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Several important models of machine learning algorithms have been successfully generalized to the quantum world, with potential speedup to training classical classifiers and applications to data analytics in quantum physics that can be…

Quantum Physics · Physics 2021-10-01 Ji Guan , Wang Fang , Mingsheng Ying

We propose an efficient scheme for verifying quantum computations in the `high complexity' regime i.e. beyond the remit of classical computers. Previously proposed schemes remarkably provide confidence against arbitrarily malicious…

Quantum Physics · Physics 2017-05-24 Richard Jozsa , Sergii Strelchuk

Quantum computers and quantum algorithms have made great strides in the last few years and promise improvements over classical computing for specific tasks. Although the current hardware is not yet ready to make real impacts at the time of…

Quantum Physics · Physics 2024-08-28 Nils Quetschlich , Tobias Forster , Adrian Osterwind , Domenik Helms , Robert Wille

Traditionally, graph quality metrics focus on readability, but recent studies show the need for metrics which are more specific to the discovery of patterns in graphs. Cluster analysis is a popular task within graph analysis, yet there is…

Data Structures and Algorithms · Computer Science 2019-08-22 Amyra Meidiana , Seok-Hee Hong , Peter Eades , Daniel Keim

We introduce I/O-optimal certifying algorithms for bipartite graphs, as well as for the classes of split, threshold, bipartite chain, and trivially perfect graphs. When the input graph is a class member, the certifying algorithm returns a…

Data Structures and Algorithms · Computer Science 2022-10-25 Ulrich Meyer , Hung Tran , Konstantinos Tsakalidis

Various algorithms have been developed to simulate quantum circuits on classical hardware. Among the most prominent are approaches based on \emph{stabilizer decompositions} and \emph{tensor network contraction}. In this work, we present a…

Quantum Physics · Physics 2026-03-09 Julien Codsi , Tuomas Laakkonen

Quantum computers are now on the brink of outperforming their classical counterparts. One way to demonstrate the advantage of quantum computation is through quantum random sampling performed on quantum computing devices. However, existing…

We study space and time efficient quantum algorithms for two graph problems -- deciding whether an $n$-vertex graph is a forest, and whether it is bipartite. Via a reduction to the s-t connectivity problem, we describe quantum algorithms…

Quantum Physics · Physics 2016-10-04 Chris Cade , Ashley Montanaro , Aleksandrs Belovs

An $n$-qubit quantum circuit is said to be peaked if it has an output probability that is at least inverse-polynomially large as a function of $n$. We describe a classical algorithm with quasipolynomial runtime $n^{O(\log{n})}$ that…

Quantum Physics · Physics 2023-09-18 Sergey Bravyi , David Gosset , Yinchen Liu

The classical communication complexity of testing closeness of discrete distributions has recently been studied by Andoni, Malkin and Nosatzki (ICALP'19). In this problem, two players each receive $t$ samples from one distribution over…

Computational Complexity · Computer Science 2023-12-29 Aleksandrs Belovs , Arturo Castellanos , François Le Gall , Guillaume Malod , Alexander A. Sherstov

Understanding the computational overheads imposed by classical control systems on quantum computing platforms becomes critically important as these quantum machines grow in scale and complexity. In this work, we calculate the overheads…

Quantum Physics · Physics 2024-01-09 John R. Scott , Krishna C. Balram

We study the sample complexity of nondeterministically testable graph parameters and improve existing bounds on it by several orders of magnitude. The technique used would be also of independent interest. We also discuss the special case of…

Data Structures and Algorithms · Computer Science 2016-08-05 Marek Karpinski , Roland Markó

In recent years, quantum computers and algorithms have made significant progress indicating the prospective importance of quantum computing (QC). Especially combinatorial optimization has gained a lot of attention as an application field…

In this note, we develop a bounded-error quantum algorithm that makes $\tilde O(n^{1/4}\varepsilon^{-1/2})$ queries to a Boolean function $f$, accepts a monotone function, and rejects a function that is $\varepsilon$-far from being…

Quantum Physics · Physics 2015-03-11 Aleksandrs Belovs , Eric Blais

We initiate the study of quantum property testing in sparse directed graphs, and more particularly in the unidirectional model, where the algorithm is allowed to query only the outgoing edges of a vertex. In the classical unidirectional…

Quantum Physics · Physics 2025-11-27 Simon Apers , Frédéric Magniez , Sayantan Sen , Dániel Szabó

Connected clustering denotes a family of constrained clustering problems in which we are given a distance metric and an undirected connectivity graph $G$ that can be completely unrelated to the metric. The aim is to partition the $n$…

Data Structures and Algorithms · Computer Science 2025-11-25 Jan Eube , Heiko Röglin

Randomness is an intrinsic feature of quantum theory. The outcome of any quantum measurement will be random, sampled from a probability distribution that is defined by the measured quantum state. The task of sampling from a prescribed…

Quantum Physics · Physics 2021-01-19 Dominik Hangleiter

We consider the problem of quantum state certification, where one is given $n$ copies of an unknown $d$-dimensional quantum mixed state $\rho$, and one wants to test whether $\rho$ is equal to some known mixed state $\sigma$ or else is…

Quantum Physics · Physics 2017-11-07 Costin Bădescu , Ryan O'Donnell , John Wright

In the thesis, we use a recently developed tight characterisation of quantum query complexity, the adversary bound, to develop new quantum algorithms and lower bounds. Our results are as follows: * We develop a new technique for the…

Quantum Physics · Physics 2014-02-18 Aleksandrs Belovs

We introduce a principled and theoretically sound spectral method for $k$-way clustering in signed graphs, where the affinity measure between nodes takes either positive or negative values. Our approach is motivated by social balance…

Machine Learning · Statistics 2019-05-21 Mihai Cucuringu , Peter Davies , Aldo Glielmo , Hemant Tyagi