相关论文: EMUSE: Evolutionary Map of the Universe Search Eng…

We present an algorithm capable of detecting diffuse, dim sources of any size in an astronomical image. These sources often defeat traditional methods for source finding, which expand regions around points of high intensity. Extended…

(Abridged) We discuss the design considerations of the EXPLORE (EXtra-solar PLanet Occultation REsearch) project, a series of transiting planet searches using 4-m-class telescopes to continuously monitor a single field of stars in the…

We present radio observations of the galaxy cluster Abell S1136 at 888 MHz, using the Australian Square Kilometre Array Pathfinder radio telescope, as part of the Evolutionary Map of the Universe Early Science program. We compare these…

We introduce Deep-CEE (Deep Learning for Galaxy Cluster Extraction and Evaluation), a proof of concept for a novel deep learning technique, applied directly to wide-field colour imaging to search for galaxy clusters, without the need for…

To understand the feedback of black holes on their environment or the acceleration of ultra-high energy cosmic rays in the present cosmic epoch, a systematic, all-sky inventory of radio galaxies in the local universe is needed. Here we…

MUSE, the Multi Unit Spectroscopic Explorer, is a 2nd generation integral-field spectrograph under final assembly to see first light at the Very Large Telescope in 2013. By capturing ~ 90000 optical spectra in a single exposure, MUSE…

We present MUSE, a software framework for combining existing computational tools for different astrophysical domains into a single multiphysics, multiscale application. MUSE facilitates the coupling of existing codes written in different…

The rapidly growing ecosystem of Large Language Models (LLMs) makes it increasingly challenging to manage and utilize the vast and dynamic pool of models effectively. We propose LOCUS, a method that produces low-dimensional vector…

In this paper we present three different applications, based on deep learning methodologies, that we are developing to support the scientific analysis conducted within the ASKAP-EMU and MeerKAT radio surveys. One employs instance…

Stellar physics and evolution calculations enable a broad range of research in astrophysics. Modules for Experiments in Stellar Astrophysics (MESA) is a suite of open source libraries for a wide range of applications in computational…

Large language models (LLMs), have shown strong potential in scientific discovery, yet existing methods still face substantial challenges in the design of research workflows and multi-role collaboration mechanisms. To mitigate these issues,…

The exploration and study of exoplanets remain at the frontier of astronomical research, challenging scientists to continuously innovate and refine methodologies to navigate the vast, complex data these celestial bodies produce. This…

The Observations of Redshift Evolution in Large Scale Environments (ORELSE) survey is an ongoing imaging and spectroscopic campaign initially designed to study the effects of environment on galaxy evolution in high-redshift ($z\sim1$)…

Valuable insights into galaxy evolution can be gleaned from studies of resolved stellar populations in the local Universe. Deep photometric surveys have provided tracers of the star-formation histories in galaxies from 0.8-16 Mpc, but…

Advancements in cloud computing and distributed computing have fostered research activities in Computer science. As a result, researchers have made significant progress in Neural Networks, Evolutionary Computing Algorithms like Genetic, and…

Multi-messenger astrophysics is a fast-growing, interdisciplinary field that combines data, which vary in volume and speed of data processing, from many different instruments that probe the Universe using different cosmic messengers:…

The 2 Micron All-Sky Survey (2MASS) will observe over one-million galaxies and extended Galactic sources covering the entire sky at wavelengths between 1 and 2 microns. The survey catalog will have both high completeness and reliability…

The increasing number and complexity of planetary exploration space missions require new tools to access, visualize and analyse data to improve their scientific return. ASI Science Data Center (ASDC) addresses this request with the web-tool…

Searching for transits provides a very promising technique for finding close-in extra-solar planets. Transiting planets present the advantage of allowing one to determine physical properties such as mass and radius unambiguously. The…

Deep reinforcement learning has achieved impressive success in control tasks. However, its policies, represented as opaque neural networks, are often difficult for humans to understand, verify, and debug, which undermines trust and hinders…