Tokamak control & safety Landing

Control Studio

A neuro-symbolic stochastic Petri-net controller for tokamak plasma control, with formal safety envelopes.

SCPN Control — Neuro-Symbolic Stochastic Petri Net Controller for Tokamak Plasma Control

Read the documentation → Source on GitHub Run demo PyPI · 0.22.1
At a glance

Live from the source repository

Reflected from the project's public GitHub repository at build time — never hand-copied.

Latest release v0.22.1 3 Jul 2026
Last activity 10 Jul 2026 most recent push
Primary language Python
On PyPI 0.22.1 scpn-control
Stars 0
control-systemsdigital-twinformal-verificationfusionfusion-energygrad-shafranovkuramotoneuro-symbolicpetri-netplasma-controlplasma-physicspyo3pythonrustspiking-neural-networktokamak
Capabilities

What this studio federates

The verbs, backends, and evidence types the studio publishes through the Hub's capability manifest — the same sealed contract the client-side verifier reads.

Verbs

reconstructsimulateanalysevalidatebenchmarkreplayregulatecertifypredictmitigatemonitorverify

Evidence types

studio.controller-latency.v1studio.controller-run.v1studio.disruption-mitigation.v1studio.disruption-prediction.v1studio.efit-reconstruction.v1studio.equilibrium-analysis.v1studio.geometry-neutral-replay.v1studio.parity-refutation.v1studio.phase-sync-monitor.v1studio.physics-validation.v1studio.safety-certificate.v1studio.scenario-simulation.v1
Live evidence bundle

Verified in your browser

This RO-Crate is fetched client-side, unpacked, and checked against the evidence contract — the server cannot silently change the boundary.

studio.unknown.v1external-dependency-blocked
level 1producer-asserted

Download RO-CrateChecking bundle…
Case studies

How this studio is used

Evidence-backed stories that show the studio in practice, with linked evidence bundles and publications.

Featured

Formal safety envelopes for tokamak control

Using neuro-symbolic stochastic Petri nets to bound plasma-control decisions before they reach the machine, with every command graded against a formal safety envelope and emitted as a studio.safety-certificate.v1 evidence bundle.

Publications

Related publications

Peer-reviewed and whitepaper outputs that cite this studio's evidence bundles.

SCPN Control: Neuro-Symbolic Stochastic Petri Net Controller for Plasma Control

1 Mar 2026

Documentation

Read the full docs

SCPN Control is a research-grade control and validation package for fusion plasma control loops. It turns stochastic Petri-net logic into executable neuro-symbolic controllers, surrounds those controllers with formal contracts, and connects them to equilibrium, transport, disruption, digital-twin, and hardware-in-the-loop evidence gates.

Open the documentation → README on GitHub

The full documentation is maintained in the project's own repository and rendered on its GitHub Pages — this page links to the canonical source rather than duplicating it.

Reflecting anulum/scpn-control @ 8106334 · fetched 10 Jul 2026 · sources: projects.json, github-api, pypi, federation.json