Exact and practical pattern matching for quantum circuit optimization

Qiskit/qiskit-terra 11 Sep 2019

An important building block for many quantum circuit optimization techniques is pattern matching, where given a large and a small quantum circuit, we are interested in finding all maximal matches of the small circuit, called pattern, in the large circuit, considering pairwise commutation of quantum gates.

Quantum Physics Data Structures and Algorithms

0.02 stars / hour

A Generic Compilation Strategy for the Unitary Coupled Cluster Ansatz

CQCL/pytket 20 Jul 2020

We describe a compilation strategy for Variational Quantum Eigensolver (VQE) algorithms which use the Unitary Coupled Cluster (UCC) ansatz, designed to reduce circuit depth and gate count.

Quantum Physics Emerging Technologies

0.02 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

0.02 stars / hour

Build your own tensor network library: DMRjulia I. Basic library for the density matrix renormalization group

bakerte/dmrjulia 7 Sep 2021

The code can be used as an educational tool to understand how tensor network computations are done in the context of entanglement renormalization or as a template for other codes in low level languages.

Quantum Physics

0.02 stars / hour

Physics-Constrained Bayesian Neural Network for Fluid Flow Reconstruction with Sparse and Noisy Data

Jianxun-Wang/Physics-constrained-Bayesian-deep-learning 15 Jan 2020

In many applications, flow measurements are usually sparse and possibly noisy.

Computational Physics Data Analysis, Statistics and Probability Fluid Dynamics

0.02 stars / hour

Unified treatment of synchronization patterns in generalized networks with higher-order, multilayer, and temporal interactions

y-z-zhang/SBD 1 Oct 2020

When describing complex interconnected systems, one often has to go beyond the standard network description to account for generalized interactions.

Adaptation and Self-Organizing Systems Disordered Systems and Neural Networks

0.02 stars / hour

SPHinXsys: an open-source multi-physics and multi-resolution library based on smoothed particle hydrodynamics

Xiangyu-Hu/SPHinXsys 23 Oct 2020

In this paper, we present an open-source multi-resolution and multi-physics library: SPHinXsys (pronunciation: s'finksis) which is an acronym for \underline{S}moothed \underline{P}article \underline{H}ydrodynamics (SPH) for \underline{in}dustrial comple\underline{X} \underline{sys}tems.

Computational Physics

0.02 stars / hour

Riemannian optimization of isometric tensor networks

mhauru/MERA.jl 7 Jul 2020

We discuss the geometry of Grassmann and Stiefel manifolds, the Riemannian manifolds of isometric tensors, and review how state-of-the-art optimization methods like nonlinear conjugate gradient and quasi-Newton algorithms can be implemented in this context.

Quantum Physics Strongly Correlated Electrons

0.02 stars / hour

Super-resolution and denoising of fluid flow using physics-informed convolutional neural networks without high-resolution labels

Jianxun-Wang/PICNNSR 4 Nov 2020

By leveraging the conservation laws and boundary conditions of fluid flows, the CNN-SR model is trained without any HR labels.

Fluid Dynamics Computational Physics

0.02 stars / hour

Quantum information with continuous variables

ansu5555/pdf-viewer-reactjs 13 Oct 2004

We review the progress in quantum information based on continuous quantum variables, with emphasis on quantum optical implementations in terms of the quadrature amplitudes of the electromagnetic field.

Quantum Physics

0.02 stars / hour