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Open Access Publications from the University of California

LBL Publications

Lawrence Berkeley National Laboratory (Berkeley Lab) has been a leader in science and engineering research for more than 70 years. Located on a 200 acre site in the hills above the Berkeley campus of the University of California, overlooking the San Francisco Bay, Berkeley Lab is a U.S. Department of Energy (DOE) National Laboratory managed by the University of California. It has an annual budget of nearly $480 million (FY2002) and employs a staff of about 4,300, including more than a thousand students.

Berkeley Lab conducts unclassified research across a wide range of scientific disciplines with key efforts in fundamental studies of the universe; quantitative biology; nanoscience; new energy systems and environmental solutions; and the use of integrated computing as a tool for discovery. It is organized into 17 scientific divisions and hosts four DOE national user facilities. Details on Berkeley Lab's divisions and user facilities can be viewed here.

Deep Generative Models for Fast Photon Shower Simulation in ATLAS

(2024)

Abstract: The need for large-scale production of highly accurate simulated event samples for the extensive physics programme of the ATLAS experiment at the Large Hadron Collider motivates the development of new simulation techniques. Building on the recent success of deep learning algorithms, variational autoencoders and generative adversarial networks are investigated for modelling the response of the central region of the ATLAS electromagnetic calorimeter to photons of various energies. The properties of synthesised showers are compared with showers from a full detector simulation using geant4. Both variational autoencoders and generative adversarial networks are capable of quickly simulating electromagnetic showers with correct total energies and stochasticity, though the modelling of some shower shape distributions requires more refinement. This feasibility study demonstrates the potential of using such algorithms for ATLAS fast calorimeter simulation in the future and shows a possible way to complement current simulation techniques.

Artificial Intelligence for the Electron Ion Collider (AI4EIC)

(2024)

The Electron-Ion Collider (EIC), a state-of-the-art facility for studying the strong force, is expected to begin commissioning its first experiments in 2028. This is an opportune time for artificial intelligence (AI) to be included from the start at this facility and in all phases that lead up to the experiments. The second annual workshop organized by the AI4EIC working group, which recently took place, centered on exploring all current and prospective application areas of AI for the EIC. This workshop is not only beneficial for the EIC, but also provides valuable insights for the newly established ePIC collaboration at EIC. This paper summarizes the different activities and R&D projects covered across the sessions of the workshop and provides an overview of the goals, approaches and strategies regarding AI/ML in the EIC community, as well as cutting-edge techniques currently studied in other experiments.

Software Performance of the ATLAS Track Reconstruction for LHC Run 3

(2024)

Charged particle reconstruction in the presence of many simultaneous proton–proton (pp) collisions in the LHC is a challenging task for the ATLAS experiment’s reconstruction software due to the combinatorial complexity. This paper describes the major changes made to adapt the software to reconstruct high-activity collisions with an average of 50 or more simultaneous pp interactions per bunch crossing (pile-up) promptly using the available computing resources. The performance of the key components of the track reconstruction chain and its dependence on pile-up are evaluated, and the improvement achieved compared to the previous software version is quantified. For events with an average of 60pp collisions per bunch crossing, the updated track reconstruction is twice as fast as the previous version, without significant reduction in reconstruction efficiency and while reducing the rate of combinatorial fake tracks by more than a factor two.

Cover page of Estimating geographic variation of infection fatality ratios during epidemics.

Estimating geographic variation of infection fatality ratios during epidemics.

