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

0.02 stars / hour

Disorder in Andreev reflection of a quantum Hall edge

autonomousvision/stylegan_xl 2 Jan 2022

We find the statistical distribution of the conductance and its dependence on electron density, magnetic field, and temperature.

Mesoscale and Nanoscale Physics Superconductivity

0.02 stars / hour

Efficient numerical simulations with Tensor Networks: Tensor Network Python (TeNPy)

tenpy/tenpy 30 Apr 2018

Tensor product state (TPS) based methods are powerful tools to efficiently simulate quantum many-body systems in and out of equilibrium.

Strongly Correlated Electrons

0.02 stars / hour

The geometry of nonlinear least squares with applications to sloppy models and optimization

JuliaOpt/LsqFit.jl 7 Oct 2010

Parameter estimation by nonlinear least squares minimization is a common problem with an elegant geometric interpretation: the possible parameter values of a model induce a manifold in the space of data predictions.

Statistical Mechanics Computational Physics Data Analysis, Statistics and Probability

0.02 stars / hour

SeQUeNCe: A Customizable Discrete-Event Simulator of Quantum Networks

sequence-toolbox/SeQUeNCe 25 Sep 2020

We implement a comprehensive suite of network protocols and demonstrate the use of SeQUeNCe by simulating a photonic quantum network with nine routers equipped with quantum memories.

Quantum Physics

0.02 stars / hour

Variational Quantum Pulse Learning

mit-han-lab/torchquantum 31 Mar 2022

Inspired by the promising performance of VQC, in this paper we propose variational quantum pulses (VQP), a novel paradigm to directly train quantum pulses for learning tasks.

Quantum Physics

0.02 stars / hour

Modified Shallow Water Equations for significantly varying seabeds

huwb/crest-oceanrender 29 Feb 2012

The novel system is a non-dispersive non-hydrostatic extension of the classical Saint-Venant equations.

Classical Physics Analysis of PDEs Numerical Analysis Computational Physics Fluid Dynamics

0.02 stars / hour

Uncertainty propagation with functionally correlated quantities

JuliaPhysics/Measurements.jl 27 Oct 2016

Many uncertainty propagation software exist, written in different programming languages, but not all of them are able to handle functional correlation between quantities.

Data Analysis, Statistics and Probability

0.02 stars / hour

Wavelet Adaptive Proper Orthogonal Decomposition for Large Scale Flow Data

adaptive-cfd/WABBIT 10 Nov 2020

The proper orthogonal decomposition (POD) is a powerful classical tool in fluid mechanics used, for instance, for model reduction and extraction of coherent flow features.

Fluid Dynamics Numerical Analysis Numerical Analysis

0.02 stars / hour

Data-Driven Collective Variables for Enhanced Sampling

luigibonati/data-driven-CVs 16 Feb 2020

Designing an appropriate set of collective variables is crucial to the success of several enhanced sampling methods.

Chemical Physics Computational Physics

0.02 stars / hour