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Detector requirements and simulation results for the EIC exclusive, diffractive and tagging physics program using the ECCE detector concept

This article presents a collection of simulation studies using the ECCE detector concept in the context of the EIC’s exclusive, diffractive, and tagging physics program, which aims to further explore the rich quark–gluon structure of nucleons and nuclei. To successfully execute the program, ECCE proposed to utilize the detector system close to the beamline to ensure exclusivity and tag ion beam/fragments for a particular reaction of interest. Preliminary studies confirm the proposed technology and design satisfy the requirements. Further, the projected physics impact results are based on the projected detector performance from the simulation at 10 or 100 fb -1 of integrated luminosity. Additionally, insights related to a potential second EIC detector are documented, which could serve as a guidepost for future development.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Studies of Cherenkov photon production in PbF 2 crystals using proton beams at Fermilab

Future lepton colliders such as the FCC-ee, CEPC, ILC, or a muon collider will collect large data samples that allow precision physics studies with unprecedented accuracy, especially when the data is collected by innovative state-of-the-art detectors. An electromagnetic calorimeter based on scintillating crystals, designed to separately record Cherenkov and scintillation light, can achieve precision measurements of electrons and photons without sacrificing jet energy resolution, given adequate light collection efficiency and separation. This paper presents initial measurements from a program aimed at developing such a calorimeter system for future colliders. Finally, we focus on using PbF 2 crystals to enhance the understanding of Cherenkov light collection, marking the first step in this endeavor.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Integral and Separate Effects Test Facilities To Support Water Cooled Small Modular Reactors: A Review

This study reviews previous experimental facilities and test programs relevant to water-cooled reactor system design and analysis to meet regulatory compliances. This study aims to find the best solution for designing the required experiments, obtaining necessary test data, and verifying the developed computer code/models to support the new reactor design and development while minimizing cost and time while leveraging experiences from previous facilities to minimize. Nuclear reactor licensing requires supportive design, analysis, and experimental results to ensure the safety of the full-scale prototype reactor in regular operation, as well as during postulated accident scenarios. These reactor design analyses are generally performed using system codes and other associated simulation tools that require assessment, verification and validation using an appropriate experimental dataset. Experimental facilities used for reactor system safety analysis and system code assessments are categorized into integral effects test (IET) and separate effects test (SET) facilities. Further, these IET and SET experiments and studies use geometrically scaled systems to reproduce the prototype system behavior at a reasonable cost, albeit with some scaling-related distortions. The design challenge of these model facilities is to identify and minimize scaling distortions while reproducing the most important operational phenomena in steady-state operation and in postulated accident scenarios. Lessons learned from previous experimental facilities, models, and correlations can support the development of new multipurpose, scaled, hybrid, integrated, and modular experimental facilities for advanced light water-cooled small modular reactors (SMRs). Successful operation of these facilities can significantly reduce upfront reactor development and demonstration costs and time to deployment.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

A flowing liquid lithium limiter for the Experimental Advanced Superconducting Tokamak

A program involving the extensive and systematic use of lithium (Li) as a “first,” or plasma-facing, surface in Tokamak fusion research devices located at Institute of Plasma Physics, Chinese Academy of Sciences, was started in 2009. Many remarkable results have been obtained by the application of Li coatings in Experimental Advanced Superconducting Tokamak (EAST) and liquid Li limiters in the HT-7 Tokamak—both located at the institute. In furtherance of the lithium program, a flowing liquid lithium (FLiLi) limiter system has been designed and manufactured for EAST. The design of the FLiLi limiter is based on the concept of a thin flowing film which was previously tested in HT-7. Exploiting the capabilities of the existing material and plasma evaluation system on EAST, the limiter will be pre-wetted with Li and mechanically translated to the edge of EAST during plasma discharges. The limiter will employ a novel electro-magnetic pump which is designed to drive liquid Li flow from a collector at the bottom of limiter into a distributor at its top, and thus supply a continuously flowing liquid Li film to the wetted plasma-facing surface. This paper focuses on the major design elements of the FLiLi limiter. In addition, a simulation of incoming heat flux has shown that the distribution of heat flux on the limiter surface is acceptable for a future test of power extraction on EAST.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

CLASH-VLT: INSIGHTS ON THE MASS SUBSTRUCTURES IN THE FRONTIER FIELDS CLUSTER MACS J0416.1–2403 THROUGH ACCURATE STRONG LENS MODELING