(2024)

OBJECTIVES: We aim to estimate geographic variability in total numbers of infections and infection fatality ratios (IFR; the number of deaths caused by an infection per 1,000 infected people) when the availability and quality of data on disease burden are limited during an epidemic. METHODS: We develop a noncentral hypergeometric framework that accounts for differential probabilities of positive tests and reflects the fact that symptomatic people are more likely to seek testing. We demonstrate the robustness, accuracy, and precision of this framework, and apply it to the United States (U.S.) COVID-19 pandemic to estimate county-level SARS-CoV-2 IFRs. RESULTS: The estimators for the numbers of infections and IFRs showed high accuracy and precision; for instance, when applied to simulated validation data sets, across counties, Pearson correlation coefficients between estimator means and true values were 0.996 and 0.928, respectively, and they showed strong robustness to model misspecification. Applying the county-level estimators to the real, unsimulated COVID-19 data spanning April 1, 2020 to September 30, 2020 from across the U.S., we found that IFRs varied from 0 to 44.69, with a standard deviation of 3.55 and a median of 2.14. CONCLUSIONS: The proposed estimation framework can be used to identify geographic variation in IFRs across settings.

Cover page of Helping Faculty Teach Software Performance Engineering

Helping Faculty Teach Software Performance Engineering

(2024)

Over the academic year 2022–23, we discussed the teaching of software performance engineering with more than a dozen faculty across North America and beyond. Our outreach was centered on research-focused faculty with an existing interest in this course material. These discussions revealed an enthusiasm for making software performance engineering a more prominent part of a curriculum for computer scientists and engineers. Here, we discuss how MIT’s longstanding efforts in this area may serve as a launching point for community development of a software performance engineering curriculum, challenges in and solutions for providing the necessary infrastructure to universities, and future directions.

Cover page of Power Outage Economics Tool: A Prototype for the Commonwealth Edison Service Territory

Power Outage Economics Tool: A Prototype for the Commonwealth Edison Service Territory

(2024)

Estimates of the economic impact of widespread, long duration (WLD) power interruptions can be used to prioritize and justify significant investments in power system resilience. This report presents estimates of this type for WLDs originating within the Commonwealth Edison (ComEd) service territory. The intended audience for this research includes utility executives and technical staff, regulators, and government agencies. This project involved surveying ComEd customers to understand how they might respond when confronted with a WLD power interruption. The research team used the survey responses to calibrate a state-of-the-art regional economic model (“POET”) to estimate economic impacts to households and 38 industry sectors across 17 impacted micro-regions (individual counties or aggregations of counties) within ComEd’s service territory and beyond. We ran one-day, three-day, and 14-day interruption duration scenarios each with varying geographic extents as well as estimated the benefits of deploying additional backup generation across the service territory. The results were then compared to a “business as usual” scenario assuming that no interruption occurred. There are six key findings from this analysis: -There may be significant losses to gross output (business revenue), gross domestic product, and household consumption during WLD interruptions, especially multi-day interruptions that occur across all of ComEd, Cook county, or the suburbs of Chicago. -The wholesale trade and transportation sectors appear to be highly sensitive to power interruptions—losses to these sectors are large relative to the losses observed across the entire economy. -Several sector-region combinations—e.g., the transportation sector in Cook county—are very sensitive to interruptions. -High-income households experience proportionately larger losses to consumption during a one-day power interruption, but low-income households experience proportionately larger losses during the longest power interruptions. -Increasing the amount of backup generation deployed across ComEd’s service territory provides significant net benefits to system-wide gross domestic product, gross output, and household consumption relative to the existing amount of backup generation already being used. -Some micro-regions (e.g., Dekalb and Kendall counties), sectors (e.g., wholesale trade, transportation), and low-income households in Cook county may especially benefit from targeted resilience interventions. We recommend that decision-makers consider running cost-benefit analyses using each of the economic metrics presented in this report independent of one another to evaluate the robustness of the insights that each of these estimates may provide. In addition to this report, we developed a tool that will allow ComEd staff and other decision-makers to visualize the full suite of results using an easy-to-interpret, user interface. We hope that the findings from this research effort will provide valuable insights to ComEd, policymakers across Illinois, and other stakeholders who have an interest in the resilience of the power system.

