Optimization of time error in large scale synchronization network via quantum annealing method

2020 ◽  
Author(s):  
Bo Lv
Keyword(s):  
Large Scale ◽  
Quantum Annealing ◽  
Time Error ◽  
Annealing Method

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 Rapidly fabricating large-scale plasmonic silver nanosphere arrays with sub-20 nm gap on Si-pyramids by inverted annealing for highly sensitive SERS detection

RSC Advances ◽  
2017 ◽  
Vol 7 (19) ◽  
pp. 11578-11584 ◽  
Author(s):  
Yujin Wang ◽  
Yang Yang ◽  
Yu Sun ◽  
Baogang Quan ◽  
Yunlong Li ◽  
...  
Keyword(s):  
Large Scale ◽  
Highly Sensitive ◽  
Sers Detection ◽  
20 Nm ◽  
Annealing Method

An inverted annealing method is developed to fabricate rapidly plasmonic silver nanosphere arrays with sub-20 nm gaps for highly sensitive SERS detection.

scholarly journals Biermann battery as a source of astrophysical magnetic fields

2021 ◽  
Vol 30 (1) ◽  
pp. 127-131
Author(s):  
Evgeny A. Mikhailov ◽  
Ruben R. Andreasyan
Keyword(s):  
Magnetic Field ◽  
Magnetic Fields ◽  
Large Scale ◽  
Small Scale ◽  
Radio Waves ◽  
Dynamo Mechanism ◽  
Alpha Effect ◽  
Biermann Battery ◽  
Annealing Method ◽  
Initial Magnetic Field

Abstract A large number of galaxies have large-scale magnetic fields which are usually measured by the Faraday rotation of radio waves. Their origin is usually connected with the dynamo mechanism which is based on differential rotation of the interstellar medium and alpha-effect characterizing the helicity of the small-scale motions. However, it is necessary to have initial magnetic field which cannot be generated by the dynamo. One of the possible mechanisms is connected with the Biermann battery which acts because of different masses of protons and electrons passing from the central object. They produce circular currents which induce the vertical magnetic field. As for this field we can obtain the integral equation which can be solved by simulated annealing method which is widely used in different branches of mathematics

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.

An Improved Noise Quantum Annealing Method for TSP

2020 ◽  
Vol 59 (12) ◽  
pp. 3737-3755
Author(s):  
Yumin Dong ◽  
Zhijie Huang
Keyword(s):  
Quantum Annealing ◽  
Annealing Method

Adiabatic Quantum Computing and Quantum Annealing

2020 ◽  
Author(s):  
Erica K. Grant ◽  
Travis S. Humble
Keyword(s):  
Quantum Computing ◽  
Quantum Computation ◽  
Large Scale ◽  
Optimization Problems ◽  
Quantum Annealing ◽  
Adiabatic Condition ◽  
Physical Systems ◽  
Adiabatic Quantum Computing ◽  
Combinatorial Optimization Problems ◽  
Computational Performance

Adiabatic quantum computing (AQC) is a model of computation that uses quantum mechanical processes operating under adiabatic conditions. As a form of universal quantum computation, AQC employs the principles of superposition, tunneling, and entanglement that manifest in quantum physical systems. The AQC model of quantum computing is distinguished by the use of dynamical evolution that is slow with respect to the time and energy scales of the underlying physical systems. This adiabatic condition enforces the promise that the quantum computational state will remain well-defined and controllable thus enabling the development of new algorithmic approaches. Several notable algorithms developed within the AQC model include methods for solving unstructured search and combinatorial optimization problems. In an idealized setting, the asymptotic complexity analyses of these algorithms indicate computational speed-ups may be possible relative to state-of-the-art conventional methods. However, the presence of non-ideal conditions, including non-adiabatic dynamics, residual thermal excitations, and physical noise complicate the assessment of the potential computational performance. A relaxation of the adiabatic condition is captured in the complementary computational heuristic of quantum annealing, which accommodates physical systems operating at finite temperature and in open environments. While quantum annealing (QA) provides a more accurate model for the behavior of actual quantum physical systems, the possibility of non-adiabatic effects obscures a clear separation with conventional computing complexity. A series of technological advances in the control of quantum physical systems have enabled experimental AQC and QA. Prominent examples include demonstrations using superconducting electronics, which encode quantum information in the magnetic flux induced by a weak current operating at cryogenic temperatures. A family of devices developed specifically for unconstrained optimization problems has been applied to solve problems in specific domains including logistics, finance, material science, machine learning, and numerical analysis. An accompanying infrastructure has also developed to support these experimental demonstrations and to enable access of a broader community of users. Although AQC is most commonly applied in superconducting technologies, alternative approaches include optically trapped neutral atoms and ion-trap systems. The significant progress in the understanding of AQC has revealed several open topics that continue to motivate research into this model of quantum computation. Foremost is the development of methods for fault-tolerant operation that will ensure the scalability of AQC for solving large-scale problems. In addition, unequivocal experimental demonstrations that differentiate the computational power of AQC and its variants from conventional computing approaches are needed. This will also require advances in the fabrication and control of quantum physical systems under the adiabatic restrictions.

scholarly journals Traffic signal optimization on a square lattice with quantum annealing

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Daisuke Inoue ◽  
Akihisa Okada ◽  
Tadayoshi Matsumori ◽  
Kazuyuki Aihara ◽  
Hiroaki Yoshida
Keyword(s):  
Intelligent Transportation Systems ◽  
Large Scale ◽  
Control Method ◽  
Traffic Signals ◽  
Transportation Systems ◽  
Square Lattice ◽  
Quantum Annealing ◽  
Signal Optimization ◽  
Global Control ◽  
Parameter Ranges

AbstractThe spread of intelligent transportation systems in urban cities has caused heavy computational loads, requiring a novel architecture for managing large-scale traffic. In this study, we develop a method for globally controlling traffic signals arranged on a square lattice by means of a quantum annealing machine, namely the D-Wave quantum annealer. We first formulate a signal optimization problem that minimizes the imbalance of traffic flows in two orthogonal directions. Then we reformulate this problem as an Ising Hamiltonian, which is compatible with quantum annealers. The new control method is compared with a conventional local control method for a large 50-by-50 city, and the results exhibit the superiority of our global control method in suppressing traffic imbalance over wide parameter ranges. Furthermore, the solutions to the global control method obtained with the quantum annealing machine are better than those obtained with conventional simulated annealing. In addition, we prove analytically that the local and the global control methods converge at the limit where cars have equal probabilities for turning and going straight. These results are verified with numerical experiments.

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