Bifrost

The bridge between mathematical simulation and autonomous AI — connecting Asgard, Mimir, and Hugin into a single reasoning loop.

Bifrost connects three systems: Asgard, where dynamical systems are executable, differentiable, and algebraically transformable; Mimir, a foundation model that recovers mathematical structure from observed behavior; and Hugin, an autonomous AI agent framework. The result is an agentic layer where autonomous agents write equations, simulate them, inspect results, rewrite algebraically, and iterate — all within a mathematically grounded loop.

How It Works

1

Formulate

Express dynamical systems as mathematical equations — differential equations, integrals, compositions — in Asgard's formal notation. Bifrost compiles them into executable, differentiable circuits grounded in category theory. What you write is what you compute.

2

Simulate

Run compiled circuits under any supported calculus — deterministic Taylor-series solutions, Monte Carlo SDE path ensembles, or discrete sequences. The same equation, multiple interpretations. Results stream back as structured data with 3D surfaces, phase portraits, and stochastic trajectory visualizations.

3

Reason

Apply algebraic rewrite rules that transform systems while preserving mathematical correctness. Simplify, factor, find canonical forms, isolate variables, prove equivalences. The categorical structure guarantees every transformation is sound — not approximate, not heuristic.

4

Discover

Autonomous agents close the loop. They form hypotheses, test them through simulation, reason about results, and iterate. Specialized sub-agents handle sustained work — optimizing circuits to fit observed data, calibrating stochastic models to market prices, recovering governing equations from time series. Mimir proposes candidate structures; Asgard verifies them.