# SeisBench -- A Toolbox for Machine Learning in Seismology

1 Nov 2021

Accessing these various benchmark datasets for training and implementing the standardization of models is currently a time-consuming process, hindering further advancement of ML techniques within seismology.

Geophysics

111
0.02 stars / hour

# Mitiq: A software package for error mitigation on noisy quantum computers

9 Sep 2020

We introduce Mitiq, a Python package for error mitigation on noisy quantum computers.

Quantum Physics Emerging Technologies

213
0.02 stars / hour

# Overcoming timestep limitations in boosted-frame Particle-In-Cell simulations of plasma-based acceleration

28 Apr 2021

In the case of boosted-frame PIC simulations of plasma-based acceleration, this limitation can be a major hinderance as the cells are often very elongated along the longitudinal direction and the timestep is thus limited by the small, transverse cell size.

Accelerator Physics Computational Physics

142
0.02 stars / hour

# Quantum autoencoders with enhanced data encoding

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

144
0.02 stars / hour

# Graph Networks as a Universal Machine Learning Framework for Molecules and Crystals

Similarly, we show that MEGNet models trained on $\sim 60, 000$ crystals in the Materials Project substantially outperform prior ML models in the prediction of the formation energies, band gaps and elastic moduli of crystals, achieving better than DFT accuracy over a much larger data set.

Drug Discovery Formation Energy Materials Science Computational Physics

385
0.01 stars / hour

# Optimized Low-Depth Quantum Circuits for Molecular Electronic Structure using a Separable Pair Approximation

9 May 2021

We present a classically solvable model that leads to optimized low-depth quantum circuits leveraging separable pair approximations.

Quantum Physics Chemical Physics Computational Physics

261
0.01 stars / hour

# SchNetPack: A Deep Learning Toolbox For Atomistic Systems

4 Sep 2018

SchNetPack is a toolbox for the development and application of deep neural networks to the prediction of potential energy surfaces and other quantum-chemical properties of molecules and materials.

Computational Physics Chemical Physics

492
0.01 stars / hour

# Entangling Quantum Generative Adversarial Networks

30 Apr 2021

Generative adversarial networks (GANs) are one of the most widely adopted semisupervised and unsupervised machine learning methods for high-definition image, video, and audio generation.

Quantum Physics

1,446
0.01 stars / hour

# Pushing the limit of molecular dynamics with ab initio accuracy to 100 million atoms with machine learning

1 May 2020

For 35 years, {\it ab initio} molecular dynamics (AIMD) has been the method of choice for modeling complex atomistic phenomena from first principles.

Computational Physics

908
0.01 stars / hour

# Automated discovery of superconducting circuits and its application to 4-local coupler design

6 Dec 2019

Superconducting circuits have emerged as a promising platform to build quantum processors.

Quantum Physics

954
0.01 stars / hour