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We derive a formal connection between quantum data hiding and quantum privacy, confirming the intuition behind the construction of bound entangled states from which secret bits can be extracted. We present three main results. First, we show…

Quantum Physics · Physics 2018-02-21 Matthias Christandl , Roberto Ferrara

In order to be practically useful, quantum cryptography must not only provide a guarantee of secrecy, but it must provide this guarantee with a useful, sufficiently large throughput value. The standard result of generalized privacy…

Quantum Physics · Physics 2007-05-23 G. Gilbert , M. Hamrick , F. J. Thayer

Quantum communication relies on the existence of high quality quantum channels to exchange information. In practice, however, all communication links are affected by noise from the environment. Here we investigate the ability of quantum…

Quantum Physics · Physics 2025-08-12 Vishal Singh , Mark M. Wilde

Modern deep learning techniques focus on extracting intricate information from data to achieve accurate predictions. However, the training datasets may be crowdsourced and include sensitive information, such as personal contact details,…

Machine Learning · Statistics 2026-02-10 Zhongjie Shi , Puyu Wang , Chenyang Zhang , Yuan Cao

One of the remarkable features of quantum mechanics is the ability to ensure secrecy. Private states embody this effect, as they are precisely those multipartite quantum states from which two parties can produce a shared secret that cannot…

Quantum Physics · Physics 2008-10-20 Joseph M. Renes , Jean-Christian Boileau

Quantum state discrimination is an important problem in many information processing tasks. In this work we are concerned with finding its best possible sample complexity when the states are preprocessed by a quantum channel that is required…

Quantum Physics · Physics 2024-06-28 Hao-Chung Cheng , Christoph Hirche , Cambyse Rouzé

Differential privacy is a mathematical notion of data privacy that has fast become the de facto standard in privacy-preserving data analysis. Recently a lot of work has focused on differential privacy in the quantum setting. Continuing on…

Quantum Physics · Physics 2026-04-14 Arghya Mukherjee , Hassan Jameel Asghar , Gavin K. Brennen

This paper introduces coherent quantum channel discrimination as a coherent version of conventional quantum channel discrimination. Coherent channel discrimination is phrased here as a quantum interactive proof system between a verifier and…

Quantum Physics · Physics 2020-09-15 Mark M. Wilde

Differential privacy (DP) provides rigorous privacy guarantees on individual's data while also allowing for accurate statistics to be conducted on the overall, sensitive dataset. To design a private system, first private algorithms must be…

Cryptography and Security · Computer Science 2020-11-19 Mark Cesar , Ryan Rogers

The problem of discriminating between many quantum channels with certainty is analyzed under the assumption of prior knowledge of algebraic relations among possible channels. It is shown, by explicit construction of a novel family of…

Quantum Physics · Physics 2021-08-04 Zane M. Rossi , Isaac L. Chuang

The broadcast channel (BC) with one common and two private messages with leakage constraints is studied, where leakage rate refers to the normalized mutual information between a message and a channel symbol string. Each private message is…

Information Theory · Computer Science 2017-05-30 Ziv Goldfeld , Gerhard Kramer , Haim H. Permuter

There are two main factors limiting the performance of quantum key distribution --- channel transmission loss and noise. Previously, a linear bound was believed to put an upper limit on the rate-transmittance performance. Remarkably, the…

Quantum Physics · Physics 2020-07-01 Pei Zeng , Weijie Wu , Xiongfeng Ma

While it is usually known that the mean value of a single observable is enough to detect entanglement or its distillability, the counterpart of such an approach in the case of quatum privacy has been missing. Here we develop the concept of…

Quantum Physics · Physics 2013-05-30 Konrad Banaszek , Karol Horodecki , Paweł Horodecki

The quantum capacity of a noisy quantum channel determines the maximal rate at which we can code reliably over asymptotically many uses of the channel, and it characterizes the channel's ultimate ability to transmit quantum information…

Quantum Physics · Physics 2021-10-26 Xin Wang

We show a new lower bound on the sample complexity of $(\varepsilon, \delta)$-differentially private algorithms that accurately answer statistical queries on high-dimensional databases. The novelty of our bound is that it depends optimally…

Data Structures and Algorithms · Computer Science 2015-01-27 Thomas Steinke , Jonathan Ullman

Quantum privacy amplification is a central task in quantum cryptography. Given shared randomness, which is initially correlated with a quantum system held by an eavesdropper, the goal is to extract uniform randomness which is decoupled from…

Quantum Physics · Physics 2022-02-23 Robert Salzmann , Nilanjana Datta

Differential privacy is a mathematical concept that provides an information-theoretic security guarantee. While differential privacy has emerged as a de facto standard for guaranteeing privacy in data sharing, the known mechanisms to…

Cryptography and Security · Computer Science 2024-03-26 March Boedihardjo , Thomas Strohmer , Roman Vershynin

We study simple binary hypothesis testing under both local differential privacy (LDP) and communication constraints. We qualify our results as either minimax optimal or instance optimal: the former hold for the set of distribution pairs…

Statistics Theory · Mathematics 2023-12-19 Ankit Pensia , Amir R. Asadi , Varun Jog , Po-Ling Loh

Distinguishability is fundamental to information theory and extends naturally to quantum systems. While quantum state discrimination is well understood, quantum channel discrimination remains challenging due to the dynamic nature of…

Quantum Physics · Physics 2025-07-15 Kun Fang , Gilad Gour , Xin Wang

Data processing inequalities for $f$-divergences can be sharpened using constants called "contraction coefficients" to produce strong data processing inequalities. For any discrete source-channel pair, the contraction coefficients for…

Information Theory · Computer Science 2018-07-17 Anuran Makur , Lizhong Zheng