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Quantum computing for machine learning attracts increasing attention and recent technological developments suggest that especially adiabatic quantum computing may soon be of practical interest. In this paper, we therefore consider this…

Machine Learning · Statistics 2017-06-20 Christian Bauckhage , Eduardo Brito , Kostadin Cvejoski , Cesar Ojeda , Rafet Sifa , Stefan Wrobel

A quantum system will stay near its instantaneous ground state if the Hamiltonian that governs its evolution varies slowly enough. This quantum adiabatic behavior is the basis of a new class of algorithms for quantum computing. We test one…

Quantum Physics · Physics 2009-11-07 Edward Farhi , Jeffrey Goldstone , Sam Gutmann , Joshua Lapan , Andrew Lundgren , Daniel Preda

We present an efficient quantum algorithm for some independent set problems in graph theory, based on non-abelian adiabatic mixing. We illustrate the performance of our algorithm with analysis and numerical calculations for two different…

Quantum Physics · Physics 2020-01-22 Biao Wu , Hongye Yu , Frank Wilczek

We address the question of how a quantum computer can be used to simulate experiments on quantum systems in thermal equilibrium. We present two approaches for the preparation of the equilibrium state on a quantum computer. For both…

Quantum Physics · Physics 2009-10-31 Barbara M. Terhal , David P. DiVincenzo

A major challenge facing adiabatic quantum computing is that algorithm design and error correction can be difficult for adiabatic quantum computing. Recent work has considered addressing his challenge by using coherently controlled…

Quantum Physics · Physics 2015-06-19 Maria Kieferova , Nathan Wiebe

We illustrate the adiabatic quantum computing solution of the knapsack problem with both integer profits and weights. For problems with $n$ objects (or items) and integer capacity $c$, we give specific examples using both an Ising class…

Quantum Physics · Physics 2017-01-23 Mark W. Coffey

A new quantum algorithm is proposed to solve Satisfiability(SAT) problems by taking advantage of non-unitary transformation in ground state quantum computer. The energy gap scale of the ground state quantum computer is analyzed for 3-bit…

Quantum Physics · Physics 2015-06-26 Wenjin Mao

Adiabatic quantum computing is a universal model for quantum computing whose implementation using a gate-based quantum computer requires depths that are unreachable in the early fault-tolerant era. To mitigate the limitations of near-term…

Quantum Physics · Physics 2024-10-18 Ioannis Kolotouros , Ioannis Petrongonas , Miloš Prokop , Petros Wallden

Quantum computation appears to offer significant advantages over classical computation and this has generated a tremendous interest in the field. In this thesis we consider the application of quantum computers to scientific computing and…

Quantum Physics · Physics 2018-05-10 Stuart Hadfield

In this work, we attempt to solve the integer-weight knapsack problem using the D-Wave 2000Q adiabatic quantum computer. The knapsack problem is a well-known NP-complete problem in computer science, with applications in economics, business,…

Quantum Physics · Physics 2020-08-18 Lauren Pusey-Nazzaro , Prasanna Date

A major challenge in machine learning is the computational expense of training these models. Model training can be viewed as a form of optimization used to fit a machine learning model to a set of data, which can take up significant amount…

Machine Learning · Computer Science 2021-11-16 Prasanna Date , Thomas Potok

This paper concerns quantum heuristics able to extend the domain of quantum computing, defining a promising way in the large number of well-known classical algorithms. Quantum approximate heuristics take advantage of alternation between a…

Quantum Physics · Physics 2022-07-22 Eric Bourreau , Gérard Fleury , Philippe Lacomme

Compiling quantum algorithms for near-term quantum computers (accounting for connectivity and native gate alphabets) is a major challenge that has received significant attention both by industry and academia. Avoiding the exponential…

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

Due to recent technological advances, actual quantum devices are being constructed and used to perform computations. As a result, many classical problems are being restated so as to be solved on quantum computers. Some examples include…

Number Theory · Mathematics 2021-10-27 Matthew B. Crawford

The success of adiabatic quantum computation (AQC) depends crucially on the ability to maintain the quantum computer in the ground state of the evolution Hamiltonian. The computation process has to be sufficiently slow as restricted by the…

Quantum Physics · Physics 2008-07-31 Man-Hong Yung

An adiabatic quantum algorithm is essentially given by three elements: An initial Hamiltonian with known ground state, a problem Hamiltonian whose ground state corresponds to the solution of the given problem and an evolution schedule such…

Quantum Physics · Physics 2019-09-17 Davide Pastorello , Enrico Blanzieri

Properly designed control has been shown to be particularly advantageous for improving AQC accuracy and time complexity scaling. Here, an \emph{in situ} quantum control optimization protocol is developed to indirectly optimize state…

Quantum Physics · Physics 2019-06-12 Gregory Quiroz

We introduce an algorithm for combinatorial search on quantum computers that is capable of significantly concentrating amplitude into solutions for some NP search problems, on average. This is done by exploiting the same aspects of problem…

Quantum Physics · Physics 2007-05-23 Tad Hogg

We introduce an algorithm for combinatorial search on quantum computers that is capable of significantly concentrating amplitude into solutions for some NP search problems, on average. This is done by exploiting the same aspects of problem…

Artificial Intelligence · Computer Science 2009-09-25 T. Hogg