Quantum chemistry is simulating atomistic systems according to the laws of quantum mechanics, and such simulations are essential for our understanding of the world and for technological progress. Machine learning revolutionizes quantum chemistry by increasing simulation speed and accuracy and obtaining new insights. However, for nonspecialists, learning about this vast field is a formidable challenge. Quantum Chemistry in the Age of Machine Learning covers this exciting field in detail, ranging from basic concepts to comprehensive methodological details to providing detailed codes and hands-on tutorials. Such an approach helps readers get a quick overview of existing techniques and provides an opportunity to learn the intricacies and inner workings of state-of-the-art methods. The book describes the underlying concepts of machine learning and quantum chemistry, machine learning potentials and learning of other quantum chemical properties, machine learning-improved quantum chemical methods, analysis of Big Data from simulations, and materials design with machine learning. Drawing on the expertise of a team of specialist contributors, this book serves as a valuable guide for both aspiring beginners and specialists in this exciting field. - Compiles advances of machine learning in quantum chemistry across different areas into a single resource - Provides insights into the underlying concepts of machine learning techniques that are relevant to quantum chemistry - Describes, in detail, the current state-of-the-art machine learning-based methods in quantum chemistry

Advances in Quantum Chemistry presents surveys of current topics in this rapidly developing field one that has emerged at the cross section of the historically established areas of mathematics, physics, chemistry, and biology. It features detailed reviews written by leading international researchers. In this volume the readers are presented with an exciting combination of themes. - Presents surveys of current topics in this rapidly-developing field that has emerged at the cross section of the historically established areas of mathematics, physics, chemistry and biology - Features detailed reviews written by leading international researchers - Topics include: New advances in Quantum Chemical Physics; Original theory and a contemporary overview of the field of Theoretical Chemical Physics; State-of-the-Art calculations in Theoretical Chemistry

This volume presents the current status of software development in the field of computational and theoretical chemistry and gives an overview of the emerging trends. The challenges of maintaining the legacy codes and their adaptation to the rapidly growing hardware capabilities and the new programming environments are surveyed in a series of topical reviews written by the core developers and maintainers of the popular quantum chemistry and molecular dynamics programs. Special emphasis is given to new computational methodologies and practical aspects of their implementation and application in the computational chemistry codes. Modularity of the computational chemistry software is an emerging concept that enables to bypass the development and maintenance bottleneck of the legacy software and to customize the software using the best available computational procedures implemented in the form of self-contained modules. Perspectives on modular design of the computer programs for modeling molecular electronic structure, non-adiabatic dynamics, kinetics, as well as for data visualization are presented by the researchers actively working in the field of software development and application. This volume is of interest to quantum and computational chemists as well as experimental chemists actively using and developing computational software for their research. Chapters "MLatom 2: An Integrative Platform for Atomistic Machine Learning” and “Evolution of the Automatic Rhodopsin Modeling (ARM) Protocol" are available open access under a CC BY 4.0 License via link.springer.com.

Chemical modelling covers a wide range of disciplines, and this book is the first stop for any chemist, materials scientist, biochemist, or molecular physicist wishing to acquaint themselves with major developments in the applications and theory of chemical modelling. Containing both comprehensive and critical reviews, it is a convenient reference to the current literature. Coverage includes, but is not limited to, considerations towards rigorous foundations for the natural-orbital representation of molecular electronic transitions, quantum and classical embedding schemes for optical properties, machine learning for excited states, ultrafast and wave function-based electron dynamics, and attosecond chemistry.

EVOLUTION and APPLICATIONS of QUANTUM COMPUTING The book is about the Quantum Model replacing traditional computing’s classical model and gives a state-of-the-art technical overview of the current efforts to develop quantum computing and applications for Industry 4.0. A holistic approach to the revolutionary world of quantum computing is presented in this book, which reveals valuable insights into this rapidly emerging technology. The book reflects the dependence of quantum computing on the physical phenomenon of superposition, entanglement, teleportation, and interference to simplify difficult mathematical problems which would have otherwise taken years to derive a definite solution for. An amalgamation of the information provided in the multiple chapters will elucidate the revolutionary and riveting research being carried out in the brand-new domain encompassing quantum computation, quantum information and quantum mechanics. Each chapter gives a concise introduction to the topic. The book comprises 18 chapters and describes the pioneering work on the interaction between artificial intelligence, machine learning, and quantum computing along with their applications and potential role in the world of big data. Subjects include: Combinational circuits called the quantum multiplexer with secured quantum gate (CSWAP); Detecting malicious emails and URLs by using quantum text mining algorithms to distinguish between phishing and benign sites; Quantum data traffic analysis for intrusion detection systems; Applications of quantum computation in banking, netnomy and vehicular ad-hoc networks, virtual reality in the education of autistic children, identifying bacterial diseases and accelerating drug discovery; The critical domain of traditional classical cryptography and quantum cryptography. Audience The book will be very useful for researchers in computer science, artificial intelligence and quantum physics as well as students who want to understand the history of quantum computing along with its applications and have a technical state-of-the-art overview.

