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Related papers: Sampling of bosonic qubits

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It is predicted that quantum computers will dramatically outperform their conventional counterparts. However, large-scale universal quantum computers are yet to be built. Boson sampling is a rudimentary quantum algorithm tailored to the…

Integrated quantum photonics has emerged as one of the leading platforms for scaling quantum information processing, offering compact, stable, and low-loss hardware with precise phase and mode control. Advances in integrated photonics…

Gaussian boson sampling is a promising scheme for demonstrating a quantum computational advantage using photonic states that are accessible in a laboratory and, thus, offer scalable sources of quantum light. In this contribution, we study…

Quantum Physics · Physics 2019-02-22 D. S. Phillips , M. Walschaers , J. J. Renema , I. A. Walmsley , N. Treps , J. Sperling

It is known that, by accounting for the multiboson interferences up to a finite order, the output distribution of noisy Boson Sampling, with distinguishability of bosons serving as noise, can be approximately sampled from in a time…

Quantum Physics · Physics 2023-07-12 Valery Shchesnovich

For near-term quantum devices, an important challenge is to develop efficient methods to certify that noise levels are low enough to allow potentially useful applications to be carried out. We present such a method tailored to photonic…

Quantum Physics · Physics 2022-02-11 Rawad Mezher , Shane Mansfield

Quantum computation, aiming at tackling hard problems beyond classical approaches, has been flourishing with each passing day. Unfortunately, a fully scalable and fault-tolerant universal quantum computer remains challenging based on the…

The search for new, application-specific quantum computers designed to outperform any classical computer is driven by the ending of Moore's law and the quantum advantages potentially obtainable. Photonic networks are promising examples,…

Quantum Physics · Physics 2018-04-13 B. Opanchuk , L. Rosales-Zárate , M. D. Reid , P. D. Drummond

Machine learning is widely applied in modern society, but has yet to capitalise on the unique benefits offered by quantum resources. Boson sampling -- a quantum-interference based sampling protocol -- is a resource that is classically hard…

It has been proven that Boson sampling is a much promising model of optical quantum computation, which has been applied to designing quantum computer successfully, such as "Jiuzhang". However, the meaningful randomness of Boson sampling…

Quantum Physics · Physics 2022-06-07 Jinjing Shi , Tongge Zhao , Yizhi Wang , Chunlin Yu , Yuhu Lu , Ronghua Shi , Shichao Zhang , Junjie Wu

We introduce a novel approach to solve optimization problems on a boson sampling device assisted by classical machine-learning techniques. By virtue of the parity function, we map all measurement patterns, which label the basis spanning an…

Quantum Physics · Physics 2021-12-21 Kamil Bradler , Hugo Wallner

We provide general sufficient conditions for the efficient classical simulation of quantum-optics experiments that involve inputting states to a quantum process and making measurements at the output. The first condition is based on the…

Quantum Physics · Physics 2016-06-23 Saleh Rahimi-Keshari , Timothy C. Ralph , Carlton M. Caves

To simulate noisy boson sampling approximating it by only the lower-order multi-boson interferences (e.g., by a smaller number of interfering bosons and classical particles) is very popular idea. I show that the output data from any such…

Quantum Physics · Physics 2022-04-19 Valery Shchesnovich

We study supervised learning algorithms in which a quantum device is used to perform a computational subroutine - either for prediction via probability estimation, or to compute a kernel via estimation of quantum states overlap. We design…

Quantum Physics · Physics 2021-07-07 Ulysse Chabaud , Damian Markham , Adel Sohbi

We demonstrate how boson sampling with photons of partial distinguishability can be expressed in terms of interference of fewer photons. We use this observation to propose a classical algorithm to simulate the output of a boson sampler fed…

Scattershot photon sources are known to have useful properties for optical quantum computing and boson sampling purposes, in particular for scaling to large numbers of photons. This paper investigates the application of these scattershot…

Quantum Physics · Physics 2021-09-22 Joshua J. Guanzon , Austin P. Lund , Timothy C. Ralph

It is known that quantum correlations exhibited by a maximally entangled qubit pair can be simulated with the help of shared randomness, supplemented with additional resources, such as communication, post-selection or non-local boxes. For…

Quantum Physics · Physics 2009-11-11 Julien Degorre , Sophie Laplante , Jérémie Roland

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

Verification of a quantum advantage in the presence of noise is a key open problem in the study of near-term quantum devices. In this work, we show how to assess the quality of photonic interference in a linear optical quantum device (boson…

Quantum Physics · Physics 2021-03-03 Jelmer J. Renema , Hui Wang , Jian Qin , Xiang You , Chaoyang Lu , Jianwei Pan

Boson is one of the most basic types of particles and preserves the commutation relation. An efficient way to measure a bosonic system is important not only for simulating complex physics phenomena of bosons (such as nuclei) on a qubit…

Quantum Physics · Physics 2023-07-28 Tianren Gu , Xiao Yuan , Bujiao Wu

We develop an alternative boson sampling model operating on single-photon states followed by linear interferometry and Gaussian measurements. The hardness proof for simulating such continuous-variable measurements is established in two main…

Quantum Physics · Physics 2017-09-19 Levon Chakhmakhchyan , Nicolas J. Cerf