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arxiv: 2605.25368 · v1 · pith:K6GJ2FMWnew · submitted 2026-05-25 · ⚛️ physics.plasm-ph · astro-ph.IM· physics.chem-ph

Bayesian Estimation of Spectroscopic Parameters: Application to the Atomic Nitrogen Bound-Bound System

Pith reviewed 2026-06-29 20:05 UTC · model grok-4.3

classification ⚛️ physics.plasm-ph astro-ph.IMphysics.chem-ph
keywords Bayesian inferenceatomic nitrogenEinstein coefficientsStark broadeningradiative heat fluxhypersonic entryshock tube spectraspectroscopic parameters
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0 comments X

The pith

Bayesian inversion of shock tube spectra reduces uncertainty in atomic nitrogen radiative heat flux predictions by a factor of five.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The paper applies Bayesian inversion to equilibrium spectral radiance measurements from two shock tube shots to infer ten Einstein coefficients and eight Stark broadening coefficients for atomic nitrogen. This quantifies and shrinks the parametric uncertainty that has limited predictions of radiative heating during atmospheric entry. The resulting joint posterior, which also accounts for nuisance uncertainties in temperature and density, is propagated through stagnation-line flow simulations for a 3 m sphere at entry speeds of 10, 12, and 14 km/s. A sympathetic reader would care because tighter spectroscopic constraints translate directly into narrower uncertainty bands on the heat loads that thermal protection systems must withstand.

Core claim

Inverting the measured spectra from shots at 10.32 and 10.72 km/s produces posterior distributions for the eighteen spectroscopic parameters whose uncertainties are substantially smaller than the prior literature ranges; forward propagation of this joint posterior through the flow field then reduces the standard deviation of predicted radiative heat flux by roughly a factor of five relative to the prior, with the largest improvement at 14 km/s where the standard deviation falls from 10.4 to 1.94 W/cm².

What carries the argument

Hybrid principal component analysis and polynomial chaos expansion surrogate model together with a joint likelihood over the two shots, used inside Markov chain Monte Carlo sampling to obtain the posterior over the spectroscopic parameters.

If this is right

  • Posterior uncertainties on the Einstein coefficients and Stark widths are markedly narrower than the prior bands drawn from the literature.
  • The standard deviation of radiative heat flux at 14 km/s drops from 10.4 W/cm² to 1.94 W/cm² when the inferred posteriors replace the priors.
  • The same reduction pattern holds, though smaller in absolute terms, at the lower entry speeds of 12 and 10 km/s.
  • The hybrid surrogate enables tractable sampling across eight separate wavelength regions while coupling the two experimental shots.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • The method could be applied to other radiating species once suitable equilibrium spectra become available.
  • If spectroscopic uncertainty was previously the dominant contributor to heat-flux scatter, vehicle thermal-protection margins could be tightened without raising risk.
  • Additional wavelength coverage or higher-resolution spectra would be expected to shrink the remaining posterior width further.
  • The framework already folds temperature and density uncertainty into the inference, so the same pipeline can absorb other measured nuisance quantities.

Load-bearing premise

The post-shock region is in local thermodynamic equilibrium so the Boltzmann distribution fixes species populations without additional free parameters.

What would settle it

New measurements of the same nitrogen lines that fall outside the reported posterior intervals, or spectra recorded under conditions where the local thermodynamic equilibrium assumption is known to fail, would show whether the inferred parameter distributions are consistent with independent data.

read the original abstract

Atomic nitrogen bound-bound radiation is a major component of the radiative heat flux on hypersonic vehicles entering nitrogen-dominated atmospheres, yet its prediction is limited by substantial parametric uncertainty in the published Einstein coefficients and Stark broadening coefficients. In the present study, these spectroscopic parameters are inferred and their uncertainty is quantified through Bayesian inversion of equilibrium spectral radiance measured in the NASA Ames Electric-Arc Shock Tube for two shots of the Test 62 campaign at shock speeds of 10.32 and 10.72 km/s. The inference is restricted to the post-shock equilibrium region, where the Boltzmann assumption closes the species population degree of freedom. The residual uncertainty in the post-shock temperature and species number densities is incorporated as a coupled nuisance parameter distribution. A hybrid principal component analysis and polynomial chaos expansion surrogate model and a likelihood formulated jointly over the two shots enable tractable Markov chain Monte Carlo sampling across multiple wavelength regions. Eighteen parameters in total, ten Einstein coefficients and eight Stark broadening coefficients, are inferred across eight wavelength regions, with posterior uncertainties significantly reduced relative to the prior literature bands. Forward propagation of the joint posterior through the stagnation-line flow field around a 3 m radius sphere at entry velocities of 10, 12, and 14 km/s demonstrates a reduction in the standard deviation of the predicted radiative heat flux by approximately a factor of five compared with the prior, in particular at 14 km/s, it drops from 10.4 to 1.94 W/cm$^{2}$.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

