English
Related papers

Related papers: Enhanced Convergence and Robust Performance of Ran…

200 papers

The present thesis deals with various methods of quantum error correction. It is divided into two parts. In the first part, dynamical decoupling methods are considered which have the task of suppressing the influence of residual…

Quantum Physics · Physics 2009-09-30 Oliver Kern

Randomized saturation designs are a family of designs which assign a possibly different treatment proportion to each cluster of a population at random. As a result, they generalize the well-known (stratified) completely randomized designs…

Methodology · Statistics 2022-03-21 Chencheng Cai , Jean Pouget-Abadie , Edoardo M. Airoldi

The loss of coherence is one of the main obstacles for the implementation of quantum information processing. The efficiency of dynamical decoupling schemes, which have been introduced to address this problem, is limited itself by the…

Control over the quantum dynamics of chaotic kicked rotor systems is demonstrated. Specifically, control over a number of quantum coherent phenomena is achieved by a simple modification of the kicking field. These include the enhancement of…

Quantum Physics · Physics 2009-11-10 Jiangbin Gong , Hans Jakob Worner , Paul Brumer

Conventionally in quantum sensing, the goal is to estimate one or more unknown parameters that are assumed to be deterministic - that is, they do not change between shots of the quantum-sensing protocol. We instead consider the setting…

We describe a new family of coupling designs, extending the basic principle of stratified randomization to experiments with continuous, constrained multivariate, text/image and other irregular treatment spaces. Our approach is to first…

Econometrics · Economics 2026-04-14 Max Cytrynbaum , Fredrik Sävje

We develop theoretically and demonstrate experimentally a universal dynamical decoupling method for robust quantum sensing with unambiguous signal identification. Our method uses randomisation of control pulses to suppress simultaneously…

We propose a data-driven control method for systems with aleatoric uncertainty, for example, robot fleets with variations between agents. Our method leverages shared trajectory data to increase the robustness of the designed controller and…

Robotics · Computer Science 2024-03-25 Alexander von Rohr , Dmitrii Likhachev , Sebastian Trimpe

We consider how randomness can be made to play a useful role in quantum information processing - in particular, for decoherence control and the implementation of quantum algorithms. For a two-level system in which the decoherence channel is…

Quantum Physics · Physics 2007-05-23 Chiu Fan Lee , Neil F. Johnson

Resource tradeoffs can often be established by solving an appropriate robust optimization problem for a variety of scenarios involving constraints on optimization variables and uncertainties. Using an approach based on sequential convex…

Quantum Physics · Physics 2013-12-17 Robert L. Kosut , Matthew D. Grace , Constantin Brif

In this paper, we present a robust distributed model predictive control (DMPC) scheme for dynamically decoupled nonlinear systems which are subject to state constraints, coupled state constraints and input constraints. In the proposed…

Systems and Control · Electrical Eng. & Systems 2024-10-07 Adrian Wiltz , Fei Chen , Dimos V. Dimarogonas

Coherent errors in quantum operations are ubiquitous. Whether arising from spurious environmental couplings or errors in control fields, such errors can accumulate rapidly and degrade the performance of a quantum circuit significantly more…

Quantum Physics · Physics 2022-05-03 Anthony M. Polloreno , Kevin C. Young

We study the sample efficiency of domain randomization and robust control for the benchmark problem of learning the linear quadratic regulator (LQR). Domain randomization, which synthesizes controllers by minimizing average performance over…

Systems and Control · Electrical Eng. & Systems 2025-02-19 Tesshu Fujinami , Bruce D. Lee , Nikolai Matni , George J. Pappas

I investigate the problem of optimally discriminating between two open quantum dynamical processes in a single-shot scenario, with the goal of minimizing the error probability of identification. This task involves optimising both the input…

Quantum Physics · Physics 2025-12-10 Massimiliano F. Sacchi

In this paper, we present a distributed model predictive control (DMPC) scheme for dynamically decoupled systems which are subject to state constraints, coupling state constraints and input constraints. In the proposed control scheme,…

Systems and Control · Electrical Eng. & Systems 2024-08-17 Adrian Wiltz , Fei Chen , Dimos V. Dimarogonas

Dynamical decoupling (DD) is a popular technique for protecting qubits from the environment. However, unless special care is taken, experimental errors in the control pulses used in this technique can destroy the quantum information instead…

Quantum Physics · Physics 2011-06-20 Alexandre M. Souza , Gonzalo A. Alvarez , Dieter Suter

Quantum computers, which process information encoded in quantum mechanical systems, hold the potential to solve some of the hardest computational problems. A substantial obstacle for the further development of quantum computers is the fact…

Quantum Physics · Physics 2012-11-02 Alexandre M. Souza , Gonzalo A. Álvarez , Dieter Suter

Protecting quantum states from the decohering effects of the environment is of great importance for the development of quantum computation devices and quantum simulators. Here, we introduce a continuous dynamical decoupling protocol that…

Quantum Physics · Physics 2019-04-10 İ. Yalçınkaya , B. Çakmak , G. Karpat , F. F. Fanchini

Refocusing, or dynamical decoupling, is a coherent control technique where the internal dynamics of a quantum system is effectively averaged out by an application of specially designed driving fields. The method has originated in nuclear…

Quantum Physics · Physics 2007-06-05 Leonid P. Pryadko , Gregory Quiroz

Choosing control inputs randomly can result in a reduced expected cost in optimal control problems with stochastic constraints, such as stochastic model predictive control (SMPC). We consider a controller with initial randomization, meaning…

Robotics · Computer Science 2016-07-07 Masahiro Ono , Mahmoud El Chamie , Marco Pavone , Behcet Acikmese