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Quantum hypothesis testing concerns the discrimination between quantum states. This paper introduces a novel lower bound for asymmetric quantum hypothesis testing that is based on the Nussbaum-Szko{\l}a mapping. The lower bound provides a…

Quantum Physics · Physics 2026-05-21 Jorge Lizarribar-Carrillo , Gonzalo Vazquez-Vilar , Tobias Koch

We consider the quantum complexities of the following three problems: searching an ordered list, sorting an un-ordered list, and deciding whether the numbers in a list are all distinct. Letting N be the number of elements in the input list,…

Quantum Physics · Physics 2016-12-30 Peter Hoyer , Jan Neerbek , Yaoyun Shi

In this paper, we propose a branch-and-bound algorithm for solving nonconvex quadratic programming problems with box constraints (BoxQP). Our approach combines existing tools, such as semidefinite programming (SDP) bounds strengthened…

Optimization and Control · Mathematics 2024-11-06 Marco Locatelli , Veronica Piccialli , Antonio M. Sudoso

Measuring how quickly iterative methods converge is essential in computational mathematics, but current approaches have significant limitations. Q-order analysis requires strict smoothness conditions, while R-order analysis lacks precision…

Numerical Analysis · Mathematics 2025-04-09 Xiangmin Jiao , Hongji Gao

Quantum entanglement is a fundamental property of quantum mechanics and plays a crucial role in quantum computation and information. We study entanglement via the lens of computational complexity by considering quantum generalizations of…

Quantum Physics · Physics 2024-03-01 Fernando Granha Jeronimo , Pei Wu

We improve the upper bound on the minimal resources required for measurement-based quantum computation. Minimizing the resources required for this model is a key issue for experimental realization of a quantum computer based on projective…

Quantum Physics · Physics 2007-09-20 Simon Perdrix

We introduce a cutting-plane framework for nonconvex quadratic programs (QPs) that progressively tightens convex relaxations. Our approach leverages the doubly nonnegative (DNN) relaxation to compute strong lower bounds and generate…

Optimization and Control · Mathematics 2025-10-06 Zheng Qu , Defeng Sun , Jintao Xu

There has been a surge of progress in recent years in developing algorithms for testing and learning quantum states that achieve optimal copy complexity. Unfortunately, they require the use of entangled measurements across many copies of…

Quantum Physics · Physics 2020-04-20 Sebastien Bubeck , Sitan Chen , Jerry Li

We first discuss a framework for discrete quantum processes (DQP). It is shown that the set of q-probability operators is convex and its set of extreme elements is found. The property of consistency for a DQP is studied and the quadratic…

General Relativity and Quantum Cosmology · Physics 2022-09-01 Stan Gudder

We study the hardness of Approximate Query Processing (AQP) of various types of queries involving joins over multiple tables of possibly different sizes. In the case where the query result is a single value (e.g., COUNT, SUM, and…

Databases · Computer Science 2020-10-02 Tianyu Liu , Chi Wang

This paper investigates the problem of efficient constrained global optimization of hybrid models that are a composition of a known white-box function and an expensive multi-output black-box function subject to noisy observations, which…

Machine Learning · Statistics 2023-07-31 Congwen Lu , Joel A. Paulson

In the circuit model of quantum computing, amplitude amplification techniques can be used to find solutions to NP-hard problems defined on $n$-bits in time $\text{poly}(n) 2^{n/2}$. In this work, we investigate whether such general…

We present a new framework for assessing the power of measurement-based quantum computation (MBQC) on short-range entangled symmetric resource states, in spatial dimension one. It requires fewer assumptions than previously known. The…

Quantum Physics · Physics 2024-01-03 Robert Raussendorf , Wang Yang , Arnab Adhikary

In this paper, combinatorial quantitative group testing (QGT) with noisy measurements is studied. The goal of QGT is to detect defective items from a data set of size $n$ with counting measurements, each of which counts the number of…

Information Theory · Computer Science 2022-02-01 Yun-Han Li , I-Hsiang Wang

This paper makes two primary contributions. First, we introduce the concept of counting martingales and use it to define counting measures, counting dimensions, and counting strong dimensions. Second, we apply these new tools to strengthen…

Computational Complexity · Computer Science 2025-08-12 John M. Hitchcock , Adewale Sekoni , Hadi Shafei

Inspired by the Elitzur-Vaidman bomb testing problem [arXiv:hep-th/9305002], we introduce a new query complexity model, which we call bomb query complexity $B(f)$. We investigate its relationship with the usual quantum query complexity…

Quantum Physics · Physics 2014-12-01 Cedric Yen-Yu Lin , Han-Hsuan Lin

Learned index structures aim to accelerate queries by training machine learning models to approximate the rank function associated with a database attribute. While effective in practice, their theoretical limitations are not fully…

Data Structures and Algorithms · Computer Science 2026-01-13 Luis Alberto Croquevielle , Roman Sokolovskii , Thomas Heinis

As quantum computing resources remain scarce and error rates high, minimizing the resource consumption of quantum circuits is essential for achieving practical quantum advantage. Here we consider the natural problem of, given a circuit $C$,…

Quantum Physics · Physics 2026-02-27 Adam Husted Kjelstrøm , Andreas Pavlogiannis , Jaco van de Pol

We consider a modification of the Quantifier Elimination (QE) problem called Partial QE (PQE). In PQE, only a small part of the formula is taken out of the scope of quantifiers. The appeal of PQE is that many verification problems, e.g.…

Logic in Computer Science · Computer Science 2019-07-16 Eugene Goldberg

Finding shape correspondences can be formulated as an NP-hard quadratic assignment problem (QAP) that becomes infeasible for shapes with high sampling density. A promising research direction is to tackle such quadratic optimization problems…

Computer Vision and Pattern Recognition · Computer Science 2021-08-20 Marcel Seelbach Benkner , Zorah Lähner , Vladislav Golyanik , Christof Wunderlich , Christian Theobalt , Michael Moeller