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Here we study the NP-complete $K$-SAT problem. Although the worst-case complexity of NP-complete problems is conjectured to be exponential, there exist parametrized random ensembles of problems where solutions can typically be found in…

Disordered Systems and Neural Networks · Physics 2019-07-11 Hendrik Schawe , Roman Bleim , Alexander K. Hartmann

Run-times of quantum algorithms are often studied via an asymptotic, worst-case analysis. Whilst useful, such a comparison can often fall short: it is not uncommon for algorithms with a large worst-case run-time to end up performing well on…

Quantum Physics · Physics 2023-10-11 Chris Cade , Marten Folkertsma , Ido Niesen , Jordi Weggemans

Establishing quantum advantage for variational quantum algorithms is an important direction in quantum computing. In this work, we apply the Quantum Approximate Optimisation Algorithm (QAOA) -- a popular variational quantum algorithm for…

Quantum Physics · Physics 2024-01-08 Andrew El-Kadi , Roberto Bondesan

We study the classical complexity of the exact Boson Sampling problem where the objective is to produce provably correct random samples from a particular quantum mechanical distribution. The computational framework was proposed by Aaronson…

Data Structures and Algorithms · Computer Science 2017-10-19 Peter Clifford , Raphaël Clifford

One of the potential applications of a quantum computer is solving quantum chemical systems. It is known that one of the fastest ways to obtain somewhat accurate solutions classically is to use approximations of density functional theory.…

Quantum Physics · Physics 2020-11-18 Thomas E. Baker , David Poulin

I describe one quantum approach to solving 3-satisfiability (3-SAT), the well known problem in computer science. The approach is based on repeatedly measuring the truth value of the clauses forming the 3-SAT proposition using a…

Quantum Physics · Physics 2015-09-03 Simon Benjamin

Quantum computation holds promise for the solution of many intractable problems. However, since many quantum algorithms are stochastic in nature they can only find the solution of hard problems probabilistically. Thus the efficiency of the…

Quantum Physics · Physics 2009-11-07 Sebastian Maurer , Tad Hogg , Bernardo Huberman

We propose a hybrid quantum-classical algorithm to compute approximate solutions of binary combinatorial problems. We employ a shallow-depth quantum circuit to implement a unitary and Hermitian operator that block-encodes the weighted…

Quantum Physics · Physics 2023-06-16 Natacha Kuete Meli , Florian Mannel , Jan Lellmann

Despite the fundamental role the Quantum Satisfiability (QSAT) problem has played in quantum complexity theory, a central question remains open: At which local dimension does the complexity of QSAT transition from "easy" to "hard"? Here, we…

Quantum Physics · Physics 2024-01-05 Dorian Rudolph , Sevag Gharibian , Daniel Nagaj

The Traveling Salesman Problem (TSP) is a classical NP-hard problem that plays a crucial role in combinatorial optimization. In this paper, we are interested in the quantum search framework for the TSP because it has robust theoretical…

Quantum Physics · Physics 2025-04-25 Bai Xujun , Shang Yun

In the oracle identification problem, we are given oracle access to an unknown N-bit string x promised to belong to a known set C of size M and our task is to identify x. We present a quantum algorithm for the problem that is optimal in its…

Quantum Physics · Physics 2014-04-24 Robin Kothari

Attaining a quantum speedup in solving practically useful optimization problems has been one of the holy grails in the field of quantum computing. While prior approaches have demonstrated speedups for certain structured problem classes,…

Quantum Physics · Physics 2026-05-04 Jan Ljubas , Tim Byrnes

Graph sparsification underlies a large number of algorithms, ranging from approximation algorithms for cut problems to solvers for linear systems in the graph Laplacian. In its strongest form, "spectral sparsification" reduces the number of…

Quantum Physics · Physics 2023-05-09 Simon Apers , Ronald de Wolf

A recent breakthrough by Ambainis, Balodis, Iraids, Kokainis, Pr\=usis and Vihrovs (SODA'19) showed how to construct faster quantum algorithms for the Traveling Salesman Problem and a few other NP-hard problems by combining in a novel way…

Quantum Physics · Physics 2020-07-16 Masayuki Miyamoto , Masakazu Iwamura , Koichi Kise , François Le Gall

Given the success of deep learning in classical machine learning, quantum algorithms for traditional neural network architectures may provide one of the most promising settings for quantum machine learning. Considering a fully-connected…

Quantum Physics · Physics 2021-07-21 Alexander Zlokapa , Hartmut Neven , Seth Lloyd

Submodular functions are set functions mapping every subset of some ground set of size $n$ into the real numbers and satisfying the diminishing returns property. Submodular minimization is an important field in discrete optimization theory…

Data Structures and Algorithms · Computer Science 2020-01-16 Yassine Hamoudi , Patrick Rebentrost , Ansis Rosmanis , Miklos Santha

Finding a quantum computing method to solve nondeterministic polynomial time (NP)-complete problems is currently of paramount importance in quantum information science. Here an experiment is presented to demonstrate the use of Rydberg atoms…

Quantum Physics · Physics 2024-07-03 Seokho Jeong , Minhyuk Kim , Minki Hhan , Jaewook Ahn

In Exact Quantum Query model, almost all of the Boolean functions for which non-trivial query algorithms exist are symmetric in nature. The most well known techniques in this domain exploit parity decision trees, in which the parity of two…

Quantum Physics · Physics 2021-05-18 Chandra Sekhar Mukherjee , Subhamoy Maitra

Quantum computers show potential for achieving computational advantage over classical computers, with many candidate applications in combinatorial optimisation. We present an application level benchmarking framework for near-term quantum…

We study the performance of stochastic local search algorithms for random instances of the $K$-satisfiability ($K$-SAT) problem. We introduce a new stochastic local search algorithm, ChainSAT, which moves in the energy landscape of a…

Data Structures and Algorithms · Computer Science 2009-11-13 Mikko Alava , John Ardelius , Erik Aurell , Petteri Kaski , Supriya Krishnamurthy , Pekka Orponen , Sakari Seitz
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