119 citations · 675 across the 30 of their papers we have counts for
7 papers · 1 filter
Fisher Forecasting for the DESC with
Paul Rogozenski, Sankarshana Srinivasan, Javier Sánchez +15
The Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) has begun its ten-year survey of the entire visible southern hemisphere. To ensure robust cosmological measurem…
KiDS-Legacy: The consistency test of the large-scale structure with Bernardeau-Nishimichi-Taruya transform
Shiming Gu, Ziang Yan, Ludovic van Waerbeke +10
We perform the first -cut cosmic shear analysis of the KiDS-Legacy survey. This method uses the Bernardeau-Nishimichi-Taruya (BNT) transform to construct weak-lensing kernels th…
Balancing bias, baryons, and scale cuts in LSST 3x2pt analysis
Ottavia Truttero, Maria Tsedrik, Joe Zuntz +4
Stage IV surveys such as LSST will probe deeply into the nonlinear regime, where systematic effects from galaxy bias and baryonic feedback become dominant and poorly constrained nu…
Probing Physics Beyond the Standard Model through Combined Analyses of Next-Generation Type Ia Supernova, CMB, and BAO Surveys
Srinivasan Raghunathan, Ayan Mitra, Nikolina Šarčević +11
Observations of Type Ia supernovae (\sne), which probe the late Universe, together with baryon acoustic oscillations (BAO) and the cosmic microwave background (CMB), which probe th…
Smokescreen: A Python package for data vector blinding and encryption in cosmological analyses
Arthur Loureiro, Jessica Muir, Jonathan Blazek +10
Smokescreen is an open-source Python library for data-vector concealment (blinding) in cosmological analyses. Data-vector blinding works by applying cosmology-dependent shifts to t…
Inverting Fisher biases for fast systematics exploration
Biancamaria Sersante, Christos Georgiou, Nora Elisa Chisari
Upcoming cosmological surveys will achieve increasingly precise constraints in cosmological parameter estimation. To guarantee the robustness of cosmological analyses, it is essent…
Opportunities in AI/ML for the Rubin LSST Dark Energy Science Collaboration
LSST Dark Energy Science Collaboration, Eric Aubourg, Camille Avestruz +63
The Vera C. Rubin Observatory's Legacy Survey of Space and Time (LSST) will produce unprecedented volumes of heterogeneous astronomical data (images, catalogs, and alerts) that cha…