UC Berkeley Previously Published Works

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.

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.

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 Gender, racial-ethnic, and socioeconomic disparities in the development of social-emotional competence among elementary school students

Gender, racial-ethnic, and socioeconomic disparities in the development of social-emotional competence among elementary school students

(2024)

Social-emotional competence (SEC) has been demonstrated to be a crucial factor for student mental health and is malleable through the high-quality implementation of effective school-based social and emotional learning (SEL) programs. SEL is now widely practiced in the United States as a Tier 1 strategy for the entire student body, yet it remains unclear whether disparities exist in the development of SEC across socioculturally classified subgroups of students. Also, despite the field’s widespread concern about teacher bias in assessing SEC within diverse student bodies, little evidence is available on the measurement invariance of the SEC assessment tools used to explore and facilitate SEC development. Based on a sociocultural view of student SEC development, this study aimed to measure and examine the extent to which gender, racial-ethnic, and socioeconomic disparities exist in SEC developmental trajectories during elementary school years. Specifically, using 3 years of SEC assessment data collected from a districtwide SEL initiative (N = 5452; Grades K–2 at baseline; nine measurement occasions), this study (a) tested the measurement invariance of a widely-used, teacher-rated SEC assessment tool (DESSA-Mini) across student gender, race and ethnicity, and socioeconomic status (SES); and (b) examined the extent to which multiyear SEC growth trajectories differed across these subgroups under a routine SEL practice condition. The invariance testing results supported strict factorial invariance of the DESSA-Mini across all the examined subgroups, thereby providing a foundation for valid cross-group comparisons of student SEC growth. The piecewise latent growth modeling results indicated that boys (vs. girls), Black students (vs. White students), Hispanic students (vs. White students), and low-income students (vs. middle-to-high-income students) started with a lower level of SEC, with these gaps being sustained or slightly widened throughout 3 elementary school years. Based on these findings, this study calls for future research that can inform practice efforts to ensure equitable SEC assessments and produce more equitable SEL outcomes, thereby promoting equity in school mental health.

Lets Connect: Impact Evaluation of an Intervention to Reduce Mental Health Disparities Among People Who are LGBTQ+ .

(2024)

Lesbian, gay, bisexual, transgender, queer, or similarly identified (LGBTQ+) people experience substantial mental health disparities compared to heterosexuals. The Lets Connect intervention was designed to improve mental health outcomes for LGBTQ+ people. This impact evaluation aimed to assess effectiveness of this intervention during its pilot phase, using a single arm pilot trial. Respondents completed baseline surveys at intervention start, a post survey on the last day of the intervention (at 6 weeks), then a follow-up survey 6 weeks after the intervention ended (at 12 weeks). Pre-post differences in outcomes were analyzed using paired t-tests, chi-square tests, and generalized estimating equations to evaluate impact on mental health outcomes at 6 and 12 weeks, and identify characteristics associated with loss to follow-up. The average value of all three outcome measures decreased substantially between the baseline and post surveys; all of these differences were highly statistically significant, and further decreased between the end of the intervention at 6 weeks and the 12 week follow-up survey. Lets Connect participants did experience substantial improvements in mental health outcomes, on average, between the start and end of this intervention. Further study of this intervention using a randomized design and control group is warranted.

Reinvented: An Attosecond Chemist

Leone, Stephen R

(2024)

Attosecond science requires a substantial rethinking of how to make measurements on very short timescales; how to acquire the necessary equipment, technology, and personnel; and how to build a set of laboratories for such experiments. This entails a rejuvenation of the author in many respects, in the laboratory itself, with regard to students and postdocs, and in generating funding for research. It also brings up questions of what it means to do attosecond science, and the discovery of the power of X-ray spectroscopy itself, which complements the short timescales addressed. The lessons learned, expressed in the meanderings of this autobiographical article, may be of benefit to others who try to reinvent themselves. Expected final online publication date for the Annual Review of Physical Chemistry, Volume 75 is April 2024. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Randomized Trial of Dynamic Choice HIV Prevention at Antenatal and Postnatal Care Clinics in Rural Uganda and Kenya

(2024)

Background

Pregnant and postpartum women in Sub-Saharan Africa are at high risk of HIV acquisition. We evaluated a person-centered dynamic choice intervention for HIV prevention (DCP) among women attending antenatal and postnatal care.

