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Stochastic reduced-order models are widely used to represent the effective dynamics of complex systems, but estimating their drift and diffusion coefficients from data remains challenging. Standard approaches often rely on short-time…

Machine Learning · Statistics 2026-04-28 Ludovico T. Giorgini

We provide model reduction formulas for open quantum systems consisting of a target component which weakly interacts with a strongly dissipative environment. The time-scale separation between the uncoupled dynamics and the interaction…

The reduced basis method is a powerful model reduction technique designed to speed up the computation of multiple numerical solutions of parametrized partial differential equations. We consider a quantity of interest, which is a linear…

Analysis of PDEs · Mathematics 2014-07-11 Alexandre Janon , Maëlle Nodet , Clémentine Prieur

The gradient descent approach is the key ingredient in variational quantum algorithms and machine learning tasks, which is an optimization algorithm for finding a local minimum of an objective function. The quantum versions of gradient…

Quantum Physics · Physics 2022-04-19 Jin-Min Liang , Shi-Jie Wei , Shao-Ming Fei

In this work, we propose to efficiently solve time dependent parametrized optimal control problems governed by parabolic partial differential equations through the certified reduced basis method. In particular, we will exploit an error…

Numerical Analysis · Mathematics 2021-03-10 Maria Strazzullo , Francesco Ballarin , Gianluigi Rozza

We introduce a new analytical method for studying the open quantum systems problem of a discrete system weakly coupled to an environment of harmonic oscillators. Our approach is based on a phase space representation of the density matrix…

Quantum Physics · Physics 2015-02-27 Amir Fruchtman , Brendon W. Lovett , Simon C. Benjamin , Erik M. Gauger

We develop an innovative numerical technique to describe few-body systems. Correlated Gaussian basis functions are used to expand the channel functions in the hyperspherical representation. The method is proven to be robust and efficient…

Atomic Physics · Physics 2014-11-18 Javier von Stecher , Chris H. Greene

We propose a procedure to fully reconstruct the time-dependent coefficients of convolutionless non-Markovian dissipative generators via a finite number of experimental measurements. By combining a tomography based approach with a proper…

Quantum Physics · Physics 2011-09-26 Bruno Bellomo , Antonella De Pasquale , Giulia Gualdi , Ugo Marzolino

One of the most promising applications of quantum computing is simulating quantum many-body systems. However, there is still a need for methods to efficiently investigate these systems in a native way, capturing their full complexity. Here,…

Quantum Physics · Physics 2022-01-07 Korbinian Kottmann , Friederike Metz , Joana Fraxanet , Niccolo Baldelli

We present a reduced basis approach to solve the convected Helmholtz equation with several physical parameters. Physical parameters characterize the aeroacoustic wave propagation in terms of the wave and Mach numbers. We compute solutions…

Numerical Analysis · Mathematics 2015-06-10 Myoungnyoun Kim , Imbo Sim

We develop a real-time Full Configuration Interaction Quantum Monte Carlo approach for the modeling of driven-dissipative open quantum systems. The method enables stochastic sampling of the Liouville-von-Neumann time evolution of the…

Quantum Physics · Physics 2018-06-06 Alexandra Nagy , Vincenzo Savona

We discuss applications of a recently developed method for model reduction based on linear response theory of weakly coupled dynamical systems. We apply the weak coupling method to simple stochastic differential equations with slow and fast…

Statistical Mechanics · Physics 2016-12-21 Jeroen Wouters , Stamen I. Dolaptchiev , Valerio Lucarini , Ulrich Achatz

Open Markovian quantum systems with fast and full Hamiltonian control can be reduced to an equivalent control system on the standard simplex modelling the dynamics of the eigenvalues of the density matrix describing the quantum state. We…

Quantum Physics · Physics 2025-03-04 Emanuel Malvetti , Frederik vom Ende , Gunther Dirr , Thomas Schulte-Herbrüggen

Foundations of a new projection-based model reduction approach for convection dominated nonlinear fluid flows are summarized. In this method the evolution of the flow is approximated in the Lagrangian frame of reference. Global basis…

Fluid Dynamics · Physics 2021-10-05 Rambod Mojgani , Maciej Balajewicz

The development of techniques that reduce experimental complexity and minimize errors is an utmost importance for modeling quantum channels. In general, quantum simulators are focused on universal algorithms, whose practical implementation…

Quantum Physics · Physics 2024-02-26 Fabrício Lustosa , Roberto M. Serra , Luciano S. Cruz , Breno Marques

We characterize the dissipative phase transition in a driven dissipative Bose-Einstein condensate of neutral atoms. Our results generalize the work on dissipative nonlinear Kerr resonators towards many modes and stronger interactions. We…

Quantum Gases · Physics 2022-11-09 Jens Benary , Christian Baals , Erik Bernhart , Jian Jiang , Marvin Röhrle , Herwig Ott

Conventional strategies of quantum metrology are built upon POVMs, thereby possessing several general features, including the demolition of the state to be measured, the need of performing a number of measurements, and the degradation of…

Quantum Physics · Physics 2019-07-25 Da-Jian Zhang , Jiangbin Gong

Numerical simulation of individual open quantum systems has proven advantages over density operator computations. Quantum state diffusion with a moving basis (MQSD) provides a practical numerical simulation method which takes full advantage…

Quantum Physics · Physics 2009-10-28 R. Schack , T. A. Brun , I. C. Percival

In this contribution, we introduce and numerically evaluate a certified and adaptive localized reduced basis method as a local model in a trust-region optimization method for parameter optimization constrained by partial differential…

Numerical Analysis · Mathematics 2023-05-10 Tim Keil , Mario Ohlberger , Felix Schindler

Adiabatic quantum computing is a universal model for quantum computing whose implementation using a gate-based quantum computer requires depths that are unreachable in the early fault-tolerant era. To mitigate the limitations of near-term…

Quantum Physics · Physics 2024-10-18 Ioannis Kolotouros , Ioannis Petrongonas , Miloš Prokop , Petros Wallden