CORSIKA 8 - Towards a modern framework for the simulation of extensive air showers

Current and future challenges in astroparticle physics require novel simulation tools to achieve higher precision and more flexibility. For three decades the FORTRAN version of CORSIKA served the community in an excellent way. However, the effort to maintain and further develop this complex package is getting increasingly difficult. To overcome existing limitations, and designed as a very open platform for all particle cascade simulations in astroparticle physics, we are developing CORSIKA 8 based on modern C++ and Python concepts. Here, we give a brief status report of the project.Comment: 4 pages, 3 figures; Proceedings of Ultra High Energy Cosmic Rays 201

Distributed computation of persistent homology

Persistent homology is a popular and powerful tool for capturing topological features of data. Advances in algorithms for computing persistent homology have reduced the computation time drastically -- as long as the algorithm does not exhaust the available memory. Following up on a recently presented parallel method for persistence computation on shared memory systems, we demonstrate that a simple adaption of the standard reduction algorithm leads to a variant for distributed systems. Our algorithmic design ensures that the data is distributed over the nodes without redundancy; this permits the computation of much larger instances than on a single machine. Moreover, we observe that the parallelism at least compensates for the overhead caused by communication between nodes, and often even speeds up the computation compared to sequential and even parallel shared memory algorithms. In our experiments, we were able to compute the persistent homology of filtrations with more than a billion (10^9) elements within seconds on a cluster with 32 nodes using less than 10GB of memory per node

A Stable Multi-Scale Kernel for Topological Machine Learning

Topological data analysis offers a rich source of valuable information to study vision problems. Yet, so far we lack a theoretically sound connection to popular kernel-based learning techniques, such as kernel SVMs or kernel PCA. In this work, we establish such a connection by designing a multi-scale kernel for persistence diagrams, a stable summary representation of topological features in data. We show that this kernel is positive definite and prove its stability with respect to the 1-Wasserstein distance. Experiments on two benchmark datasets for 3D shape classification/retrieval and texture recognition show considerable performance gains of the proposed method compared to an alternative approach that is based on the recently introduced persistence landscapes

Air shower genealogy for muon production

Measurements of the muon content of extensive air showers at the highest energies show discrepancies compared to simulations as large as the differences between proton and iron. This so-called muon puzzle is commonly attributed to a lack of understanding of the hadronic interactions in the shower development. Furthermore, measurements of the fluctuations of muon numbers suggest that the discrepancy is likely a cumulative effect of interactions of all energies in the cascade. A feature of the air shower simulation code CORSIKA 8 allows us to access all previous generations of final-state muons up to the first interaction. With this technique, we study the influence of interactions happening at any intermediate stage in the cascade on muons depending on their lateral distance in a quantitative way and compare our results with predictions of the Heitler-Matthews model.Comment: 8 pages, 4 figures, proceedings of the 37th International Cosmic Ray Conference (ICRC 2021); v2: references update

Air shower genealogy for muon production

Measurements of the muon content of extensive air showers at the highest energies show discrepancies compared to simulations as large as the differences between proton and iron. This so-called muon puzzle is commonly attributed to a lack of understanding of the hadronic interactions in the shower development. Furthermore, measurements of the fluctuations of muon numbers suggest that the discrepancy is likely a cumulative effect of interactions of all energies in the cascade. A feature of the air shower simulation code CORSIKA 8 allows us to access all previous generations of final-state muons up to the first interaction. With this technique, we study the influence of interactions happening at any intermediate stage in the cascade on muons depending on their lateral distance in a quantitative way and compare our results with predictions of the Heitler-Matthews model.Comment: 8 pages, 4 figures, proceedings of the 37th International Cosmic Ray Conference (ICRC 2021); v2: references update

Social Isolation and Loneliness during COVID-19 Lockdown: Associations with Depressive Symptoms in the German Old-Age Population

Lockdowns during the COVID-19 pandemic increase the risk of social isolation and loneliness, which may affect mental wellbeing. Therefore, we aimed to investigate associations between social isolation and loneliness with depressive symptoms in the German old-age population during the first COVID-19 lockdown. A representative sample of randomly selected individuals at least 65 years old (n = 1005) participated in a computer-assisted standardized telephone interview in April 2020. Sociodemographic data, aspects of the personal life situation, attitudes towards COVID-19 and standardized screening measures on loneliness (UCLA 3-item loneliness scale), depression (Brief Symptom Inventory/BSI-18), and resilience (Brief Resilience Scale/BRS) were assessed. Associations were inspected using multivariate regression models. Being lonely, but not isolated (β = 0.276; p < 0.001) and being both isolated and lonely (β = 0.136; p < 0.001) were associated with higher depressive symptoms. Being isolated, but not lonely was not associated with depressive symptoms. Thus, the subjective emotional evaluation, i.e., feeling lonely, of the social situation during lockdown seems more relevant than the objective state, i.e., being isolated. Normal (β = −0.203; p < 0.001) and high resilience (β = −0.308; p < 0.001) were associated with lower depressive symptoms across groups. Therefore, strengthening coping skills may be a support strategy during lockdowns, especially for lonely older individuals

Validity of Chatbot Use for Mental Health Assessment: Experimental Study

BACKGROUND: Mental disorders in adolescence and young adulthood are major public health concerns. Digital tools such as text-based conversational agents (ie, chatbots) are a promising technology for facilitating mental health assessment. However, the human-like interaction style of chatbots may induce potential biases, such as socially desirable responding (SDR), and may require further effort to complete assessments. OBJECTIVE: This study aimed to investigate the convergent and discriminant validity of chatbots for mental health assessments, the effect of assessment mode on SDR, and the effort required by participants for assessments using chatbots compared with established modes. METHODS: In a counterbalanced within-subject design, we assessed 2 different constructs—psychological distress (Kessler Psychological Distress Scale and Brief Symptom Inventory-18) and problematic alcohol use (Alcohol Use Disorders Identification Test-3)—in 3 modes (chatbot, paper-and-pencil, and web-based), and examined convergent and discriminant validity. In addition, we investigated the effect of mode on SDR, controlling for perceived sensitivity of items and individuals’ tendency to respond in a socially desirable way, and we also assessed the perceived social presence of modes. Including a between-subject condition, we further investigated whether SDR is increased in chatbot assessments when applied in a self-report setting versus when human interaction may be expected. Finally, the effort (ie, complexity, difficulty, burden, and time) required to complete the assessments was investigated. RESULTS: A total of 146 young adults (mean age 24, SD 6.42 years; n=67, 45.9% female) were recruited from a research panel for laboratory experiments. The results revealed high positive correlations (all P<.001) of measures of the same construct across different modes, indicating the convergent validity of chatbot assessments. Furthermore, there were no correlations between the distinct constructs, indicating discriminant validity. Moreover, there were no differences in SDR between modes and whether human interaction was expected, although the perceived social presence of the chatbot mode was higher than that of the established modes (P<.001). Finally, greater effort (all P<.05) and more time were needed to complete chatbot assessments than for completing the established modes (P<.001). CONCLUSIONS: Our findings suggest that chatbots may yield valid results. Furthermore, an understanding of chatbot design trade-offs in terms of potential strengths (ie, increased social presence) and limitations (ie, increased effort) when assessing mental health were established