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Related papers: Non-linear Boson Sampling

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A novel family of Cosine series Quantum Sampling (QCoSamp) operators appropriate for quantum computing is described. The development of quantum algorithms, analogous to classical algorithms, we apply to the harmonic analysis of signals. We…

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

Determination of the quantum nature of correlations between two spatially separated systems plays a crucial role in quantum information science. Of particular interest is the questions of if and how these correlations enable quantum…

Quantum Physics · Physics 2017-09-27 Farid Shahandeh , Austin P. Lund , Timothy C. Ralph

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

We introduce a connection between a near-term quantum computing device, specifically a Gaussian boson sampler, and the graph isomorphism problem. We propose a scheme where graphs are encoded into quantum states of light, whose properties…

Quantum Physics · Physics 2021-04-08 Kamil Bradler , Shmuel Friedland , Josh Izaac , Nathan Killoran , Daiqin Su

Simulating out-of-equilibrium dynamics of quantum field theories in nature is challenging with classical methods, but is a promising application for quantum computers. Unfortunately, simulating interacting bosonic fields involves a high…

Incorporating nonlinearity into quantum machine learning is essential for learning a complicated input-output mapping. We here propose quantum algorithms for nonlinear regression, where nonlinearity is introduced with feature maps when…

Quantum Physics · Physics 2018-08-30 Dan-Bo Zhang , Shi-Liang Zhu , Z. D. Wang

Boson sampling (BS) is a multimode linear optical problem that is expected to be intractable on classical computers. It was recently suggested that molecular vibronic spectroscopy (MVS) is computationally as complex as BS. In this review,…

Quantum Physics · Physics 2018-09-19 Seungbeom Chin , Joonsuk Huh

Quantum non-Gaussian states of photons and phonons are conclusive and direct witnesses of higher-than-quadratic nonlinearities in optical and mechanical processes. Moreover, they are proven resources for quantum sensing, communication and…

Quantum Physics · Physics 2025-03-14 Lukáš Lachman , Radim Filip

Nonlinear processes with individual quanta beyond bilinear interactions are essential for quantum technology with bosonic systems. Diverse coherent splitting and merging of quanta in them already manifest in the estimation of their…

Quantum Physics · Physics 2025-04-25 Payman Mahmoudi , Atirach Ritboon , Radim Filip

We introduce a new method for representing the low energy subspace of a bosonic field theory on the qubit space of digital quantum computers. This discretization leads to an exponentially precise description of the subspace of the…

Quantum Physics · Physics 2018-10-17 Alexandru Macridin , Panagiotis Spentzouris , James Amundson , Roni Harnik

Quantum computers solve intractable problems which classically require an exponentially long time to compute. With the development of large-scale experiments that claim quantum advantage, a vital issue has now emerged. What are the errors,…

Quantum Physics · Physics 2026-04-15 Ned Goodman , Alexander S. Dellios , Margaret D. Reid , Peter D. Drummond

Linear optics quantum computing (LOQC) is a promising approach to implementing scalable quantum computation (QC). However, this approach has very demanding physical resource requirements. Recently, Aaronson & Arkhipov showed that a…

Quantum Physics · Physics 2015-06-03 Peter P. Rohde , Timothy C. Ralph

Gaussian boson sampling (GBS) is a promising candidate for an experimental demonstration of quantum advantage using photons. However, sufficiently large noise might hinder a GBS implementation from entering the regime where quantum speedup…

Quantum Physics · Physics 2024-01-24 Gabriele Bressanini , Hyukjoon Kwon , M. S. Kim

Quantum computers have long been expected to efficiently solve complex classical differential equations. Most digital, fault-tolerant approaches use Carleman linearization to map nonlinear systems to linear ones and then apply quantum…

The determination of the computational complexity of the boson sampling problem with single boson sources has opened a novel research direction in the quantum computing field. Some research effort has also been devoted towards the use of…

Quantum Physics · Physics 2015-06-11 Vincenzo Tamma , Simon Laibacher

Demonstrating quantum superiority for some computational task will be a milestone for quantum technologies and would show that computational advantages are possible not only with a universal quantum computer but with simpler physical…

Quantum Physics · Physics 2018-11-06 Juan Miguel Arrazola , Eleni Diamanti , Iordanis Kerenidis

Boson-Sampling holds the potential to experimentally falsify the Extended Church Turing thesis. The computational hardness of Boson-Sampling, however, complicates the certification that an experimental device yields correct results in the…

Quantum Physics · Physics 2014-07-14 Malte C. Tichy , Klaus Mayer , Andreas Buchleitner , Klaus Mølmer

Non-classical interference of photons lies at the heart of optical quantum information processing. This effect is exploited in universal quantum gates as well as in purpose-built quantum computers that solve the BosonSampling problem.…

We present a variation of a quantum algorithm for the machine learning task of classification with graph-structured data. The algorithm implements a feature extraction strategy that is based on Gaussian boson sampling (GBS) a near term…

Quantum Physics · Physics 2026-05-13 Amanuel Anteneh , Olivier Pfister
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