Monte Carlo Physics Simulator Skill

SkillDev tools

Monte Carlo simulation skill for statistical physics, particle transport, and stochastic processes

Instructions available. Your AI can read the instructions. Execution depends on the setup they require.

Account requirements not reviewed. Check the skill instructions before use; ahel provides instructions and does not run this skill.

Add ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.

Then ask your AI: use the Monte Carlo Physics Simulator Skill skill

What this skill tells your AI

The instructions your AI receives, as published by a5c-ai/babysitter in library/specializations/domains/science/physics/skills/monte-carlo-physics-simulator/SKILL.md and read by ahel’s review.

Purpose

Provide Monte Carlo simulation capabilities for statistical physics, particle transport, and stochastic processes in physics applications.

Capabilities

Metropolis algorithm implementation
Wang-Landau sampling
Parallel tempering coordination
Variance reduction techniques
Autocorrelation analysis
Error estimation and jackknife/bootstrap

Usage Guidelines

Choose appropriate sampling algorithms for the problem
Implement variance reduction for rare events
Monitor autocorrelation for independent samples
Use proper error estimation techniques

Dependencies

Custom MC codes
OpenMC
Geant4

Process Integration

Monte Carlo Simulation Implementation
Statistical Analysis Pipeline
Monte Carlo Event Generation

Signals

GitHub stars: 2k
Forks: 112
Last commit: Sep 2026

Advanced

Item type: skill
Key: monte-carlo-physics-simulator
Source: github.com/a5c-ai/babysitter

github.com/a5c-ai/babysitter