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The Jordan structure of finite-dimensional quantum theory is derived, in a conspicuously easy way, from a few simple postulates concerning abstract probabilistic models (each defined by a set of basic measurements and a convex set of…

Quantum Physics · Physics 2019-07-10 Alexander Wilce

We consider the Unambiguous State Discrimination (USD) of two mixed quantum states. We study the rank and the spectrum of the elements of an optimal USD measurement. This naturally leads to a partial fourth reduction theorem. This theorem…

Quantum Physics · Physics 2007-12-11 Philippe Raynal , Norbert Lütkenhaus

A natural measure in the space of density matrices describing N-dimensional quantum systems is proposed. We study the probability P that a quantum state chosen randomly with respect to the natural measure is not entangled (is separable). We…

Quantum Physics · Physics 2009-10-31 Karol Zyczkowski , Pawel Horodecki , Anna Sanpera , Maciej Lewenstein

In previously exhibited hidden variable models of quantum state preparation and measurement, the number of continuous hidden variables describing the actual state of a single realization is never smaller than the quantum state manifold…

Quantum Physics · Physics 2011-03-23 Alberto Montina

Works of Hooley and Heath-Brown imply a near-optimal bound on the number $N$ of integral solutions to $x_1^3+\dots+x_6^3 = 0$ in expanding regions, conditional on automorphy and GRH for certain Hasse--Weil $L$-functions; for regions of…

Number Theory · Mathematics 2023-04-20 Victor Y. Wang

We derive the spectral density of the equiprobable mixture of two random density matrices of a two-level quantum system. We also work out the spectral density of mixture under the so-called quantum addition rule. We use the spectral…

Quantum Physics · Physics 2018-04-20 Lin Zhang , Jiamei Wang , Zhihua Chen

Recent works at the interface of algebraic combinatorics, algebraic geometry, number theory, and topology have provided new integer-valued invariants on integer partitions. It is natural to consider the distribution of partitions when…

Number Theory · Mathematics 2022-04-19 Kathrin Bringmann , William Craig , Joshua Males , Ken Ono

The volume of the quantum mechanical state space over $n$-dimensional real, complex and quaternionic Hilbert-spaces with respect to the canonical Euclidean measure is computed, and explicit formulas are presented for the expected value of…

Mathematical Physics · Physics 2009-11-11 Attila Andai

The usual notion of separability has to be reconsidered when applied to states describing identical particles. A definition of separability not related to any a priori Hilbert space tensor product structure is needed: this can be given in…

Quantum Physics · Physics 2010-02-26 F. Benatti , R. Floreanini , U. Marzolino

We derive the relation between the Hilbert space of certain geometries under the Bohr-Sommerfeld quantization and the perturbative prepotentials for the supersymmetric five-dimensional SU(N) gauge theories with massive fundamental matters…

High Energy Physics - Theory · Physics 2008-11-26 Yui Noma

Determining the measurement uncertainty region is a difficult problem for generic sets of observables. For this reason the literature on exact measurement uncertainty regions is focused on symmetric sets of observables, where the symmetries…

Quantum Physics · Physics 2019-09-12 Oliver Reardon-Smith

Cosmological models and their parameters are widely debated, especially about whether the current discrepancy between the values of the Hubble constant, $H_{0}$, obtained by type Ia supernovae (SNe Ia), and the Planck data from the Cosmic…

Let $\mathcal{H} \subset \mathcal{H}_{n,d} := \mathbb{R}[x_1$,$\ldots$, $x_n]_d$ be a vector space, and $A$ be a compact semialgebraic subset of $\mathbb{P}_{\mathbb{R}}^{n-1}$. We shall study some PSD cones $\mathcal{P} = \mathcal{P}(A$,…

Algebraic Geometry · Mathematics 2024-08-08 Tetsuya Ando

This paper addresses the problem of approximating an unknown probability distribution with density $f$ -- which can only be evaluated up to an unknown scaling factor -- with the help of a sequential algorithm that produces at each iteration…

Statistics Theory · Mathematics 2024-09-23 Pascal Bianchi , Bernard Delyon , Victor Priser , François Portier

We study the spaces $Q_m$ of $m$-quasi-invariant polynomials of the symmetric group $S_n$ in characteristic $p$. Using the representation theory of the symmetric group we describe the Hilbert series of $Q_m$ for $n=3$, proving a conjecture…

Representation Theory · Mathematics 2022-09-30 Frank Wang

We report on experimental measurement of the Hilbert-Schmidt distance between two two-qubit states by many-particle interference. We demonstrate that our three-step method for measuring distances in Hilbert space is far less complex than…

Quantum Physics · Physics 2021-12-28 Vojtěch Trávníček , Karol Bartkiewicz , Antonín Černoch , Karel Lemr

In this paper we obtain the rates of convergence of the algorithms given in [13] and [14] for an automatic computation of the centered Hausdorff and packing measures of a totally disconnected self-similar set. We evaluate these rates…

Dynamical Systems · Mathematics 2017-04-26 Marta Llorente , M. Eugenia Mera , Manuel Moran

In this paper, we study regression problems over a separable Hilbert space with the square loss, covering non-parametric regression over a reproducing kernel Hilbert space. We investigate a class of spectral/regularized algorithms,…

Machine Learning · Statistics 2022-07-18 Junhong Lin , Alessandro Rudi , Lorenzo Rosasco , Volkan Cevher

In this project we examine several different quantum key distribution protocols which we divide into ones utilizing qubits whose Hilbert spaces are two dimensional and ones whose Hilbert space dimension is greater than two, these units of…

Quantum Physics · Physics 2024-02-05 Yuval Idan , Avihai Didi

We initiate the rigorous study of classification in semimetric spaces, which are point sets with a distance function that is non-negative and symmetric, but need not satisfy the triangle inequality. For metric spaces, the doubling dimension…

Machine Learning · Computer Science 2015-02-24 Lee-Ad Gottlieb , Aryeh Kontorovich