P
Physics World Model
← All principles

Neutrino Oscillation Parameter Extraction L1-485

Particle PhysicsNeutrino physicsδ=5 · challengingL_DAG = 3.5📋 Stub — not mineable
📋

Unclaimed Principle — open for contribution

This Principle is declared in the catalog but has no reference solver, no pinned dataset, and is not registered on-chain. There is no reward pool. Submitting a cert against this Principle today will record the cert for reproducibility but pay zero PWM.

To claim it as a Bounty #7 contribution: open a PR adding (1) a reference solver, (2) ≥1 dataset pinned to IPFS, (3) updates to the L3 manifest with dataset CIDs. After verifier-agent triple-review, the founders' 3-of-5 multisig signs PWMRegistry.register() and the Principle becomes mineable.

Forward model E

Neutrino Oscillation Parameter Extraction: Neutrino oscillation fitting: extract PMNS mixing angles and mass-squared differences from appearance/disappearance spectra. The forward operator produces the measurement through a 3-node primitive DAG (M.pmns.mixing_matrix…); recovery is posed as a parameter_estimation problem. Difficulty tier delta=5 with effective condition number kappa_eff~500; flux_normalization_uncertainty_percent, cross_section_model_error set the accuracy floor at the Omega boundary. See the forward_model field for the closed-form equation.

L-DAG

L.linear_op -> S.matter.msw_effect -> O.chi2.event_rates
L.linear_opS.matter.msw_effectO.chi2.event_rates

Well-posedness W

Existence:
true
Uniqueness:
true
Stability:
conditional
κ:
10000

Existence of the recovered PMNS_parameter_vector is guaranteed within the declared Omega bounds. Uniqueness holds on the measurement-supported subspace; out-of-support modes are controlled by declared priors. Stability is conditionally stable (kappa_eff ~= 500); flux_normalization_uncertainty_percent dominates the stability cliff; the remaining mismatch parameters contribute higher-order bias terms. Poisson sets the irreducible data-fidelity floor.

Solvability C

Solver class:
statistical [chi2_minimization_GLoBES or Bayesian_NOvA or MCMC_T2K]
Convergence rate q:
2
Complexity:
O(N_bins * N_params) per chi2 evaluation + oscillation probability per iteration

Specs (0)

No L2 specs registered yet for this principle.