Quantum simulation with just-in-time compilation

qiboteam/qibo 16 Mar 2022

In parallel to the development of quantum devices, efficient simulation tools are needed in order to design and benchmark quantum algorithms and applications before deployment on quantum hardware.

Quantum Physics High Energy Physics - Phenomenology Computational Physics

0.07 stars / hour

Quantum autoencoders with enhanced data encoding

Quantum-TII/qibo 13 Oct 2020

We present the enhanced feature quantum autoencoder, or EF-QAE, a variational quantum algorithm capable of compressing quantum states of different models with higher fidelity.

Quantum Physics Statistical Mechanics High Energy Physics - Theory

0.07 stars / hour

A Universal Machine Learning Model for Elemental Grain Boundary Energies

materialsvirtuallab/maml 28 Jan 2022

By machine learning on a large computed database of 361 small $\Sigma$ ($\Sigma < 10$) GBs of more than 50 metals, we develop a model that can predict the grain boundary energies to within a mean absolute error of 0. 13 J m$^{-2}$.

Materials Science Computational Physics

0.05 stars / hour

A unified framework for machine learning collective variables for enhanced sampling simulations: $\texttt{mlcolvar}$

luigibonati/mlcolvar 31 May 2023

Here we present $\texttt{mlcolvar}$, a Python library that simplifies the construction of these variables and their use in the context of enhanced sampling through a contributed interface to the PLUMED software.

Computational Physics

0.05 stars / hour

Structural Dynamics Descriptors for Metal Halide Perovskites

WMD-group/PDynA 19 May 2023

Here, we report the quantitative analysis of structural dynamics in time and space from molecular dynamics simulations of perovskite crystals.

Materials Science

0.04 stars / hour

Unitary Partitioning and the Contextual Subspace Variational Quantum Eigensolver

ucl-ccs/symmer 7 Jul 2022

Our results indicate that CS-VQE combined with measurement reduction is a promising approach to allow feasible eigenvalue computations on noisy intermediate-scale quantum devices.

Quantum Physics

0.06 stars / hour

Geometric deep learning reveals the spatiotemporal fingerprint of microscopic motion

softmatterlab/deeptrack2 13 Feb 2022

The characterization of dynamical processes in living systems provides important clues for their mechanistic interpretation and link to biological functions.

Data Analysis, Statistics and Probability Image and Video Processing Biological Physics Quantitative Methods

0.04 stars / hour

Unified Graph Neural Network Force-field for the Periodic Table

usnistgov/alignn 12 Sep 2022

Classical force fields (FF) based on machine learning (ML) methods show great potential for large scale simulations of materials.

Materials Science

0.04 stars / hour

A comprehensive and fair comparison of two neural operators (with practical extensions) based on FAIR data

lululxvi/deepxde 10 Nov 2021

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

0.04 stars / hour

Investigating Quantum Approximate Optimization Algorithms under Bang-bang Protocols

google-research/google-research 27 May 2020

The quantum approximate optimization algorithm (QAOA) is widely seen as a possible usage of noisy intermediate-scale quantum (NISQ) devices.

Quantum Physics

0.03 stars / hour