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Boson Sampling represents a promising witness 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 Permanent-of-Gaussians…

Quantum Physics · Physics 2015-12-01 Ludovico Latmiral

The quantum walk was originally proposed as a quantum mechanical analogue of the classical random walk, and has since become a powerful tool in quantum information science. In this paper, we show that discrete time quantum walks provide a…

Mesoscale and Nanoscale Physics · Physics 2010-09-30 Takuya Kitagawa , Mark S. Rudner , Erez Berg , Eugene Demler

Modelling of photonic devices traditionally involves solving the equations of light-matter interaction and light propagation, and it is restrained by their applicability. Here we demonstrate an alternative modelling methodology by creating…

Quantum Physics · Physics 2024-11-21 Anton N. Vetlugin , Cesare Soci , Nikolay I. Zheludev

Quantum sensing encompasses highly promising techniques with diverse applications including noise-reduced imaging, super-resolution microscopy as well as imaging and spectroscopy in challenging spectral ranges. These detection schemes use…

Quantum Physics · Physics 2022-11-23 Felix Riexinger , Mirco Kutas , Björn Haase , Michael Bortz , Georg von Freymann

Boson sampling is one of the leading protocols for demonstrating a quantum advantage, but the theory of how this protocol responds to noise is still incomplete. We extend the theory of classical simulation of boson sampling with partial…

Quantum Physics · Physics 2025-03-07 S. N. van den Hoven , E. Kanis , J. J. Renema

Quantum sensing exploits quantum phenomena to enhance the detection and estimation of classical parameters of physical systems and biological entities, particularly so as to overcome the inefficiencies of its classical counterparts. A…

Quantum random walks use interference to obtain faster state space exploration, which can be used for algorithmic purposes. Photonic technologies provide a natural platform for many recent experimental demonstrations. Here we analyze…

Quantum Physics · Physics 2022-03-04 Ricardo M. R. Adão , Manuel Caño-García , Jana B. Nieder , Ernesto F. Galvão

BosonSampling is a restricted model of quantum computation proposed recently, where a non-adaptive linear-optical network is used to solve a sampling problem that seems to be hard for classical computers. Here we show that, even if the…

Quantum Physics · Physics 2015-04-22 Daniel J. Brod

Photon losses are among the strongest imperfections affecting multi-photon interference. Despite their importance, little is known about their effect on boson sampling experiments. In this work we show that using classical computers, one…

Quantum Physics · Physics 2019-08-07 Raúl García-Patrón , Jelmer J. Renema , Valery Shchesnovich

Although the Schr{\"o}dinger and Heisenberg pictures are equivalent formulations of quantum mechanics, simulations performed choosing one over the other can greatly impact the computational resources required to solve a problem. Here we…

Quantum Physics · Physics 2024-02-27 Dario Cilluffo , Nicola Lorenzoni , Martin B. Plenio

The quantum walk is the quantum analogue of the well-known random walk, which forms the basis for models and applications in many realms of science. Its properties are markedly different from the classical counterpart and might lead to…

In recent years, there has been heightened interest in quantum teleportation, which allows for the transfer of unknown quantum states over arbitrary distances. Quantum teleportation not only serves as an essential ingredient in…

Multiple bosons undergoing coherent evolution in a coupled network of sites constitute a so-called quantum walk system. The simplest example of such a two-particle interference is the celebrated Hong-Ou-Mandel interference. When scaling to…

Quantum Physics · Physics 2017-01-25 Samuel Goldstein , Simcha Korenblit , Ydan Bendor , Hao You , Michael R. Geller , Nadav Katz

In this work, we give a hybrid quantum-classical algorithm for solving electronic structure problems of molecules using only linear quantum optical systems. The variational ansatz we proposed is a hybrid of non-interacting Boson dynamics…

Recently developed quantum algorithms suggest that quantum computers can solve certain problems and perform certain tasks more efficiently than conventional computers. Among other reasons, this is due to the possibility of creating…

Quantum Physics · Physics 2007-05-23 Rolando D. Somma

Quantum simulation in its current state faces experimental overhead in terms of physical space and cooling. We propose boson sampling as an alternative compact synthetic platform performing at room temperature. Identifying the capability of…

Quantum Physics · Physics 2025-04-03 Anuprita V. Kulkarni , Vatsana Tiwari , Auditya Sharma , Ankur Raina

Scientists in quantum technology aspire to quantum advantage: a computational result unattainable with classical computers. Gaussian boson sampling experiment has been already claimed to achieve this goal. In this setup squeezed light…

Quantum Physics · Physics 2022-07-08 A. S. Popova , A. N. Rubtsov

Photons have been a flagship system for studying quantum mechanics, advancing quantum information science, and developing quantum technologies. Quantum entanglement, teleportation, quantum key distribution and early quantum computing…

Quantum Physics · Physics 2019-12-12 Sergei Slussarenko , Geoff J. Pryde

Enhancing optical nonlinearities so that they become appreciable on the single photon level and lead to nonclassical light fields has been a central objective in quantum optics for many years. After this has been achieved in individual…

Quantum Physics · Physics 2016-09-20 Michael J. Hartmann

Gaussian boson sampling is a promising candidate for showing experimental quantum advantage. While there is evidence that noiseless Gaussian boson sampling is hard to efficiently simulate using a classical computer, the current Gaussian…

Quantum Physics · Physics 2024-09-24 Changhun Oh , Minzhao Liu , Yuri Alexeev , Bill Fefferman , Liang Jiang
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