We present a detailed mass reconstruction and a novel study on the substructure properties in the core of the Cluster Lensing And Supernova survey with Hubble (CLASH) and Frontier Fields galaxy cluster MACS J0416.1–2403. We show and employ our extensive spectroscopic data set taken with the VIsible Multi-Object Spectrograph instrument as part of our CLASH-VLT program, to confirm spectroscopically 10 strong lensing systems and to select a sample of 175 plausible cluster members to a limiting stellar mass of log (M {sub *}/M {sub ☉}) ≅ 8.6. We reproduce the measured positions of a set of 30 multiple images with a remarkable median offset of only 0.''3 by means of a comprehensive strong lensing model comprised of two cluster dark-matter halos, represented by cored elliptical pseudo-isothermal mass distributions, and the cluster member components, parameterized with dual pseudo-isothermal total mass profiles. The latter have total mass-to-light ratios increasing with the galaxy HST/WFC3 near-IR (F160W) luminosities. The measurement of the total enclosed mass within the Einstein radius is accurate to ∼5%, including the systematic uncertainties estimated from six distinct mass models. We emphasize that the use of multiple-image systems with spectroscopic redshifts and knowledge of cluster membership based on extensive spectroscopic information is key to constructing robust high-resolution mass maps. We also produce magnification maps over the central area that is covered with HST observations. We investigate the galaxy contribution, both in terms of total and stellar mass, to the total mass budget of the cluster. When compared with the outcomes of cosmological N-body simulations, our results point to a lack of massive subhalos in the inner regions of simulated clusters with total masses similar to that of MACS J0416.1–2403. Our findings of the location and shape of the cluster dark-matter halo density profiles and on the cluster substructures provide intriguing tests of the assumed collisionless, cold nature of dark matter and of the role played by baryons in the process of structure formation.

79 ASTRONOMY AND ASTROPHYSICS↗

The HIBEAM instrument at the European spallation source

The European spallation source (ESS) will be the world’s brightest neutron source and will open a new intensity frontier in particle physics. The HIBEAM collaboration aims to exploit the unique potential of the ESS with a dedicated ESS instrument for particle physics which offers world-leading capability in a number of areas. The HIBEAM program includes the first search in thirty years for free neutrons converting to antineutrons and searches for sterile neutrons, ultralight axion dark matter and nonzero neutron electric charge. This paper outlines the capabilities, design, infrastructure, and scientific potential of the HIBEAM program, including its dedicated beamline, neutron optical system, magnetic shielding and control, and detectors for neutrons and antineutrons. Additionally, we discuss the long-term scientific exploitation of HIBEAM, which may include measurements of the neutron electric dipole moment and precision studies of neutron decays.

47 OTHER INSTRUMENTATION↗

The parallelism motifs of genomic data analysis

Genomic datasets are growing dramatically as the cost of sequencing continues to decline and small sequencing devices become available. Enormous community databases store and share these data with the research community, but some of these genomic data analysis problems require large-scale computational platforms to meet both the memory and computational requirements. These applications differ from scientific simulations that dominate the workload on high-end parallel systems today and place different requirements on programming support, software libraries and parallel architectural design. For example, they involve irregular communication patterns such as asynchronous updates to shared data structures. We consider several problems in high-performance genomics analysis, including alignment, profiling, clustering and assembly for both single genomes and metagenomes. We identify some of the common computational patterns or ‘motifs’ that help inform parallelization strategies and compare our motifs to some of the established lists, arguing that at least two key patterns, sorting and hashing, are missing. This article is part of a discussion meeting issue ‘Numerical algorithms for high-performance computational science’.

59 BASIC BIOLOGICAL SCIENCES↗

Scrutinizing Variables for Checkpoint Using Automatic Differentiation

Checkpoint/Restart (C/R) saves the running state of the programs periodically, which consumes considerable time and system resources. We observe that not every piece of data is involved in the computation in typical HPC applications; such unused data should be excluded from checkpointing for better storage and compute efficiency. We propose a systematic approach that leverages automatic differentiation (AD) to scrutinize every element within variables (e.g., arrays) necessary for checkpointing. This allows us to identify critical and uncritical elements and eliminate uncritical elements from checkpointing. Specifically, we inspect every single element within a variable necessary for checkpointing with an AD tool to determine whether the element has an impact on the application output or not. We validate our approach with all benchmarks from the NPB suite. We visualize the distribution of critical and uncritical elements within a variable with respect to its binary impact (yes or no) on the application output.

