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Related papers: Bitwise Quantum Min-Entropy Sampling and New Lower…

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Quantum approximate optimization algorithm (QAOA) aims to solve discrete optimization problems by sampling bitstrings using a parameterized quantum circuit. The circuit parameters (angles) are optimized in the way that minimizes the cost…

Quantum Physics · Physics 2023-11-29 A. Yu. Chernyavskiy , B. I. Bantysh , Yu. I. Bogdanov

Given a collection of probability distributions $p_{1},\ldots,p_{m}$, the minimum entropy coupling is the coupling $X_{1},\ldots,X_{m}$ ($X_{i}\sim p_{i}$) with the smallest entropy $H(X_{1},\ldots,X_{m})$. While this problem is known to be…

Information Theory · Computer Science 2021-09-21 Cheuk Ting Li

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 new framework is introduced for examining and evaluating the fundamental limits of lossless data compression, that emphasizes genuinely non-asymptotic results. The {\em sample complexity} of compressing a given source is defined as the…

Information Theory · Computer Science 2026-04-16 Terence Viaud , Ioannis Kontoyiannis

Many of the traditional results in information theory, such as the channel coding theorem or the source coding theorem, are restricted to scenarios where the underlying resources are independent and identically distributed (i.i.d.) over a…

Quantum Physics · Physics 2009-06-28 Nilanjana Datta , Renato Renner

We study quantum soft covering and privacy amplification against quantum side information. The former task aims to approximate a quantum state by sampling from a prior distribution and querying a quantum channel. The latter task aims to…

Quantum Physics · Physics 2022-02-24 Yu-Chen Shen , Li Gao , Hao-Chung Cheng

Generalizing the bounded kernel results of Borgs, Chayes, Lov\'asz, S\'os and Vesztergombi (2008), we prove two Sampling Lemmas for unbounded kernels with respect to the cut norm. On the one hand, we show that given a (symmetric) kernel…

Probability · Mathematics 2024-11-12 Panna Tímea Fekete , Dávid Kunszenti-Kovács

The extraction of randomness from weakly random seeds is a problem of central importance with multiple applications. In the device-independent setting, this problem of quantum randomness amplification has been mainly restricted to specific…

Quantum Physics · Physics 2023-04-20 Ravishankar Ramanathan

We develop a quantum version of the probability estimation framework [arXiv:1709.06159] for randomness generation with quantum side information. We show that most of the properties of probability estimation hold for quantum probability…

Quantum Physics · Physics 2023-02-06 Emanuel Knill , Yanbao Zhang , Honghao Fu

We derive a family of optimal protocols, in the sense of saturating the quantum Cram\'{e}r-Rao bound, for measuring a linear combination of $d$ field amplitudes with quantum sensor networks, a key subprotocol of general quantum sensor…

Quantum Physics · Physics 2023-10-03 Adam Ehrenberg , Jacob Bringewatt , Alexey V. Gorshkov

In this note, we revisit the recursive random contraction algorithm of Karger and Stein for finding a minimum cut in a graph. Our revisit is occasioned by a paper of Fox, Panigrahi, and Zhang which gives an extension of the Karger-Stein…

Data Structures and Algorithms · Computer Science 2020-10-30 David R. Karger , David P. Williamson

We show that the moment generating function of the Kullback-Leibler divergence (relative entropy) between the empirical distribution of $n$ independent samples from a distribution $P$ over a finite alphabet of size $k$ (i.e. a multinomial…

Information Theory · Computer Science 2020-10-06 Rohit Agrawal

We formulate the notion of minimax estimation under storage or communication constraints, and prove an extension to Pinsker's theorem for nonparametric estimation over Sobolev ellipsoids. Placing limits on the number of bits used to encode…

Statistics Theory · Mathematics 2017-04-13 Yuancheng Zhu , John Lafferty

We construct an optimal quantum universal variable-length code that achieves the admissible minimum rate, i.e., our code is used for any probability distribution of quantum states. Its probability of exceeding the admissible minimum rate…

Quantum Physics · Physics 2009-11-07 Masahito Hayashi , Keiji Matsumoto

Many quantum information measures can be written as an optimization of the quantum relative entropy between sets of states. For example, the relative entropy of entanglement of a state is the minimum relative entropy to the set of separable…

Quantum Physics · Physics 2018-08-09 Hamza Fawzi , Omar Fawzi

We consider the task of deriving a key with high HILL entropy from an unpredictable source. Previous to this work, the only known way to transform unpredictability into a key that was $\eps$ indistinguishable from having min-entropy was via…

Cryptography and Security · Computer Science 2015-04-29 Maciej Skorski , Alexander Golovnev , Krzysztof Pietrzak

We study the approximability of instances of the minimum entropy set cover problem, parameterized by the average frequency of a random element in the covering sets. We analyze an algorithm combining a greedy approach with another one biased…

Data Structures and Algorithms · Computer Science 2012-08-01 Cosmin Bonchis , Gabriel Istrate

We relate the the distinguishability of quantum states with their robustness of the entanglement, where the robustness of any resource quantifies how tolerant it is to noise. In particular, we identify upper and lower bounds on the…

Quantum Physics · Physics 2025-12-24 Debarupa Saha , Kornikar Sen , Chirag Srivastava , Ujjwal Sen

In this paper we give improved constructions of several central objects in the literature of randomness extraction and tamper-resilient cryptography. Our main results are: (1) An explicit seeded non-malleable extractor with error $\epsilon$…

Computational Complexity · Computer Science 2016-08-02 Xin Li

We study randomized algorithms for constrained optimization, in abstract frameworks that include, in strictly increasing generality: convex programming; LP-type problems; violator spaces; and a setting we introduce, consistent spaces. Such…

Computational Geometry · Computer Science 2019-06-04 Kenneth L. Clarkson , Bernd Gärtner , Johannes Lengler , May Szedlak