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Designs, structures connected to averaging with respect to a given measure using finite sets of points, have proven themselves as invaluable tools across the field of quantum information, finding their uses in state and process tomography,…

Quantum Physics · Physics 2025-02-25 Jakub Czartowski , Karol Życzkowski

We study approximation of embeddings between finite dimensional L_p spaces in the quantum model of computation. For the quantum query complexity of this problem matching (up to logarithmic factors) upper and lower bounds are obtained. The…

Quantum Physics · Physics 2007-05-23 Stefan Heinrich

A fundamental question asks how uniformly finite sets of pure quantum states can be distributed in a Hilbert space. The Welch bounds address this question, and are saturated by $k$-designs, i.e. sets of states reproducing the $k$-th Haar…

Quantum Physics · Physics 2026-02-27 Riccardo Castellano , Dmitry Grinko , Sadra Boreiri , Nicolas Brunner , Jef Pauwels

We extend Stein's celebrated Wasserstein bound for normal approximation via exchangeable pairs to the multi-dimensional setting. As an intermediate step, we exploit the symmetry of exchangeable pairs to obtain an error bound for smooth test…

Probability · Mathematics 2020-09-22 Xiao Fang , Yuta Koike

This paper is concerned with minimizing a sum of rational functions over a compact set of high-dimension. Our approach relies on the second Lasserre's hierarchy (also known as the upper bounds hierarchy) formulated on the pushforward…

Optimization and Control · Mathematics 2020-12-11 Jean Bernard Lasserre , Victor Magron , Swann Marx , Olivier Zahm

We study the quantitative stability of the mapping that to a measure associates its pushforward measure by a fixed (non-smooth) optimal transport map. We exhibit a tight H\"older-behavior for this operation under minimal assumptions. Our…

Optimization and Control · Mathematics 2024-01-08 Guillaume Carlier , Alex Delalande , Quentin Mérigot

The approximation of probability measures on compact metric spaces and in particular on Riemannian manifoldsby atomic or empirical ones is a classical task in approximation and complexity theory with a wide range of applications. Instead of…

Optimization and Control · Mathematics 2021-01-12 Martin Ehler , Manuel Gräf , Sebastian Neumayer , Gabriele Steidl

We describe algorithms to obtain an approximate classical description of a $d$-dimensional quantum state when given access to a unitary (and its inverse) that prepares it. For pure states we characterize the query complexity for…

Quantum Physics · Physics 2022-07-19 Joran van Apeldoorn , Arjan Cornelissen , András Gilyén , Giacomo Nannicini

Bounds of the accuracy of the normal approximation to the distribution of a sum of independent random variables are improved under relaxed moment conditions, in particular, under the absence of moments of orders higher than the second.…

Probability · Mathematics 2015-07-06 V. Yu. Korolev , A. V. Dorofeeva

We study the optimal rectangular-discrepancy approximation of permutons by finite permutations. We transfer bounds from discrepancy theory to this more restricted setup. Moreover, we show that superlinear approximation can occur only for…

Combinatorics · Mathematics 2026-05-05 Balázs Maga

We present an approach to approximate reachable sets for linear systems with bounded L-infinity controls in finite time. Our first approach investigates the boundaries of these sets and reveals an exact characterization for single-input,…

Optimization and Control · Mathematics 2026-03-18 Steven Nguyen , Jorge Cortés , Boris Kramer

This paper is concerned with the analysis of the randomized subspace iteration for the computation of low-rank approximations. We present three different kinds of bounds. First, we derive both bounds for the canonical angles between the…

Numerical Analysis · Mathematics 2018-11-13 Arvind K. Saibaba

We propose a novel Branch-and-Bound method for reachability analysis of neural networks in both open-loop and closed-loop settings. Our idea is to first compute accurate bounds on the Lipschitz constant of the neural network in certain…

Systems and Control · Electrical Eng. & Systems 2023-04-20 Taha Entesari , Sina Sharifi , Mahyar Fazlyab

This thesis includes a survey of the results known for private and approximate private quantum channels. We develop the best known upper bound for $\epsilon$-randomizing maps, $n+2\log(1/\epsilon)+c$ bits required to $\epsilon$-randomize an…

Quantum Physics · Physics 2007-05-23 Paul Dickinson

A design is a collection of distinct points in a given set $X$, which is assumed to be a compact subset of $R^d$, and the mesh-ratio of a design is the ratio of its fill distance to its separation radius. The uniformity constant of a…

Statistics Theory · Mathematics 2021-12-21 Luc Pronzato , Anatoly Zhigljavsky

Spatial approximations have been traditionally used in spatial databases to accelerate the processing of complex geometric operations. However, approximations are typically only used in a first filtering step to determine a set of candidate…

We present and study approximate notions of dimensional and margin complexity, which correspond to the minimal dimension or norm of an embedding required to approximate, rather then exactly represent, a given hypothesis class. We show that…

Machine Learning · Computer Science 2020-03-10 Pritish Kamath , Omar Montasser , Nathan Srebro

We establish efficient approximate counting algorithms for several natural problems in local lemma regimes. In particular, we consider the probability of intersection of events and the dimension of intersection of subspaces. Our approach is…

Data Structures and Algorithms · Computer Science 2025-12-12 Ryan L. Mann , Gabriel Waite

This note establishes a theoretical framework for finding (potentially overparameterized) approximations of a function on a compact set with a-priori bounds for the generalization error. The approximation method considered is to choose,…

Systems and Control · Electrical Eng. & Systems 2026-03-23 Arthur C. B. de Oliveira , Ruigang Wang , Ian R. Manchester , Eduardo D. Sontag

We give bounds on the average fidelity achievable by any quantum state estimator, which is arguably the most prominently used figure of merit in quantum state tomography. Moreover, these bounds can be computed online---that is, while the…

Quantum Physics · Physics 2015-12-16 Richard Kueng , Christopher Ferrie
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