D-Wave and predecessors: From simulated to quantum annealing

2014 ◽  
Vol 12 (03) ◽  
pp. 1430002 ◽  
Author(s):  
Eliahu Cohen ◽  
Boaz Tamir
Keyword(s):  
Genetic Algorithm ◽  
Image Processing ◽  
Large Scale ◽  
Quantum Computer ◽  
Research Area ◽  
Hill Climbing ◽  
Quantum Annealing ◽  
Challenging Research ◽  
Computer Based ◽  
D Wave

On May 2011, D-Wave Systems Inc. announced "D-Wave One", as "the world's first commercially available quantum computer". No wonder this adiabatic quantum computer based on 128-qubit chip-set provoked an immediate controversy. Over the last 40 years, quantum computation has been a very promising yet challenging research area, facing major difficulties producing a large scale quantum computer. Today, after Google has purchased "D-Wave Two" containing 512 qubits, criticism has only increased. In this work, we examine the theory underlying the D-Wave, seeking to shed some light on this intriguing quantum computer. Starting from classical algorithms such as Metropolis algorithm, genetic algorithm (GA), hill climbing and simulated annealing, we continue to adiabatic computation and quantum annealing towards better understanding of the D-Wave mechanism. Finally, we outline some applications within the fields of information and image processing. In addition, we suggest a few related theoretical ideas and hypotheses.

scholarly journals Efficient Criteria of Quantumness for a Large System of Qubits

2022 ◽  
Vol 9 ◽  
Author(s):  
Shohei Watabe ◽  
Michael Zach Serikow ◽  
Shiro Kawabata ◽  
Alexandre Zagoskin
Keyword(s):  
Large Scale ◽  
Quantum Computer ◽  
Quantum Systems ◽  
Quantum Annealing ◽  
Coherent Systems ◽  
Adiabatic Evolution ◽  
Quantum Domain ◽  
Basic Parameters ◽  
Efficient Criteria ◽  
D Wave

In order to model and evaluate large-scale quantum systems, e.g., quantum computer and quantum annealer, it is necessary to quantify the “quantumness” of such systems. In this paper, we discuss the dimensionless combinations of basic parameters of large, partially quantum coherent systems, which could be used to characterize their degree of quantumness. Based on analytical and numerical calculations, we suggest one such number for a system of qubits undergoing adiabatic evolution, i.e., the accessibility index. Applying it to the case of D-Wave One superconducting quantum annealing device, we find that its operation as described falls well within the quantum domain.

scholarly journals Designing Peptides on a Quantum Computer

2019 ◽  
Author(s):  
Vikram Khipple Mulligan ◽  
Hans Melo ◽  
Haley Irene Merritt ◽  
Stewart Slocum ◽  
Brian D. Weitzner ◽  
...  
Keyword(s):  
Protein Design ◽  
Real World ◽  
Large Scale ◽  
Quantum Computer ◽  
Research Area ◽  
Side Chain ◽  
Quantum Computers ◽  
Amino Acid Side Chain ◽  
Processing Unit ◽  
D Wave

AbstractAlthough a wide variety of quantum computers are currently being developed, actual computational results have been largely restricted to contrived, artificial tasks. Finding ways to apply quantum computers to useful, real-world computational tasks remains an active research area. Here we describe our mapping of the protein design problem to the D-Wave quantum annealer. We present a system whereby Rosetta, a state-of-the-art protein design software suite, interfaces with the D-Wave quantum processing unit to find amino acid side chain identities and conformations to stabilize a fixed protein backbone. Our approach, which we call the QPacker, uses a large side-chain rotamer library and the full Rosetta energy function, and in no way reduces the design task to a simpler format. We demonstrate that quantum annealer-based design can be applied to complex real-world design tasks, producing designed molecules comparable to those produced by widely adopted classical design approaches. We also show through large-scale classical folding simulations that the results produced on the quantum annealer can inform wet-lab experiments. For design tasks that scale exponentially on classical computers, the QPacker achieves nearly constant runtime performance over the range of problem sizes that could be tested. We anticipate better than classical performance scaling as quantum computers mature.

scholarly journals Hierarchical System Decomposition Using Genetic Algorithm for Future Sustainable Computing

2020 ◽  
Vol 12 (6) ◽  
pp. 2177
Author(s):  
Jun-Ho Huh ◽  
Jimin Hwa ◽  
Yeong-Seok Seo
Keyword(s):  
Genetic Algorithm ◽  
Software Architecture ◽  
Large Scale ◽  
Structural Characteristics ◽  
Optimal Solution ◽  
Hill Climbing ◽  
Software Systems ◽  
Small Scale ◽  
Hill Climbing Algorithm ◽  
Architecture Management