Setting

Rural Kenya and Uganda.

Methods

Women (aged 15 years or older) at risk of HIV acquisition seen at antenatal and postnatal care clinics were individually randomized to DCP vs. standard of care (SEARCH; NCT04810650). The DCP intervention included structured client choice of product (daily oral pre-exposure prophylaxis or postexposure prophylaxis), service location (clinic or out of facility), and HIV testing modality (self-test or provider-administered), with option to switch over time and person-centered care (phone access to clinician, structured barrier assessment and counseling, and provider training). The primary outcome was biomedical prevention coverage-proportion of 48-week follow-up with self-reported pre-exposure prophylaxis or postexposure prophylaxis use, compared between arms using targeted maximum likelihood estimation.

Results

Between April and July 2021, we enrolled 400 women (203 intervention and 197 control); 38% were pregnant, 52% were aged 15-24 years, and 94% reported no pre-exposure prophylaxis or postexposure prophylaxis use for ≥6 months before baseline. Among 384/400 participants (96%) with outcome ascertained, DCP increased biomedical prevention coverage 40% (95% CI: 34% to 47%; P < 0.001); the coverage was 70% in intervention vs. 29% in control. DCP also increased coverage during months at risk of HIV (81% in intervention, 43% in control; 38% absolute increase; 95% CI: 31% to 45%; P < 0.001).

Conclusion

A person-centered dynamic choice intervention that provided flexibility in product, testing, and service location more than doubled biomedical HIV prevention coverage in a high-risk population already routinely offered access to biomedical prevention options.

Cover page of Lithium-Ion Transport and Exchange between Phases in a Concentrated Liquid Electrolyte Containing Lithium-Ion-Conducting Inorganic Particles

Lithium-Ion Transport and Exchange between Phases in a Concentrated Liquid Electrolyte Containing Lithium-Ion-Conducting Inorganic Particles

(2024)

Understanding Li⁺ transport in organic-inorganic hybrid electrolytes, where Li⁺ has to lose its organic solvation shell to enter and transport through the inorganic phase, is crucial to the design of high-performance batteries. As a model system, we investigate a range of Li⁺-conducting particles suspended in a concentrated electrolyte. We show that large Li_1.3Al_0.3Ti_1.7P₃O₁₂ and Li₆PS₅Cl particles can enhance the overall conductivity of the electrolyte. When studying impedance using a cell with a large cell constant, the Nyquist plot shows two semicircles: a high-frequency semicircle related to ion transport in the bulk of both phases and a medium-frequency semicircle attributed to Li⁺ transporting through the particle/liquid interfaces. Contrary to the high-frequency resistance, the medium-frequency resistance increases with particle content and shows a higher activation energy. Furthermore, we show that small particles, requiring Li⁺ to overcome particle/liquid interfaces more frequently, are less effective in facilitating Li⁺ transport. Overall, this study provides a straightforward approach to study the Li⁺ transport behavior in hybrid electrolytes.

Chemical Bonding and the Role of Node-Induced Electron Confinement

(2024)

The chemical bond is the cornerstone of chemistry, providing a conceptual framework to understand and predict the behavior of molecules in complex systems. However, the fundamental origin of chemical bonding remains controversial and has been responsible for fierce debate over the past century. Here, we present a unified theory of bonding, using a separation of electron delocalization effects from orbital relaxation to identify three mechanisms [node-induced confinement (typically associated with Pauli repulsion, though more general), orbital contraction, and polarization] that each modulate kinetic energy during bond formation. Through analysis of a series of archetypal bonds, we show that an exquisite balance of energy-lowering delocalizing and localizing effects are dictated simply by atomic electron configurations, nodal structure, and electronegativities. The utility of this unified bonding theory is demonstrated by its application to explain observed trends in bond strengths throughout the periodic table, including main group and transition metal elements.

1 supplemental PDF