In the past decade, one of the major challenges of particle physics has been to gain an in-depth understanding of the role of quark flavor. In this time frame, measurements and the theoretical interpretation of their results have advanced tremendously. A much broader understanding of flavor particles has been achieved; apart from their masses and quantum numbers, there now exist detailed measurements of the characteristics of their interactions allowing stringent tests of Standard Model predictions. Among the most interesting phenomena of flavor physics is the violation of the CP symmetry that has been subtle and difficult to explore. In the past, observations of CP violation were confined to neutral K mesons, but since the early 1990s, a large number of CP-violating processes have been studied in detail in neutral B mesons. In parallel, measurements of the couplings of the heavy quarks and the dynamics for their decays in large samples of K, D, and B mesons have been greatly improved in accuracy and the results are being used as probes in the search for deviations from the Standard Model. In the near future, there will be a transition from the current to a new generation of experiments; thus a review of the status of quark flavor physics is timely. This report is the result of the work of physicists attending the 5th CKM workshop, hosted by the University of Rome "La Sapienza", September 9-13, 2008. It summarizes the results of the current generation of experiments that are about to be completed and it confronts these results with the theoretical understanding of the field which has greatly improved in the past decade. (C) 2010 Elsevier B.V. All rights reserved

Imagine being able to predict -with unprecedented accuracy and precision -the structure of the proton and neutron, and the forces between them, directly from the dynamics of quarks and gluons, and then using this information in calculations of the structure and reactions of atomic nuclei and of the properties of dense neutron stars (NSs). Also imagine discovering new and exotic states of matter, and new laws of nature, by being able to collect more experimental data than we dream possible today, analyzing it in real time to feed back into an experiment, and curating the data with full tracking capabilities and with fully distributed data mining capabilities. Making this vision a reality would improve basic scientific understanding, enabling us to precisely calculate, for example, the spectrum of gravity waves emitted during NS coalescence, and would have important societal applications in nuclear energy research, stockpile stewardship, and other areas. This review presents the components and characteristics of the exascale computing ecosystems necessary to realize this vision.Nuclear physics research and its applications, more than many other areas of science, rely heavily on large-scale, high-performance computing (HPC). HPC is integral to (1) the design and optimization of an extensive and vibrant experimental program, (2) acquisition and handling of large volumes of experimental data, and (3) large-scale simulations of emergent complex systems -from the subatomic to the cosmological. Dramatic progress has already been made in enhancing our understanding of strongly-interacting matter across many areas of physics: from the quark and gluon structure of the proton and neutron, the building blocks of atomic nuclei; to relating the hot dense plasma in the early universe to the near-perfect fluid produced at the Relativistic Heavy Ion Collider (RHIC); to the structure of rare isotopes and the reactions required to form all the elements of the universe; to the creation and properties of the dense cold matter formed in supernovae and NSs.In addition to pursuing new analytical and experimental techniques and algorithms and more complete physical models at higher resolution, the following broadly grouped areas relevant to the U.S. Department of Energy (DOE) Office of Advanced Scientific Computing Research (ASCR) and the National Science Foundation (NSF) would directly affect the mission need of the DOE Office of Science (SC) Nuclear Physics (NP) program.Exascale capability computing and associated capacity computing will revolutionize our understanding of nuclear physics and nuclear applications.Closely tied to the needs for exascale hardware are the requirements for new software (codes, algorithms, and workflows) appropriate for the exascale ecosystem, which can be developed through collaborations among ASCR and NSF mathematicians and computer scientists and NP scientists.

A possibility of new type experimental searches for new physics beyond the standard model is being introduced in the symmetry tests in neutron-induced compound states according to the successful operation of intense pulsed neutron sources. The basis of experiment design is discussed.

A difficult problem concerns the determination of magnetic field components within an experimentally inaccessible region when direct field measurements are not feasible. In this paper, we propose a new method of accessing magnetic field components using non-disruptive magnetic field measurements on a surface enclosing the experimental region. Magnetic field components in the experimental region are predicted by solving a set of partial differential equations (Ampere’s law and Gauss’ law for magnetism) numerically with the aid of physics-informed neural networks (PINNs). Prediction errors due to noisy magnetic field measurements and small number of magnetic field measurements are regularized by the physics information term in the loss function. We benchmark our model by comparing it with an older method. The new method we present will be of broad interest to experiments requiring precise determination of magnetic field components, such as searches for the neutron electric dipole moment.

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