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We define several quantitative measures of the robustness of a quantum gate against noise. Exact analytic expressions for the robustness against depolarizing noise are obtained for all unitary quantum gates, and it is found that the…

Quantum Physics · Physics 2009-11-10 Aram W. Harrow , Michael A. Nielsen

In this paper, we show how to use low-fidelity operations to control the dynamics of quantum systems. Noisy operations usually drive a system to evolve into a mixed state and damage the coherence. Sometimes frequent noisy operations result…

Quantum Physics · Physics 2015-06-12 Ying Li

With the advent of physical qubits exhibiting strong noise bias, it becomes increasingly relevant to identify which quantum gates can be efficiently implemented on error-correcting codes designed to address a single dominant error type.…

Quantum Physics · Physics 2025-07-09 Victor Barizien , Hugo Jacinto , Nicolas Sangouard

Understanding what can be learned from experiments is central to scientific progress. In this work, we use a learning-theoretic perspective to study the task of learning physical operations in a quantum machine when all operations (state…

Quantum Physics · Physics 2022-04-29 Hsin-Yuan Huang , Steven T. Flammia , John Preskill

Measurement based quantum computation (MBQC) is an effective paradigm for universal quantum computation. In this scheme, the universal set of quantum gates are realized by only local measurements on the prior prepared cluster states. The…

Quantum Physics · Physics 2013-11-26 Ding Zhong , Jian Wang , Ning Dai , Liang-Zhu Mu , Heng Fan

We discuss the speed-error-heat triangle and related problems with rapidly increasing energy dissipation and error rate during miniaturization. These and the independently growing need of unconditional data security have provoked…

General Physics · Physics 2008-08-20 Laszlo B. Kish

Reliability analysis aims at estimating the failure probability of an engineering system. It often requires multiple runs of a limit-state function, which usually relies on computationally intensive simulations. Traditionally, these…

Computation · Statistics 2024-01-22 Anderson V. Pires , Maliki Moustapha , Stefano Marelli , Bruno Sudret

Analyzing the impact of noise is of fundamental importance to understand the advantages provided by quantum systems. While the classical simulability of noisy discrete-variable systems is increasingly well understood, noisy bosonic circuits…

Quantum Physics · Physics 2026-01-12 Varun Upreti , Ulysse Chabaud , Zoë Holmes , Armando Angrisani

A major problem in exploiting microscopic systems for developing a new technology based on the principles of Quantum Information is the influence of noise which tends to work against the quantum features of such systems. It becomes then…

Quantum Physics · Physics 2009-11-13 Angelo Bassi , D. -A. Deckert

This chapter considers the computational and statistical aspects of learning linear thresholds in presence of noise. When there is no noise, several algorithms exist that efficiently learn near-optimal linear thresholds using a small amount…

Machine Learning · Computer Science 2020-11-16 Maria-Florina Balcan , Nika Haghtalab

As fault-tolerant quantum computers scale, certifying the accuracy of computations performed with encoded logical qubits will soon become classically intractable. This creates a critical need for scalable, device-independent certification…

Quantum Physics · Physics 2025-10-08 James Mills , Adithya Sireesh , Dominik Leichtle , Joschka Roffe , Elham Kashefi

We report an experimental evaluation of the "input-output surface" for a biochemical AND gate. The obtained data are modeled within the rate-equation approach, with the aim to map out the gate function and cast it in the language of logic…

Molecular Networks · Quantitative Biology 2010-10-12 V. Privman , G. Strack , D. Solenov , M. Pita , E. Katz

Utilizing the hyperspace of noise-based logic, we show two string verification methods with low communication complexity. One of them is based on continuum noise-based logic. The other one utilizes noise-based logic with random telegraph…

Information Theory · Computer Science 2011-02-10 Laszlo B. Kish , Sunil Khatri , Tamas Horvath

Once upon a time, predictions for the accuracy of inference on gravitational-wave signals relied on computationally inexpensive but often inaccurate techniques. Recently, the approach has shifted to actual inference on noisy signals with…

Instrumentation and Methods for Astrophysics · Physics 2015-12-09 Carl-Johan Haster , Ilya Mandel , Will M. Farr

The possibility of a new type of computing, where thermal noise is the information carrier and the clock in a computer, is studied. The information channel capacity and the lower limit of energy requirement/dissipation are studied in a…

General Physics · Physics 2007-05-23 Laszlo B. Kish

In recent years, a considerable research effort has shown the energy benefits of implementing neural networks with memristors or other emerging memory technologies. However, for extreme-edge applications with high uncertainty, access to…

In this paper, a general circuit scheme for noise-tolerant logic design based on Markov Random Field theory and differential Cascade Voltage Switch technique has been proposed, which is an extension of the work in [1-3], [4]. A block with…

Hardware Architecture · Computer Science 2015-03-10 Xinghua Yang , Fei Qiao , Qi Wei , Huazhong Yang

Nanomechanical systems have been proposed as an alternative computing platform for high radiation environments, where semiconductor electronics traditionally fail, as well as to allow improved gate densities and energy consumption. While…

Applied Physics · Physics 2022-12-07 T. Jin , C. G. Baker , E. Romero , N. P. Mauranyapin , T. M. F. Hirsch , W. P. Bowen , G. I. Harris

Likelihood functions evaluated using particle filters are typically noisy, computationally expensive, and non-differentiable due to Monte Carlo variability. These characteristics make conventional optimization methods difficult to apply…

Methodology · Statistics 2026-01-13 Genshiro Kitagawa

This paper presents a robust data-driven controller design based on the noisy input-output data without assumptions on the statistical properties of the noises. We start with the direct data-representation of system models that take…

Optimization and Control · Mathematics 2023-02-24 Chin-Yao Chang , Andrey Bernstein
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