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Applications of Quantum Mechanical Techniques to Areas Outside of Quantum Mechanics

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Book Series: Frontiers Research Topics ISSN: 16648714 ISBN: 9782889454273 Year: Pages: 162 DOI: 10.3389/978-2-88945-427-3 Language: English
Publisher: Frontiers Media SA
Subject: Science (General) --- Physics (General)
Added to DOAB on : 2018-11-16 17:17:57
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This book deals with applications of quantum mechanical techniques to areas outside of quantum mechanics, so-called quantum-like modeling. Research in this area has grown over the last 15 years. But even already more than 50 years ago, the interaction between Physics Nobelist Pauli and the psychologist Carl Jung in the 1950's on seeking to find analogous uses of the complementarity principle from quantum mechanics in psychology needs noting. This book does NOT want to advance that society is quantum mechanical! The macroscopic world is manifestly not quantum mechanical. But this rules not out that one can use concepts and the mathematical apparatus from quantum physics in a macroscopic environment. A mainstay ingredient of quantum mechanics, is 'quantum probability' and this tool has been proven to be useful in the mathematical modelling of decision making. In the most basic experiment of quantum physics, the double slit experiment, it is known (from the works of A. Khrennikov) that the law of total probability is violated. It is now well documented that several decision making paradoxes in psychology and economics (such as the Ellsberg paradox) do exhibit this violation of the law of total probability. When data is collected with experiments which test 'non-rational' decision making behaviour, one can observe that such data often exhibits a complex non-commutative structure, which may be even more complex than if one considers the structure allied to the basic two slit experiment. The community exploring quantum-like models has tried to address how quantum probability can help in better explaining those paradoxes. Research has now been published in very high standing journals on resolving some of the paradoxes with the mathematics of quantum physics. The aim of this book is to collect the contributions of world's leading experts in quantum like modeling in decision making, psychology, cognition, economics, and finance.

Quantum Structures in Cognitive and Social Science

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Book Series: Frontiers Research Topics ISSN: 16648714 ISBN: 9782889198764 Year: Pages: 168 DOI: 10.3389/978-2-88919-876-4 Language: English
Publisher: Frontiers Media SA
Subject: Science (General) --- Psychology
Added to DOAB on : 2016-01-19 14:05:46
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Traditional approaches to cognitive psychology correspond with a classical view of logic and probability theory. More specifically, one typically assumes that cognitive processes of human thought are founded on the Boolean structures of classical logic, while the probabilistic aspects of these processes are based on the Kolmogorovian structures of classical probability theory. However, growing experimental evidence indicates that the models founded on classical structures systematically fail when human decisions are at stake. These experimental deviations from classical behavior have been called `paradoxes’, `fallacies’, `effects’ or `contradictions’, depending on the specific situation where they appear. But, they involve a broad spectrum of cognitive and social science domains, ranging from conceptual combination to decision making under uncertainty, behavioral economics, and linguistics. This situation has constituted a serious drawback to the development of various disciplines, like cognitive science, linguistics, artificial intelligence, economic modeling and behavioral finance. A different approach to cognitive psychology, initiated two decades ago, has meanwhile matured into a new domain of research, called ‘quantum cognition’. Its main feature is the use of the mathematical formalism of quantum theory as modeling tool for these cognitive situations where traditional classically based approaches fail. Quantum cognition has recently attracted the interest of important journals and editing houses, academic and funding institutions, popular science and media. Specifically, within a quantum cognition approach, one assumes that human decisions do not necessarily obey the rules of Boolean logic and Kolmogorovian probability, and can on the contrary be modeled by the quantum-mechanical formalism. Different concrete quantum-theoretic models have meanwhile been developed that successfully represent the cognitive situations that are classically problematical, by explaining observed deviations from classicality in terms of genuine quantum effects, such as `contextuality’, `emergence’, `interference’, `superposition’, `entanglement’ and `indistinguishability’. In addition, the validity of these quantum models is convincingly confirmed by new experimental tests. We also stress that, since the use of a quantum-theoretic framework is mainly for modeling purposes, the identification of quantum structures in cognitive processes does not presuppose (without being incompatible with it) the existence of microscopic quantum processes in the human brain. In this Research Topic, we review the major achievements that have been obtained in quantum cognition, by providing an accurate picture of the state-of-the-art of this emerging discipline. Our overview does not pretend to be either complete or exhaustive. But, we aim to introduce psychologists and social scientists to this challenging new research area, encouraging them, at the same time, to consider its promising results. It is our opinion that, if continuous progress in this domain can be realized, quantum cognition can constitute an important breakthrough in cognitive psychology, and potentially open the way towards a new scientific paradigm in social science.

