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Related papers: On classical simulation algorithms for noisy Boson…

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We address the use of a single qubit as a quantum probe to characterize the properties of classical noise. In particular, we focus on the characterization of classical noise arising from the interaction with a stochastic field described by…

Quantum Physics · Physics 2015-10-07 Claudia Benedetti , Matteo G. A. Paris

Classical simulations of noisy quantum circuits are instrumental to our understanding of the behavior of real-world quantum systems and the identification of regimes where one expects quantum advantage. In this work, we present a highly…

Quantum Physics · Physics 2026-02-17 Simon Cichy , Paul K. Faehrmann , Lennart Bittel , Jens Eisert , Hakop Pashayan

We introduce an algorithm for the classical simulation of Gaussian boson sampling that is quadratically faster than previously known methods. The complexity of the algorithm is exponential in the number of photon pairs detected, not the…

Gaussian boson sampling (GBS) is a variety of boson sampling overcoming the stable single-photon preparation difficulty of the later. However, like those in the original version, noises in GBS will also result in the deviation of output…

Quantum Physics · Physics 2026-05-19 Yang Ji , Yongzheng Wu , Shi Wang , Jie Hou , Zijian Wang , Bo Jiang

BosonSampling, which we proposed three years ago, is a scheme for using linear-optical networks to solve sampling problems that appear to be intractable for a classical computer. In arXiv:1306.3995, Gogolin et al. claimed that even an ideal…

Quantum Physics · Physics 2013-10-02 Scott Aaronson , Alex Arkhipov

Experimental demonstration of the quantum advantage over classical simulations with Boson Sampling is currently under intensive investigation. There seems to be a scalability issue to the necessary number of bosons on the linear optical…

Quantum Physics · Physics 2021-09-07 Valery Shchesnovich

Gaussian boson sampling (GBS) allows for a way to demonstrate quantum supremacy with the relatively modest experimental resources of squeezed light sources, linear optics, and photon detection. In a realistic experimental setting, numerous…

Quantum Physics · Physics 2022-03-09 Junheng Shi , Tim Byrnes

Boson sampling has emerged as an important tool to demonstrate the difference between quantum and classical computers and has attracted the interest of experimentalists and theoreticians. In this work we study Boson sampling from general,…

Quantum Physics · Physics 2024-03-27 Craig S. Hamilton , Igor Jex

Gaussian boson sampling is a model of photonic quantum computing that has attracted attention as a platform for building quantum devices capable of performing tasks that are out of reach for classical devices. There is therefore significant…

Boson Sampling represents a promising approach to obtain an evidence of the supremacy of quantum systems as a resource for the solution of computational problems. The classical hardness of Boson Sampling has been related to the so called…

Quantum Physics · Physics 2016-11-09 Ludovico Latmiral , Nicolò Spagnolo , Fabio Sciarrino

It is important to know noise levels of boson sampling in order to cautiously demonstrate the quantum computational advantage or realize certain tasks. Based on those statistical benchmark methods such as the correlators and clouds, which…

Quantum Physics · Physics 2026-05-21 Yang Ji , Yongjin Ye , Qiao Wang , Shi Wang , Jie Hou , Yongzheng Wu , Zijian Wang , Bo Jiang

We study the sensitivity to noise of |permanent(X)|^2 for random real and complex n x n Gaussian matrices X, and show that asymptotically the correlation between the noisy and noiseless outcomes tends to zero when the noise level is…

Quantum Physics · Physics 2014-11-11 Gil Kalai , Guy Kindler

We consider estimation models of the form $Y=X^*+N$, where $X^*$ is some $m$-dimensional signal we wish to recover, and $N$ is symmetrically distributed noise that may be unbounded in all but a small $\alpha$ fraction of the entries. We…

Machine Learning · Computer Science 2022-11-15 Tommaso d'Orsi , Rajai Nasser , Gleb Novikov , David Steurer

Randomized experiments are the gold standard for evaluating the effects of changes to real-world systems. Data in these tests may be difficult to collect and outcomes may have high variance, resulting in potentially large measurement error.…

Machine Learning · Statistics 2018-06-27 Benjamin Letham , Brian Karrer , Guilherme Ottoni , Eytan Bakshy

Efficiently characterizing large quantum states and processes is a central yet notoriously challenging task in quantum information science, as conventional tomography methods typically require resources that grow exponentially with system…

Quantum Physics · Physics 2026-03-03 Chenyang Li , Shengxin Zhuang , Yukun Zhang , Jingbo B. Wang , Xiao Yuan , Yusen Wu , Chuan Wang

It has recently been shown that many of the existing quasi-Newton algorithms can be formulated as learning algorithms, capable of learning local models of the cost functions. Importantly, this understanding allows us to safely start…

Machine Learning · Statistics 2017-04-06 Adrian G. Wills , Thomas B. Schön

Quantum photonic processors are emerging as promising platforms to prove preliminary evidence of quantum computational advantage towards the realization of universal quantum computers. In the context of non-universal noisy intermediate…

Quantum Physics · Physics 2025-01-14 Denis Stanev , Taira Giordani , Nicolò Spagnolo , Fabio Sciarrino

A boson sampling device is a specialised quantum computer that solves a problem which is strongly believed to be computationally hard for classical computers. Recently a number of small-scale implementations have been reported, all based on…

Boson sampling is a well-defined task that is strongly believed to be intractable for classical computers, but can be efficiently solved by a specific quantum simulator. However, an outstanding problem for large-scale experimental boson…

Boson sampling is a problem intractable for classical computers, but can be naturally solved on a specialized photonic quantum simulator which requires less resources than building a universal quantum computer. The biggest challenge to…