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Standard approaches to quantum statistical inference rely on measurements that induce a collapse of the wave function, effectively consuming the quantum state to extract information. In this work, we investigate the fundamental limits of…

Quantum Physics · Physics 2026-02-20 Cristina Butucea , Jan Johannes , Henning Stein

Currently most progresses on quantum secret sharing suffer from rate-distance bound, and thus the key rates are limited. In addition to the limited key rate, the technical difficulty and the corresponding cost together prevent large-scale…

Quantum Physics · Physics 2023-10-09 Chen-Long Li , Yao Fu , Wen-Bo Liu , Yuan-Mei Xie , Bing-Hong Li , Min-Gang Zhou , Hua-Lei Yin , Zeng-Bing Chen

We study quantum differential privacy (QDP) by defining a notion of the order of informativeness between pairs of quantum states. In particular, we show that if the hypothesis testing divergence of one pair dominates over that of the other…

Quantum Physics · Physics 2026-02-04 Naqueeb Ahmad Warsi , Ayanava Dasgupta , Masahito Hayashi

This paper investigates the soft covering lemma under both the relative entropy and the total variation distance as the measures of deviation. The exact order of the expected deviation of the random i.i.d. code for the soft covering problem…

Information Theory · Computer Science 2019-02-22 Mohammad Hossein Yassaee

Quantum state and process tomography are typically analyzed under the assumption that devices emit independent and identically distributed (i.i.d.) states or channels. In realistic experiments, however, noise, drift, feedback, or…

Quantum Physics · Physics 2026-02-26 Leonardo Zambrano

We investigate quantum state discrimination with confidentiality. $N$ observers share a given quantum state belonging to a finite set of known states. The observers want to determine the state as accurately as possible and send a…

Quantum Physics · Physics 2015-06-30 Kenji Nakahira , Tsuyoshi Sasaki Usuda , Kentaro Kato

We give an operational meaning to the min-entropy of a quantum state as a resource measure for various interconnected tasks. In particular, we show that the min-entropy without smoothing measures the amount of quantum information that can…

Quantum Physics · Physics 2021-04-28 Seok Hyung Lie , Seongjeon Choi , Hyunseok Jeong

We show new lower bounds on the sample complexity of $(\varepsilon, \delta)$-differentially private algorithms that accurately answer large sets of counting queries. A counting query on a database $D \in (\{0,1\}^d)^n$ has the form "What…

Cryptography and Security · Computer Science 2018-10-25 Mark Bun , Jonathan Ullman , Salil Vadhan

The problem of determining the best achievable performance of arbitrary lossless compression algorithms is examined, when correlated side information is available at both the encoder and decoder. For arbitrary source-side information pairs,…

Information Theory · Computer Science 2020-07-15 Lampros Gavalakis , Ioannis Kontoyiannis

We revisit Wald's celebrated Sequential Probability Ratio Test for sequential tests of two simple hypotheses, under privacy constraints. We propose DP-SPRT, a wrapper that can be calibrated to achieve desired error probabilities and privacy…

Machine Learning · Statistics 2026-02-05 Thomas Michel , Debabrota Basu , Emilie Kaufmann

Finding the minimal relative entropy of two quantum states under semidefinite constraints is a pivotal problem located at the mathematical core of various applications in quantum information theory. An efficient method for providing…

Quantum Physics · Physics 2026-02-02 Gereon Koßmann , René Schwonnek

Differential privacy comes equipped with multiple analytical tools for the design of private data analyses. One important tool is the so-called "privacy amplification by subsampling" principle, which ensures that a differentially private…

Machine Learning · Computer Science 2018-11-26 Borja Balle , Gilles Barthe , Marco Gaboardi

In the approximate quantiles problem, the goal is to output $m$ quantile estimates, the ranks of which are as close as possible to $m$ given quantiles $0 \leq q_1 \leq\dots \leq q_m \leq 1$. We present a mechanism for approximate quantiles…

Data Structures and Algorithms · Computer Science 2025-12-15 Jacob Imola , Fabrizio Boninsegna , Hannah Keller , Anders Aamand , Amrita Roy Chowdhury , Rasmus Pagh

We prove an achievability result for privacy amplification and decoupling in terms of the sandwiched R\'enyi entropy of order $\alpha \in (1,2]$; this extends previous results which worked for $\alpha=2$. The fact that this proof works for…

Quantum Physics · Physics 2022-01-11 Frédéric Dupuis

The fidelity-based smooth min-relative entropy is a distinguishability measure that has appeared in a variety of contexts in prior work on quantum information, including resource theories like thermodynamics and coherence. Here we provide a…

Quantum Physics · Physics 2024-05-29 Theshani Nuradha , Mark M. Wilde

The rates of quantum cryptographic protocols are usually expressed in terms of a conditional entropy minimized over a certain set of quantum states. In particular, in the device-independent setting, the minimization is over all the quantum…

Quantum Physics · Physics 2022-10-05 Peter Brown , Hamza Fawzi , Omar Fawzi

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

As often emerges in various basic quantum properties such as R\'enyi and Tsallis entropies, the trace of quantum state powers $\text{tr}(\rho^q)$ has attracted a lot of attention. The recent work of Liu and Wang (SODA 2025) showed that,…

Quantum Physics · Physics 2026-04-03 Kean Chen , Yupan Liu , Qisheng Wang

We consider the privacy amplification properties of a sampling scheme in which a user's data is used in k steps chosen randomly and uniformly from a sequence (or set) of t steps. This sampling scheme has been recently applied in the context…

Machine Learning · Computer Science 2026-01-16 Vitaly Feldman , Moshe Shenfeld