Quantum Mechanical/Molecular Mechanical Approaches for the Investigation of Chemical Systems - Recent Developments and Advanced Applications

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Book Series: Frontiers Research Topics ISSN: 16648714 ISBN: 9782889456260 Year: Pages: 188 DOI: 10.3389/978-2-88945-626-0 Language: English
Publisher: Frontiers Media SA
Subject: Science (General) --- Chemistry (General)
Added to DOAB on : 2019-01-23 14:53:43
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The QM/MM method, short for quantum mechanical/molecular mechanical, is a highly versatile approach for the study of chemical phenomena, combining the accuracy of quantum chemistry to describe the region of interest with the efficiency of molecular mechanical potentials to represent the remaining part of the system. Originally conceived in the 1970s by the influential work of the the Nobel laureates Martin Karplus, Michael Levitt and Arieh Warshel, QM/MM techniques have evolved into one of the most accurate and general approaches to investigate the properties of chemical systems via computational methods. Whereas the first applications have been focused on studies of organic and biomolecular systems, a large variety of QM/MM implementations have been developed over the last decades, extending the range of applicability to address research questions relevant for both solution and solid-state chemistry as well. Despite approaching their 50th anniversary in 2022, the formulation of improved QM/MM methods is still an active field of research, with the aim to (i) extend the applicability to address an even broader range of research questions in chemistry and related disciplines, and (ii) further push the accuracy achieved in the QM/MM description beyond that of established formulations. While being a highly successful approach on its own, the combination of the QM/MM strategy with other established theoretical techniques greatly extends the capabilities of the computational approaches. For instance the integration of a suitable QM/MM technique into the highly successful Monte-Carlo and molecular dynamics simulation protocols enables the description of the chemical systems on the basis of an ensemble that is in part constructed on a quantum-mechanical basis. This eBook presents the contributions of a recent Research Topic published in Frontiers in Chemistry, that highlight novel approaches as well as advanced applications of QM/MM method to a broad variety of targets. In total 2 review articles and 10 original research contributions from 48 authors are presented, covering 12 different countries on four continents. The range of research questions addressed by the individual contributions provide a lucid overview on the versatility of the QM/MM method, and demonstrate the general applicability and accuracy that can be achieved for different problems in chemical sciences. Together with the development of improved algorithms to enhance the capabilities of quantum chemical methods and the continuous advancement in the capacities of computational resources, it can be expected that the impact of QM/MM methods in chemical sciences will be further increased already in the near future.