Huang, Xin [Kobe University]↗

TU-H-207A-02: Relative Importance of the Various Factors Influencing the Accuracy of Monte Carlo Simulated CT Dose Index

Purpose: Monte Carlo simulation is a frequently used technique for assessing patient dose in CT. The accuracy of a Monte Carlo program is often validated using the standard CT dose index (CTDI) phantoms by comparing simulated and measured CTDI{sub 100}. To achieve good agreement, many input parameters in the simulation (e.g., energy spectrum and effective beam width) need to be determined. However, not all the parameters have equal importance. Our aim was to assess the relative importance of the various factors that influence the accuracy of simulated CTDI{sub 100}. Methods: A Monte Carlo program previously validated for a clinical CT system was used to simulate CTDI{sub 100}. For the standard CTDI phantoms (32 and 16 cm in diameter), CTDI{sub 100} values from central and four peripheral locations at 70 and 120 kVp were first simulated using a set of reference input parameter values (treated as the truth). To emulate the situation in which the input parameter values used by the researcher may deviate from the truth, additional simulations were performed in which intentional errors were introduced into the input parameters, the effects of which on simulated CTDI{sub 100} were analyzed. Results: At 38.4-mm collimation, errors in effective beam width up to 5.0 mm showed negligible effects on simulated CTDI{sub 100} (<1.0%). Likewise, errors in acrylic density of up to 0.01 g/cm{sup 3} resulted in small CTDI{sub 100} errors (<2.5%). In contrast, errors in spectral HVL produced more significant effects: slight deviations (±0.2 mm Al) produced errors up to 4.4%, whereas more extreme deviations (±1.4 mm Al) produced errors as high as 25.9%. Lastly, ignoring the CT table introduced errors up to 13.9%. Conclusion: Monte Carlo simulated CTDI{sub 100} is insensitive to errors in effective beam width and acrylic density. However, they are sensitive to errors in spectral HVL. To obtain accurate results, the CT table should not be ignored. This work was supported by a Faculty Research and Development Award from Cleveland State University.

60 APPLIED LIFE SCIENCES↗

Python and HPC for High Energy Physics Data Analyses

High level abstractions in Python that can utilize computing hardware well seem to be an attractive option for writing data reduction and analysis tasks. In this paper, we explore the features available in Python which are useful and efficient for end user analysis in High Energy Physics (HEP). A typical vertical slice of an HEP data analysis is somewhat fragmented: the state of the reduction/analysis process must be saved at certain stages to allow for selective reprocessing of only parts of a generally time-consuming workflow. Also, algorithms tend to to be modular because of the heterogeneous nature of most detectors and the need to analyze different parts of the detector separately before combining the information. This fragmentation causes difficulties for interactive data analysis, and as data sets increase in size and complexity (O10 TiB for a “small” neutrino experiment to the O10 PiB currently held by the CMS experiment at the LHC), data analysis methods traditional to the field must evolve to make optimum use of emerging HPC technologies and platforms. Mainstream big data tools, while suggesting a direction in terms of what can be done if an entire data set can be available across a system and analysed with high-level programming abstractions, are not designed with either scientific computing generally, or modern HPC platform features in particular, such as data caching levels, in mind. Our example HPC use case is a search for a new elementary particle which might explain the phenomenon known as “Dark Matter”. Here, using data from the CMS detector, we will use HDF5 as our input data format, and MPI with Python to implement our use case.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Controlling Matter at the Molecular Scale with DNA Circuits

In recent years, a diverse set of mechanisms have been developed that allow DNA strands with specific sequences to sense information in their environment and to control material assembly, disassembly, and reconfiguration. These sequences could serve as the inputs and outputs for DNA computing circuits, enabling DNA circuits to act as chemical information processors to program complex behavior in chemical and material systems. In this review, we describe processes that can be sensed and controlled within such a paradigm. Specifically, there are interfaces that can release strands of DNA in response to chemical signals, wavelengths of light, pH, or electrical signals, as well as DNA strands that can direct the self-assembly and dynamic reconfiguration of DNA nanostructures, regulate particle assemblies, control encapsulation, and manipulate materials including DNA crystals, hydrogels, and vesicles. These interfaces have the potential to enable chemical circuits to exert algorithmic control over responsive materials, which may ultimately lead to the development of materials that grow, heal, and interact dynamically with their environments.