A Hierarchical Subsystem Decomposition (HSD) is of great help in understanding large-scale software systems from the software architecture level. However, due to the lack of software architecture management, HSD documentations are often outdated, or they disappear in the course of repeated changes of a software system. Thus, in this paper, we propose a new approach for recovering HSD according to the intended design criteria based on a genetic algorithm to find an optimal solution. Experiments are performed to evaluate the proposed approach using two open source software systems with the 14 fitness functions of the genetic algorithm (GA). The HSDs recovered by our approach have different structural characteristics according to objectives. In the analysis on our GA operators, crossover contributes to a relatively large improvement in the early phase of a search. Mutation renders small-scale improvement in the whole search. Our GA is compared with a Hill-Climbing algorithm (HC) implemented by our GA operators. Although it is still in the primitive stage, our GA leads to higher-quality HSDs than HC. The experimental results indicate that the proposed approach delivers better performance than the existing approach.

A New Genetic Algorithm for the RCPSP in Large Scale

2013 ◽  
Vol 4 (2) ◽  
pp. 29-40 ◽  
Author(s):  
Hossein Zoulfaghari ◽  
Javad Nematian ◽  
Nader Mahmoudi ◽  
Mehdi Khodabandeh
Keyword(s):  
Genetic Algorithm ◽  
Genetic Algorithms ◽  
Project Scheduling ◽  
Large Scale ◽  
Resource Constraints ◽  
Research Area ◽  
New Method ◽  
Scheduling Problem ◽  
Academic Problem ◽  
Project Scheduling Problem

The Resource Constrained Project Scheduling Problem (RCPSP) is a well-studied academic problem that has been shown to be well suited to optimization via Genetic Algorithms (GA). In this paper, a new method will be designed that would be able to solve RCPSP. This research area is very common in industry especially when a set of activities needs to be finished as soon as possible subject to two sets of constraints, precedence constraints and resource constraints. The presented algorithm in this paper is used to solve large scale RCPSP and improves solutions. Finally, for comparing, results are reported for the most famous classical problems that are taken from PSPLIB.

The D-Wave quantum computer – advantages and disadvantages of moving away from the circuit model

2021 ◽  
Vol 0 (11-12/2020) ◽  
pp. 23-32
Author(s):  
Kacper Lenkiewicz ◽  
Joanna Wiśniewska
Keyword(s):  
Quantum Computing ◽  
Quantum Computer ◽  
Quantum Effects ◽  
Circuit Model ◽  
Quantum Annealing ◽  
Advantages And Disadvantages ◽  
Scientific Papers ◽  
The Subject ◽  
A Company ◽  
D Wave

The paper is based on a thesis with the same title. The purpose of this thesis is to analyse D-Wave devices using quantum effects. The research focuses on demonstrating the advantages and disadvantages of a company moving away from the circuit model in its computers. The subject of the research is the used adiabatic model of quantum computing based on the mechanism of quantum annealing. The research is based on publicly available, comprehensive documentation of D-Wave Systems. On the basis of scientific papers, conferences and information contained in websites, controversies, disadvantages and advantages of the solutions adopted have been described.

scholarly journals Quantum computing cryptography: Finding cryptographic Boolean functions with quantum annealing by a 2000 qubit D-wave quantum computer

2020 ◽  
Vol 384 (10) ◽  
pp. 126214 ◽  
Author(s):  
Feng Hu ◽  
Lucas Lamata ◽  
Mikel Sanz ◽  
Xi Chen ◽  
Xingyuan Chen ◽  
...  
Keyword(s):  
Quantum Computing ◽  
Boolean Functions ◽  
Quantum Computer ◽  
Quantum Annealing ◽  
D Wave

A hybrid approach for cost-optimized lateral transshipment in a supply chain environment

2016 ◽  
Vol 22 (4) ◽  
pp. 860-878
Author(s):  
Dilupa Nakandala ◽  
Henry Lau ◽  
Andrew Ning
Keyword(s):  
Genetic Algorithm ◽  
Supply Chain ◽  
Inventory Management ◽  
Large Scale ◽  
Hybrid Approach ◽  
Hybrid Genetic Algorithm ◽  
Hill Climbing ◽  
Initial Population ◽  
Content Type ◽  
Lateral Transshipment

