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Gaussian Boson Sampling is a model of photonic quantum computing where single-mode squeezed states are sent through linear-optical interferometers and measured using single-photon detectors. In this work, we employ a recent exact sampling…

Quantum Physics · Physics 2021-03-29 Brajesh Gupt , Juan Miguel Arrazola , Nicolás Quesada , Thomas R. Bromley

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

While recent advances have established efficient quantum algorithms for preparing Gibbs states of finite-dimensional systems, comparable complexity results for bosonic and other infinite-dimensional models remain unexplored. We introduce…

Quantum Physics · Physics 2026-04-08 Simon Becker , Cambyse Rouzé , Robert Salzmann

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 non-universal model for quantum computing inspired by the original formulation of the Boson Sampling problem. Nowadays, it represents a paradigmatic quantum platform to reach the quantum advantage regime in a…

Gaussian Boson Sampling (GBS) is a quantum computing concept based on drawing samples from a multimode nonclassical Gaussian state using photon-number resolving detectors. It was initially posed as a near-term approach aiming to achieve…

Quantum Physics · Physics 2022-06-22 S. Sempere-Llagostera , R. B. Patel , I. A. Walmsley , W. S. Kolthammer

The impact of a noisy Gaussian channel on a wide range of non-Gaussian input states is studied in this work. The nonclassical nature of the states, both input and output, is developed by studying the corresponding photon statistics and…

Quantum Physics · Physics 2023-08-04 Ramniwas Meena , Subhashish Banerjee

Boson Sampling is a task that is conjectured to be computationally hard for a classical computer, but which can be efficiently solved by linear-optical interferometers with Fock state inputs. Significant advances have been reported in the…

Quantum Physics · Physics 2023-04-14 Nicolò Spagnolo , Daniel J. Brod , Ernesto F. Galvão , Fabio Sciarrino

Gaussian Boson Sampling (GBS) generate random samples of photon-click patterns from a class of probability distributions that are hard for a classical computer to sample from. Despite heroic demonstrations for quantum supremacy using GBS,…

Quantum Physics · Physics 2024-02-07 Mushkan Sureka , Saikat Guha

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…

While universal quantum computers ideally solve problems such as factoring integers exponentially more efficiently than classical machines, the formidable challenges in building such devices motivate the demonstration of simpler,…

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

Boson Sampling is a computational task strongly believed to be hard for classical computers, but efficiently solvable by orchestrated bosonic interference in a specialised quantum computer. Current experimental schemes, however, are still…

Imaging thermal sources naturally yields Gaussian states at the receiver, raising the question of whether Gaussian measurements can perform optimally in quantum imaging. In this work, we establish no-go theorems on the performance of…

Quantum Physics · Physics 2025-08-15 Yunkai Wang , Sisi Zhou

One of the main advantages expected from using quantum probes as thermometers is non invasiveness, i.e., a negligible perturbation to the thermal sample. However, invasiveness is rarely investigated explicitly. Here, focusing on a…

Quantum Physics · Physics 2024-03-19 Francesco Albarelli , Matteo G. A. Paris , Bassano Vacchini , Andrea Smirne

Gaussian Boson Sampling (GBS) is a near-term platform for photonic quantum computing. Recent efforts have led to the discovery of GBS algorithms with applications to graph-based problems, point processes, and molecular vibronic spectra in…

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

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

Entangled states, like the two-mode squeezed vacuum state, are known to give quantum advantage in the illumination protocol, a method to detect a weakly reflecting target submerged in a thermal background. We use non-Gaussian photon-added…

Quantum Physics · Physics 2024-04-03 Rivu Gupta , Saptarshi Roy , Tamoghna Das , Aditi Sen De

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 2018-04-10 Bogdan Opanchuk , Laura Rosales-Zarate , Margaret D Reid , Peter D Drummond