59 BASIC BIOLOGICAL SCIENCES↗

Profiling the BLAST bioinformatics application for load balancing on high-performance computing clusters

Abstract Background The Basic Local Alignment Search Tool (BLAST) is a suite of commonly used algorithms for identifying matches between biological sequences. The user supplies a database file and query file of sequences for BLAST to find identical sequences between the two. The typical millions of database and query sequences make BLAST computationally challenging but also well suited for parallelization on high-performance computing clusters. The efficacy of parallelization depends on the data partitioning, where the optimal data partitioning relies on an accurate performance model. In previous studies, a BLAST job was sped up by 27 times by partitioning the database and query among thousands of processor nodes. However, the optimality of the partitioning method was not studied. Unlike BLAST performance models proposed in the literature that usually have problem size and hardware configuration as the only variables, the execution time of a BLAST job is a function of database size, query size, and hardware capability. In this work, the nucleotide BLAST application BLASTN was profiled using three methods: shell-level profiling with the Unix “time” command, code-level profiling with the built-in “profiler” module, and system-level profiling with the Unix “gprof” program. The runtimes were measured for six node types, using six different database files and 15 query files, on a heterogeneous HPC cluster with 500+ nodes. The empirical measurement data were fitted with quadratic functions to develop performance models that were used to guide the data parallelization for BLASTN jobs. Results Profiling results showed that BLASTN contains more than 34,500 different functions, but a single function, RunMTBySplitDB, takes 99.12% of the total runtime. Among its 53 child functions, five core functions were identified to make up 92.12% of the overall BLASTN runtime. Based on the performance models, static load balancing algorithms can be applied to the BLASTN input data to minimize the runtime of the longest job on an HPC cluster. Four test cases being run on homogeneous and heterogeneous clusters were tested. Experiment results showed that the runtime can be reduced by 81% on a homogeneous cluster and by 20% on a heterogeneous cluster by re-distributing the workload. Discussion Optimal data partitioning can improve BLASTN’s overall runtime 5.4-fold in comparison with dividing the database and query into the same number of fragments. The proposed methodology can be used in the other applications in the BLAST+ suite or any other application as long as source code is available.

59 BASIC BIOLOGICAL SCIENCES↗

Marine Corps Base Camp Lejeune MARDIS Database

Critical military training and testing on lands along the nation’s coastal and estuarine shorelines are increasingly placed at risk because of encroachment pressures in surrounding areas, impairments due to other anthropogenic disturbances, and changes in climate and sea level. The U.S. Department of Defense (DoD) intends to enhance and sustain its training and testing assets and also optimize its stewardship of natural resources through the development and application of an ecosystem-based management approach on DoD installations. To accomplish this goal, particularly for installations in estuarine/coastal environments, the Strategic Environmental Research and Development Program (SERDP) launched the Defense Coastal/Estuarine Research Program (DCERP) as a 10-year effort at Marine Corps Base Camp Lejeune (MCBCL) in North Carolina. The results of the second 5 years of the program (DCERP2) are presented in the DCERP2 Final Report.There were four overarching objectives of DCERP2. The first objective was to understand the effects of climate change impacts, including warming temperatures, variability in the hydrological cycle, storm events, and sea level rise on the coastal ecosystems at MCBCL from observations and measurements made over the 10-year program. The second objective was to understand the carbon cycle of the coastal and terrestrial ecosystems at MCBCL through a highly integrated sampling program. The third objective was to develop models, tools, and indicators to evaluate current and projected future ecosystem state changes and translate scientific findings into actionable information for installation managers. The last objective was to recommend adaptive management strategies to sustain ecosystem natural resources within the context of an active military installation.The Defense Coastal/Estuarine Research Program (DCERP) Monitoring and Research Data Information System (MARDIS) database is the long-term repository for all DCERP monitoring and research data. Metadata provide supporting information about monitoring and research data that include, but are not limited to, a description of the location where the data were collected, the field and laboratory methods used to collect and analyze the data, and the spatial extent and temporal frequency of the data collected. In MARDIS, metadata fields have been combined with the actual sampling data fields; therefore, DCERP metadata are not a separate element, table, or document, but instead they are an integral component of each data record.

