
Stochastic models are highly relevant tools in science, engineering, and society. Recent work suggests emerging quantum computing technologies can substantially decrease the memory requirements for simulating stochastic models.
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A device called a `Gaussian Boson Sampler’ has initially been proposed as a nearterm demonstration of classically intractable quantum computation. As recently shown, it can also be used to decide whether two graphs are isomorphic.
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As a promising candidate for exhibiting quantum computational supremacy, Gaussian boson sampling (GBS) is designed to exploit the ease of experimental preparation of Gaussian states. In this work, we establish sufficient conditions for efficient approximate simulation of GBS under the effect of errors such as photon losses and dark counts.
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We study the practical performance of quantuminspired algorithms for recommendation systems and linear systems of equations. These algorithms were shown to have an exponential asymptotic speedup…
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We consider conditional photonic nonGaussian state preparation using multimode Gaussian states and photonnumberresolving detectors in the presence of photon loss. While simulation of such state preparation is often computationally challenging, we show that obtaining the required multimode Gaussian state Fock matrix
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We report the first demonstrations of both quadrature squeezed vacuum and photon number difference squeezing generated in an integrated nanophotonic device. Squeezed light is generated via strongly driven spontaneous fourwave mixing below threshold in silicon nitride microring resonators.
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We introduce a quantum approximate optimization algorithm (QAOA) for continuous optimization. The algorithm is based on the dynamics of a quantum system moving in an energy potential which encodes the objective function. By approximating the dynamics at finite time steps, the algorithm can be expressed as alternating evolution under…
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Molecular Docking with Gaussian Boson Sampling
February 2019
Gaussian Boson Samplers are photonic quantum devices with the potential to perform tasks that are intractable for classical systems. As with other nearterm quantum technologies, an outstanding challenge is to identify specific problems of practical interest where these quantum devices can prove useful.
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Nonlinear coupling of linearly uncoupled resonators
January 2019
We demonstrate a system composed of two resonators that are coupled solely through a nonlinear interaction, and where the linear properties of each resonator can be controlled locally.
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We present a hybrid linearoptical architecture that simultaneously exploits spatial and temporal degrees of freedom of light to effect arbitrary discrete unitary transformations.
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Linear multiport photonic interferometers: loss analysis of temporallyencoded architectures
December 2018
Implementing spatiallyencoded universal linear multiport interferometers on integrated photonic platforms with high controllability becomes increasingly difficult as the number of modes increases.
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Evaluating analytic gradients on quantum hardware
November 2018
An important application for nearterm quantum computing lies in optimization tasks, with applications ranging from quantum chemistry and drug discovery to machine learning.
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