Dark Energy Survey Year 6 Results: fast and interpretable posterior predictive checks for correlated cosmic probes
Year: 2026
Type: preprint
Abstract: We present a fast and numerically stable framework for conducting posterior predictive distribution (PPD) tests of internal consistency in correlated cosmological probes. Our method, developed as a validation check for the Dark Energy Survey (DES) Year 6 combined analysis of weak lensing and galaxy clustering, employs a Gaussian-mixture model to efficiently approximate the high-dimensional PPD and introduces a scalar consistency metric, $Δ_{\rm PPD}$, defined as the fraction of the PPD at lower probability density than the observed data. This method avoids challenges related to calibration and numerical stability that impacted PPD methods previously used in DES Year 3. After demonstrating performance with a toy model, we confirm that when applied to DES Year 3 measurements, $Δ_{\rm PPD}$ identifies the same inter-probe tensions as published, calibrated PPD results while requiring only minutes per test. We further validate the method on several noise realizations of simulated DES Y6 analyses, demonstrating that $Δ_{\rm PPD}$ responds coherently to injected inconsistency, while highlighting two effects which can complicate the interpretation of PPD tests for increasingly complex models. First, internal tensions that can be absorbed as shifts in nuisance parameters become more difficult to detect. Second, poorly constrained directions in parameter space can induce projection effects in PPDs for disjoint sets of observables, producing reports of tension even for consistent data. We conclude that $Δ_{\rm PPD}$ provides a practical PPD-based diagnostic for multiprobe unblinding, to be interpreted with care alongside other validation checks. This framework has already played an important role in DES analyses and is well suited for application to forthcoming Stage-IV surveys such as LSST, Euclid, and Roman, where fast, robust internal consistency tests will be essential.
Source: arXiv (Cornell University)
Authors: Doux, C., Muir, J., Ferté, A., Raveri, M., Cid, D. Sanchez, Weaverdyck, N., Baxter, E. J., d'Assignies, W., Karwal, T., Amon, A., Anbajagane, D., Andrade-Oliveira, F., Becker, M. R., Blazek, J., Rosell, A. Carnero, Chang, C., Coloma-Nadal, J. M., Crocce, M., DeRose, J., Dodelson, S., Giannini, G., Krause, E., Legnani, E., MacCrann, N., Mena-Fernández, J., Porredon, A., Prat, J., Preston, C., Rodriguez-Monroy, M., Rogozenski, P., Rosenfeld, R., Samuroff, S., Sanchez, E., Sevilla-Noarbe, I., Soares-Santos, M., To, C., Troxel, M. A., Yamamoto, M., Yin, B., Zuntz, J., Allam, S., Aguena, M., Bacon, D., Brooks, D., Camilleri, R., Cawthon, R., da Costa, L. N., Desai, S., Doel, P., Glazebrook, K., Honscheid, K., Huterer, D., Kuehn, K., Marshall, J. L., Miquel, R., Paterno, M., Malagón, A. A. Plazas, Smith, M., Suchyta, E., Tucker, D. L., Vikram, V., Weller, J.
Language: English
Subfield: Astronomy and Astrophysics
Field: Physics and Astronomy
Domain: Physical Sciences
Open Access status: green
Funders: National Science Foundation, U.S. Department of Energy, University of Pennsylvania, Ohio State University, University of Chicago, University of Portsmouth, Centres de Recerca de Catalunya, University College London, European Commission, University of Sussex, Deutsche Forschungsgemeinschaft, Generalitat de Catalunya, Conselho Nacional de Desenvolvimento Científico e Tecnológico, Financiadora de Estudos e Projetos, Ministerio de Ciencia e Innovación, Institut de Física d'Altes Energies, University of Illinois at Urbana-Champaign, Science and Technology Facilities Council, European Regional Development Fund, Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas, Office of Advanced Cyberinfrastructure, Integrated Electronics Engineering Center, Binghamton University, Argonne National Laboratory, Fermilab, Lawrence Berkeley National Laboratory, SLAC National Accelerator Laboratory
Awards: G1054097061, G1336129044, G1453181110, G1746333638, G179674260, Track 4: Advanced CI Coordination Ecosystem: Monitoring and Measurement Services, G2233160401, G2554159582, G2817899265, G2848635288, G2885514473, G302750986, G3439265645, G3562386289, The Dark Energy Survey Data Management Operations, Track 1: ACCESS Resource Allocations Marketplace and Platform Services (RAMPS), G4010157413, G4471177777, G454676879, G4655338613, ACO: An Open CI Ecosystem to Advance Scientific Discovery (OpenCI), Track 3: COre National Ecosystem for CyberinfrasTructure (CONECT), G5367127336, G5464919783, G5602398950, G5704573845, G6513613686, G656518222, G6709186444, G6754955425, G6941735741, G7788408655, G7835623888, G8284171658, Track 2: Customized Multi-tier Assistance, Training, and Computational Help (MATCH) for End User ACCESS to CI, Collaborative Research: The Dark Energy Survey Data Management Operations, G8562358136, G8851268641, G8920660035, G946511789
OpenAlex ID: W7220451098