"","is_internal_anchor":false},{"doi":"","year":2025,"title":"Y. Mellieret al.(Euclid), Euclid. I. Overview of the Euclid mission, Astron. Astrophys.697, A1 (2025), arXiv:2405.13491 [astro-ph.CO]","work_id":"15ed38b8-e601-4fbb-b3c5-a0d8b595c401","ref_index":5,"cited_arxiv_id":"","is_internal_anchor":false}],"resolved_work":72,"snapshot_sha256":"13f8acc33674def4370f52b7f0ed5acb7928f2a8f5e16e71228b4ef7091654e0","internal_anchors":22},"formal_canon":{"evidence_count":2,"snapshot_sha256":"8aefcfd0463bfcb4dbfe4ef987e281b3b9b4298e1166d8fa59d052e86b9f62e1"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"}