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Dynamical Frustration in ANNNI Model and Annealing
Simulated annealing is usually applied to systems with frustration, like spin glasses and optimisation problems, where the energy landscape is...
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Combinatorial Optimization and the Physics of Disordered Systems
The purpose of this chapter of this monograph is to confront the reader with a number of optimization algorithms that are exact and polynomial in...
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Ergodicity, Replica Symmetry, Spin Glass and Quantum Phase Transition
This pedagogical lecture note is aimed at a tutorial introduction to the essential concepts of spin glass with a focus on quantum spin glass in order...
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Decoherence and Quantum Couplings in a Noisy Environment
In this chapter, I will review the established theory of quantum systems coupled to noisy condensed-phase environments, emphasising the central role...
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Finding Exponential Product Formulas of Higher Orders
In the present article, we review the progress in the last two decades of the work on the Suzuki-Trotter decomposition, or the exponential product...
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Exploring Complex Landscapes with Classical Monte Carlo
Nowadays, the annealing concept is useful in (at least) two different fields, namely Physics and Optimization. The annealing strategy was well known...
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Quantum Spin Glasses
In this chapter of this monograph we want to provide an overview on the current status of our knowledge on the theory of quantum spin glasses. Spin...
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Deterministic and Stochastic Quantum Annealing Approaches
The idea of quantum annealing (QA) is a late offspring of the celebrated simulated thermal annealing by Kirkpatrick et al. [1]. In simulated...
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Simulated Quantum Annealing by the Real-time Evolution
It has been revealed during the last few decades that approaches originating from the physics succeeds in solving combinatorial optimization problems...
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Transverse Ising Model, Glass and Quantum Annealing
In many physical systems, cooperative interactions between spin-like (two-state) degrees of freedom tend to establish some kind of order in the...
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Quantum Spin Glasses Quantum Annealing, and Probabilistic Information Processing
Recently, problems of information processing were investigated from the statistical mechanical point of view [1]. Among them, image restoration (see...
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Quantum Annealing of a ±J Spin Glass and a Kinetically Constrained System
Thermal annealing [1] is known to be a very general and useful method for obtaining approximate solutions of multi-variable optimization problems....
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Experiments on Quantum Annealing
The standard deterministic, gate-based computation paradigms underlying modern digital computing are not those that nature uses to perform complex...
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A Brief Review of Bilevel Optimization Techniques and Their Applications
Bilevel optimization is an area of applied mathematics that deals with hierarchical decision-making processes, where a decision at one level affects...
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Optimization of Concrete Chimneys Considering Random Underground Blast and Temperature Effects
Generally, design of concrete chimney is accomplished considering wind or earthquake loadings disregarding the blast effects. However, in recent...
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Optimization and Machine Learning Algorithms for Intelligent Microwave Sensing: A Review
Microwave sensors find growing applications in remote sensing, material analysis, and process monitoring. Yet, the intricate interplay between...
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Deep Learning in Stock Market: Techniques, Purpose, and Challenges
In recent years, deep learning has witnessed a growing interest due to its ability to solve complex problems and offer accurate results. It has found...
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Solving Crop** Pattern Optimization Problems Using Robust Positive Mathematical Programming
Agricultural activities occur in an environment that is constantly changing. In each crop** season, farmers must make management decisions based on...
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Develo** Housing at Sea: A Case for Humanitarian Assistance and Residency Vessels
The ship** industry, and especially, the cruise and ferry sector have experienced substantial blue growth in recent years. This chapter aims to...
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Chaotic Shuffled Frog Lea** Algorithm
To improve the efficiency of meta-heuristic algorithms, a strong and efficient method is to divide the entire population into small complexes and...