Theoretical and Computational Photochemistry: Fundamentals, Methods, Applications and Synergy with Experimental Approaches provides a comprehensive overview of photoactive systems and photochemical processes. After an introduction to photochemistry, the book discusses the key computational chemistry methods applied to the study of light-induced processes over the past decade, and further outlines recent research topics to which these methods have been applied. By discussing the synergy between experimental and computational data, the book highlights how theoretical studies could facilitate understanding experimental findings. This helpful guide is for both theoretical chemists and experimental photochemistry researchers interested in utilizing computational photochemistry methods for their own work. - Reviews the fundamentals of photochemistry, helping those new to the field in understanding key concepts - Provides detailed guidance and comparison of computational and theoretical methods, highlighting the suitability of each method for different case studies - Outlines current applications to encourage discussion of the synergy between experimental and computational data, and inspiring further application of these methods to other photochemical processes

Deep, theoretical resource on the essence of chemistry, explaining the sixteen most important concepts including redox states and bond types Exploring Chemical Concepts Through Theory and Computation provides a comprehensive account of how the three widely used theoretical frameworks of valence bond theory, molecular orbital theory, and density functional theory, along with a variety of important chemical concepts, can between them describe and efficiently and reliably predict key chemical parameters and phenomena. By comparing the three main theoretical frameworks, readers will become competent in choosing the right modeling approach for their task. The authors go beyond a simple comparison of existing algorithms to show how data-driven theories can explain why chemical compounds behave the way they do, thus promoting a deeper understanding of the essence of chemistry. The text is contributed to by top theoretical and computational chemists who have turned computational chemistry into today's data-driven and application-oriented science. Exploring Chemical Concepts Through Theory and Computation discusses topics including: Orbital-based approaches, density-based approaches, chemical bonding, partial charges, atoms in molecules, oxidation states, aromaticity and antiaromaticity, and acidity and basicity Electronegativity, hardness, softness, HSAB, sigma-hole interactions, charge transport and energy transfer, and homogeneous and heterogeneous catalysis Electrophilicity, nucleophilicity, cooperativity, frustration, homochirality, and energy decomposition Chemical concepts in solids, excited states, spectroscopy and machine learning, and catalysis and machine learning, and as well as key connections between related concepts Aimed at both novice and experienced computational, theoretical, and physical chemists, Exploring Chemical Concepts Through Theory and Computation is an essential reference to gain a deeper, more advanced holistic understanding of the field of chemistry as a whole.

This primer helps the reader understand the basic categories of molecular representations and provides computational tools to generate molecular descriptors in each of these categories. After reading this primer, you will be able to use various methods to generate machine and/or human interpretable representations of molecular systems for inputs to machine learning models or for general chemical data science applications.

​The ten-volume set LNCS 12949 – 12958 constitutes the proceedings of the 21st International Conference on Computational Science and Its Applications, ICCSA 2021, which was held in Cagliari, Italy, during September 13 – 16, 2021. The event was organized in a hybrid mode due to the Covid-19 pandemic.The 466 full and 18 short papers presented in these books were carefully reviewed and selected from 1588 submissions. Part X of the set includes the proceedings of the following workshops: ​International Workshop on Smart and Sustainable Island Communities (SSIC 2021); International Workshop on Science, Technologies and Policies to Innovate Spatial Planning (STP4P 2021); International Workshop on Sustainable Urban Energy Systems (SUREN-SYS 2021); International Workshop on Ports of the future - smartness and sustainability (SmartPorts 2021); International Workshop on Smart Tourism (SmartTourism 2021); International Workshop on Space Syntax for Cities in Theory and Practice (Syntax_City 2021); International Workshop on Theoretical and Computational Chemistryand its Applications (TCCMA 2021); International Workshop on Urban Form Studies (UForm 2021); International Workshop on Urban Space Accessibility and Safety (USAS2021); International Workshop on Virtual and Augmented Reality and Ap-plcations (VRA 2021); International Workshop on Advanced and Computational Methods for Earth Science applications (WACM4ES 2021).

In a world driven by technology and data, classical computing faces limitations in tackling complex challenges like climate modeling and financial risk assessment. These barriers impede our aspirations to revolutionize industries and solve intricate real-world problems. To bridge this gap, we must embrace quantum computing. Edited by Alex Khang PH, Principles and Applications of Quantum Computing is a transformative solution to this challenge. It delves into the interdisciplinary realms of computer science, physics, and mathematics, unveiling the incredible potential of quantum computing, which outperforms supercomputers by 158 million times. This technology, rooted in quantum mechanics, offers solutions to global problems and opens new frontiers in AI, cybersecurity, finance, drug development, and more. By engaging with this book, you become a pioneer in the quantum revolution, contributing to reshaping the limits of what's achievable in our digital age.