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In Amin and Choi \cite{AC09}, we show that an adiabatic quantum algorithm for the NP-hard maximum independent set (MIS) problem on a set of special family of graphs in which there are exponentially many local maxima would have the…

Quantum Physics · Physics 2011-08-04 Vicky Choi

Geometric quantum computation is the idea that geometric phases can be used to implement quantum gates, i.e., the basic elements of the Boolean network that forms a quantum computer. Although originally thought to be limited to adiabatic…

Quantum Physics · Physics 2016-09-16 Erik Sjöqvist , Vahid Azimi Mousolou , Carlo M. Canali

Quantum annealing is guaranteed to find the ground state of optimization problems in the adiabatic limit. Recent work [Phys. Rev. X 6, 031010 (2016)] has found that for some barrier tunneling problems, quantum annealing can be run much…

Quantum Physics · Physics 2017-04-05 Lucas T. Brady , Wim van Dam

Designing proper time-dependent control fields for slowly varying the system to the ground state that encodes the problem solution is crucial for adiabatic quantum computation. However, inevitable perturbations in real applications demand…

Quantum Physics · Physics 2020-07-22 Xiaodong Yang , Ran Liu , Jun Li , Xinhua Peng

Quantum-classical hybrid dynamics is crucial for accurately simulating complex systems where both quantum and classical behaviors need to be considered. However, coupling between classical and quantum degrees of freedom and the exponential…

Quantum Physics · Physics 2024-08-09 Changnan Peng , Jin-Peng Liu , Gia-Wei Chern , Di Luo

Of late, we are witnessing spectacular developments in Quantum Information Processing with the availability of Noisy Intermediate-Scale Quantum devices of different architectures and various software development kits to work on quantum…

Quantum Physics · Physics 2021-02-23 Sayantan Pramanik , M Girish Chandra

This article is a brief introduction to quantum algorithms for the eigenvalue problem in quantum many-body systems. Rather than a broad survey of topics, we focus on providing a conceptual understanding of several quantum algorithms that…

Quantum Physics · Physics 2024-06-10 Dean Lee

Adiabatic quantum computing (AQC) started as an approach to solving optimization problems, and has evolved into an important universal alternative to the standard circuit model of quantum computing, with deep connections to both classical…

Quantum Physics · Physics 2018-02-05 Tameem Albash , Daniel A. Lidar

We consider an inverse problem for a finite graph $(X,E)$ where we are given a subset of vertices $B\subset X$ and the distances $d_{(X,E)}(b_1,b_2)$ of all vertices $b_1,b_2\in B$. The distance of points $x_1,x_2\in X$ is defined as the…

Combinatorics · Mathematics 2024-02-13 Joonas Ilmavirta , Matti Lassas , Jinpeng Lu , Lauri Oksanen , Lauri Ylinen

Adiabatic quantum computation provides an alternative approach to quantum computation using a time-dependent Hamiltonian. The time evolution of entanglement during the adiabatic quantum search algorithm is studied, and its relevance as a…

Quantum Physics · Physics 2009-11-11 Daria Ahrensmeier

We propose a hybrid quantum-classical approximate optimization algorithm for photonic quantum computing, specifically tailored for addressing continuous-variable optimization problems. Inspired by counterdiabatic protocols, our algorithm…

Quantum Physics · Physics 2024-10-03 Pranav Chandarana , Koushik Paul , Mikel Garcia-de-Andoin , Yue Ban , Mikel Sanz , Xi Chen

The discrete formulation of adiabatic quantum computing is compared with other search methods, classical and quantum, for random satisfiability (SAT) problems. With the number of steps growing only as the cube of the number of variables,…

Quantum Physics · Physics 2009-11-07 Tad Hogg

We study the problem of estimating the number of edges in an $n$-vertex graph, accessed via the Bipartite Independent Set query model introduced by Beame et al. (ITCS '18). In this model, each query returns a Boolean, indicating the…

Data Structures and Algorithms · Computer Science 2022-07-07 Raghavendra Addanki , Andrew McGregor , Cameron Musco

Quantum graphs are commonly used as models of complex quantum systems, for example molecules, networks of wires, and states of condensed matter. We consider quantum statistics for indistinguishable spinless particles on a graph,…

Mathematical Physics · Physics 2011-01-11 JM Harrison , JP Keating , JM Robbins

The design of new quantum algorithms has proven to be an extremely difficult task. This paper considers a different approach to the problem, by studying the problem of 'quantum state generation'. This approach provides intriguing links…

Quantum Physics · Physics 2007-05-23 Dorit Aharonov , Amnon Ta-Shma

We propose a new variant of the controlled-NOT quantum logic gate based on adiabatic level-crossing dynamics of the q-bits. The gate has a natural implementation in terms of the Cooper pair transport in arrays of small Josephson tunnel…

Quantum Physics · Physics 2009-10-30 D. V. Averin

This paper introduces an efficient quantum computing method for reducing special graphs in the context of the graph coloring problem. The special graphs considered include both symmetric and non-symmetric graphs where the axis passes…

Quantum Physics · Physics 2025-10-21 Lord Sen , Shyamapada Mukherjee

Quantum annealers have grown in complexity to the point that quantum computations involving few thousands of qubits are now possible. In this paper, \textcolor{black}{with the intentions to show the feasibility of quantum annealing to…

Materials Science · Physics 2020-12-30 Virginia Carnevali , Ilaria Siloi , Rosa Di Felice , Marco Fornari

Matching problems on 3D shapes and images are challenging as they are frequently formulated as combinatorial quadratic assignment problems (QAPs) with permutation matrix constraints, which are NP-hard. In this work, we address such problems…

Computer Vision and Pattern Recognition · Computer Science 2021-07-09 Marcel Seelbach Benkner , Vladislav Golyanik , Christian Theobalt , Michael Moeller

Adiabatic quantum computers can solve difficult optimization problems (e.g., the quadratic unconstrained binary optimization problem), and they seem well suited to train machine learning models. In this paper, we describe an adiabatic…

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