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Entanglement and entanglement-assisted are useful resources to enhance the mutual information of the Pauli channels, when the noise on consecutive uses of the channel has some partial correlations. In this paper, We study quantum…

Quantum Physics · Physics 2007-05-23 A. Fahmi

Noise sources unavoidably affect any quantum technological device. Noise's main features are expected to strictly depend on the physical platform on which the quantum device is realized, in the form of a distinguishable fingerprint. Noise…

Quantum Physics · Physics 2022-04-04 Stefano Martina , Lorenzo Buffoni , Stefano Gherardini , Filippo Caruso

Quantum error correction protects quantum information against environmental noise. When using qubits, a measure of quality of a code is the maximum number of errors that it is able to correct. We show that a suitable notion of ``number of…

Quantum Physics · Physics 2007-05-23 Emanuel Knill , Raymond Laflamme , Lorenza Viola

Imaging, detection and ranging of objects in the presence of significant background noise is a fundamental challenge in optical sensing. Overcoming the limitations imposed in conventional methods, quantum light sources show higher…

Quantum Physics · Physics 2022-10-11 Hashir Kuniyil , Helin Ozel , Hasan Yılmaz , Kadir Durak

We investigate all possible noise environments for controlled remote state preparation. We find that the optimal efficiency is not only dependent on the isolate decay rate but also dependent on the coupling term of environments. Such a…

Quantum Physics · Physics 2016-04-06 Yuan-hua Li , Zisheng Wang , Hua-qing Zhou , Xian-feng Chen

In this paper we consider adversarial noise models that will fail quantum error correction and fault-tolerant quantum computation. We describe known results regarding high-rate noise, sequential computation, and reversible noisy…

Quantum Physics · Physics 2009-04-22 Gil Kalai

Due to omnipresent environmental interferences, quantum coherences inevitably undergo irreversible transformations over certain time-scales, thus leading to the loss of encoded information. This process, known as decoherence, has been a…

Quantum Physics · Physics 2014-06-19 Swathi S. Hegde , T. S. Mahesh

Excess noise is a major obstacle to high-performance continuous-variable quantum key distribution (CVQKD), which is mainly derived from the amplitude attenuation and phase fluctuation of quantum signals caused by channel instability. Here,…

Quantum Physics · Physics 2022-07-22 Kexin Liang , Geng Chai , Zhengwen Cao , Qing Wang , Lei Wang , Jinye Peng

Quantum noise is known to strongly affect quantum computation, thus potentially limiting the performance of currently available quantum processing units. Even learning models based on variational quantum algorithms, which were designed to…

Quantum Physics · Physics 2026-02-04 Francesco Scala , Giacomo Guarnieri , Aurelien Lucchi

We propose and discuss two postulates on the nature of errors in highly correlated noisy physical stochastic systems. The first postulate asserts that errors for a pair of substantially correlated elements are themselves substantially…

Quantum Physics · Physics 2007-05-23 Gil Kalai

Previous studies in quantum information have recognized that specific types of noise can encode information in certain applications. However, the role of noise in Quantum Hypothesis Testing (QHT), traditionally assumed to undermine…

Quantum Physics · Physics 2024-08-06 Qing Li , Lingna Wang , Min Jiang , Ze Wu , Haidong Yuan , Xinhua Peng

Under ideal conditions, quantum metrology promises a precision gain over classical techniques scaling quadratically with the number of probe particles. At the same time, no-go results have shown that generic, uncorrelated noise limits the…

Quantum Physics · Physics 2017-07-13 J. B. Brask , R. Chaves , J. Kolodynski

Manually labeled corpora are expensive to create and often not available for low-resource languages or domains. Automatic labeling approaches are an alternative way to obtain labeled data in a quicker and cheaper way. However, these labels…

Machine Learning · Computer Science 2018-07-24 Michael A. Hedderich , Dietrich Klakow

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

Noise in entangled quantum systems is difficult to characterize due to many-body effects involving multiple degrees of freedom. This noise poses a challenge to quantum computing, where two-qubit gate performance is critical. Here, we…

Applications of the quantum switch on quantum channels have recently become a topic of intense discussion. In the present work, we show that some useless (for communication) channels may provide useful communication under the action of…

Quantum Physics · Physics 2023-04-11 Arindam Mitra , Himanshu Badhani , Sibasish Ghosh

Using a dissipative quantum neural network (DQNN) accompanied by conjugate layers, we upgrade the performance of the existing quantum auto-encoder (QAE) network as a quantum denoiser of a noisy m-qubit GHZ state. Our new denoising…

Quantum Physics · Physics 2023-11-20 Armin Ahmadkhaniha , Marzieh Bathaee

Learning unknown processes affecting a quantum system reveals underlying physical mechanisms and enables suppression, mitigation, and correction of unwanted effects. Describing a general quantum process requires an exponentially large…

Demonstrating quantum advantage with less powerful but more realistic devices is of great importance in modern quantum information science. Recently, a significant quantum speedup was achieved in the problem of learning a hidden parity…

Quantum Physics · Physics 2018-03-28 Daniel K. Park , June-Koo K. Rhee , Soonchil Lee

The sound of crashing waves, the roar of fast-moving cars -- sound conveys important information about the objects in our surroundings. In this work, we show that ambient sounds can be used as a supervisory signal for learning visual…

Computer Vision and Pattern Recognition · Computer Science 2016-12-06 Andrew Owens , Jiajun Wu , Josh H. McDermott , William T. Freeman , Antonio Torralba