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The surface code, one of the leading candidates for quantum error correction, is known to protect encoded quantum information against stochastic, i.e., incoherent errors. The protection against coherent errors, such as from unwanted gate…

Quantum Physics · Physics 2025-10-28 Jan Behrends , Benjamin Béri

We investigate definitions of and protocols for multi-party quantum computing in the scenario where the secret data are quantum systems. We work in the quantum information-theoretic model, where no assumptions are made on the computational…

Quantum Physics · Physics 2007-05-23 Adam Smith

Data compression is a ubiquitous aspect of modern information technology, and the advent of quantum information raises the question of what types of compression are feasible for quantum data, where it is especially relevant given the…

Quantum Physics · Physics 2014-12-17 Lee A. Rozema , Dylan H. Mahler , Alex Hayat , Peter S. Turner , Aephraim M. Steinberg

Bipartite quantum interactions have applications in a number of different areas of quantum physics, reaching from fundamental areas such as quantum thermodynamics and the theory of quantum measurements to other applications such as quantum…

Quantum Physics · Physics 2018-12-21 Stefan Bäuml , Siddhartha Das , Mark M. Wilde

The operational meaning of coherence measure lies at very heart of the coherence theory. In this paper, we provide an operational interpretation for geometric coherence, by proving that the geometric coherence of a quantum state is equal to…

Quantum Physics · Physics 2018-09-26 Chunhe Xiong , Junde Wu

Distributed quantum sensing enables the estimation of multiple parameters encoded in spatially separated probes. While traditional quantum sensing is often focused on estimating a single parameter with maximum precision, distributed quantum…

Quantum Physics · Physics 2025-01-27 Luís Bugalho , Majid Hassani , Yasser Omar , Damian Markham

We study an optimum measurement for quantum state discrimination, which maximizes the probability of correct results when the probability of inconclusive results is fixed at a given value. The measurement describes minimum-error…

Quantum Physics · Physics 2012-09-26 Ulrike Herzog

We study exact local compression of a quantum bipartite state; that is, applying local quantum operations to reduce the dimensions of the Hilbert spaces while perfectly preserving the correlation. We provide a closed-form expression for the…

Quantum Physics · Physics 2025-05-08 Kohtaro Kato

In the number partitioning problem (NPP) one aims to partition a given set of $N$ real numbers into two subsets with approximately equal sum. The NPP is a well-studied optimization problem and is famous for possessing a…

Statistics Theory · Mathematics 2025-05-28 Rushil Mallarapu , Mark Sellke

With the advance of quantum information technology, the question of how to most efficiently test quantum circuits is becoming of increasing relevance. Here we introduce the statistics of lengths of measurement sequences that allows one to…

Quantum Physics · Physics 2022-10-27 N. Milazzo , D. Braun , O. Giraud

Statistical data depth plays an important role in the analysis of multivariate data sets. The main outcome is a center-outward ordering of the observations that can be used both to highlight features of the underlying distribution of the…

Statistics Theory · Mathematics 2026-03-11 Giacomo Francisci , Claudio Agostinelli

A pure state of fixed Hamming weight is a superposition of computational basis states such that each bitstring in the superposition has the same number of ones. Given a Hilbert space of the form $\mathcal{H} = (\mathbb{C}_2)^{\otimes n}$,…

Quantum Physics · Physics 2025-01-22 Soorya Rethinasamy , Margarite L. LaBorde , Mark M. Wilde

We consider a high-dimensional mean estimation problem over a binary hidden Markov model, which illuminates the interplay between memory in data, sample size, dimension, and signal strength in statistical inference. In this model, an…

Statistics Theory · Mathematics 2022-10-13 Yihan Zhang , Nir Weinberger

We study the canonical statistical task of computing the principal component from $n$ i.i.d.~data in $d$ dimensions under $(\varepsilon,\delta)$-differential privacy. Although extensively studied in literature, existing solutions fall short…

Machine Learning · Computer Science 2022-05-30 Xiyang Liu , Weihao Kong , Prateek Jain , Sewoong Oh

Sequential quantum information processing may lie in the peaceful coexistence of no-go theorems on quantum operations, such as the no-cloning theorem, the monogamy of correlations, and the no-signalling principle. In this work, we…

Quantum Physics · Physics 2024-11-25 Hanwool Lee , Kieran Flatt , Joonwoo Bae

Data hiding is the art of concealing messages with limited perceptual changes. Recently, deep learning has enriched it from various perspectives with significant progress. In this work, we conduct a brief yet comprehensive review of…

Cryptography and Security · Computer Science 2022-04-20 Chaoning Zhang , Chenguo Lin , Philipp Benz , Kejiang Chen , Weiming Zhang , In So Kweon

The Lie--Trotter product formula is a foundational approximation for the quantum partition function, yet obtaining rigorous error bounds for the unbounded Hamiltonians common in physics remains a significant challenge. This paper provides a…

Quantum Physics · Physics 2025-10-21 Xuda Ye , Zhennan Zhou

Data hiding is the art of hiding secret data into a cover object such as digital image for covert communication. In this paper, we make the first step towards hiding ``data hiding'', which is totally different from many conventional works…

Cryptography and Security · Computer Science 2022-12-19 Hanzhou Wu , Gen Liu , Xinpeng Zhang

Measurement is a fundamental notion in the usual approximate quantum mechanics of measured subsystems. Probabilities are predicted for the outcomes of measurements. State vectors evolve unitarily in between measurements and by reduction of…

General Relativity and Quantum Cosmology · Physics 2014-01-14 James B. Hartle

The statistics of gap ratios between consecutive energy levels is a widely used tool, in particular in the context of many-body physics, to distinguish between chaotic and integrable systems, described respectively by Gaussian ensembles of…

Disordered Systems and Neural Networks · Physics 2022-02-28 Olivier Giraud , Nicolas Macé , Eric Vernier , Fabien Alet
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