Quantitative Biology: Dynamics of Living Systems

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Book Series: Frontiers Research Topics ISSN: 16648714 ISBN: 9782889452132 Year: Pages: 136 DOI: 10.3389/978-2-88945-213-2 Language: English
Publisher: Frontiers Media SA
Subject: Biology --- Neurology --- Physiology --- Science (General)
Added to DOAB on : 2017-10-13 14:57:01
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With the emergence of Systems Biology, there is a greater realization that the whole behavior of a living system may not be simply described as the sum of its elements. To represent a living system using mathematical principles, practical quantities with units are required. Quantities are not only the bridge between mathematical description and biological observations; they often stand as essential elements similar to genome information in genetics. This important realization has greatly rejuvenated research in the area of Quantitative Biology. Because of the increased need for precise quantification, a new era of technological development has opened. For example, spatio-temporal high-resolution imaging enables us to track single molecule behavior in vivo. Clever artificial control of experimental conditions and molecular structures has expanded the variety of quantities that can be directly measured. In addition, improved computational power and novel algorithms for analyzing theoretical models have made it possible to investigate complex biological phenomena. This research topic is organized on two aspects of technological advances which are the backbone of Quantitative Biology: (i) visualization of biomolecules, their dynamics and function, and (ii) generic technologies of model optimization and numeric integration. We have also included articles highlighting the need for new quantitative approaches to solve some of the long-standing cell biology questions. In the first section on visualizing biomolecules, four cutting-edge techniques are presented. Ichimura et al. provide a review of quantum dots including their basic characteristics and their applications (for example, single particle tracking). Horisawa discusses a quick and stable labeling technique using click chemistry with distinct advantages compared to fluorescent protein tags. The relatively small physical size, stability of covalent bond and simple metabolic labeling procedures in living cells provides this type of technology a potential to allow long-term imaging with least interference to protein function. Obien et al. review strategies to control microelectrodes for detecting neuronal activity and discuss techniques for higher resolution and quality of recordings using monolithic integration with on-chip circuitry. Finally, the original research article by Amariei et al. describes the oscillatory behavior of metabolites in bacteria. They describe a new method to visualize the periodic dynamics of metabolites in large scale cultures populations. These four articles contribute to the development of quantitative methods visualizing diverse targets: proteins, electrical signals and metabolites. In the second section of the topic, we have included articles on the development of computational tools to fully harness the potential of quantitative measurements through either calculation based on specific model or validation of the model itself. Kimura et al. introduce optimization procedures to search for parameters in a quantitative model that can reproduce experimental data. They present four examples: transcriptional regulation, bacterial chemotaxis, morphogenesis of tissues and organs, and cell cycle regulation. The original research article by Sumiyoshi et al. presents a general methodology to accelerate stochastic simulation efforts. They introduce a method to achieve 130 times faster computation of stochastic models by applying GPGPU. The strength of such accelerated numerical calculation are sometimes underestimated in biology; faster simulation enables multiple runs and in turn improved accuracy of numerical calculation which may change the final conclusion of modeling study. This also highlights the need to carefully assess simulation results and estimations using computational tools.

New Frontiers in Multiscale Modelling of Advanced Materials

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Book Series: Frontiers Research Topics ISSN: 16648714 ISBN: 9782889197552 Year: Pages: 91 DOI: 10.3389/978-2-88919-755-2 Language: English
Publisher: Frontiers Media SA
Subject: General and Civil Engineering --- Materials
Added to DOAB on : 2016-04-07 11:22:02
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Atomistic simulations, based on ab-initio and semi-empirical approaches, are nowadays widespread in many areas of physics, chemistry and, more recently, biology. Improved algorithms and increased computational power widened the areas of application of these computational methods to extended materials of technological interest, in particular allowing unprecedented access to the first-principles investigation of their electronic, optical, thermodynamical and mechanical properties, even where experiments are not available. However, for a big impact on the society, this rapidly growing field of computational approaches to materials science has to face the unfavourable scaling with the system size, and to beat the time-scale bottleneck. Indeed, many phenomena, such as crystal growth or protein folding for example, occur in a space/time scale which is normally out of reach of present simulations. Multi-scale approaches try to combine different scale algorithms along with matching procedures in order to bridge the gap between first-principles and continuum-level simulations. This Research Topic aims at the description of recent advances and applications in these two emerging fields of ab-inito and multi-scale materials modelling for both ground and excited states. A variety of theoretical and computational techniques are included along with the application of these methods to systems at increasing level of complexity, from nano to micro. Crossing the borders between several computational, theoretical and experimental techniques, this Research Topic aims to be of interest to a broad community, including experimental and theoretical physicists, chemists and engineers interested in materials research in a broad sense.

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