中文
相关论文

相关论文: Comparison of Strong Gravitational Lens Model Soft…

200 篇论文

The precision reached by current and forthcoming strong-lensing observations requires to accurately model various perturbations to the main deflector. Hitherto, theoretical models have been developed to account for either cosmological…

广义相对论与量子宇宙学 · 物理学 2022-05-10 Pierre Fleury , Julien Larena , Jean-Philippe Uzan

We present Lenstronomy, a multi-purpose open-source gravitational lens modeling python package. Lenstronomy is able to reconstruct the lens mass and surface brightness distributions of strong lensing systems using forward modelling.…

宇宙学与河外天体物理 · 物理学 2018-11-14 Simon Birrer , Adam Amara

As one of the probes of universe, strong gravitational lensing systems allow us to compare different cosmological models and constrain vital cosmological parameters. This purpose can be reached from the dynamic and geometry properties of…

宇宙学与河外天体物理 · 物理学 2015-08-06 C. C. Yuan , F. Y. Wang

Quantifying image distortions caused by strong gravitational lensing and estimating the corresponding matter distribution in lensing galaxies has been primarily performed by maximum likelihood modeling of observations. This is typically a…

天体物理仪器与方法 · 物理学 2017-09-20 Yashar D. Hezaveh , Laurence Perreault Levasseur , Philip J. Marshall

In this work, we present our classification algorithm to identify strong gravitational lenses from wide-area surveys using machine learning convolutional neural network; LensExtractor. We train and test the algorithm using a wide variety of…

天体物理仪器与方法 · 物理学 2018-04-11 Milad Pourrahmani , Hooshang Nayyeri , Asantha Cooray

Upcoming large astronomical surveys are expected to capture an unprecedented number of strong gravitational lensing systems. Deep learning is emerging as a promising practical tool for the detection and quantification of these galaxy-scale…

Forthcoming large imaging surveys such as Euclid and the Vera Rubin Observatory Legacy Survey of Space and Time are expected to find more than $10^5$ strong gravitational lens systems, including many rare and exotic populations such as…

Strong lensing has developed into an important astrophysical tool for probing both cosmology and galaxies (their structure, formation, and evolution). Using the gravitational lensing theory and cluster mass distribution model, we try to…

宇宙学与河外天体物理 · 物理学 2015-05-28 Shuo Cao , Yu Pan , Marek Biesiada , Wlodzimierz Godlowski , Zong-Hong Zhu

The difficult task of observing Dark Matter subhaloes is of paramount importance since it would constrain Dark Matter particle properties (cold or warm relic) and confirm once again the longstanding $\Lambda$CDM model. In the near future…

宇宙学与河外天体物理 · 物理学 2019-10-16 Marco Chianese

Recent advances in code generation have illuminated the potential of employing large language models (LLMs) for general-purpose programming languages such as Python and C++, opening new opportunities for automating software development and…

机器学习 · 计算机科学 2025-03-06 Jiahao Gai , Hao Mark Chen , Zhican Wang , Hongyu Zhou , Wanru Zhao , Nicholas Lane , Hongxiang Fan

Comprehending long visual documents, where information is distributed across extensive pages of text and visual elements, is a critical but challenging task for modern Vision-Language Models (VLMs). Existing approaches falter on a…

计算机视觉与模式识别 · 计算机科学 2025-11-17 Dawei Zhu , Rui Meng , Jiefeng Chen , Sujian Li , Tomas Pfister , Jinsung Yoon

Strong gravitational lenses are unique cosmological probes. These produce multiple images of a single source. Whether a single galaxy, a group or a cluster, extracting cosmologically relevant information requires an accurate modeling of the…

宇宙学与河外天体物理 · 物理学 2011-12-13 Irène Balmès

We analyze cosmography as a tool to constrain modified gravity theories. We take four distinct models and obtain their parameters in terms of the cosmographic parameters favored by observational data of strong gravitational lensing. We…

广义相对论与量子宇宙学 · 物理学 2025-02-06 Mario H. Amante , Andrés Lizardo , Javier Chagoya , C. Ortiz

Parallel programs in high performance computing (HPC) continue to grow in complexity and scale in the exascale era. The diversity in hardware and parallel programming models make developing, optimizing, and maintaining parallel software…

分布式、并行与集群计算 · 计算机科学 2024-05-15 Daniel Nichols , Aniruddha Marathe , Harshitha Menon , Todd Gamblin , Abhinav Bhatele

Software development support tools have been studied for a long time, with recent approaches using Large Language Models (LLMs) for code generation. These models can generate Python code for data science and machine learning applications.…

计算与语言 · 计算机科学 2024-12-16 Piotr Gramacki , Bruno Martins , Piotr Szymański

While Large Language Models (LLMs) achieve strong performance across diverse tasks, their inference dynamics remain poorly understood because of the limited resolution of existing analysis tools. In this work, we identify an intrinsic…

人工智能 · 计算机科学 2026-05-08 Chengda Lu , Xiaoyu Fan , Wei Xu

Recently, there have been two landmark discoveries of gravitationally lensed supernovae: the first multiply-imaged SN, "Refsdal", and the first Type Ia SN resolved into multiple images, SN iPTF16geu. Fitting the multiple light curves of…

宇宙学与河外天体物理 · 物理学 2019-05-27 Justin R. Pierel , Steven A. Rodney

We present a self-consistent and versatile forward modelling software package that can produce time series and pixel-level simulations of time-varying strongly lensed systems. The time dimension, which needs to take into account different…

天体物理仪器与方法 · 物理学 2022-02-16 Georgios Vernardos

Gravitational lensing is the deflection of light rays due to the gravity of intervening masses. This phenomenon is observed in a variety of scales and configurations, involving any non-uniform mass such as planets, stars, galaxies, clusters…

Strong gravitational lensing is a powerful tool for probing the internal structure and evolution of galaxies, the nature of dark matter, and the expansion history of the Universe, among many other scientific applications. For almost all of…

天体物理仪器与方法 · 物理学 2025-03-31 Anowar J. Shajib , Nafis Sadik Nihal , Chin Yi Tan , Vedant Sahu , Simon Birrer , Tommaso Treu , Joshua Frieman