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Simulating the dynamics of many-body quantum systems is a significant challenge, especially in higher dimensions where entanglement grows rapidly. Neural quantum states (NQS) offer a promising tool for representing quantum wavefunctions,…

Quantum Physics · Physics 2024-12-17 Anka Van de Walle , Markus Schmitt , Annabelle Bohrdt

Simulating trajectories of multi-particle systems on complex energy landscapes is a central task in molecular dynamics (MD) and drug discovery, but remains challenging at scale due to computationally expensive and long simulations. Previous…

Machine Learning · Computer Science 2025-11-11 Sophia Tang , Yinuo Zhang , Pranam Chatterjee

While general quantum many-body systems require exponential resources to be simulated on a classical computer, systems of non-interacting fermions can be simulated exactly using polynomially scaling resources. Such systems may be of…

Strongly Correlated Electrons · Physics 2019-12-18 Norbert Schuch , Bela Bauer

The competition of different length scales in quantum many-body systems leads to various novel phenomena, including the emergence of correlated dynamics or non-local order. To access and investigate such effects in an itinerant…

Modern quantum optical systems such as photonic quantum computers and quantum imaging devices require great precision in their designs and implementations in the hope to realistically exploit entanglement and reach a real quantum advantage.…

Quantum Physics · Physics 2024-06-05 Nicolas Allegra

Quantum many-body control is among most challenging problems in quantum science, due to computational complexity of related underlying problems. We propose an efficient approach for solving a class of control problems for many-body quantum…

Quantum Physics · Physics 2024-02-21 I. A. Luchnikov , M. A. Gavreev , A. K. Fedorov

Numerical methods for obtaining exact dynamics of non-Markovian open quantum systems are mostly limited to either small systems or to short-time evolution only. Here, we propose a new algorithm for computing process tensors--matrix product…

Quantum Physics · Physics 2026-03-10 Émile Cochin , Jonathan Keeling , Brendon W. Lovett , Alex W. Chin

Recently, an effective Lindblad master equation for quantum systems whose dynamics are coupled to dissipative bosonic modes has been introduced [Phys. Rev. Lett. 129, 063601 (2022)]. In this approach, the bosonic modes are adiabatically…

Quantum Physics · Physics 2023-07-18 Simon B. Jäger , Ralf Betzholz

Over the last decade tensor network states (TNS) have emerged as a powerful tool for the study of quantum many body systems. The matrix product states (MPS) are one particular case of TNS and are used for the simulation of 1+1 dimensional…

High Energy Physics - Lattice · Physics 2015-11-16 Boye Buyens , Karel Van Acoleyen , Jutho Haegeman , Frank Verstraete

Since precisely controlling dissipation in realistic environments is challenging, digital simulation of the Lindblad master equation (LME) is of great significance for understanding nonequilibrium dynamics in open quantum systems. However,…

Quantum Physics · Physics 2026-02-02 Yu-Guo Liu , Heng Fan , Shu Chen

We propose a systematic and explicit method for the inverse engineering of the dynamics of an open quantum systems with no auxiliary Hamiltonian nor the prerequisite of adiabatic passage. In particular, we exploit the Lindblad dissipators…

Quantum Physics · Physics 2016-12-08 Jun Jing , Mark S. Byrd , Lian-Ao Wu

Tensor Network methods have been established as a powerful technique for simulating low dimensional strongly-correlated systems for over two decades. Employing the formalism of Matrix Product States, we investigate the phase diagram of the…

High Energy Physics - Lattice · Physics 2017-10-30 Mari Carmen Bañuls , Krzysztof Cichy , Ying-Jer Kao , C. -J. David Lin , Yu-Ping Lin , David Tao-Lin Tan

Modeling joint probability distributions over sequences has been studied from many perspectives. The physics community developed matrix product states, a tensor-train decomposition for probabilistic modeling, motivated by the need to…

Machine Learning · Computer Science 2020-10-22 Siddarth Srinivasan , Sandesh Adhikary , Jacob Miller , Guillaume Rabusseau , Byron Boots

The ability to selectively measure, initialize, and reuse qubits during a quantum circuit enables a mapping of the spatial structure of certain tensor-network states onto the dynamics of quantum circuits, thereby achieving dramatic resource…

We propose a method to obtain the thermal-equilibrium density matrix of a many-body quantum system using artificial neural networks. The variational function of the many-body density matrix is represented by a convolutional neural network…

Disordered Systems and Neural Networks · Physics 2020-03-18 Naoki Irikura , Hiroki Saito

A framework for simulating the real-time dynamics of composite particles in a simple model of dense matter that is amenable to quantum computers is developed. As a demonstration, we perform classical simulations of heavy-hadrons propagating…

Quantum Physics · Physics 2025-01-22 Roland C. Farrell , Marc Illa , Martin J. Savage

Out-of-equilibrium dynamics of non-integrable Hamiltonian many-body quantum systems are characterized by highly entangled wave functions. Near-maximal entanglement arises in systems exhibiting thermalization or pre-thermalization, where the…

There is significant interest in exploring novel phenomena in quantum light-matter interfaces, which are driven by the combination of structured dissipation and long-range interactions that are typical in such systems. To this end, it is…

The possibility to simulate the properties of many-body open quantum systems with a large number of degrees of freedom is the premise to the solution of several outstanding problems in quantum science and quantum information. The challenge…

Quantum Physics · Physics 2019-07-03 Alexandra Nagy , Vincenzo Savona

Computing dynamical distributions in quantum many-body systems represents one of the paradigmatic open problems in theoretical condensed matter physics. Despite the existence of different techniques both in real-time and frequency space,…

Disordered Systems and Neural Networks · Physics 2021-08-04 Rouven Koch , Jose L. Lado