Origin 22 Research

Ghost

Autonomous Physics General Intelligence

The world's first digital twin of civilization.
129 coupled physics domains. Zero training data.
First principles. Sub-7 seconds.

#1 in 9/21 MultiphysicsBench Fields
129 Coupled Domains
<7s Full Simulation
0 Training Data

The Engine

Not AI. Physics.

Ghost doesn't learn patterns from data. It doesn't predict the next token. It propagates causal impulses through a coupled physics mesh — the same way meteorologists forecast weather, but for civilization instead of the atmosphere.

Inject an event — a pandemic, a financial crisis, a geopolitical shock — and watch as cascading effects propagate through healthcare, energy, supply chains, markets, defense, and public psychology. At the correct timescales. In the correct order. From first principles alone.

Language Models

  • Statistical patterns in text
  • Trillions of tokens required
  • Non-deterministic outputs
  • Massive GPU clusters
  • Narrative reasoning only
  • No temporal modeling
  • No emergent detection

Ghost Engine

  • Causal physics of coupled systems
  • Zero training data
  • Fully deterministic
  • Commodity CPU — no GPU
  • Physical causal propagation
  • 10 hierarchical timescales
  • Emergent dimension detection
129 Coupled Physics Domains From molecular biology to geopolitics, financial markets to soil ecology, nuclear physics to behavioral psychology
4,200+ Coupling Edges Expert-defined strong couplings combined with algorithmically densified weak-field interactions
10 Temporal Scales Base-3 epoch nesting from quantum-level molecular dynamics to evolutionary timescales
621M+ Evaluations Per Run Verified on 192-core bare metal (c7i.metal). 129 parallel engines through FractalCell depth layers, temporal mesh coupling via lock-free FractalMap.

Benchmark

Tested on MultiphysicsBench.

Ghost was evaluated on MultiphysicsBench (arXiv:2505.17575) — a published, reproducible coupled multiphysics benchmark. No benchmark data was used during development. No parameters were tuned to fit results.

#1 In 9 of 21 Physics Fields
1,828× Lower Error (Best Field)
$14 Total Compute Cost
0 GPU CPU Only

Outperforms FNO, DeepONet, PINNs, UNet, GNOT, and Transolver across coupled multiphysics tasks — from first principles, on commodity hardware.

Architecture

Fractal Temporal Mesh

Ghost models civilization as a single coupled dynamical system. Every domain influences every other domain, across multiple timescales, through causal physics. The architecture has no precedent in existing AI or simulation systems.

01

Coupled Physics Mesh

129 domains connected through 4,200+ coupling edges with physically motivated strengths and activation thresholds. Expert-defined strong couplings combined with algorithmically densified weak-field interactions.

02

Epoch-Gated Dynamics

Base-3 temporal hierarchy where each domain evolves on its natural timescale. Molecular dynamics don't fire at the same rate as geopolitical shifts. The system respects the physics of time.

03

Cross-Scale Propagation

Impulses propagate across temporal scales with physically motivated attenuation. A molecular event can trigger civilizational change — if the physics supports it.

04

Emergent Dimension Detection

When sustained cross-scale pressure accumulates between domains, the system detects genuinely novel coupling dimensions — phenomena that didn't exist before the simulation ran.

05

Pressure Breakthrough

Accumulated impulses that exceed critical thresholds bypass the epoch gate entirely — modeling the real-world phenomenon where pressure builds silently until sudden phase transition.

06

Era Transition Detection

The system detects civilizational phase transitions — moments when the cascade crosses a threshold that fundamentally reorganizes the system.

Lineage

Two centuries in the making.

Ghost didn't appear from nowhere. It sits at the convergence of ideas that scientists, mathematicians, and writers have been reaching toward for over 200 years.

1814

Laplace's Demon

Pierre-Simon Laplace imagined an intellect that could model everything from first principles. Ghost draws on that tradition — not predicting the future, but modeling how 129 domains couple and cascade through causal physics.

Wikipedia →
1951

Asimov's Psychohistory

In Foundation, Hari Seldon envisioned a mathematical framework for understanding civilizations at scale. Ghost is inspired by the same ambition — modeling how domains interact and cascade, not predicting outcomes, but illuminating causal structure.

Wikipedia →
1956

Artificial General Intelligence

The stated goal of OpenAI, DeepMind, and Anthropic — intelligence that generalizes across domains. They're going through language and statistics. Ghost gets there through physics.

Wikipedia →
1984

Complexity Science

The Santa Fe Institute has spent 40 years studying coupled complex systems — how cascading effects propagate through interconnected networks. Thousands of papers. Nobody built the simulation.

Santa Fe Institute →
2002

Digital Twins

NASA, Siemens, and GE build physics simulations of individual systems — jet engines, factories, weather. The idea of scaling to everything has been theorized but never attempted across 129 coupled domains.

Wikipedia →
2017

DARPA World Modelers

The US Department of Defense explicitly funded a program for cross-domain causal modeling. Achieved ~10-20 domains with limited coupling. Ghost runs 129 domains with 4,200+ coupling edges in under 7 seconds.

DARPA →

Deployment

Commodity hardware. No GPU.

Ghost runs on a standard 48-core AWS instance. No GPU clusters. No specialized silicon. No million-dollar training runs. A full civilization simulation completes in under 7 seconds. The entire system deploys as a single Rust binary.

Runtime <7s per simulation
Hardware 48-core commodity CPU
GPU Not required
Training data None
Language Rust
Determinism 100% — same input, same output

Access

Request a briefing.

Ghost is available for sovereign, defense, energy, and infrastructure clients. Contact us for a technical briefing and demonstration.

zach@origin22.com