Multivariable Optimization: Quantum Annealing & Computation

Abstract

Recent developments in quantum annealing techniques have been indicating potential advantage of quantum annealing for solving NP-hard optimization problems. In this article we briefly indicate and discuss the beneficial features of quantum annealing techniques and compare them with those of simulated annealing techniques. We then briefly discuss the quantum annealing studies of some model spin glass and kinetically constrained systems.

9 pages, 3 figures; EPJ ST: spl. 'Debate & Discussion' issue on "Quantum Annealing: The fastest route to large scale computation?"

References in corpus (20)

• Quantum Annealing in the Transverse Ising Model
• A Quantum Adiabatic Evolution Algorithm Applied to Random Instances of an NP-Complete Problem
• Quantum annealing with more than one hundred qubits
• Theory of Quantum Annealing of an Ising Spin Glass
• Quantum Annealing and Analog Quantum Computation
• Quantum Annealing: A New Method for Minimizing Multidimensional Functions
• Quantum Search by Local Adiabatic Evolution
• Mathematical Foundation of Quantum Annealing
• Anderson localization casts clouds over adiabatic quantum optimization
• A case study in programming a quantum annealer for hard operational planning problems
• Quantum Optimization of Fully-Connected Spin Glasses
• Quantum phase transitions in transverse field spin models: from statistical physics to quantum information
• Glassy Chimeras could be blind to quantum speedup: Designing better benchmarks for quantum annealing machines
• Exponential Complexity of the Quantum Adiabatic Algorithm for certain Satisfiability Problems
• A Quantum Annealing Approach for Fault Detection and Diagnosis of Graph-Based Systems
• Quantum and Classical Glass Transitions in $LiH{o}_x{Y}_{1-x}{F}_4$
• A Near-Term Quantum Computing Approach for Hard Computational Problems in Space Exploration
• Quantum Annealing in a Kinetically Constrained System
• Quantum Annealing search of Ising spin glass ground state(s) with tunable transverse & longitudinal fields
• Quantum Annealing and Computation: A Brief Documentary Note

Cited by in corpus (20)

• Application of Quantum Annealing to Training of Deep Neural Networks
• Quantum Annealing: An Overview
• QUBO Formulations for Training Machine Learning Models
• Strengths and weaknesses of weak-strong cluster problems: A detailed overview of state-of-the-art classical heuristics vs quantum approaches
• Seeking Quantum Speedup Through Spin Glasses: The Good, the Bad, and the Ugly
• Adiabatic Quantum Linear Regression
• Best-case performance of quantum annealers on native spin-glass benchmarks: How chaos can affect success probabilities
• Quantum Annealing for Large MIMO Downlink Vector Perturbation Precoding
• Quantum Annealing - Foundations and Frontiers
• Possible Ergodic-nonergodic regions in the quantum Sherrington-Kirkpatrick spin glass model and quantum annealing
• Development of Econophysics: A biased account and perspective from Kolkata
• A QUBO model of the RNA folding problem optimized by variational hybrid quantum annealing
• Non-Adiabatic Quantum Dynamics of Grover's Adiabatic Search Algorithm
• On the Question of Ergodicity in Quantum Spin Glass Phase and its role in Quantum Annealing
• Lossy compression of statistical data using quantum annealer
• A general learning scheme for classical and quantum Ising machines
• A Lattice-Reduction Aided Vector Perturbation Precoder Relying on Quantum Annealing
• Tensor Decompositions and Adiabatic Quantum Computing for Discovering Practical Matrix Multiplication Algorithms
• Lack of a thermodynamic finite-temperature spin-glass phase in the two-dimensional randomly-coupled ferromagnet
• Quantum Annealing for the Set Splitting Problem