天体物理仪器与方法
Cryogenic sub-Hz cROss torsion-bar detector with quantum NOn-demolition Speed meter(CHRONOS) is a proposed next-generation ground-based gravitational-wave observatory designed to explore the sub-Hz frequency band with unprecedented…
Modern wide-field time-domain surveys facilitate the study of transient, variable and moving phenomena by conducting image differencing and relaying alerts to their communities. Machine learning tools have been used on data from these…
The family of multi-plane phase retrieval sensors, such as the curvature and nonlinear curvature wavefront sensors (WFS), contain tip/tilt information embedded in their signals. We have built a nonlinear curvature WFS to study different…
The tens of millions of spectra being captured by the Dark Energy Spectroscopic Instrument (DESI) provide tremendous discovery potential. In this work we show how Machine Learning, in particular Variational Autoencoders (VAE), can detect…
We present a methodology for acquiring and reducing transiting exoplanet light curves obtained with the OPTICAM instrument in the Observatorio Astron\'omico Nacional en la Sierra de San Pedro M\'artir (OAN-SPM). The OPTICAM sCMOS detectors…
Large time-domain sky surveys generate extensive multi-year catalogs of light curves in which scientifically valuable transients, such as supernovae (SNe), are vastly outnumbered by artifacts and routine star variability. While supervised…
The detection of life on rocky exoplanets in the habitable zones of nearby stars would be a paradigm-shifting advance, and it is one of the greatest scientific challenges of our time. There is no single spectral feature that is an…
The advancement in sensitivity and field of view of next-generation wide-field survey telescopes requires astrometric measurements with high precision, even in the presence of significant geometric distortions. To address this challenge, we…
Radio interferometry enables high-resolution imaging of astronomical radio sources by synthesizing a large effective aperture from an array of antennas and solving a deconvolution problem to reconstruct the image. Deep learning has emerged…
We use Lomonosov-2 supercomputing facility for the generation of extensive air shower events with Cherenkov light which is a rather time consuming procedure. At primary energies slightly below 100 PeV a substantial part of events are killed…
Optimization of the SPHERE-3 detector configuration, designed to study the mass composition of primary cosmic rays in the energy range 1--1000 PeV by registering Cherenkov light reflected from the snow surface, requires simulation of a…
We report here on studies to determine the accuracy of estimated corrections of Ionospheric Faraday Rotation Measure (IFRM) using observations of the Moon with the Very Large Array (VLA) and MeerKAT telescopes. To estimate the IFRM requires…
The STIS echelle gratings can be used with a variety of different central wavelength settings. "Secondary" wavelength settings, designed to cover select absorption or emission lines, have not been calibrated as precisely as their primary…
Recent improvements to stellar atmospheric models have merited updated flux calibration for high priority STIS observing modes. Specifically, in the FUV and NUV, continuum differences of 1-3% are present between the newest models…
unxt is a Python package for unit-aware computing with JAX. unxt is built on top of quax, which provides a framework for building array-like objects that can be used with JAX. unxt extends quax to provide support for unit-aware computing…
The Kolmogorov stochasticity parameter (KSP) as a sensitive descriptor of the degree of randomness of signals was used to analyze the properties of the NANOGrav pulsar timing data associated with a stochastic gravitational wave background.…
GRAVITY+ improves by orders of magnitude the sensitivity, sky-coverage and contrast of the Very Large Telescope Interferometer (VLTI). A central part of this project is the development of Gravity Plus Adaptive Optics (GPAO), a dedicated…
Foundational models have emerged as a powerful paradigm in deep learning field, leveraging their capacity to learn robust representations from large-scale datasets and effectively to diverse downstream applications such as classification.…
We present a GPU-accelerated transient detection pipeline developed for time-domain surveys with the Dark Energy Camera (DECam). It enables real-time-capable image processing, incorporating science-driven candidate filtering to support…
In ground-based high-contrast instruments, non-common path aberrations (NCPAs) limit detection performance, as they are unseen by the adaptive optics (AO) wavefront sensor but impact the astrophysical image, creating quasi-static speckles.…