Simulating Extensive Air Showers: Investigating the LDF for Electrons and Muons Using the AIRES System
Bibliographic record
Abstract
Extensive air showers (EAS), cascades of electromagnetic radiation and ionized particles produced when primary cosmic rays (CRs) interact with atmospheric nuclei, generate a plethora of secondary particles, including electrons, muons, alpha particles, X-rays, and neutrons.These phenomena, pivotal in the exploration of high-energy CR interactions, have prompted advancements in simulating the lateral distribution function (LDF) of secondary particles.Utilizing AIR-shower extended simulations (AIRES) software (version 19.04.10), this study presents simulations of EAS to elucidate the impact on the LDF at the high energy thresholds of 1016, 1018 and 1019 eV.The focus is on secondary muons and electrons, considering the influence of primary protons and iron nuclei across zenith angles of 0, 20, and 40.Through the application of an exponential function model, novel coefficients were derived, reflecting the variation of the LDF relative to the distance from the shower core.These coefficients are instrumental in astrophysics and particle physics, offering a nuanced understanding of CR interactions with earth's atmosphere.By delineating the spatial particle distribution during interactions, insights into the shower's lateral extent and configuration are gleaned, facilitating the deduction of the initiating CR's energy.Such knowledge is crucial for CR spectrum analysis.The investigation of electron and muon LDFs not only advances fundamental particle physics but also holds implications for space exploration, radiation protection, and other domains.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".