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Related papers: Mixed Dynamical Decoupling

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Dynamical decoupling (DD) is a promising tool for preserving the quantum states of qubits. However, small imperfections in the control pulses can seriously affect the fidelity of decoupling, and qualitatively change the evolution of the…

Quantum Physics · Physics 2015-05-20 Zhi-Hui Wang , V. V. Dobrovitski

Dynamical decoupling is a technique aimed at suppressing the interaction between a quantum system and its environment by applying frequent unitary operations on the system alone. In the present paper, we analytically study the dynamical…

Quantum Physics · Physics 2025-08-15 Alexander Hahn , Daniel Burgarth , Davide Lonigro

The excellent sensitivities of quantum sensors are a double-edged sword: minuscule quantities can be observed, but any undesired signal acts as noise. This is challenging when detecting quantities that are obscured by such noise. Decoupling…

Dynamic mode decomposition (DMD) represents an effective means for capturing the essential features of numerically or experimentally generated flow fields. In order to achieve a desirable tradeoff between the quality of approximation and…

Fluid Dynamics · Physics 2014-12-11 Mihailo R. Jovanović , Peter J. Schmid , Joseph W. Nichols

We experimentally demonstrate a robust dynamical decoupling protocol with bounded controls using long soft pulses, eliminating a challenging requirement of strong control pulses in conventional implementations. This protocol is accomplished…

Quantum Physics · Physics 2016-09-28 F. Wang , C. Zu , L. He , W. -B. Wang , W. -G. Zhang , L. -M. Duan

Dynamical decoupling (DD) is a low-overhead method for quantum error suppression. Despite extensive work in DD design, finding pulse sequences that optimally decouple computational qubits on noisy quantum hardware is not well understood. In…

Quantum Physics · Physics 2026-04-22 Christopher Tong , Helena Zhang , Bibek Pokharel

Dynamic mode decomposition (DMD) is a popular technique for modal decomposition, flow analysis, and reduced-order modeling. In situations where a system is time varying, one would like to update the system's description online as time…

Optimization and Control · Mathematics 2017-07-11 Hao Zhang , Clarence W. Rowley , Eric A. Deem , Louis N. Cattafesta

The dynamic mode decomposition (DMD) is a data-driven method used for identifying the dynamics of complex nonlinear systems. It extracts important characteristics of the underlying dynamics using measured time-domain data produced either by…

Numerical Analysis · Mathematics 2020-11-24 Ion Victor Gosea , Igor Pontes Duff

Quantum computers must be able to function in the presence of decoherence. The simplest strategy for decoherence reduction is dynamical decoupling (DD), which requires no encoding overhead and works by converting quantum gates into…

Quantum Physics · Physics 2018-12-05 Bibek Pokharel , Namit Anand , Benjamin Fortman , Daniel Lidar

The nitrogen vacancy (NV) color center in diamond is an enormously important platform for the development of quantum sensors, including for single spin and single molecule NMR. Detection of weak single-spin signals is greatly enhanced by…

Quantum Physics · Physics 2017-05-29 J. E. Lang , J. Casanova , Z. -Y. Wang , M. B. Plenio , T. S. Monteiro

Based on a theorem we establish on dynamical decoupling of time-dependent systems, we present a scheme of nested Uhrig dynamical decoupling (NUDD) to protect multi-qubit systems in generic quantum baths to arbitrary decoupling orders, using…

Quantum Physics · Physics 2011-02-10 Zhen-Yu Wang , Ren-Bao Liu

In this work we develop a numerical framework to investigate the renormalization of the non-Markovian dynamics of an open quantum system to which dynamical decoupling is applied. We utilize a non-Markovian master equation which is derived…

Quantum Physics · Physics 2007-06-13 Pochung Chen

We present a novel continuous dynamical decoupling scheme for the construction of a robust qubit in a three-level system. By means of a clock transition adjustment, we first show how robustness to environmental noise is achieved, while…

New magnetometry techniques based on Nitrogen Vacancy (NV) defects in diamond have received much attention of late as a means to probe nanoscale magnetic environments. The sensitivity of a single NV magnetometer is primarily determined by…

Quantum Physics · Physics 2015-05-18 Liam T. Hall , Charles D. Hill , Jared H. Cole , Lloyd C. L. Hollenberg

We demonstrate the use of dynamic decoupling techniques to extend the coherence time of a single memory qubit by nearly two orders of magnitude. By extending the Hahn spin-echo technique to correct for unknown, arbitrary polynomial…

Quantum Physics · Physics 2011-02-10 David J. Szwer , Simon C. Webster , Andrew M. Steane , David M. Lucas

Dynamic network-level models directly addressing ride-sourcing services can support the development of efficient strategies for both congestion alleviation and promotion of more sustainable mobility. Recent developments presented models…

Physics and Society · Physics 2023-01-25 Caio Vitor Beojone , Nikolas Geroliminis

Dynamical decoupling protocols are one of the most used tools for efficient quantum error corrections and for reservoir engineering. In this paper we study the effect of dynamical decoupling pulses on the preservation of both quantum and…

Quantum Physics · Physics 2015-12-23 Carole Addis , Göktuğ Karpat , Sabrina Maniscalco

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

The Dynamic Mode Decomposition (DMD) extracted dynamic modes are the non-orthogonal eigenvectors of the matrix that best approximates the one-step temporal evolution of the multivariate samples. In the context of dynamical system analysis,…

Statistics Theory · Mathematics 2020-03-09 Arvind Prasadan , Raj Rao Nadakuditi

The dynamic mode decomposition (DMD) is a data-driven approach that extracts the dominant features from spatiotemporal data. In this work, we introduce sparse-mode DMD, a new variant of the optimized DMD framework that specifically…

Machine Learning · Statistics 2025-07-29 Sara M. Ichinaga , Steven L. Brunton , Aleksandr Y. Aravkin , J. Nathan Kutz
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