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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

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 (DD) is a powerful method for controlling arbitrary open quantum systems. In quantum spin control, DD generally involves a sequence of timed spin flips ($\pi$ rotations) arranged to average out or selectively enhance…

Dynamic Mode Decomposition (DMD) is a data-driven technique to identify a low dimensional linear time invariant dynamics underlying high-dimensional data. For systems in which such underlying low-dimensional dynamics is time-varying, a…

Signal Processing · Electrical Eng. & Systems 2020-04-09 Mustaffa Alfatlawi , Vaibhav Srivastava

Dynamical decoupling (DD) is an active and effective method for suppressing decoherence of a quantum system from its environment. In contrast to the nominal biaxial DD,this work presents a uniaxial decoupling protocol that requires a…

Quantum Physics · Physics 2019-01-15 Qi Yao , Jun Zhang , Xiao-feng Yi , Li You , Wenxian Zhang

We demonstrate a simple pulse shaping technique designed to improve the fidelity of spin-dependent force operations commonly used to implement entangling gates in trapped-ion systems. This extension of the M{\o}lmer-S{\o}rensen gate can…

Quantum Physics · Physics 2013-05-30 D. Hayes , S. M. Clark , S. Debnath , D. Hucul , I. V. Inlek , K. W. Lee , Q. Quraishi , C. Monroe

We study how dynamical decoupling (DD) pulse sequences can improve the reliability of quantum computers. We prove upper bounds on the accuracy of DD-protected quantum gates and derive sufficient conditions for DD-protected gates to…

Quantum Physics · Physics 2011-07-19 Hui Khoon Ng , Daniel A. Lidar , John Preskill

We model repetitive quantum error correction (QEC) with the single-error-correcting five-qubit code on a network of individually-controlled qubits with always-on Ising couplings, using our previously designed universal set of quantum gates…

Quantum Physics · Physics 2016-04-27 Amrit De , Leonid P. Pryadko

Quantum error correcting (QEC) stabilizer codes enable protection of quantum information against errors during storage and processing. Simulation of noisy QEC codes is used to identify the noise parameters necessary for advantageous…

Quantum Physics · Physics 2025-03-17 Sascha Heußen , Don Winter , Manuel Rispler , Markus Müller

Dynamical error suppression techniques are commonly used to improve coherence in quantum systems. They reduce dephasing errors by applying control pulses designed to reverse erroneous coherent evolution driven by environmental noise.…

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

Dynamic Mode Decomposition (DMD) is a model-order reduction approach, whereby spatial modes of fixed temporal frequencies are extracted from numerical or experimental data sets. The DMD low-rank or reduced operator is typically obtained by…

Numerical Analysis · Mathematics 2023-01-25 Quincy A. Huhn , Mauricio E. Tano , Jean C. Ragusa , Youngsoo Choi

Dropout is a technique that silences the activity of units stochastically while training deep networks to reduce overfitting. Here we introduce Quantal Synaptic Dilution (QSD), a biologically plausible model of dropout regularisation based…

Machine Learning · Computer Science 2020-09-29 Gardave S Bhumbra

Aperiodic dynamical decoupling (DD) sequences of $\pi$ pulses are of great interest to decoherence control and have been recently extended from single-qubit to two-qubit systems. If the environmental noise power spectrum is made available,…

Quantum Physics · Physics 2011-10-25 Yu Pan , Zai-Rong Xi , Jiangbin Gong

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

The dynamic mode decomposition (DMD) has become a leading tool for data-driven modeling of dynamical systems, providing a regression framework for fitting linear dynamical models to time-series measurement data. We present a simple…

Numerical Analysis · Mathematics 2017-04-11 Travis Askham , J. Nathan Kutz

Dynamic mode decomposition (DMD) is a recently developed tool for the analysis of the behavior of complex dynamical systems. In this paper, we will propose an extension of DMD that exploits low-rank tensor decompositions of potentially…

Numerical Analysis · Mathematics 2019-08-14 Stefan Klus , Patrick Gelß , Sebastian Peitz , Christof Schütte

Quantum coherence remains a fundamental challenge for advancing quantum technologies. Although dynamical decoupling can suppress decoherence noise, it frequently misestimates decoherence times due to control errors -- a previously…

Quantum Physics · Physics 2026-02-17 Weibin Ni , Zhijie Li , Guanyu Qu , Asif Equbal , Zhecheng Sun , Jiale Dai , Fazhan Shi , Lei Sun

Dynamical decoupling (DD) is an efficient tool for preserving quantum coherence in solid-state spin systems. However, the imperfections of real pulses can ruin the performance of long DD sequences. We investigate the accumulation and…

We propose a new method for computing Dynamic Mode Decomposition (DMD) evolution matrices, which we use to analyze dynamical systems. Unlike the majority of existing methods, our approach is based on a variational formulation consisting of…

Numerical Analysis · Mathematics 2019-05-24 Omri Azencot , Wotao Yin , Andrea Bertozzi