2 major / 0 minor

Summary. The paper claims that Bayesian MCMC sampling over a joint likelihood, using a hybrid PCA-PCE surrogate and nuisance parameters for post-shock T and densities, infers 18 spectroscopic parameters (10 Einstein A coefficients and 8 Stark broadening coefficients) from equilibrium radiance spectra in two NASA Ames EAST shots at 10.32 and 10.72 km/s. The resulting joint posterior, when propagated through a stagnation-line flow solver for a 3 m sphere at 10–14 km/s, reduces the standard deviation of predicted radiative heat flux by a factor of approximately five relative to literature priors (e.g., from 10.4 to 1.94 W/cm² at 14 km/s).

Significance. If the LTE assumption and surrogate accuracy hold, the work supplies a data-driven tightening of uncertainty on atomic nitrogen bound-bound radiation, a dominant contributor to radiative heating in nitrogen atmospheres. The joint two-shot likelihood, nuisance-parameter treatment, and end-to-end propagation to flight-relevant heat flux constitute a concrete advance over prior uncertainty bands.

major comments (2)
  1. [Abstract] Abstract (paragraph on inference restriction): The central uncertainty-reduction claim rests on the post-shock region being in LTE so that the Boltzmann relation closes level populations from a single T without additional free parameters. No quantitative test (e.g., consistency of multiple line ratios, comparison with independent T diagnostics, or sensitivity study) is reported to confirm that deviations from LTE remain below the precision needed for the reported factor-of-five drop in heat-flux standard deviation.
  2. [Abstract] Abstract (surrogate and sampling paragraph): Tractable MCMC is enabled by the hybrid PCA-PCE surrogate, yet no quantitative surrogate error bounds, cross-validation metrics, or MCMC convergence diagnostics (e.g., Gelman-Rubin statistic, effective sample size) are supplied. These diagnostics are load-bearing for the reliability of the reported posterior widths and the downstream heat-flux uncertainty reduction.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for their constructive comments, which highlight important aspects of the LTE assumption and numerical validation. We respond to each major comment below and will incorporate revisions to strengthen the manuscript.

read point-by-point responses
  1. Referee: [Abstract] Abstract (paragraph on inference restriction): The central uncertainty-reduction claim rests on the post-shock region being in LTE so that the Boltzmann relation closes level populations from a single T without additional free parameters. No quantitative test (e.g., consistency of multiple line ratios, comparison with independent T diagnostics, or sensitivity study) is reported to confirm that deviations from LTE remain below the precision needed for the reported factor-of-five drop in heat-flux standard deviation.

    Authors: The manuscript restricts inference to the post-shock equilibrium region of the selected EAST shots, relying on prior literature characterizations of these conditions to justify the Boltzmann closure. No new quantitative LTE validation (such as line-ratio consistency checks) is performed within this work. We will add a sensitivity study in the revised manuscript quantifying the effect of plausible small LTE deviations on the posterior widths and downstream heat-flux uncertainty, together with explicit references to existing equilibrium assessments of the Test 62 shots. revision: yes

  2. Referee: [Abstract] Abstract (surrogate and sampling paragraph): Tractable MCMC is enabled by the hybrid PCA-PCE surrogate, yet no quantitative surrogate error bounds, cross-validation metrics, or MCMC convergence diagnostics (e.g., Gelman-Rubin statistic, effective sample size) are supplied. These diagnostics are load-bearing for the reliability of the reported posterior widths and the downstream heat-flux uncertainty reduction.

    Authors: We agree that surrogate accuracy and MCMC convergence metrics are necessary to support the reported posterior uncertainties. The revised manuscript will include quantitative surrogate validation (cross-validation errors and error bounds) and MCMC diagnostics (Gelman-Rubin statistics and effective sample sizes) for the chains used in the joint two-shot inference. revision: yes

Circularity Check

0 steps flagged

No significant circularity detected

full rationale

The derivation proceeds by Bayesian inversion of measured post-shock radiance to obtain posteriors on 18 spectroscopic parameters (Einstein A and Stark coefficients), then forward-propagates the joint posterior through an independent stagnation-line flow solver to obtain radiative heat flux statistics at different velocities. This forward step is statistically independent of the inference data and does not reduce by the paper's own equations to a quantity defined in terms of the fitted parameters themselves. No self-citations, uniqueness theorems, or ansatzes imported from prior author work appear as load-bearing elements; the LTE closure is an explicit modeling assumption rather than a definitional loop. The reported uncertainty reduction is therefore a genuine propagation result rather than a tautology.

