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

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

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

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

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

Computational Physics Data Analysis, Statistics and Probability Fluid Dynamics

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

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

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

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

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