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Using and extending fractional order statistic theory, we characterize the $O(n^{-1})$ coverage probability error of the previously proposed confidence intervals for population quantiles using $L$-statistics as endpoints in Hutson (1999).…

Statistics Theory · Mathematics 2018-02-28 Matt Goldman , David M. Kaplan

In this paper we present two semi-implicit-type second order Compact Approximate Taylor (CAT2) numerical schemes and blend them with a local a posteriori Multi-dimensional Optimal Order Detection (MOOD) paradigm to solve hyperbolic systems…

Numerical Analysis · Mathematics 2023-09-26 E. Macca , S. Boscarino

In this note we develop a prelimit analysis of performance measures for importance sampling schemes related to small noise diffusion processes. In importance sampling the performance of any change of measure is characterized by its second…

Probability · Mathematics 2014-07-30 Konstantinos Spiliopoulos

We derived an asymptotic bound the accuracy of the estimation when we use the quantum correlation in the measuring apparatus. It is also proved that this bound can be achieved in any model in the quantum two-level system. Moreover, we show…

Quantum Physics · Physics 2007-05-23 Masahito Hayashi , Keiji Matsumoto

Quantum computation has been growing rapidly in both theory and experiments. In particular, quantum computing devices with a large number of qubits have been developed by IBM, Google, IonQ, and others. The current quantum computing devices…

Quantum Physics · Physics 2021-02-10 Rishabh Gupta , Rongxin Xia , Raphael D. Levine , Sabre Kais

The need to perform quantum state tomography on ever larger systems has spurred a search for methods that yield good estimates from incomplete data. We study the performance of compressed sensing (CS) and least squares (LS) estimators in a…

Quantum Physics · Physics 2013-03-15 A. Smith , C. A. Riofrío , B. E. Anderson , H. Sosa-Martinez , I. H. Deutsch , P. S. Jessen

We consider an extension of the conditional min- and max-entropies to infinite-dimensional separable Hilbert spaces. We show that these satisfy characterizing properties known from the finite-dimensional case, and retain…

Quantum Physics · Physics 2011-09-20 Fabian Furrer , Johan Aberg , Renato Renner

There are no universally accepted definitions of R\'enyi conditional entropy and R\'enyi mutual information, although motivated by different applications, several definitions have been proposed in the literature. In this paper, we consider…

Information Theory · Computer Science 2025-11-05 Shi-Bing Li , Ke Li , Lei Yu

Well-controlled quantum devices with their increasing system size face a new roadblock hindering further development of quantum technologies: The effort of quantum tomography---the characterization of processes and states within a quantum…

Quantum Physics · Physics 2017-05-26 C. A. Riofrio , D. Gross , S. T. Flammia , T. Monz , D. Nigg , R. Blatt , J. Eisert

Bosonic two-mode squeezed states are paradigmatic entangled Gaussian states that have wide utility in quantum information and metrology. Here, we show that the basic structure of these states can be generalized to arbitrary bipartite…

Quantum Physics · Physics 2025-02-27 Mikhail Mamaev , Martin Koppenhöfer , Andrew Pocklington , Aashish A. Clerk

During a spontaneous change, a macroscopic physical system will evolve towards a macro-state with more realizations. This observation is at the basis of the Statistical Mechanical version of the Second Law of Thermodynamics, and it provides…

Statistical Mechanics · Physics 2020-04-22 Mengjie Zu , Arunkumar Bupathy , Daan Frenkel , Srikanth Sastry

The study of conditional $q$-entropies in composite quantum systems has recently been the focus of considerable interest, particularly in connection with the problem of separability. The $q$-entropies depend on the density matrix $\rho$…

Quantum Physics · Physics 2009-11-10 J. Batle , A. R. Plastino , M. Casas , A. Plastino

Asymptotic expansions are presented for the moments of bound states in one-dimensional anharmonic potentials. The results are derived by using the SAFE method and include only the first non-zero wave-related correction to the familiar…

Quantum Physics · Physics 2023-05-31 G. W. Forbes , Miguel A. Alonso

Smoothing is a technique that estimates the state of a system using measurement information both prior and posterior to the estimation time. Two notable examples of this technique are the Rauch-Tung-Striebel and Mayne-Fraser-Potter…

Quantum Physics · Physics 2021-09-24 Kiarn T. Laverick

We refine a recently-proposed class of local entropic loss functions by restricting the smoothening regularization to only a subset of weights. The new loss functions are referred to as partial local entropies. They can adapt to the…

Machine Learning · Computer Science 2021-04-14 Daniele Musso

We develop an asymptotic theory of estimation of a shift parameter in a pure quantum state to study the relation between entangled and unentangled covariant estimates in the analytically most transparent way. After recollecting basics of…

Quantum Physics · Physics 2011-11-09 A. S. Holevo

The minimum error probability for distinguishing between two quantum states is bounded by the Helstrom limit, derived under the assumption that measurement strategies are restricted to positive operator-valued measurements. We explore…

Quantum Physics · Physics 2026-01-28 Swati Choudhary , Aparajita Bhattacharyya , Ujjwal Sen

Continuous-variable codes are an expedient solution for quantum information processing and quantum communication involving optical networks. Here we characterize the squeezed comb, a finite superposition of equidistant squeezed coherent…

Quantum Physics · Physics 2021-01-15 Namrata Shukla , Stefan Nimmrichter , Barry C. Sanders

The uncertainty principle is a fundamental principle in quantum physics. It implies that the measurement outcomes of two incompatible observables can not be predicted simultaneously. In quantum information theory, this principle can be…

Quantum Physics · Physics 2016-06-24 F. Adabi , S. Salimi , S. Haseli

We design an algorithm which finds an $\epsilon$-approximate stationary point (with $\|\nabla F(x)\|\le \epsilon$) using $O(\epsilon^{-3})$ stochastic gradient and Hessian-vector products, matching guarantees that were previously available…

Machine Learning · Computer Science 2020-06-25 Yossi Arjevani , Yair Carmon , John C. Duchi , Dylan J. Foster , Ayush Sekhari , Karthik Sridharan