dyson_reference

io.github.beepboop2025/noisefloor · Verify this server

Generate a seeded synthetic real-symmetric Brownian-matrix path to illustrate eigenvalue repulsion (beta=1). Use for reproducible numerical education or research references; choose spectral_assessment to analyze observed market panels. No market data is accepted or fetched. All arguments are optional: defaults are dimension=6, steps=40, dt=0.05 and seed=0. Returns status=synthetic, parameters, beta, normalization and path with steps+1 snapshots; each snapshot contains synthetic time and ordered eigenvalues, starting from all zeros. Negative eigenvalues are valid because this is not a covariance matrix. There is no mean reversion, market calibration or factor identity tracking. Reuse seed with the recorded runtime and implementation fingerprint for replay. Out-of-range or noninteger size/step/seed inputs return a tool error. Example: {"dimension":3,"steps":5,"dt":0.05,"seed":7}.