OPH is an active research program aiming to construct a fundamental theory of physics from observer consistency.
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Updated
Apr 5, 2026 - Python
OPH is an active research program aiming to construct a fundamental theory of physics from observer consistency.
Repository hosting the KLFitter library – the Kinematic Likelihood Fitter.
Open source toolkit for simulating and visualizing particle interactions as predicted by the Standard Model
Mathematica package for algebraic calculations in elementary particle physics. Performs automated calculation of all one- and two-loop Feynman integrals reducable to scalar integrals independent of external momenta and depending on up to two different masses.
Spectral Causal Theory: derivations, verification, analysis, and publications.
Book Particle Physics by Christoph Berger and Gregor Herten
Several implementations of the standard PPHPC agent-based model
Using the patterns and particles of physics as the building blocks of programs
Geometric Information Field Theory. 33 SM predictions from pure topology. 0.24% mean deviation. Zero free parameters. open source, Lean 4 verified, falsifiable.
The W(3,3)-E8 Correspondence Theorem: deriving the Standard Model from a single finite geometry with zero free parameters
Wolfram Language package calculating the couplings and mixings of the SM and MSSM
A simulator of the Big Bang.
Book II : Standard Model gauge group, particle masses and couplings derived from d=3 — 170 predictions
This paper explores the fascinating evolution of string theory, from its origins as a novel approach known as ”bootstrap models” in relativistic particle physics to its current status as a candidate theory of quantum gravity.
MIXED frustration fraction R across U(1), SU(2), SU(3) and SM gauge groups — lattice Monte Carlo + FSS (HGST E7)
Systematic scan of the Kreuzer-Skarke database for χ=−6 Calabi-Yau 3-folds — multi-tier screening pipeline + open catalogue of results
Universal Measurement Contract Protocol (UMCP) — a contract-first validation framework implementing Generative Collapse Dynamics. 21 domains · 716 proven theorems · 19k+ tests · 44 structural identities · Python + C++17 accelerator.
Computational companion to Projective Process Monism — a framework deriving physical constants from CP³/RP³ topology. Two interactive notebooks: five parameter-free predictions compared to measurement, and a constraint sensitivity analysis showing the framework's parameters are geometrically forced
Revolutionary method to derive fundamental physics parameters from observed constants using iterative backward-forward reconstruction. Predicting 31% Higgs coupling anomalies and new physics beyond Standard Model.
A concise, cheatsheet about properties of elementary particles in the standard model.
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