Related papers: AbacusHOD: A highly efficient extended multi-trace…
The Earth observation satellites (EOSs) scheduling is of great importance to achieve efficient observation missions. The agile EOSs (AEOS) with stronger attitude maneuvering capacity can greatly improve observation efficiency while…
Precise and accurate predictions of the halo mass function for cluster mass scales in $w\nu{\rm CDM}$ cosmologies are crucial for extracting robust and unbiased cosmological information from upcoming galaxy cluster surveys. Here, we present…
The past several decades have seen significant advancement in applications using cosmic-ray muons for tomography scanning of unknown objects. One of the most promising developments is the application of this technique in border security for…
We present Kosmulator, a modular and vectorised Python framework designed to accelerate the statistical testing of cosmological models. As the theoretical landscape expands beyond standard $\Lambda$CDM, implementing new expansion histories…
We present a new galaxy cluster lens modeling approach, hybrid-Lenstool, that is implemented in the publicly available modeling software Lenstool. hybrid-Lenstool combines a parametric approach to model the core of the cluster, and a…
ixpeobssim is a simulation and analysis framework, based on the Python programming language and the associated scientific ecosystem, specifically developed for the Imaging X-ray Polarimetry Explorer (IXPE). Given a source model and the…
The galaxy bias parameters are crucial for modeling the large-scale structure in cosmology, yet uncertainties in these parameters often degrade the precision of cosmological constraints. In this work, we investigate how different Halo…
Precise and flexible control of structured light fields is essential for applications ranging from optical trapping and quantum simulation to microscopy and materials processing. Acousto-optical deflectors (AODs) are widely used in these…
Homomorphic Encryption (HE) provides strong data privacy for cloud services but at the cost of prohibitive computational overhead. While GPUs have emerged as a practical platform for accelerating HE, there remains an order-of-magnitude…
Deep learning approaches for marine fog detection and forecasting have outperformed traditional methods, demonstrating significant scientific and practical importance. However, the limited availability of open-source datasets remains a…
The joint analysis of different cosmological probes, such as galaxy clustering and weak lensing, can potentially yield invaluable insights into the nature of the primordial Universe, dark energy and dark matter. However, the development of…
This paper presents OCTOPUS, a relativistic ray-tracing algorithm developed within a Fortran-based, OpenMP-accelerated framework, designed for asymptotically flat, spherically symmetric curved spacetimes. The code efficiently and accurately…
Robust measurements of cosmological parameters from galaxy surveys rely on our understanding of systematic effects that impact the observed galaxy density field. In this paper we present, validate, and implement the idea of adopting the…
We apply two compression methods to the galaxy power spectrum monopole/quadrupole and bispectrum monopole measurements from the BOSS DR12 CMASS sample. Both methods reduce the dimension of the original data-vector to the number of…
Despite their theoretical advantages, track-before-detect (TBD) methods remain largely absent from real-world multi-target tracking applications due to their computational complexity and limited scalability. This paper presents a scalable…
Urban water-surface robust perception serves as the foundation for intelligent monitoring of aquatic environments and the autonomous navigation and operation of unmanned vessels, especially in the context of waterway safety. It is worth…
An accurate theoretical template for the galaxy power spectrum is a key for the success of ongoing and future spectroscopic surveys. We examine to what extent the Effective Field Theory of Large Scale Structure is able to provide such a…
The wide deployment of IoT sensors has enabled the collection of very big time series across different domains, from which advanced analytics can be performed to find unknown relationships, most importantly the correlations between them.…
Shot noise is an important ingredient to any measurement or theoretical modeling of discrete tracers of the large scale structure. Recent work has shown that the shot noise in the halo power spectrum becomes increasingly sub-Poissonian at…
We present an algorithm to extend subhalo merger trees in a low-resolution dark-matter-only simulation by conditionally matching them to those in a high-resolution simulation. The algorithm is general and can be applied to simulation data…