Purpose – When making sourcing decisions, both cost optimization and customer demand fulfillment are equally important for firm competitiveness. The purpose of this paper is to develop a stochastic search technique, hybrid genetic algorithm (HGA), for cost-optimized decision making in wholesaler inventory management in a supply chain network of wholesalers, retailers and suppliers. Design/methodology/approach – This study develops a HGA by using a mixture of greedy-based and randomly generated solutions in the initial population and a local search method (hill climbing) applied to individuals selected for performing crossover before crossover is implemented and to the best individual in the population at the end of HGA as well as gene slice and integration. Findings – The application of the proposed HGA is illustrated by considering multiple scenarios and comparing with the other commonly adopted methods of standard genetic algorithm, simulated annealing and tabu search. The simulation results demonstrate the capability of the proposed approach in producing more effective solutions. Practical implications – The pragmatic importance of this method is for the inventory management of wholesaler operations and this can be scalable to address real contexts with multiple wholesalers and multiple suppliers with variable lead times. Originality/value – The proposed stochastic-based search techniques have the capability in producing good-quality optimal or suboptimal solutions for large-scale problems within a reasonable time using ordinary computing resources available in firms.

A Computer-Based System for Mass Customization of Prefabricated Housing

2013 ◽  
Vol 38 (1) ◽  
pp. 20-30
Author(s):  
Avi Friedman ◽  
Aaron Sprecher ◽  
Basem Eid Mohamed
Keyword(s):  
Mass Customization ◽  
Research Area ◽  
Web Based ◽  
Market Sector ◽  
Challenging Research ◽  
Canadian Market ◽  
Computer Based ◽  
Configuration System ◽  
Configuration Systems ◽  
A Company

The concept of employing web-based configuration systems towards mass customization of housing has been implemented by some prefabricated housing companies around the globe, and has become a challenging research area in the last few decades as an outcome of advancements in communication and design technologies. Different methodologies have been employed with the aim of efficiently engaging future homebuyers in the design of their homes. The thrust of this paper is to systematically formalize an advanced configuration system for mass customization of prefabricated housing for a company operating in the Canadian market. The focus is on one floor bungalows which are common within the Province of Quebec. Such housing models targets a specific market sector; elderly couples seeking retirement homes, with the aim of improving affordability through maintaining particular design and production qualities.

Programming a D-wave annealing-based quantum computer: tools and techniques

2019 ◽  
Vol 19 (9&10) ◽  
pp. 721-759
Author(s):  
Scott Pakin ◽  
Steven P. Reinhardt
Keyword(s):  
Ising Model ◽  
Programming Model ◽  
Quantum Computer ◽  
Solution Technique ◽  
Quantum Annealing ◽  
Model Hamiltonian ◽  
Practical Standpoint ◽  
Np Hard Problem ◽  
Tools And Techniques ◽  
D Wave

Quantum annealing is a form of quantum computing that exploits quantum effects to probabilistically solve a specific, NP-hard problem: finding the ground state of a classical, Ising-model Hamiltonian. Because physical quantum annealers are already available, there exists the pressing question of how to program such systems. That is, how can one map a computational problem into the coefficients of an Ising-model Hamiltonian for solution by quantum-annealing hardware? In this article, we address that question primarily from a practical standpoint. We survey extant software tools intended for programming D-wave annealing-based quantum processors and examine the programming model and solution technique promoted by each tool in an attempt to showcase the variety of contemporary approaches to solving computationally challenging problems on an existing annealing-based quantum computer.

Some comments about observations and image processing of comet 29P/Schwassmann-Wachmann 1

1999 ◽  
Vol 173 ◽  
pp. 243-248
Author(s):  
D. Kubáček ◽  
A. Galád ◽  
A. Pravda
Keyword(s):  
Image Processing ◽  
Large Scale ◽  
Harvard College ◽  
Oak Ridge ◽  
Large Scale Structures ◽  
Short Period Comet ◽  
Short Period ◽  
Scale Structures ◽  
Harvard College Observatory ◽  
Period Comet

AbstractUnusual short-period comet 29P/Schwassmann-Wachmann 1 inspired many observers to explain its unpredictable outbursts. In this paper large scale structures and features from the inner part of the coma in time periods around outbursts are studied. CCD images were taken at Whipple Observatory, Mt. Hopkins, in 1989 and at Astronomical Observatory, Modra, from 1995 to 1998. Photographic plates of the comet were taken at Harvard College Observatory, Oak Ridge, from 1974 to 1982. The latter were digitized at first to apply the same techniques of image processing for optimizing the visibility of features in the coma during outbursts. Outbursts and coma structures show various shapes.

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