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The asymptotic safety scenario in quantum gravity is reviewed, according to which a renormalizable quantum theory of the gravitational field is feasible which reconciles asymptotically safe couplings with unitarity. All presently known…

General Relativity and Quantum Cosmology · Physics 2010-11-02 M. Niedermaier

The Altshuler-Shklovskii formulas [1] predict, for any disordered quantum system in the diffusive regime, a universal power law behaviour for the correlation functions of the mesoscopic eigenvalue density. In this paper and its companion…

Probability · Mathematics 2014-03-21 Laszlo Erdos , Antti Knowles

We study high-dimensional asymptotic performance limits of binary supervised classification problems where the class conditional densities are Gaussian with unknown means and covariances and the number of signal dimensions scales faster…

Machine Learning · Statistics 2016-11-17 Mohammad Hossein Rohban , Prakash Ishwar , Birant Orten , William C. Karl , Venkatesh Saligrama

One of the main concepts in quantum physics is a density matrix, which is a symmetric positive definite matrix of trace one. Finite probability distributions can be seen as a special case when the density matrix is restricted to be…

Quantum Physics · Physics 2009-01-12 Manfred K Warmuth , Dima Kuzmin

We introduce a class of paired binary matrices called admixed arrays, which arise in analyses of large-scale genetic data and can be viewed as weighted edge colorings of complete bipartite graphs. This combinatorial structure gives rise to…

Combinatorics · Mathematics 2026-04-13 Alan J. Aw

We introduce quantum Markov categories as a structure that refines and extends a synthetic approach to probability theory and information theory so that it includes quantum probability and quantum information theory. In this broader…

Quantum Physics · Physics 2020-12-29 Arthur J. Parzygnat

Estimation of quantum relative entropy and its R\'{e}nyi generalizations is a fundamental statistical task in quantum information theory, physics, and beyond. While several estimators of these divergences have been proposed in the…

Quantum Physics · Physics 2024-10-16 Sreejith Sreekumar , Mario Berta

Our capacity to process information depends on the computational power at our disposal. Information theory captures our ability to distinguish states or communicate messages when it is unconstrained with unrivaled beauty and elegance. For…

Quantum Physics · Physics 2026-04-08 Johannes Jakob Meyer , Asad Raza , Jacopo Rizzo , Lorenzo Leone , Sofiene Jerbi , Jens Eisert

The eigenvalue correlations of random matrices from the Jacobi Unitary Ensemble have a known asymptotic behavior as their size tends to infinity. In the bulk of the spectrum the behavior is described in terms of the sine kernel, and at the…

Mathematical Physics · Physics 2010-07-29 Arno Kuijlaars , Maarten Vanlessen

In a topological quantum computer, universality is achieved by braiding and quantum information is natively protected from small local errors. We address the problem of compiling single-qubit quantum operations into braid representations…

Quantum Physics · Physics 2015-06-17 Vadym Kliuchnikov , Alex Bocharov , Krysta M. Svore

In this work, we show that the sample complexity required in quantum learning theory within a general parametric framework, is fundamentally governed by the inverse Fisher information matrix. More specifically, we derive upper and lower…

Quantum Physics · Physics 2026-03-11 Hyukgun Kwon , Seok Hyung Lie , Liang Jiang

We give a quantum reduction from finding short codewords in a random linear code to decoding for the Hamming metric. This is the first time such a reduction (classical or quantum) has been obtained. Our reduction adapts to linear codes…

Cryptography and Security · Computer Science 2023-06-06 Thomas Debris-Alazard , Maxime Remaud , Jean-Pierre Tillich

We present nonasymptotic concentration inequalities for sums of independent and identically distributed random variables that yield asymptotic strong Gaussian approximations of Koml\'os, Major, and Tusn\'ady (KMT) [1975,1976]. The constants…

Probability · Mathematics 2025-10-01 Ian Waudby-Smith , Martin Larsson , Aaditya Ramdas

We establish the asymptotic theory in quantile autoregression when the model parameter is specified with respect to moderate deviations from the unit boundary of the form (1 + c / k) with a convergence sequence that diverges at a rate…

Econometrics · Economics 2023-08-22 Christis Katsouris

We study the fermionic non-Gaussianity in typical quantum states, focusing on Haar random states of qubits with or without a global $U(1)$ symmetry. Using the Weingarten calculus, we derive analytical predictions for the non-Gaussianity,…

Statistical Mechanics · Physics 2026-05-20 Filiberto Ares , Sara Murciano , Pasquale Calabrese

In this work we illustrate the resurgent structure of the $\lambda$-deformation; a two-dimensional integrable quantum field theory that has an RG flow with an $SU(N)_k$ Wess-Zumino-Witten conformal fixed point in the UV. To do so we use…

High Energy Physics - Theory · Physics 2023-05-10 Lucas Schepers , Daniel C. Thompson

We study the statistical behaviour of quantum entanglement in bipartite systems over fermionic Gaussian states as measured by von Neumann entropy. The formulas of average von Neumann entropy with and without particle number constrains have…

Mathematical Physics · Physics 2023-10-31 Youyi Huang , Lu Wei

In this article we derive a useful expectation identity using the language of quantum statistical mechanics, where density matrices represent the state of knowledge about the system. This identity allows to establish relations between…

Quantum Physics · Physics 2024-10-29 Boris Maulén , Sergio Davis , Daniel Pons

It is common to model random errors in a classical measurement by the normal (Gaussian) distribution, because of the central limit theorem. In the quantum theory, the analogous hypothesis is that the matrix elements of the error in an…

Quantum Physics · Physics 2009-11-10 S. G. Rajeev

The density weighted average derivative (DWAD) of a regression function is a canonical parameter of interest in economics. Classical first-order large sample distribution theory for kernel-based DWAD estimators relies on tuning parameter…

Econometrics · Economics 2024-02-16 Matias D. Cattaneo , Max H. Farrell , Michael Jansson , Ricardo Masini
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