Conditioning CAMELS-SAM simulations on the stellar mass function or stellar-to-halo mass relation reduces uncertainty in b_phi by 88-97% for DESI emission line galaxy samples while remaining consistent across galaxy formation variations.
and Genel, Shy and Krause, Elisabeth and Somerville, Rachel S
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DESI DR2 and ACT DR6 data yield 17σ LRG-velocity, 8.3σ ELG-velocity, and 6.8σ QSO-velocity detections plus a 3.1σ velocity-velocity signal, producing f_NL^loc = 15.9_{-34.4}^{+34.6} from the velocity field.
New simulations show that cross-correlating gravitational wave background anisotropies with galaxy distributions can enable discovery at angular scales of 4-6 degrees with next-generation observatories.
Cross-correlating LRG and QSO samples in DESI DR1 yields f_NL^loc = 2.1 with 68% uncertainties of +8.8 and -8.3, an incremental improvement over auto-correlations alone.
citing papers explorer
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Informative Priors on Primordial Non-Gaussianity Bias $b_{\phi}$ From Galaxy Formation
Conditioning CAMELS-SAM simulations on the stellar mass function or stellar-to-halo mass relation reduces uncertainty in b_phi by 88-97% for DESI emission line galaxy samples while remaining consistent across galaxy formation variations.
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Measurement of the galaxy-velocity power spectrum of DESI tracers with the kinematic Sunyaev-Zeldovich effect using DESI DR2 and ACT DR6
DESI DR2 and ACT DR6 data yield 17σ LRG-velocity, 8.3σ ELG-velocity, and 6.8σ QSO-velocity detections plus a 3.1σ velocity-velocity signal, producing f_NL^loc = 15.9_{-34.4}^{+34.6} from the velocity field.
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Prospects for multi-messenger discovery of the gravitational-wave background anisotropies via cross-correlation with galaxies
New simulations show that cross-correlating gravitational wave background anisotropies with galaxy distributions can enable discovery at angular scales of 4-6 degrees with next-generation observatories.
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Local primordial non-Gaussianity using cross-correlations of DESI tracers
Cross-correlating LRG and QSO samples in DESI DR1 yields f_NL^loc = 2.1 with 68% uncertainties of +8.8 and -8.3, an incremental improvement over auto-correlations alone.