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The GRAPE$.$jl package (https://github.com/JuliaQuantumControl/GRAPE.jl) implements Gradient Ascent Pulse Engineering, a widely used method of quantum optimal control. Its purpose is to find controls that steer a quantum system in a…

In this paper we present \texttt{SymOrb.jl}, a software which combines group representation theory and variational methods to provide numerical solutions of singular dynamical systems of paramount relevance in Celestial Mechanics and other…

StateSpaceModels.jl is an open-source Julia package for modeling, forecasting and simulating time series in a state-space framework. The package represents a straightforward tool that can be useful for a wide range of applications that deal…

Computation · Statistics 2020-02-11 Raphael Saavedra , Guilherme Bodin , Mario Souto

Accurate, global Potential Energy Surfaces (PES) expressed in sum-of-products (SOP) form are a prerequisite for efficient high-dimensional quantum dynamics simulations using the MCTDH method. This work introduces a methodology for…

Chemical Physics · Physics 2026-03-31 Antoine Aerts

The exact contraction of a generic two-dimensional (2D) tensor network state (TNS) is known to be exponentially hard, making simulation of 2D systems difficult. The recently introduced class of isometric TNS (isoTNS) represents a subset of…

Strongly Correlated Electrons · Physics 2023-06-13 Yantao Wu , Sajant Anand , Sheng-Hsuan Lin , Frank Pollmann , Michael P. Zaletel

Although many efficient heuristics have been developed to solve binary optimization problems, these typically produce correlated solutions for degenerate problems. Most notably, transverse-field quantum annealing - the heuristic employed in…

Disordered Systems and Neural Networks · Physics 2019-06-27 Zheng Zhu , Andrew J. Ochoa , Helmut G. Katzgraber

The open-source software package SolidStateDetectors$.$jl to calculate the fields and simulate the drifts of charge carriers in solid state detectors, together with the corresponding pulses, is introduced. The package can perform all…

Instrumentation and Detectors · Physics 2026-02-17 I. Abt , F. Fischer , F. Hagemann , L. Hauertmann , O. Schulz , M. Schuster , A. J. Zsigmond

Motivated by the recent success of tensor networks to calculate the residual entropy of spin ice and kagome Ising models, we develop a general framework to study frustrated Ising models in terms of infinite tensor networks %, i.e. tensor…

Statistical Mechanics · Physics 2021-01-20 Bram Vanhecke , Jeanne Colbois , Laurens Vanderstraeten , Frank Verstraete , Frédéric Mila

Pulgon-tools is an open-source software package providing building blocks for the analysis and modeling of quasi-one-dimensional (quasi-1D) periodic systems based on line-group theory. While mature libraries exist for space-group detection…

Computational Physics · Physics 2026-03-31 Yu-Jie Cen , Sandro Wieser , Georg K. H. Madsen , Jesús Carrete

This thesis is divided into two mainly independent parts: In the first part, we derive a criterion to determine when a translationally invariant Matrix Product State (MPS) has long range localizable entanglement, which indicates that the…

Strongly Correlated Electrons · Physics 2015-09-22 Thorsten B. Wahl

We present a high-accuracy procedure for electronic structure calculations of strongly correlated materials. To address limitations in current electronic structure methods, we employ density functional theory in combination with the…

We introduce an enriched entanglement structure for spin networks, inspired by tensor-network constructions, in which internal links can carry a controlled and discrete amount of entanglement. In the spin-network picture, vertices are dual…

High Energy Physics - Theory · Physics 2025-12-16 Mai Qi , Eugenia Colafranceschi

We present TNRKit, an open-source Julia package for Tensor Network Renormalization (TNR) of two- and three-dimensional classical statistical models and Euclidean lattice field theories. Built on top of TensorKit, it provides a…

Strongly Correlated Electrons · Physics 2026-04-21 Victor Vanthilt , Adwait Naravane , Chenqi Meng , Atsushi Ueda

Hierarchical optimization architectures are used in power systems to manage disturbances and phenomena that arise at multiple spatial and temporal scales. We present a graph modeling abstraction for representing such architectures and an…

Optimization and Control · Mathematics 2023-09-20 David L. Cole , Harsha Gangammanavar , Victor M. Zavala

A typical quantum state obeying the area law for entanglement on an infinite 2D lattice can be represented by a tensor network ansatz -- known as an infinite projected entangled pair state (iPEPS) -- with a finite bond dimension $D$. Its…

Strongly Correlated Electrons · Physics 2018-07-11 Piotr Czarnik , Jacek Dziarmaga

We simulate the Shastry-Sutherland model in two dimensions by means of infinite projected entangled-pair states (iPEPS) - a variational tensor network method where the accuracy can be systematically controlled by the so-called bond…

Strongly Correlated Electrons · Physics 2015-06-12 Philippe Corboz , Frederic Mila

Semidefinite programs (SDPs) are a framework for exact or approximate optimization that have widespread application in quantum information theory. We introduce a new method for using reductions to construct integrality gaps for SDPs. These…

Quantum Physics · Physics 2019-03-18 Aram W. Harrow , Anand Natarajan , Xiaodi Wu

A bivariate version of the multicanonical Monte Carlo method and its application to the simulation of the three-dimensional $\pm J$ Ising spin glass are described. We found the autocorrelation time associated with this particular…

Disordered Systems and Neural Networks · Physics 2009-09-25 Naomichi Hatano , James E. Gubernatis

We study the antiferromagnetic kagome Heisenberg model with additional scalar-chiral interaction by using the infinite projected entangled-pair state (iPEPS) ansatz. We discuss in detail the implementation of optimization algorithm in the…

Strongly Correlated Electrons · Physics 2019-05-29 R. Haghshenas , Shou-Shu Gong , D. N. Sheng

This paper proposes a new framework using physics-informed neural networks (PINNs) to simulate complex structural systems that consist of single and double beams based on Euler-Bernoulli and Timoshenko theory, where the double beams are…

Machine Learning · Computer Science 2023-09-26 Taniya Kapoor , Hongrui Wang , Alfredo Nunez , Rolf Dollevoet