output
20182026
most citedDark Energy Survey Year 3 Results: Cosmological Constraints from Galaxy Clustering and Weak Lensing

1.2k citations

Showing 2020 · astro-ph.IMShow all

8 papers · 2 filters

astro-ph.IM2020★ 46 cited

Fundamental physics with Espresso: Towards an accurate wavelength calibration for a precision test of the fine-structure constant

Tobias M. Schmidt, Paolo Molaro, Michael T. Murphy +56

Observations of metal absorption systems in the spectra of distant quasars allow to constrain a possible variation of the fine-structure constant throughout the history of the Univ…

astro-ph.IM2020★ 27 cited

Spectral index of the Galactic foreground emission in the 50-87 MHz range

Marta Spinelli, Gianni Bernardi, Hugh Garsden +4

Total-power radiometry with individual meter-wave antennas is a potentially effective way to study the Cosmic Dawn () through measurement of sky brightness arising from th…

astro-ph.IM2020★ 82 cited

Dark Energy Survey Year 3 Results: Point-Spread Function Modeling

M. Jarvis, G. M. Bernstein, A. Amon +79

We introduce a new software package for modeling the point-spread function (PSF) of astronomical images, called Piff (PSFs In the Full FOV), which we apply to the first three years…

astro-ph.IM2020★ 16 cited

Reducing ground-based astrometric errors with Gaia and Gaussian processes

W. F. Fortino, G. M. Bernstein, P. H. Bernardinelli +64

Stochastic field distortions caused by atmospheric turbulence are a fundamental limitation to the astrometric accuracy of ground-based imaging. This distortion field is measurable…

astro-ph.IM2020★ 537 cited

ESPRESSO@VLT -- On-sky performance and first results

F. Pepe, S. Cristiani, R. Rebolo +97

ESPRESSO is the new high-resolution spectrograph of ESO's Very-Large Telescope (VLT). It was designed for ultra-high radial-velocity precision and extreme spectral fidelity with th…

astro-ph.IM2020★ 55 cited

The miniJPAS survey: star-galaxy classification using machine learning

P. O. Baqui, V. Marra, L. Casarini +31

Future astrophysical surveys such as J-PAS will produce very large datasets, which will require the deployment of accurate and efficient Machine Learning (ML) methods. In this work…

astro-ph.IM2020★ 12 cited

Noise from Undetected Sources in Dark Energy Survey Images

K. Eckert, G. M. Bernstein, A. Amara +66

For ground-based optical imaging with current CCD technology, the Poisson fluctuations in source and sky background photon arrivals dominate the noise budget and are readily estima…

astro-ph.IM2020★ 78 cited

Updated design of the CMB polarization experiment satellite LiteBIRD

H. Sugai, P. A. R. Ade, Y. Akiba +216

Recent developments of transition-edge sensors (TESs), based on extensive experience in ground-based experiments, have been making the sensor techniques mature enough for their app…