Trending Research
Quantum simulation with just-in-time compilation
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
Quantum autoencoders with enhanced data encoding
Quantum-TII/qibo
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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
A Universal Machine Learning Model for Elemental Grain Boundary Energies
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
A unified framework for machine learning collective variables for enhanced sampling simulations: $\texttt{mlcolvar}$
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
Structural Dynamics Descriptors for Metal Halide Perovskites
Here, we report the quantitative analysis of structural dynamics in time and space from molecular dynamics simulations of perovskite crystals.
Materials Science
Unitary Partitioning and the Contextual Subspace Variational Quantum Eigensolver
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
Geometric deep learning reveals the spatiotemporal fingerprint of microscopic motion
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
Unified Graph Neural Network Force-field for the Periodic Table
usnistgov/alignn
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Classical force fields (FF) based on machine learning (ML) methods show great potential for large scale simulations of materials.
Materials Science
A comprehensive and fair comparison of two neural operators (with practical extensions) based on FAIR data
lululxvi/deepxde
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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
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The quantum approximate optimization algorithm (QAOA) is widely seen as a possible usage of noisy intermediate-scale quantum (NISQ) devices.
Quantum Physics
