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We present a time dependent variational method to learn the mechanisms of equilibrium reactive processes and efficiently evaluate their rates within a transition path ensemble. This approach builds off variational path sampling methodology…

Chemical Physics · Physics 2023-07-10 Aditya N. Singh , David T. Limmer

We investigate the critical behavior, both in space and time, of the wetting interface within the coexistence region around the first-order phase transition of a fully-connected quantum Ising model in slab geometry. For that, we employ the…

Statistical Mechanics · Physics 2023-03-07 Claudia Artiaco , Andrea Nava , Michele Fabrizio

Targeting to understand the underlying explainable factors behind observations and modeling the conditional generation process on these factors, we connect disentangled representation learning to Diffusion Probabilistic Models (DPMs) to…

Computer Vision and Pattern Recognition · Computer Science 2023-10-31 Tao Yang , Yuwang Wang , Yan Lv , Nanning Zheng

We extend the concept of superadiabatic dynamics, or transitionless quantum driving, to quantum open systems whose evolution is governed by a master equation in the Lindblad form. We provide the general framework needed to determine the…

Quantum Physics · Physics 2015-06-16 G. Vacanti , R. Fazio , S. Montangero , G. M. Palma , M. Paternostro , V. Vedral

We present an efficient algorithm for simulating open quantum systems dynamics described by the Lindblad master equation on quantum computers, addressing key challenges in the field. In contrast to existing approaches, our method achieves…

Quantum Physics · Physics 2024-12-31 Giovanni Di Bartolomeo , Michele Vischi , Tommaso Feri , Angelo Bassi , Sandro Donadi

Recent advances in quantum simulators permit unitary evolution interspersed with locally resolved mid-circuit measurements. This paves the way for the observation of large-scale space-time structures in quantum trajectories and opens a…

We introduce a universal method for accelerating Lindblad dynamics that preserves the original trajectory through Hilbert space. The technique provides exact fast processes analytically, which are Markovian and do not require manipulation…

Quantum Physics · Physics 2025-12-04 Bertúlio de Lima Bernardo

In this letter, we introduce a novel method for investigating dissipation (gain) and thermalization in an open quantum system. In this method, the quantum system is coupled linearly with a copy of itself or with another system described by…

World-wide efforts aim at the realization of advanced quantum simulators and processors. However, despite the development of intricate hardware and pulse control systems, it may still not be generally known which effective quantum dynamics,…

For open quantum systems,a short-time evolution is usually well described by the effective non-Hermitian Hamiltonians,while long-time dynamics requires the Lindblad master equation,in which the Liouvillian superoperators characterize the…

Quantum Physics · Physics 2024-04-19 Jilian Zhong , Xiaoyue Li

Collective radiance effects in quantum degenerate systems, such as superradiance and subradiance of a partially inverted ensemble, are shaped by the interplay of spatial confinement and exchange statistics. We investigate this interplay…

Quantum Gases · Physics 2026-04-03 Julian Lyne , Kai Phillip Schmidt , Claudiu Genes , Nico S. Bassler

This text is a short introduction to the physics of driven-dissipative many-body systems, focusing on a few selected topics. Beyond its more ``historical'' interest in the study of atomic physics and quantum optics, presently the modeling…

Quantum Physics · Physics 2026-04-02 Fabrizio Minganti , Alberto Biella

We present a Bayesian algorithm to identify generators of open quantum system dynamics, described by a Lindblad master equation, that are compatible with measured experimental data. The algorithm, based on a Markov Chain Monte Carlo…

Quantum Physics · Physics 2025-09-15 Stewart Wallace , Yoann Altmann , Brian D. Gerardot , Erik M. Gauger , Cristian Bonato

We investigate the time evolution of an open quantum system described by a Lindblad master equation with dissipation acting only on a part of the degrees of freedom ${\cal H}_0$ of the system, and targeting a unique dark state in ${\cal…

Quantum Physics · Physics 2018-11-09 Vladislav Popkov , Simon Essink , Carlo Presilla , Gunter Schütz

In generic closed quantum systems, the complexity of operators increases under time evolution governed by the Heisenberg equation, reflecting the scrambling of local quantum information. However, when systems interact with an external…

Quantum Physics · Physics 2024-03-14 Pengfei Zhang , Zhenhua Yu

Recent works on quantum resource theories of non-Gaussianity, which are based upon the type of tools available in contemporary experimental settings, put Gaussian states and their convex combinations on equal footing. Motivated by this, in…

Quantum Physics · Physics 2022-11-14 Tomasz Linowski , Alexander Teretenkov , Łukasz Rudnicki

Feedback control in open quantum dynamics is crucial for the advancement of various coherent platforms. However, currently only a handful of feedback master equations exist in the literature, which are restricted to specific types of…

Quantum Physics · Physics 2025-12-10 Alberto J. B. Rosal , Patrick P. Potts , Gabriel T. Landi

We introduce a method to simulate open quantum many-body dynamics by combining time-dependent variational Monte Carlo (tVMC) with quantum trajectory techniques. Our approach unravels the Lindblad master equation into an ensemble of…

Control of quantum dissipative systems can be challenging because control variables are typically part of the system Hamiltonian, which can only generate motion along unitary orbits of the system. To transit between orbits, one must harness…

Quantum Physics · Physics 2012-01-04 Patrick Rooney , Anthony Bloch , Chitra Rangan

Interpretable machine learning techniques are becoming essential tools for extracting physical insights from complex quantum data. We build on recent advances in variational autoencoders to demonstrate that such models can learn physically…