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Related papers: Co-simulation errors due to step size changes

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Simulation techniques are providing with each passing day a deeper insight into the structure and properties of materials. Two main obstacles appear for the cooperation of simulation and experiment: on the one hand, the frequent lack of a…

Materials Science · Physics 2018-06-29 Francesca Peccati , Rubén Laplaza , Julia Contreras-García

Quantum states evolving at equidistant steps into a set of mutually orthogonal states of finite or infinite cardinality p exhibit an interesting physical effect. The analysis of the amplitudes of the state at half the step time with the…

Quantum Physics · Physics 2009-09-29 Hans-Rudolf Thomann

Optimization via simulation has been well established to find optimal solutions and designs in complex systems. However, it still faces modeling and computational challenges when extended to the multi-stage setting. This survey reviews the…

Optimization and Control · Mathematics 2023-12-08 Zhuo Zhang , Dan Wang , Haoxiang Yang , Shubin Si

Many time-dependent differential equations are equipped with invariants. Preserving such invariants under discretization can be important, e.g., to improve the qualitative and quantitative properties of numerical solutions. Recently,…

Numerical Analysis · Mathematics 2023-11-27 Sebastian Bleecke , Hendrik Ranocha

We study the impact of competing time delays in coupled stochastic synchronization and coordination problems. We consider two types of delays: transmission delays between interacting elements and processing, cognitive, or execution delays…

Statistical Mechanics · Physics 2011-01-12 D. Hunt , G. Korniss , B. K. Szymanski

Master equations are commonly used to model the dynamics of physical systems, including systems that implement single-valued functions like a computer's update step. However, many such functions cannot be implemented by any master equation,…

Statistical Mechanics · Physics 2019-04-23 David H. Wolpert , Artemy Kolchinsky , Jeremy A. Owen

We consider the Cahn-Hilliard equation with standard double-well potential. We employ a prototypical class of first order in time semi-implicit methods with implicit treatment of the linear dissipation term and explicit extrapolation of the…

Numerical Analysis · Mathematics 2021-11-12 Dong Li

Classical simulations of time-dependent quantum systems are widely used in quantum control research. In particular, these simulations are commonly used to host iterative optimal control algorithms. This is convenient for algorithms that are…

Quantum Physics · Physics 2021-11-23 Tyler Jones , Kaiah Steven , Xavier Poncini , Matthew Rose , Arkady Fedorov

Dynamical decoupling is an important tool to counter decoherence and dissipation effects in quantum systems originating from environmental interactions. It has been used successfully in many experiments; however, there is still a gap…

Quantum Physics · Physics 2014-06-25 J. Z. Bernád , H. Frydrych

In scalable machine learning systems, model training is often parallelized over multiple nodes that run without tight synchronization. Most analysis results for the related asynchronous algorithms use an upper bound on the information…

Machine Learning · Computer Science 2022-04-12 Xuyang Wu , Sindri Magnusson , Hamid Reza Feyzmahdavian , Mikael Johansson

The inevitable existence of static internal imperfections and residual interactions in some quantum computer architectures result in internal decoherence, dissipation, and destructive unitary shifts of active algorithms. By exact numerical…

Quantum Physics · Physics 2009-11-13 Murat Cetinbas , Joshua Wilkie

We propose to use the effect of measurements instead of their number to study the time evolution of quantum systems under monitoring. This time redefinition acts like a microscope which blows up the inner details of seemingly instantaneous…

Quantum Physics · Physics 2016-02-02 Michel Bauer , Denis Bernard , Antoine Tilloy

Quantum states are described by wave functions whose phases cannot be directly measured, but which play a vital role in quantum effects such as interference and entanglement. The loss of the relative phase information, termed decoherence,…

Chemical Physics · Physics 2019-12-20 Jia Chen , Cong Hu , John F. Stanton , Stephen Hill , Hai-Ping Cheng , Xiao-Guang Zhang

Certain physical aspects of quantum error correction are discussed for a quantum computer (n-qubit register) in contact with a decohering environment. Under rather plausible assumptions upon the form of the computer-environment interaction,…

Quantum Physics · Physics 2008-02-03 M. Biskup , P. Cejnar , R. Kotecky

Evolutionary synthesis models are a fundamental tool to interpret the properties of observed stellar systems. In order to achieve a meaningful comparison between models and real data, it is necessary to calibrate the models themselves, i.e.…

Parallel Monte Carlo simulations often expose faults in random number generators

Distributed, Parallel, and Cluster Computing · Computer Science 2011-04-04 Boris D. Lubachevsky

It is possible to reduce some types of quantum computation errors by symmetrizing the quantum state of a redundant array. Various models are discussed.

Quantum Physics · Physics 2007-05-23 Asher Peres

An operational measure to quantify the sizes of some ``macroscopic quantum superpositions'', realized in recent experiments, is proposed. The measure is based on the fact that a superposition presents greater sensitivity in interferometric…

Quantum Physics · Physics 2009-11-10 Gunnar Björk , Piero G. Luca Mana

Measurement-based quantum computing is an alternative paradigm to the circuit-based model. This approach can be advantageous in certain scenarios, such as when read-out is fast and accurate, but two-qubit gates realized via inter-particle…

Quantum Physics · Physics 2021-11-16 Zhangjie Qin , Woo-Ram Lee , Brian DeMarco , Bryce Gadway , Svetlana Kotochigova , V. W. Scarola

An interpolation error is an integral of the squared error of a regression model over a domain of interest. We consider the interpolation error for the case of misspecified Gaussian process regression: used covariance function differs from…

Statistics Theory · Mathematics 2018-03-28 A. Zaytsev , E. Romanenkova , D. Ermilov