54 ENVIRONMENTAL SCIENCES↗

ASCENDS: Advanced data SCiENce toolkit for Non-Data Scientists

Recently, advances in machine learning and artificial intelligence have been playing more and more critical roles in a wide range of areas. For the last several years, industries have shown that how learning from data, identifying patterns and making decisions with minimal human intervention can be extremely useful to their business (e.g., image classification, recommending a product to a customer, finding friends in a social network, predicting customers actions, etc.). These success stories have been motivating scientists who study physics, chemistry, materials, medicine, and many other subjects, to explore a new pathway of utilizing machine learning techniques like regression and classification for their scientific activities. However, most existing machine learning tools, systems, and methodologies have been developed for programming experts but not for scientists (or any users) who have no or little knowledge of programming. ASCENDS is a toolkit that is developed to assist scientists (or any persons) who want to use their data for machine learning tasks, more specifically, correlation analysis, regression, and classification. ASCENDS does not require programming skills. Instead, it provides a set of simple but powerful CLI (Command Line Interface) and GUI (Graphic User Interface) tools for non-data scientists to be able to intuitively perform advanced data analysis and machine learning techniques. ASCENDS has been implemented by wrapping around opensource software including Keras, TensorFlow, and scikit-learn.

97 MATHEMATICS AND COMPUTING↗

MAMA Software User Guide: Tips for Segmenting with MAMA

This document reviews the six ways to segment with the MAMA software. Mama is not a threshold based segmentation system, like many of the image analyses programs you may be have used in the past. The MAMA software is set up to allow you to segment iteratively, and do so in a variety of ways. Six different ways are show below. They can be used in almost any combination—sometimes the choice depends on the image, sometimes it depends on user preferences for what type of interactions a user is willing to do. In the examples below, by “easy”, we mean an image for which MAMA segmentation works great and little clean-up is needed. By hard image, we mean an image for which accurate segmentation is very challenging. Many metal micrographs, and particles with rough textures fall into this class.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

The RAJA Portability Layer: Overview and Status

As computer architectures become increasingly complex and diverse, application developers face difficult challenges to achieve high performance while maintaining code portability. The problem is especially acute for large ASC multiphysics codes. Efficient parallel execution often requires tuning algorithms and data access to match processor and memory system constraints. Changing compiler directives and parallel programming model constructs on thousands of individual loops in a large code is disruptive and unwieldy. RAJA is a programming approach that we have been developing at Lawrence Livermore National Laboratory to encapsulate platform-specific concerns, related to both hardware and parallel programming models. The RAJA abstraction layer simplifies porting C/C++ codes to various programming models and architectures by reducing effort and developer disruption. In this report, we motivate and describe key aspects of RAJA. We also present a preliminary assessment of RAJA based on exploration in three ASC hydrodynamics codes at LLNL, which was one part of a three-part ASC Level 2 milestone, completed in September 2014.

97 MATHEMATICS AND COMPUTING↗

California Energy Systems for the 21st Century 2016 Annual Report

The California Energy Systems for the 21st Century (CES-21) Program is a public-private collaborative research and development program between the California Joint Utilities1 and Lawrence Livermore National Laboratory (LLNL). The purpose of this annual report is to provide the California Public Utilities Commission (CPUC or Commission) with a summary of the 2016 progress of the CES-21 Program.

24 POWER TRANSMISSION AND DISTRIBUTION↗

FY17 Status Report on NEAMS Neutronics Activities

Under the U.S. DOE NEAMS program, the high-fidelity neutronics code system has been developed to support the multiphysics modeling and simulation capability named SHARP. The neutronics code system includes the high-fidelity neutronics code PROTEUS, the cross section library and preprocessing tools, the multigroup cross section generation code MC2-3, the in-house meshing generation tool, the perturbation and sensitivity analysis code PERSENT, and post-processing tools. The main objectives of the NEAMS neutronics activities in FY17 are to continue development of an advanced nodal solver in PROTEUS for use in nuclear reactor design and analysis projects, implement a simplified sub-channel based thermal-hydraulic (T/H) capability into PROTEUS to efficiently compute the thermal feedback, improve the performance of PROTEUS-MOCEX using numerical acceleration and code optimization, improve the cross section generation tools including MC2-3, and continue to perform verification and validation tests for PROTEUS.

47 OTHER INSTRUMENTATION↗