The recent rapid innovations in supercomputer technology are changing the concepts of numerical calculations employed in solving a wide variety of nuclear many-body problems. The purpose of the XVII RCNP International Symposium on Innovative Computational Methods in Nuclear Many-Body Problems (INNOCOM97) was to discuss the frontiers of various computational methods and to exchange ideas in wide fields of nuclear physics. The subjects discussed at the symposium covered almost all the areas of nuclear physics.
The development of ion traps has spurred significant experimental activities able to link measurable quantities to the most fundamental aspects of physics. The first chapter sets the scene and motivates the use of ion traps with an in-depth survey of the low-energy electroweak sector of the standard model amenable to precision test. The next parts then introduce and review aspects of the theory, simulation and experimental implementation of such traps. Last but not least, two important applications, namely high resolution mass spectrometry in Penning traps and tests of fundamental physics - such as the CPT theorem - with trapped antiprotons are discussed. This volume bridges the gap between the graduate textbook and the research literature and will assist graduate students and newcomers to the field in quickly entering and mastering the subject matter.
The quantum nuclear many-body problem lies at the heart of low-energy nuclear physics and represents a fundamental challenge to our understanding of the universe. This book presents various many-body techniques used to describe nuclei from the basic interactions among nucleons. It provides a brief description of modern nuclear forces and their application in finite nuclei. It also includes an overview of several many-body techniques used in the field, including quantum Monte Carlo, configuration interaction, and coupled cluster methods. The book covers the key algorithms necessary to build out and/or use computer codes for simple problems. It also focuses on important high-performance computing aspects, modern computing languages, parallelization methods and libraries, and basic quantum many-body training.
Many-body nuclear physics is the bridge that takes us from the fundamental laws governing individual nucleons to understanding how groups of them interact together to form the nuclei that lie at the heart of all atoms-the building blocks of our universe. Many powerful techniques of classical computation have been developed over the years in order to study ever more complex nuclear systems. However, we seem to be approaching the limits of such classical techniques as the complexity of many-body quantum systems grows exponentially. Yet, the recent development of quantum computers offers one hope as they are predicted to provide a significant advantage over classical computers when tackling problems such as the quantum many-body problem. In this thesis, we focus on developing and applying algorithms to tackle various many-body nuclear physics problems that can be run on the near-term quantum computers of the current noisy intermediate-scale quantum (NISQ) era. As these devices are small and noisy, we focus our algorithms on various many-body toy models in order to gain insight and create a foundation upon which future algorithms will be built to tackle the intractable problems of our time. In the first part, we tailor current quantum algorithms to efficiently run on NISQ devices and apply them to three pairing models of many-body nuclear physics, the Lipkin model, the Richardson pairing model, and collective neutrino oscillations. For the first two models, we solve for the ground-state energy while for the third, we simulate the time evolution and characterize the entanglement. In the second part, we develop novel algorithms to increase the efficiency and applicability of current algorithms on NISQ devices. These include an algorithm that compresses circuit depth to allow for less noisy computation and a variational method to prepare an important class of quantum states. Error mitigation techniques used to improve the accuracy of results are also discussed. All together, this work provides a road map for applications of the quantum computers of tomorrow to solve what nuclear phenomena mystify us today.
The process of realizing the ground state of some typical (frustrated) quantum many-body systems, starting from the ‘disordered’ or excited states, can be formally mapped to the search of solutions for computationally hard problems. The dynamics through the critical point, in between, are therefore extremely crucial. In the context of such computational optimization problems, the dynamics (of rapid quenching or slow annealing), while tuning the appropriate elds or uctuations, in particular while crossing the quantum critical point, are extremely intriguing and are being investigated these days intensively. Several successful methods and tricks are now well established. This volume gives a collection of introductory reviews on such developments written by well-known experts. It concentrates on quantum phase transitions and their dynamics as the transition or critical points are crossed. Both the quenching and annealing dynamics are extensively covered. We hope these timely reviews will inspire the young researchers to join and c- tribute to this fast-growing, intellectually challenging, as well as technologically demanding eld. We are extremely thankful to the contributors for their intensive work and pleasant cooperations. We are also very much indebted to Kausik Das for his help in compiling this book. Finally, we express our gratitude to Johannes Zittartz, Series Editor, LNP, and Christian Caron of physics editorial department of Springer for their encouragement and support.
Quantum many-body physics is the body of knowledge which studies systems of many interacting particles and the mathematical framework for calculating properties of these systems. Methods in many-body physics which use a first principles approach to solving the many-body Schrodinger equation are referred to as ab initio methods, and provide approximate solutions which are systematically improvable. Coupled cluster theory is an ab initio quantum many-body method which has been shown to provide accurate calculations of ground state energies for a wide range of systems in quantum chemistry and nuclear physics. Calculations of physical properties using ab initio many-body methods can be computationally expensive, requiring the development of efficient data structures, algorithms and techniques in high-performance computing to achieve numerical accuracy.Many physical systems of interest are difficult or impossible to measure experimentally, and so are reliant on predictive and accurate calculations from many-body theory. Neutron stars in particular are difficult to collect observational data for, but simulations of infinite nuclear matter can provide key insights to the internal structure of these astronomical objects. The main focus of this thesis is the development of a large and versatile coupled cluster program which implements a sparse tensor storage scheme and efficient tensor contraction algorithms. A distributed memory data structure for these large, sparse tensors is used so that the code can run in a high-performance computing setting, and can thus handle the computational challenges of infinite nuclear matter calculations using large basis sets. By validating these data structures and algorithms in the context of coupled cluster theory and infinite nuclear matter, they can be applied to a wide range of many-body methods and physical systems.
