相关论文: PyNMC: An Open-Source Framework for Neutron Multip…
Instrumentation for nuclear applications is developing very fast, due to fast changing of technology in electronics in connection to Moore's Prediction ("doubling of transistor density integration on an IC for every two years"). The…
An open source software package for performing dynamic RMS simulation of small to medium-sized power systems is presented, written entirely in the Python programming language. The main objective is to facilitate fast prototyping of new wide…
With the growing demands of consumer electronic products, the computational requirements are increasing exponentially. Due to the applications' computational needs, the computer architects are trying to pack as many cores as possible on a…
PiNNAcLe is an implementation of our adaptive learn-on-the-fly algorithm for running machine-learning potential (MLP)-based molecular dynamics (MD) simulations -- an emerging approach to simulate the large-scale and long-time dynamics of…
DNN+NeuroSim is an integrated framework to benchmark compute-in-memory (CIM) accelerators for deep neural networks, with hierarchical design options from device-level, to circuit-level and up to algorithm-level. A python wrapper is…
This paper presents a framework that enables a systematic and rational choice of NMPC design components such as control updating period, down-sampling period for prediction, control parameterization, prediction horizon's length, the maximum…
We present an open-source software for the simulation of observables in magnetic resonance experiments, including nuclear magnetic/quadrupole resonance NMR/NQR and electron spin resonance (ESR), developed to assist experimental research in…
We present the \texttt{NeuMC} software package, based on \pytorch, aimed at facilitating the research on neural samplers in lattice field theories. Neural samplers based on normalizing flows are becoming increasingly popular in the context…
Quantum simulation of chemistry and materials is predicted to be an important application for both near-term and fault-tolerant quantum devices. However, at present, developing and studying algorithms for these problems can be difficult due…
As hybrid quantum-classical models gain traction in machine learning, there is a growing need for tools that assess their effectiveness beyond raw accuracy. We present QMetric, a Python package offering a suite of interpretable metrics to…
Simulations of hadronic and nuclear interactions are essential in both collider and astroparticle physics. The Chromo package provides a unified Python interface to multiple widely used hadronic event generators, including EPOS, DPMJet,…
The Jiangmen Underground Neutrino Observatory (JUNO) is a neutrino experiment to determine neutrino mass hierarchy. It has a central detector used for neutrino detection, which consists of a spherical acrylic vessel containing 20 kt LS and…
OpenMC is an open source Monte Carlo neutral particle transport application that has recently been ported to GPU using the OpenMP target offloading model. We examine the performance of OpenMC at scale on the Frontier, Polaris, and Aurora…
Given two algorithms for the same problem, can we determine whether they are meaningfully different? In full generality, the question is uncomputable, and empirically it is muddied by competing notions of similarity. Yet, in many…
A paper study is conducted on the detection of fissile material using neutron coincidence counters. Three unknown independent properties of assays of fissile material assays are identified to be the effective mass, the (alpha,n) production…
Numerical simulations are a powerful tool to study quantum systems beyond exactly solvable systems lacking an analytic expression. For one-dimensional entangled quantum systems, tensor network methods, amongst them Matrix Product States…
Scalable and efficient numerical simulations continue to gain importance, as computation is firmly established as the third pillar of discovery, alongside theory and experiment. Meanwhile, the performance of computing hardware grows through…
We present PrismSSL, a Python library that unifies state-of-the-art self-supervised learning (SSL) methods across audio, vision, graphs, and cross-modal settings in a single, modular codebase. The goal of the demo is to show how researchers…
Formal verification of masking in post-quantum cryptographic (PQC) hardware relies on SMT solvers over finite domains. Our prior work established structural dependency analysis at scale [1] and quantified the security margin of partial NTT…
In the field of nuclear reactor physics, transient phenomena are usually studied using deterministic or hybrids methods. These methods require many approximations, such as: geometry, time and energy discretizations, material homogenization…