P
Physics World Model
← All principles

Stellar Atmosphere Spectral Inversion L1-371

AstrophysicsStellar spectroscopyδ=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

Stellar Atmosphere Spectral Inversion: Stellar spectral inversion: recover T_eff, log g, [Fe/H] from high-resolution spectra via atmosphere model fitting. The forward operator produces the measurement through a 3-node primitive DAG (S.radiative.transfer_lte…); recovery is posed as a nonlinear_inverse problem. Difficulty tier delta=5 with effective condition number kappa_eff~500; continuum_normalization_error, wavelength_calibration_error_kms set the accuracy floor at the Omega boundary. See the forward_model field for the closed-form equation.

L-DAG

S.radiative.transfer_lte -> G.structured -> O.chi2.spectral_lines
S.radiative.transfer_lteG.structuredO.chi2.spectral_lines

Well-posedness W

Existence:
true
Uniqueness:
true
Stability:
conditional
κ:
50000

Existence of the recovered 1D_atmospheric_profile 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); continuum_normalization_error dominates the stability cliff; the remaining mismatch parameters contribute higher-order bias terms. Shot poisson sets the irreducible data-fidelity floor.

Solvability C

Solver class:
statistical [MCMC_SED_fitting or chi2_grid_search (FERRE) or NN_emulator]
Convergence rate q:
2
Complexity:
O(N_lambda * N_grid) for chi2 grid search per iteration

Specs (0)

No L2 specs registered yet for this principle.