# A cross-disciplinary introduction to quantum annealing-based algorithms

@article{VenegasAndraca2018ACI, title={A cross-disciplinary introduction to quantum annealing-based algorithms}, author={Salvador El{\'i}as Venegas-Andraca and William Cruz-Santos and Catherine C. McGeoch and Marco Lanzagorta}, journal={Contemporary Physics}, year={2018}, volume={59}, pages={174 - 197} }

Abstract A central goal in quantum computing is the development of quantum hardware and quantum algorithms in order to analyse challenging scientific and engineering problems. Research in quantum computation involves contributions from both physics and computer science; hence this article presents a concise introduction to basic concepts from both fields that are used in annealing-based quantum computation, an alternative to the more familiar quantum gate model. We introduce some concepts from…

## Topics from this paper

## 31 Citations

Theory versus practice in annealing-based quantum computing

- Computer ScienceTheor. Comput. Sci.
- 2020

This paper proposes models of computation and of algorithms that lie on a scale of instantiation between pencil-and-paper abstraction and physical device that can provide a common language, allowing researchers from both ends to communicate and share their results.

Perspectives of quantum annealing: Methods and implementations.

- Physics, MedicineReports on progress in physics. Physical Society
- 2020

This perspectives article first gives a brief introduction to the concept of quantum annealing, and then highlights new pathways that may clear the way towards feasible and large scale quantumAnnealing.

A QUBO Formulation of Minimum Multicut Problem Instances in Trees for D-Wave Quantum Annealers

- Computer Science, MedicineScientific Reports
- 2019

This work proposes using quantum annealing for the theory of cuts, a field of paramount importance in theoretical computer science, and proposes a method to formulate the Minimum Multicut Problem into the QUBO representation.

Polymer Physics by Quantum Computing.

- Medicine, PhysicsPhysical review letters
- 2021

This work develops a formalism based on interacting binary tensors that allows for tackling sampling equilibrium ensembles of dense polymer mixtures using quantum annealing machines, and offers a promising avenue to harness the rapid development of quantum machines for sampling discrete models of filamentous soft-matter systems.

A Quantum Adiabatic Algorithm for Multiobjective Combinatorial Optimization

- Computer ScienceAxioms
- 2019

A theorem proving that the quantum adiabatic algorithm can find Pareto-optimal solutions in finite-time is demonstrated, opening the door to solve multiobjective optimization problems using current technology based on quantum annealing.

What Is the Optimal Annealing Schedule in Quantum Annealing

- Computer Science, Materials Science2020 IEEE Symposium Series on Computational Intelligence (SSCI)
- 2020

A theoretical explanation for empirical successes of quantum annealing is provided, by proving that these two schedules are indeed optimal (in some reasonable sense).

Many Known Quantum Algorithms Are Optimal: Symmetry-Based Proofs

- 2021

Many quantum algorithms have been proposed which are drastically more efficient that 1 the best of the non-quantum algorithms for solving the same problems. A natural question is: are 2 these quantum…

Recent advances for quantum classifiers

- Physics, Computer ScienceScience China Physics, Mechanics & Astronomy
- 2021

This review gives a relatively comprehensive overview of quantum classifiers, including a number of quantum classification algorithms, including quantum support vector machine, quantum kernel methods, quantum decision tree, and quantum nearest neighbor algorithm.

Integer Programming Techniques for Minor-Embedding in Quantum Annealers

- Computer Science, PhysicsCPAIOR
- 2020

The proposed integer programming techniques for solving the minor-embedding problem are able to detect instance infeasibility and provide bounds on solution quality, capabilities not offered by currently employed heuristic methods.

SU(2) lattice gauge theory on a quantum annealer

- PhysicsPhysical Review D
- 2021

Lattice gauge theory is an essential tool for strongly interacting non-Abelian fields, such as those in quantum chromodynamics where lattice results have been of central importance for several…

## References

SHOWING 1-10 OF 98 REFERENCES

Adiabatic Quantum Computation and Quantum Annealing: Theory and Practice

- Computer ScienceAdiabatic Quantum Computation and Quantum Annealing: Theory and Practice
- 2014

This monograph presents an introductory overview of Adiabatic quantum computation, a survey of basic principles of quantum computation and what is known about the AQC model and the QA algorithm paradigm, and reviews the D-Wave technology stack.

Optimization through quantum annealing: theory and some applications

- Computer Science
- 2006

The theory and the practical implementation of both classical and quantum annealing are illustrated – highlighting the crucial differences between these two methods – by means of results recently obtained in experiments, in simple toy-models, and more challenging combinatorial optimization problems.

Thermally assisted quantum annealing of a 16-qubit problem.

- Physics, MedicineNature communications
- 2013

It is experimentally demonstrated that, even with annealing times eight orders of magnitude longer than the predicted single-qubit decoherence time, the probabilities of performing a successful computation are similar to those expected for a fully coherent system.

Experimental evaluation of an adiabiatic quantum system for combinatorial optimization

- Computer ScienceCF '13
- 2013

An experimental study of a novel computing system (algorithm plus platform) that carries out quantum annealing, a type of adiabatic quantum computation, to solve optimization problems to solve NP-hard problem domains is described.

Quantum Simulation of Tunneling in Small Systems

- Computer Science, PhysicsScientific reports
- 2012

It is shown that a set of tunneling problems may be investigated with no ancillary qubits and a cost of one single-qubit operator per time step for the potential evolution, eliminating at least half of the quantum gates required for the algorithm and more than that in the general case.

Benchmarking a quantum annealing processor with the time-to-target metric

- Physics, Mathematics
- 2015

In the evaluation of quantum annealers, metrics based on ground state success rates have two major drawbacks. First, evaluation requires computation time for both quantum and classical processors…

Multiple Query Optimization on the D-Wave 2X Adiabatic Quantum Computer

- Computer Science, PhysicsProc. VLDB Endow.
- 2016

This paper shows how an MQO problem instance can be transformed into a mathematical formula that complies with the restrictive input format accepted by the quantum annealer, and finds a class of problem instances where the quantumAnnealer is three orders of magnitude faster than other approaches.

An introduction to quantum machine learning

- Computer Science, Physics
- 2014

This contribution gives a systematic overview of the emerging field of quantum machine learning and presents the approaches as well as technical details in an accessible way, and discusses the potential of a future theory of quantum learning.

Graph Partitioning using Quantum Annealing on the D-Wave System

- Computer Science, PhysicsArXiv
- 2017

Results for graph partitioning using quantum and hybrid classical-quantum approaches are shown to be comparable to current "state of the art" methods and sometimes better.

What is the Computational Value of Finite Range Tunneling

- Physics, Computer Science
- 2015

It is demonstrated how finite range tunneling can provide considerable computational advantage over classical processors for a crafted problem designed to have tall and narrow energy barriers separating local minima, the D-Wave 2X quantum annealer achieves significant runtime advantages relative to Simulated Annealing.