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We analyze the optimal state, as given by Berry and Wiseman [Phys. Rev. Lett {\bf 85}, 5098, (2000)], under the canonical phase measurement in the presence of photon loss. The model of photon loss is a generic fictitious beam splitter, and…

Quantum Physics · Physics 2009-01-07 Aravind Chiruvelli , Hwang Lee

Measurement incompatibility is a distinguishing property of quantum physics and an essential resource for many quantum information processing tasks. We introduce an approach to verify the joint measurability of measurements based on…

We present a general framework for hypothesis testing on distributions of sets of individual examples. Sets may represent many common data sources such as groups of observations in time series, collections of words in text or a batch of…

Methodology · Statistics 2021-02-03 Alexis Bellot , Mihaela van der Schaar

We study how useful random states are for quantum metrology, i.e., surpass the classical limits imposed on precision in the canonical phase estimation scenario. First, we prove that random pure states drawn from the Hilbert space of…

Given additional distributional information in the form of moment restrictions, kernel density and distribution function estimators with implied generalised empirical likelihood probabilities as weights achieve a reduction in variance due…

Methodology · Statistics 2019-10-08 Vitaliy Oryshchenko , Richard J. Smith

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

How can one fully harness the power of physics encoded in relativistic $N$-body phase space? Topologically, phase space is isomorphic to the product space of a simplex and a hypersphere and can be equipped with explicit coordinates and a…

High Energy Physics - Phenomenology · Physics 2024-08-26 Tianji Cai , Junyi Cheng , Nathaniel Craig , Giacomo Koszegi , Andrew J. Larkoski

In this paper we will turn our attention to the problem of obtaining phase-space probability density functions. We will show that it is possible to obtain functions which assume only positive values over all its domain of definition.

Quantum Physics · Physics 2007-05-23 L. S. F. Olavo

We characterize the asymptotic performance of nonparametric goodness of fit testing. The exponential decay rate of the type-II error probability is used as the asymptotic performance metric, and a test is optimal if it achieves the maximum…

Machine Learning · Statistics 2019-03-19 Shengyu Zhu , Biao Chen , Pengfei Yang , Zhitang Chen

Two commonly arising computational tasks in Bayesian learning are Optimization (Maximum A Posteriori estimation) and Sampling (from the posterior distribution). In the convex case these two problems are efficiently reducible to each other.…

Machine Learning · Computer Science 2019-11-07 Kunal Talwar

Change-point detection has garnered significant attention due to its broad range of applications, including epidemic disease outbreaks, social network evolution, image analysis, and wireless communications. In an online setting, where new…

Machine Learning · Statistics 2024-08-26 Zihan Wang

Fractional statistical moments are utilized for various tasks of uncertainty quantification, including the estimation of probability distributions. However, an estimation of fractional statistical moments of costly mathematical models by…

Methodology · Statistics 2024-03-05 Lukáš Novák , Marcos Valdebenito , Matthias Faes

We obtain a positive probability distribution or Q-function for an arbitrary fermionic many-body system. This is different to previous Q-function proposals, which were either restricted to a subspace of the overall Hilbert space, or used…

Quantum Physics · Physics 2015-03-27 Laura E. C. Rosales-Zarate , P. D. Drummond

We extend the wide-sense spatial stationarity concept of coherence holography in the regime of phase-space using the wigner distribution function. We focus mainly on the incoherent light source and the Fourier and Fresnel propagation…

Optics · Physics 2021-02-10 Rishabh Kumar Bhalavi , Rakesh Kumar Singh

BosonSampling is an intermediate model of quantum computation where linear-optical networks are used to solve sampling problems expected to be hard for classical computers. Since these devices are not expected to be universal for quantum…

Quantum Physics · Physics 2016-01-27 Scott Aaronson , Daniel J. Brod

Models of physics beyond the Standard Model often contain a large number of parameters. These form a high-dimensional space that is computationally intractable to fully explore. Experimental constraints project onto a subspace of viable…

High Energy Physics - Theory · Physics 2022-01-05 Jacob Hollingsworth , Michael Ratz , Philip Tanedo , Daniel Whiteson

Measuring the spectral phase of a pulse is key for performing wavelength resolved ultrafast measurements in the few femtosecond regime. However, accurate measurements in real experimental conditions can be challenging. We show that the…

We give a new framework for proving the existence of low-degree, polynomial approximators for Boolean functions with respect to broad classes of non-product distributions. Our proofs use techniques related to the classical moment problem…

Computational Complexity · Computer Science 2013-01-07 Adam Klivans , Raghu Meka

In quantum optics, nonclassicality of quantum states is commonly associated with negativities of phase-space quasiprobability distributions. We argue that the impossibility of any classical simulations with phase-space functions is a…

Quantum Physics · Physics 2022-01-03 A. A. Semenov , A. B. Klimov

Many developing quantum technologies make use of quantum networks of different types. Even linear quantum networks are nontrivial, as the output photon distributions can be exponentially complex. Despite this, they can still be…

Quantum Physics · Physics 2022-03-02 A. Dellios , Peter D. Drummond , Bogdan Opanchuk , Run Yan Teh , Margaret D. Reid
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