Axiom & Free-Parameter Ledger

1 free parameters · 1 axioms · 0 invented entities

The inference rests on the equilibrium assumption to close populations and on the accuracy of the hybrid surrogate for the forward radiative transfer model; no new entities are postulated.

free parameters (1)
  • post-shock temperature and species densities
    Treated as coupled nuisance parameters whose residual uncertainty is propagated into the likelihood.
axioms (1)
  • domain assumption Boltzmann assumption closes the species population degree of freedom in the post-shock equilibrium region
    Invoked to restrict the inference and remove population degrees of freedom.

pith-pipeline@v0.9.1-grok · 5804 in / 1290 out tokens · 36951 ms · 2026-06-29T20:05:09.274202+00:00 · methodology

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Reference graph

Works this paper leans on

71 extracted references

  1. [1]

    Analysis of an electromagnetic mitigation scheme for reentry telemetry through plasma,

    Kim, M., Keidar, M., and Boyd, I. D., “Analysis of an electromagnetic mitigation scheme for reentry telemetry through plasma,” Journal of Spacecraft and Rockets , Vol. 45, No. 6, 2008, pp. 1223–1229

  2. [2]

    Analysis of shockwave radiation data in nitrogen,

    Cruden, B. A., and Brandis, A. M., “Analysis of shockwave radiation data in nitrogen,” AIAA Aviation 2019 Forum , 2019, p. 3359. 29

  3. [3]

    Validation cases for recombining nitrogen and air plasmas,

    Tibère-Inglesse, A. C., McGuire, S. D., Mariotto, P ., and Laux, C. O., “Validation cases for recombining nitrogen and air plasmas,” Plasma Sources Science and Technology, Vol. 27, No. 11, 2018, p. 115010

  4. [4]

    On inelastic hydrogen atom collisions in stellar atmospheres,

    Barklem, P ., Belyaev, A., Guitou, M., Feautrier, N., Gadéa, F. X., and Spielfiedel, A., “On inelastic hydrogen atom collisions in stellar atmospheres,” Astronomy & Astrophysics, Vol. 530, 2011, p. A94

  5. [5]

    Modeling of electronic excitation in weakly ionized nitrogen mixtures,

    Aiken, T. T., and Boyd, I. D., “Modeling of electronic excitation in weakly ionized nitrogen mixtures,” AIAA AVIATION 2023 Forum, 2023, p. 3619

  6. [6]

    Bayesian calibration of computer models,

    Kennedy, M. C., and O’Hagan, A., “Bayesian calibration of computer models,” Journal of the Royal Statistical Society: Series B (Statistical Methodology), Vol. 63, No. 3, 2001, pp. 425–464

  7. [7]

    Bayesian Methods in Engineering Design Problems,

    Swiler, L. P ., “Bayesian Methods in Engineering Design Problems,” Tech. Rep. SAND2005-3294, Sandia National Laborato- ries, 2006

  8. [8]

    Rebuilding freestream atmospheric conditions using surface pressure and heat flux data,

    Cortesi, A. F., Congedo, P . M., Magin, T. E., Van Hove, B., and Karatekin, O., “Rebuilding freestream atmospheric conditions using surface pressure and heat flux data,” 8th AIAA Atmospheric and Space Environments Conference , 2016, p. 4196

  9. [9]

    Forward and backward uncertainty quantification with active subspaces: application to hypersonic flows around a cylinder,

    Cortesi, A. F., Constantine, P . G., Magin, T. E., and Congedo, P . M., “Forward and backward uncertainty quantification with active subspaces: application to hypersonic flows around a cylinder,” Journal of Computational Physics , Vol. 407, 2020, p. 109079

  10. [10]

    Estimation of the nitrogen ionization reaction rate using electric arc shock tube data and Bayesian model analysis,

    Miki, K., Panesi, M., Prudencio, E., and Prudhomme, S., “Estimation of the nitrogen ionization reaction rate using electric arc shock tube data and Bayesian model analysis,” Physics of Plasmas, Vol. 19, No. 2, 2012

  11. [11]

    Stochastic operator learning for chemistry in non-equilibrium flows,

    Kuppa, M., Ghanem, R., and Panesi, M., “Stochastic operator learning for chemistry in non-equilibrium flows,” Journal of Computational Physics, 2025, p. 114381

  12. [12]

    Uncertainty quantification of a graphite nitridation experiment using a Bayesian approach,

    Upadhyay, R., Miki, K., Ezekoye, O., and Marschall, J., “Uncertainty quantification of a graphite nitridation experiment using a Bayesian approach,” Experimental Thermal and Fluid Science , Vol. 35, No. 8, 2011, pp. 1588–1599

