Warm Dense Matter (WDM) occupies a loosely defined region of phase space intermediate between solid, liquid, gas, and plasma, and typically shares characteristics of two or more of these phases. WDM is generally associated with the combination of strongly coupled ions and moderately degenerate electrons, and careful attention to quantum physics and electronic structure is essential. The lack of a small perturbation parameter greatly limits approximate attempts at its accurate description. Since WDM resides at the intersection of solid state and high energy density physics, many high energy density physics (HEDP) experiments pass through this difficult region of phase space. Thus, understanding and modeling WDM is key to the success of experiments on diverse facilities. These include the National Ignition Campaign centered on the National Ignition Facility (NIF), pulsed-power driven experiments on the Z machine, ion-beam-driven WDM experiments on the NDCX-II, and fundamental WDM research at the Linear Coherent Light Source (LCLS). Warm Dense Matter is also ubiquitous in planetary science and astrophysics, particularly with respect to unresolved questions concerning the structure and age of the gas giants, the nature of exosolar planets, and the cosmochronology of white dwarf stars. In this book we explore established and promising approaches to the modeling of WDM, foundational issues concerning the correct theoretical description of WDM, and the challenging practical issues of numerically modeling strongly coupled systems with many degrees of freedom.

This book highlights the proceedings of the International Conference on Atomic, Molecular, Optical and Nano-Physics with Applications (CAMNP 2019), organized by the Department of Applied Physics, Delhi Technological University, New Delhi, India. It presents experimental and theoretical studies of atoms, ions, molecules and nanostructures both at the fundamental level and on the application side using advanced technology. It highlights how modern tools of high-field and ultra-fast physics are no longer merely used to observe nature but can be used to reshape and redirect atoms, molecules, particles or radiation. It brings together leading researchers and professionals on the field to present and discuss the latest finding in the following areas, but not limited to: Atomic and Molecular Structure, Collision Processes, Data Production and Applications Spectroscopy of Solar and Stellar Plasma Intense Field, Short Pulse Laser and Atto-Second Physics Laser Technology, Quantum Optics and applications Bose Einstein condensation Nanomaterials and Nanoscience Nanobiotechnolgy and Nanophotonics Nano and Micro-Electronics Computational Condensed Matter Physics

This volume contains contributed survey papers from the main speakers at the LMS/EPSRC Symposium “Building bridges: connections and challenges in modern approaches to numerical partial differential equations”. This meeting took place in July 8-16, 2014, and its main purpose was to gather specialists in emerging areas of numerical PDEs, and explore the connections between the different approaches. The type of contributions ranges from the theoretical foundations of these new techniques, to the applications of them, to new general frameworks and unified approaches that can cover one, or more than one, of these emerging techniques.

This volume presents a series of articles concerning current important topics in quantum chemistry. - 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

Machine learning and artificial intelligence have propelled research across various molecular science disciplines thanks to the rapid progress in computing hardware, algorithms, and data accumulation. This book presents recent machine learning applications in the broad research field of molecular sciences. Written by an international group of renowned experts, this edited volume covers both the machine learning methodologies and state-of-the-art machine learning applications in a wide range of topics in molecular sciences, from electronic structure theory to nuclear dynamics of small molecules, to the design and synthesis of large organic and biological molecules. This book is a valuable resource for researchers and students interested in applying machine learning in the research of molecular sciences.

This textbook teaches finite element methods from a computational point of view. It focuses on how to develop flexible computer programs with Python, a programming language in which a combination of symbolic and numerical tools is used to achieve an explicit and practical derivation of finite element algorithms. The finite element library FEniCS is used throughout the book, but the content is provided in sufficient detail to ensure that students with less mathematical background or mixed programming-language experience will equally benefit. All program examples are available on the Internet.

The purpose of this book is to convey to the worldwide scientific community the rapid and enthusiastic progress of state-of-the-art quantum chemistry. Quantum chemistry continues to grow with remarkable success particularly due to rapid progress in supercomputers. The usefulness of quantum chemistry is almost limitless. Its application covers not only physical chemistry but also organic and inorganic chemistry, physics, and life sciences. This book deals with all of these topics. Frontiers of Quantum Chemistry is closely related to the symposium of the same name held at Kwansei Gakuin University at Nishinomiya, Japan, in November 2015. The book's contributors, however, include not only invited speakers at the symposium but also many other distinguished scientists from wide areas of quantum chemistry around the world.