Deepak Samuel

A 31.9M-parameter Llama-architecture causal language model trained from scratch to reconstruct particle-track parameters from detector hit patterns, treating track fitting as a language translation problem: an array of encoded hit positions is translated into a short domain-specific "call" that regenerates it. A detector stack has 12 layers, each with 32 strips. A charged particle (e.g. a cosmic muon) crosses the stack roughly in a straight line, hitting strip round(slp layer + icpt) in every layer it geometrically passes through (slp = slope in strips/layer, icpt = intercept in strips). Each hit is encoded as a single integer layer 32 + strip in [0, 383]. - add — spurious hits not on the…