相关论文: DOME: Discrete oriented muon emission in GEANT4 si…
Cosmic muon imaging technology is increasingly being applied in various fields. However, simulating cosmic muons typically requires the rapid generation of a large number of muons and tracking their complex trajectories through intricate…
Traditional cosmological hydrodynamical simulations usually assume equal-numbered but unequal-mass dark matter and baryonic particles, which can lead to spurious collisional heating due to energy equipartition. To avoid such a numerical…
A test of Geant4 simulation of electron backscattering recently published in this journal prompted further investigation into the causes of the observed behaviour. An interplay between features of geometry and physics algorithms implemented…
We present a framework for generating lightcone simulations tailored to the analysis of Stage-IV cosmic shear data using Higher-Order Statistics (HOS). We revisit key design choices from previous simulation campaigns and re-optimize several…
Computing atomic-scale properties of chemically disordered materials requires an efficient exploration of their vast configuration space. Traditional approaches such as Monte Carlo or Special Quasirandom Structures either entail sampling an…
Production of a neutrino source through proton induced reaction is studied by using the particle transport code, GEANT4. Unstable isotope such as $^{27}$Si can be produced when $^{27}$Al target is bombarded by 15 MeV energetic proton beams.…
Quantum mechanics offers a fundamentally unpredictable entropy source due to the intrinsic probabilistic nature of quantum measurements, making it attractive for secure random number generation. This paper explores the practicality of…
Partially spatially coherent qubits are more immune to turbulent atmospheric conditions than coherent qubits, which makes them excellent candidates for free-space quantum communication. In this article, we report the generation of partially…
We introduce a diffusion-based generative model to describe the distribution of galaxies in our Universe directly as a collection of points in 3-D space (coordinates) optionally with associated attributes (e.g., velocities and masses),…
We report an experimental realisation of a quantum random number generator using a plasmonic beamsplitter. Free-space single photons are converted into propagating single surface plasmon polaritons on a gold stripe waveguide via a grating.…
A Gaussian Process GP based ground segmentation method is proposed in this paper which is fully developed in a probabilistic framework. The proposed method tends to obtain a continuous realistic model of the ground. The LiDAR…
Deep learning has proven to yield fast and accurate predictions of quantum-chemical properties to accelerate the discovery of novel molecules and materials. As an exhaustive exploration of the vast chemical space is still infeasible, we…
When measuring diameters of partially resolved sources often a technique called gaussian deconvolution is used. This technique yields a gaussian diameter which subsequently has to be multiplied with a conversion factor to obtain the true…
We present a quantum algorithm for efficiently sampling transformed Gaussian random fields on $d$-dimensional domains, based on an enhanced version of the classical moving average method. Pointwise transformations enforcing boundedness are…
Geant4 is an object-oriented toolkit for the simulation of the passage of particles through matter. Its development was initially motivated by the requirements of physics experiments at high energy hadron colliders under construction in the…
Achieving chemical accuracy in quantum simulations is often constrained by the measurement bottleneck: estimating operators requires a large number of shots, which remains costly even on fault-tolerant devices and is further exacerbated on…
Text-to-3D, known for its efficient generation methods and expansive creative potential, has garnered significant attention in the AIGC domain. However, the pixel-wise rendering of NeRF and its ray marching light sampling constrain the…
Diffusion models generate data by learning to reverse a forward process, where samples are progressively perturbed with Gaussian noise according to a predefined noise schedule. From a geometric perspective, each noise schedule corresponds…
We report on a comparison study of the Monte Carlo packages GEANT4 and FLUKA for simulating neutron production by muons penetrating deep underground. GEANT4 is found to generate fewer neutrons at muon energies above ~100 GeV, by at most a…
Diffuse emission in gamma-rays and neutrinos are produced by the interaction of cosmic rays with the interstellar medium. Below some hundreds of TeV, the sources of these cosmic rays are most likely Galactic. Hence, observations of…