Catalogue Search | MBRL
Are you sure you want to remove the book from the shelf?
{{itemTitle}}
110,963
result(s) for
"Computational physics"
Sort by:
Quantum physics
\"The plain-English guide to understanding quantum physics. Mastering quantum physics is no easy feat, but with the help of Quantum Physics For Dummies you can work at your own pace to unlock key concepts and fascinating facts. Packed with invaluable explanations, equations, and step-by-step instructions, this book makes a challenging subject much more accessible. Great for college students taking a quantum physics course, Quantum Physics For Dummies offers complete coverage of the subject, along with numerous examples to help you tackle the tough stuff. The Schrodinger Equation, the foundations of quantum physics, vector notation, scattering theory, angular momentum--it's all in here. This handy guide helps you prepare for exams and succeed at learning quantum physics\"--Amazon.com.
Book
Challenges in nanofabrication for efficient optical metasurfaces
Optical metasurfaces have raised immense expectations as cheaper and lighter alternatives to bulk optical components. In recent years, novel components combining multiple optical functions have been proposed pushing further the level of requirement on the manufacturing precision of these objects. In this work, we study in details the influence of the most common fabrication errors on the optical response of a metasurface and quantitatively assess the tolerance to fabrication errors based on extensive numerical simulations. We illustrate these results with the design, fabrication and characterization of a silicon nanoresonator-based metasurface that operates as a beam deflector in the near-infrared range.
Journal Article
Wonders beyond numbers : a brief history of all things mathematical
Running in something approaching chronological order, this book shows that every breakthrough in math represents a single step forward, resting on the work of others, and brings to life the importance of numbers, shapes, and patterns in the world around us.
Book
Statistical Approach to Quantum Field Theory
This book opens with a self-contained introduction to path integrals in Euclidean quantum mechanics and statistical mechanics, and moves on to cover lattice field theory, spin systems, gauge theories and more. Each chapter ends with illustrative problems.
eBook
SciPy 1.0: fundamental algorithms for scientific computing in Python
SciPy is an open-source scientific computing library for the Python programming language. Since its initial release in 2001, SciPy has become a de facto standard for leveraging scientific algorithms in Python, with over 600 unique code contributors, thousands of dependent packages, over 100,000 dependent repositories and millions of downloads per year. In this work, we provide an overview of the capabilities and development practices of SciPy 1.0 and highlight some recent technical developments.
This Perspective describes the development and capabilities of SciPy 1.0, an open source scientific computing library for the Python programming language.
Journal Article
Neutron and weak-charge distributions of the 48Ca nucleus
What is the size of the atomic nucleus? This deceivably simple question is difficult to answer. Although the electric charge distributions in atomic nuclei were measured accurately already half a century ago, our knowledge of the distribution of neutrons is still deficient. In addition to constraining the size of atomic nuclei, the neutron distribution also impacts the number of nuclei that can exist and the size of neutron stars. We present an
ab initio
calculation of the neutron distribution of the neutron-rich nucleus
48
Ca. We show that the neutron skin (difference between the radii of the neutron and proton distributions) is significantly smaller than previously thought. We also make predictions for the electric dipole polarizability and the weak form factor; both quantities that are at present targeted by precision measurements. Based on
ab initio
results for
48
Ca, we provide a constraint on the size of a neutron star.
Determining—and defining—the size of an atomic nucleus is far from easy. First-principles calculations now provide accurate information on the neutron distribution of the neutron-rich
48
Ca nucleus—and constraints on the size of a neutron star.
Journal Article
The role of non-equilibrium vibrational structures in electronic coherence and recoherence in pigment–protein complexes
Recent observations of oscillatory features in the optical response of photosynthetic complexes have revealed evidence for surprisingly long-lasting electronic coherences which can coexist with energy transport. These observations have ignited multidisciplinary interest in the role of quantum effects in biological systems, including the fundamental question of how electronic coherence can survive in biological surroundings. Here we show that the non-trivial spectral structures of protein fluctuations can generate non-equilibrium processes that lead to the spontaneous creation and sustenance of electronic coherence, even at physiological temperatures. Developing new advanced simulation tools to treat these effects, we provide a firm microscopic basis to successfully reproduce the experimentally observed coherence times in the Fenna–Matthews–Olson complex, and illustrate how detailed quantum modelling and simulation can shed further light on a wide range of other non-equilibrium processes which may be important in different photosynthetic systems.
Photosynthesis is remarkably efficient. The transport of optically generated excitons from absorbing pigments, through protein complexes, to reaction centres is nearly perfect. Simulations now uncover the microscopic mechanism that drives this coherent behaviour: interactions between the excitons and the vibrational modes of the pigment-protein complex.
Journal Article
Improved Architectures and Training Algorithms for Deep Operator Networks
Operator learning techniques have recently emerged as a powerful tool for learning maps between infinite-dimensional Banach spaces. Trained under appropriate constraints, they can also be effective in learning the solution operator of partial differential equations (PDEs) in an entirely self-supervised manner. In this work we analyze the training dynamics of deep operator networks (DeepONets) through the lens of Neural Tangent Kernel theory, and reveal a bias that favors the approximation of functions with larger magnitudes. To correct this bias we propose to adaptively re-weight the importance of each training example, and demonstrate how this procedure can effectively balance the magnitude of back-propagated gradients during training via gradient descent. We also propose a novel network architecture that is more resilient to vanishing gradient pathologies. Taken together, our developments provide new insights into the training of DeepONets and consistently improve their predictive accuracy by a factor of 10-50x, demonstrated in the challenging setting of learning PDE solution operators in the absence of paired input-output observations. All code and data accompanying this manuscript will be made publicly available at
https://github.com/PredictiveIntelligenceLab/ImprovedDeepONets
.
Journal Article
Machine Learning in High Energy Physics Community White Paper
Machine learning is an important applied research area in particle physics, beginning with applications to high-level physics analysis in the 1990s and 2000s, followed by an explosion of applications in particle and event identification and reconstruction in the 2010s. In this document we discuss promising future research and development areas in machine learning in particle physics with a roadmap for their implementation, software and hardware resource requirements, collaborative initiatives with the data science community, academia and industry, and training the particle physics community in data science. The main objective of the document is to connect and motivate these areas of research and development with the physics drivers of the High-Luminosity Large Hadron Collider and future neutrino experiments and identify the resource needs for their implementation. Additionally we identify areas where collaboration with external communities will be of great benefit.
Journal Article
Computing in physics education
Computing is central to the enterprise of physics but few undergraduate physics courses include it in their curricula. Here we discuss why and how to integrate computing into physics education.
Journal Article