Cover page of Exploring Wholesale Energy Price Trends: The Renewables and Wholesale Electricity Prices (ReWEP) tool, Version 2024.1

Exploring Wholesale Energy Price Trends: The Renewables and Wholesale Electricity Prices (ReWEP) tool, Version 2024.1

(2024)

The Renewables and Wholesale Electricity Prices (ReWEP) visualization tool from Berkeley Lab has been updated with nodal electricity pricing and wind and solar generation data through the end of 2023. ReWEP users can explore trends in wholesale electricity prices and their relationship to wind and solar generation. ReWEP includes nodal pricing trends across locations, regions, and different timeframes. The tool consists of maps, time series, and other interactive figures that provide: (1) a general overview of how average pricing, negative price frequency, and extreme high prices vary over time, and (2) a summary of how pricing patterns are related to wind and solar generation. Interactive functionality allows investigation by year, season, time of day, and region, where region is defined as the Independent System Operators (ISO) or Regional Transmission Organizations (RTO) region. ReWEP also contains prices throughout much of the western United States from the Western Energy Imbalance Market and the Western Energy Imbalance Service Market.

Cover page of A call to action for building energy system modelling in the age of decarbonization

A call to action for building energy system modelling in the age of decarbonization

(2024)

As urban energy systems become decarbonized and digitalized, buildings are increasingly interconnected with one another and with the industrial and transportation sector. Transformation strategies to cost-effectively integrate distributed energy sources, and to increase load flexibility and efficiency, generally increase complexity. This complexity causes challenges that the industry is unprepared to deal with. Today's simulation programs, and the processes in which they are used, have not been developed to meet the challenges of decarbonization. Nor have they been designed for, or do they keep pace with, the energy system digitalization. Modeling, simulation and optimization tools, and the processes in which they are used, need to undergo an innovation jump. We show a path to more holistic tools and workflows that address the new requirements brought forward by the increased complexity. Without concerted actions, the building simulation community will fall short of supporting the 2050 decarbonization targets declared by many governments.

Cover page of Exploring Wholesale Energy Price Trends: The Renewables and Wholesale Electricity Prices (ReWEP) tool, Version 2024.1

Exploring Wholesale Energy Price Trends: The Renewables and Wholesale Electricity Prices (ReWEP) tool, Version 2024.1

(2024)

The Renewables and Wholesale Electricity Prices (ReWEP) visualization tool from Berkeley Lab has been updated with nodal electricity pricing and wind and solar generation data through the end of 2023. ReWEP users can explore trends in wholesale electricity prices and their relationship to wind and solar generation. ReWEP includes nodal pricing trends across locations, regions, and different timeframes. The tool consists of maps, time series, and other interactive figures that provide: (1) a general overview of how average pricing, negative price frequency, and extreme high prices vary over time, and (2) a summary of how pricing patterns are related to wind and solar generation. Interactive functionality allows investigation by year, season, time of day, and region, where region is defined as the Independent System Operators (ISO) or Regional Transmission Organizations (RTO) region. ReWEP also contains prices throughout much of the western United States from the Western Energy Imbalance Market and the Western Energy Imbalance Service Market.

Cover page of Parallel Runtime Interface for Fortran (PRIF) Specification, Revision 0.3

Parallel Runtime Interface for Fortran (PRIF) Specification, Revision 0.3

(2024)

This document specifies an interface to support the parallel features of Fortran, named the Parallel Runtime Interface for Fortran (PRIF). PRIF is a proposed solution in which the runtime library is responsible for coarray allocation, deallocation and accesses, image synchronization, atomic operations, events, and teams. In this interface, the compiler is responsible for transforming the invocation of Fortran-level parallel features into procedure calls to the necessary PRIF procedures. The interface is designed for portability across shared- and distributed-memory machines, different operating systems, and multiple architectures. Implementations of this interface are intended as an augmentation for the compiler's own runtime library. With an implementation-agnostic interface, alternative parallel runtime libraries may be developed that support the same interface. One benefit of this approach is the ability to vary the communication substrate. A central aim of this document is to define a parallel runtime interface in standard Fortran syntax, which enables us to leverage Fortran to succinctly express various properties of the procedure interfaces, including argument attributes.