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Related papers: Stochastic optimal control of open quantum systems

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In this paper, we present Quantum-Inspired Model Predictive Control (QIMPC), an approach that uses Variational Quantum Circuits (VQCs) to learn control polices in MPC problems. The viability of the approach is tested in five experiments: A…

Quantum Physics · Physics 2025-04-18 Muhammad Al-Zafar Khan , Jamal Al-Karaki

Viewing stochastic processes through the lens of occupation measures has proved to be a powerful angle of attack for the theoretical and computational analysis of stochastic optimal control problems. We present a simple modification of the…

Optimization and Control · Mathematics 2025-01-20 Flemming Holtorf , Alan Edelman , Christopher Rackauckas

We apply advanced methods of control theory to open quantum systems and we determine finite-time processes which are optimal with respect to thermodynamic performances. General properties and necessary conditions characterizing optimal…

Quantum Physics · Physics 2018-08-01 Vasco Cavina , Andrea Mari , Alberto Carlini , Vittorio Giovannetti

We consider stochastic optimal control of linear dynamical systems with additive non-Gaussian disturbance. We propose a novel, sampling-free approach, based on Fourier transformations and convex optimization, to cast the stochastic optimal…

Optimization and Control · Mathematics 2020-10-06 Vignesh Sivaramakrishnan , Abraham P. Vinod , Meeko M. K. Oishi

We propose nearly-optimal control strategies for changing states of a quantum system. We argue that quantum control optimization can be studied analytically within some protocol families that depend on a small set of parameters for…

Quantum Physics · Physics 2017-09-13 Chen Sun , Avadh Saxena , Nikolai A. Sinitsyn

In this paper, we propose a new methodology for state constrained stochastic optimal control (SOC) problems. The solution is based on past work in solving SOC problems using forward-backward stochastic differential equations (FBSDE). Our…

Systems and Control · Electrical Eng. & Systems 2021-04-07 Bolun Dai , Prashanth Krishnamurthy , Andrew Papanicolaou , Farshad Khorrami

This paper thoroughly investigates stochastic linear-quadratic optimal control problems with the Markovian regime switching system, where the coefficients of the state equation and the weighting matrices of the cost functional are random.…

Optimization and Control · Mathematics 2022-08-03 Jiaqiang Wen , Xun Li , Jie Xiong , Xin Zhang

This paper presents a stochastic model predictive control approach for nonlinear systems subject to time-invariant probabilistic uncertainties in model parameters and initial conditions. The stochastic optimal control problem entails a cost…

Optimization and Control · Mathematics 2014-10-17 Stefan Streif , Matthias Karl , Ali Mesbah

This paper presents a framework for solving the pure-state preparation problem using numerical optimal control. As an example, we consider the case where a number of qubits are dispersively coupled to a readout cavity. We model open system…

Quantum Physics · Physics 2024-06-19 Stefanie Günther , N. Anders Petersson , Jonathan L. DuBois

Control of quantum systems is a central element of high-precision experiments and the development of quantum technological applications. Control pulses that are typically temporally or spatially modulated are often designed based on…

Quantum Physics · Physics 2021-01-04 Frederic Sauvage , Florian Mintert

We investigate optimal control strategies for state to state transitions in a model of a quantum dot molecule containing two active strongly interacting electrons. The Schrodinger equation is solved nonperturbatively in conjunction with…

Quantum Physics · Physics 2016-08-14 R. Nepstad , L. Sælen , I. Degani , J. P. Hansen

We introduce an efficient algorithm for the systematic design of shallow-depth quantum circuits capable of preparing many-body quantum states represented as Matrix Product States (MPS). The proposed method leverages Schmidt spectrum…

Quantum Physics · Physics 2025-12-24 Josh Green , Joshua Snow , Jingbo B Wang

This paper studies the stochastic optimal control problem for systems with unknown dynamics. A novel decoupled data based control (D2C) approach is proposed, which solves the problem in a decoupled "open loop-closed loop" fashion that is…

Systems and Control · Computer Science 2018-09-11 Dan Yu , Mohammandhussen Rafieisakhaei , Suman Chakravorty

Closed-loop optimal control design for high-dimensional nonlinear systems has been a long-standing challenge. Traditional methods, such as solving the associated Hamilton-Jacobi-Bellman equation, suffer from the curse of dimensionality.…

Optimization and Control · Mathematics 2026-01-01 Xuanxi Zhang , Jihao Long , Wei Hu , Weinan E , Jiequn Han

High fidelity state preparation represents a fundamental challenge in the application of quantum technology. While the majority of optimal control approaches use feedback to improve the controller, the controller itself often does not…

Quantum Physics · Physics 2021-11-22 Ethan N. Evans , Ziyi Wang , Adam G. Frim , Michael R. DeWeese , Evangelos A. Theodorou

This work presents an efficient method to solve a class of continuous-time, continuous-space stochastic optimal control problems of robot motion in a cluttered environment. The method builds upon a path integral representation of the…

Systems and Control · Computer Science 2016-03-10 Jung-Su Ha , Han-Lim Choi

The paper addresses a continuous-time continuous-space chance-constrained stochastic optimal control (SOC) problem where the probability of failure to satisfy given state constraints is explicitly bounded. We leverage the notion of exit…

Systems and Control · Electrical Eng. & Systems 2025-11-26 Apurva Patil , Alfredo Duarte , Fabrizio Bisetti , Takashi Tanaka

A new class of cost functionals for optimal control of quantum systems which produces controls which are sparse in frequency and smooth in time is proposed. This is achieved by penalizing a suitable time-frequency representation of the…

Optimization and Control · Mathematics 2016-07-15 Gero Friesecke , Felix Henneke , Karl Kunisch

This paper presents a novel algorithm for solving distribution steering problems featuring nonlinear dynamics and chance constraints. Covariance steering (CS) is an emerging methodology in stochastic optimal control that poses constraints…

Robotics · Computer Science 2025-09-24 Akash Ratheesh , Vincent Pacelli , Augustinos D. Saravanos , Evangelos A. Theodorou

Optimization of constrained quantum control problems powers quantum technologies. This task becomes very difficult when these control problems are nonconvex and plagued with dense local extrema. For such problems current optimization…

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