Cosmic ray physics in calculations of cosmological structure formation
Bibliographic record
Abstract
Cosmic rays (CRs) play a decisive role within our own Galaxy. They provide partial pressure support against gravity, they trace past energetic events such as supernovae, and they reveal the underlying structure of the baryonic matter distribution through their interactions. To study the impact of CRs on galaxy and cosmic structure formation and evolution, we develop an approximative framework for treating dynamical and radiative effects of CRs in cosmological simulations. Our guiding principle is to try to find a balance between capturing as many physical properties of CR populations as possible while at the same time requiring as little extra computational resources as possible. We approximate the CR spectrum of each fluid element by a single power-law, with spatially and temporally varying normalisation, low-energy cut-off, and spectral index. Principles of conservation of particle number, energy, and pressure are then used to derive evolution equations for the basic variables describing the CR spectrum, both due to adiabatic and non-adiabatic processes. The processes considered include compression and rarefaction, CR injection via shocks in supernova remnants, injection in structure formation shock waves, in-situ re-acceleration of CRs, CR spatial diffusion, CR energy losses due to Coulomb interactions, ionisation losses, Bremsstrahlung losses, and, finally, hadronic interactions with the background gas, including the associated γ-ray and radio emission due to subsequent pion decay. We show that the formalism reproduces CR energy densities, pressure, and cooling rates with an accuracy of ∼ in steady state conditions where CR injection balances cooling. It is therefore a promising formulation to allow simulations where CR physics is included. Finally, we briefly discuss how the formalism can be included in Lagrangian simulation methods such as the smoothed particle hydrodynamics technique. Our framework is therefore well suited to be included into numerical simulation schemes of galaxy and structure formation.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".