Trending Research
A Universal Graph Deep Learning Interatomic Potential for the Periodic Table
materialsvirtuallab/m3gnet
•
•
Interatomic potentials (IAPs), which describe the potential energy surface of atoms, are a fundamental input for atomistic simulations.
Materials Science Chemical Physics
Machine learning potentials for complex aqueous systems made simple
Finally, we demonstrate the capabilities of our approach for the description of water on the rutile titanium dioxide (110) surface to analyze the structure and mobility of water on this surface.
Chemical Physics
QuanEstimation: An open-source toolkit for quantum parameter estimation
Quantum parameter estimation promises a high-precision measurement in theory, however, how to design the optimal scheme in a specific scenario, especially under a practical condition, is still a serious problem that needs to be solved case by case due to the existence of multiple mathematical bounds and optimization methods.
Quantum Physics High Energy Physics - Theory Computational Physics
Simulating the Sycamore quantum supremacy circuits
jcmgray/cotengra
•
•
We propose a general tensor network method for simulating quantum circuits.
Quantum Physics Computational Physics
A comprehensive and fair comparison of two neural operators (with practical extensions) based on FAIR data
lululxvi/deepxde
•
•
Neural operators can learn nonlinear mappings between function spaces and offer a new simulation paradigm for real-time prediction of complex dynamics for realistic diverse applications as well as for system identification in science and engineering.
Computational Physics
Investigating Quantum Approximate Optimization Algorithms under Bang-bang Protocols
google-research/google-research
•
•
The quantum approximate optimization algorithm (QAOA) is widely seen as a possible usage of noisy intermediate-scale quantum (NISQ) devices.
Quantum Physics
Automated discovery of superconducting circuits and its application to 4-local coupler design
Superconducting circuits have emerged as a promising platform to build quantum processors.
Quantum Physics
High-dimensional Bayesian Optimization of Hyperparameters for an Attention-based Network to Predict Materials Property: a Case Study on CrabNet using Ax and SAASBO
We optimize 23 hyperparameters of a materials informatics model, Compositionally-Restricted Attention-Based Network (CrabNet), over 100 adaptive design iterations using two models within the Adaptive Experimentation (Ax) Platform.
Materials Science
OpenQAOA -- An SDK for QAOA
We introduce OpenQAOA, a Python open-source multi-backend Software Development Kit to create, customise, and execute the Quantum Approximate Optimisation Algorithm (QAOA) on Noisy Intermediate-Scale Quantum (NISQ) devices and simulators.
Quantum Physics
ELECTRODE: An electrochemistry package for atomistic simulations
Here we present a feature-rich CPM implementation, called ELECTRODE, for the Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS), which includes a constrained charge method and a thermo-potentiostat.
Chemical Physics Computational Physics
