PITA, a new semi-supervised deep learning algorithm, outperforms prior photo-z methods by using a triple-task loss on images, colors, and available redshifts to produce a smooth latent space.
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BAGPIPES fitting of 9289 massive quiescent galaxies shows most SFHs rise gradually then quench in 1-2 Gyr, with faster quenching at z>1 and slower at z<1, interpreted as multiple AGN feedback and gas-supply mechanisms.
Improved pPXF uses analytic Fourier transforms of Gauss-Hermite functions for accurate convolution, providing reliable velocities even when σ is much less than the sampling ΔV.
New measurement of the Hubble parameter H(z=0.12) = 71.33 ± 4.20 km s^{-1} Mpc^{-1} obtained from cosmology-independent stellar ages of passive galaxies in DESI Data Release 1.
citing papers explorer
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Optimizing Deep Learning Photometric Redshifts for the Roman Space Telescope with HST/CANDELS
PITA, a new semi-supervised deep learning algorithm, outperforms prior photo-z methods by using a triple-task loss on images, colors, and available redshifts to produce a smooth latent space.
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Inferring the star-formation histories of massive quiescent galaxies with BAGPIPES: Evidence for multiple quenching mechanisms
BAGPIPES fitting of 9289 massive quiescent galaxies shows most SFHs rise gradually then quench in 1-2 Gyr, with faster quenching at z>1 and slower at z<1, interpreted as multiple AGN feedback and gas-supply mechanisms.
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Improving the full spectrum fitting method: accurate convolution with Gauss-Hermite functions
Improved pPXF uses analytic Fourier transforms of Gauss-Hermite functions for accurate convolution, providing reliable velocities even when σ is much less than the sampling ΔV.
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New $H(z)$ measurement at Redshift = 0.12 with DESI Data Release 1
New measurement of the Hubble parameter H(z=0.12) = 71.33 ± 4.20 km s^{-1} Mpc^{-1} obtained from cosmology-independent stellar ages of passive galaxies in DESI Data Release 1.