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Related papers: Bures Metrics for Certain High-Dimensional Quantum…

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We study a quantum analogue of the 2-Wasserstein distance as a measure of proximity on the set $\Omega_N$ of density matrices of dimension $N$. We show that such (semi-)distances do not induce Riemannian metrics on the tangent bundle of…

Quantum Physics · Physics 2023-03-01 Rafał Bistroń , Michał Eckstein , Karol Życzkowski

This work studies the entropic regularization formulation of the 2-Wasserstein distance on an infinite-dimensional Hilbert space, in particular for the Gaussian setting. We first present the Minimum Mutual Information property, namely the…

Machine Learning · Statistics 2022-03-15 Minh Ha Quang

Extensive numerical integration results lead us to conjecture that the silver mean, that is, s = \sqrt{2}-1 = .414214 plays a fundamental role in certain geometries (those given by monotone metrics) imposable on the 15-dimensional convex…

Quantum Physics · Physics 2009-11-10 Paul B. Slater

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

Given some observable H of a finite-dimensional quantum system, we investigate the typical properties of random quantum state vectors that have a fixed expectation value with respect to H. Under some some conditions on the spectrum, we…

Quantum Physics · Physics 2011-05-03 Markus Mueller , David Gross , Jens Eisert

Hilbert-Schmidt distance is one of the prominent distance measures in quantum information theory which finds applications in diverse problems, such as construction of entanglement witnesses, quantum algorithms in machine learning, and…

Quantum Physics · Physics 2020-08-13 Santosh Kumar

We consider an ensemble of random density matrices distributed according to the Bures measure. The corresponding joint probability density of eigenvalues is described by the fixed trace Bures-Hall ensemble of random matrices which, in turn,…

Mathematical Physics · Physics 2019-07-12 Ayana Sarkar , Santosh Kumar

In this brief note, it is shown that the Bures-Wasserstein (BW) metric on the space positive definite matrices lends itself to convex optimization. In other words, the computation of the BW metric can be posed as a convex optimization…

Optimization and Control · Mathematics 2023-03-08 Shravan Mohan

We find equivalent hypergeometric- and difference-equation-based formulas, $Q(k,\alpha)= G_1^k(\alpha) G_2^k(\alpha)$, for $k = -1, 0, 1,\ldots,9$, for that (rational-valued) portion of the total separability probability for generalized…

Quantum Physics · Physics 2015-04-20 Paul B. Slater

In three spatial dimensions, in the unitary limit of a non-relativistic quantum Bose or Fermi gas, the scattering length diverges. This occurs at a renormalization group fixed point, thus these systems present interesting examples of…

Quantum Gases · Physics 2011-02-16 Pye-Ton How , Andre LeClair

Strongly lensed quasar systems with time delay measurements provide "time delay distances", which are a combination of three angular diameter distances and serve as powerful tools to determine the Hubble constant $H_0$. However, current…

Cosmology and Nongalactic Astrophysics · Physics 2019-12-18 Kai Liao , Arman Shafieloo , Ryan E. Keeley , Eric V. Linder

Many Gibbs measures with mean field interactions are known to be chaotic, in the sense that any collection of $k$ particles in the $n$-particle system are asymptotically independent, as $n\to\infty$ with $k$ fixed or perhaps $k=o(n)$. This…

Probability · Mathematics 2021-05-10 Daniel Lacker

The coarse similarity class $[A]$ of $A$ is the set of all $B$ whose symmetric difference with $A$ has asymptotic density 0. There is a natural metric $\delta$ on the space $\mathcal{S}$ of coarse similarity classes defined by letting…

Logic · Mathematics 2021-06-25 Denis R. Hirschfeldt , Carl G. Jockusch, , Paul E. Schupp

The variational determination of the two-boson reduced density matrix is described for a one-dimensional system of $N$ (where $N$ ranges from $2$ to $10^4$) harmonically trapped bosons interacting via contact interaction. The ground-state…

Quantum Gases · Physics 2026-04-27 Mitchell J. Knight , Harry M. Quiney , Andy M. Martin

The density matrix of a two-level system (spin, atom) is usually determined by measuring the three non-commuting components of the Pauli vector. This density matrix can also be obtained via the measurement data of two commuting variables,…

Quantum Physics · Physics 2012-05-25 B. Mehmani , A. E. Allahverdyan , Th. M. Nieuwenhuizen

Separability and entanglement for n-qubits systems are quantified by using Hilbert-Schmidt (HS) decompositions in which the density matrices are decomposed into various terms representing certain one qubit, two-qubits,and larger qubits…

Quantum Physics · Physics 2016-02-23 Y. Ben-Aryeh

The tomographic reconstruction of the state of a quantum-mechanical system is an essential component in the development of quantum technologies. We present an overview of different tomographic methods for determining the quantum-mechanical…

Quantum Physics · Physics 2016-02-09 Roman Schmied

In this paper, we study metrics of quantum states. These metrics are natural generalization of trace metric and Bures metric. We will prove that the metrics are joint convex and contractive under quantum operation. Our results can find…

Quantum Physics · Physics 2009-02-01 Zhi-Hao Ma , Fu-Lin Zhang , Jing-Ling Chen

In a previous study (quant-ph/0207181), we formulated a conjecture that arbitrarily coupled qubits (describable by 4 x 4 density matrices) are separable with an a priori probability of 8/(11 \pi^2) = 0.0736881. For this purpose, we employed…

Quantum Physics · Physics 2007-05-23 Paul B. Slater

Embedding complex objects as vectors in low dimensional spaces is a longstanding problem in machine learning. We propose in this work an extension of that approach, which consists in embedding objects as elliptical probability…

Machine Learning · Statistics 2019-02-19 Boris Muzellec , Marco Cuturi
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