Calibrated, multi-future prediction on a quantum-information formalism — density-matrix belief states — toward a unified model of reality.
● Early-stage · built in the open
Most predictive systems collapse what comes next into one answer. Reality doesn't work that way — it branches, stays uncertain, and resolves over time.
We study how to represent that honestly: a distribution over futures that stays calibrated as evidence arrives.
Physics already has a language for systems that are genuinely uncertain and coupled to their environment. We build on it.
Representing mixed, uncertain states — not single point estimates.
Belief evolving under an environment, not in isolation.
Dynamics grounded in the conservation and symmetry principles physics relies on.
Measuring whether our distributions over futures are honest — not just plausible.
The software and machine-learning systems we build are the instrument. The subject is the physics of prediction. We build on existing work in quantum-information approaches to stochastic processes, computational mechanics, and joint-embedding predictive architectures.
Can a single formalism unify how we model reality?
The near-term work is concrete: a streaming world model that predicts well and knows what it doesn't know. The longer aim is more ambitious — and we treat it as a question to be earned, not claimed.
An independent research program founded in 2026 — publishing openly, building open tools, and collaborating with researchers in world models, quantum information, and computational physics.
Jiaxuan Chen — M.S. Physics, Brown University. Founded with a US-based co-founder.
Omytea LLC — a Wyoming-registered entity.
Researchers working on world models, quantum information, or the calibration of prediction — we'd like to hear from you.
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