  13. [13]

    A surrogate-based optimal likelihood func- tion for the Bayesian calibration of catalytic recombination in atmospheric entry protection materials,

    del Val, A., Le Maître, O. P ., Magin, T. E., Chazot, O., and Congedo, P . M., “A surrogate-based optimal likelihood func- tion for the Bayesian calibration of catalytic recombination in atmospheric entry protection materials,” Applied Mathematical Modelling, Vol. 101, 2022, pp. 791–810

  14. [14]

    Stochastic calibration of a carbon nitridation model from plasma wind tunnel experiments using a Bayesian formulation,

    del Val, A., Le Maître, O. P ., Congedo, P . M., and Magin, T. E., “Stochastic calibration of a carbon nitridation model from plasma wind tunnel experiments using a Bayesian formulation,” Carbon, Vol. 200, 2022, pp. 199–214

  15. [15]

    Bayesian calibration and assessment of gas-surface interaction models and experiments in atmospheric entry plasmas,

    del Val, A., “Bayesian calibration and assessment of gas-surface interaction models and experiments in atmospheric entry plasmas,” Ph.D. thesis, Institut polytechnique de Paris; Ecole Polytechnique (Palaiseau, France), 2021

  16. [16]

    Robust calibration of an air-carbon ablation model employing Plasmatron and molecular beam data,

    Piro, V ., Capriati, M., Bariselli, F., Congedo, P . M., and Magin, T. E., “Robust calibration of an air-carbon ablation model employing Plasmatron and molecular beam data,” Tech. Rep. hal-05214270v2, von Karman Institute for Fluid Dynamics, 2025. 30

  17. [17]

    Calibration and uncertainty quantification of vista ablator material database using bayesian inference,

    Rostkowski, P ., Venturi, S., Panesi, M., Omidy, A., Weng, H., and Martin, A., “Calibration and uncertainty quantification of vista ablator material database using bayesian inference,” Journal of Thermophysics and Heat Transfer , Vol. 33, No. 2, 2019, pp. 356–369

  18. [18]

    Effects of problem complexity reduction on parameter sensitivity and classification in charring ablator scenarios,

    Rostkowski, P ., Meurisse, J. B., Thornton, J. M., Smith, R. C., and Panesi, M., “Effects of problem complexity reduction on parameter sensitivity and classification in charring ablator scenarios,” Aerospace Science and Technology, Vol. 124, 2022, p. 107522

  19. [19]

    Non-Deterministic extension of plasma wind tunnel data calibrated model predictions to flight conditions,

    Rostkowski, P ., Meurisse, J. B., and Panesi, M., “Non-Deterministic extension of plasma wind tunnel data calibrated model predictions to flight conditions,” Aerospace Science and Technology, 2025, p. 111059

  20. [20]

    Shock tube radiation measurements in nitrogen,

    Brandis, A. M., and Cruden, B. A., “Shock tube radiation measurements in nitrogen,” 2018 Joint Thermophysics and Heat Transfer Conference, 2018, p. 3437

  21. [21]

    Measurement of radiative nonequilibrium for air shocks between 7 and 9 km/s,

    Cruden, B. A., and Brandis, A. M., “Measurement of radiative nonequilibrium for air shocks between 7 and 9 km/s,” Journal of Thermophysics and Heat Transfer, Vol. 34, No. 1, 2020, pp. 154–180

  22. [22]

    Non-equilibrium radiation for earth entry,

    Brandis, A. M., Johnston, C. O., and Cruden, B. A., “Non-equilibrium radiation for earth entry,” 46th AIAA Thermophysics Conference, 2016, p. 3690

  23. [23]

    Titan atmospheric entry radiative heating,

    Brandis, A. M., and Cruden, B. A., “Titan atmospheric entry radiative heating,” 47th AIAA Thermophysics Conference, 2017, p. 4534

  24. [24]

    L., Fuhr, J

    Wiese, W. L., Fuhr, J. R., and Deters, T. M., Atomic Transition Probabilities of Carbon, Nitrogen, and Oxygen: A Critical Data Compilation, Vol. Monograph No. 7, American Chemical Society and American Institute of Physics for the National Institute of Standards and Technology, 1996

  25. [25]

    Spectrum modeling for air shock-layer radiation at lunar-return conditions,

    Johnston, C. O., Hollis, B. R., and Sutton, K., “Spectrum modeling for air shock-layer radiation at lunar-return conditions,” Journal of Spacecraft and Rockets , Vol. 45, No. 5, 2008, pp. 865–878

  26. [26]

    Electronic-state-resolved analysis of high-enthalpy air plasma flows,

    Jo, S. M., Kwon, O. J., and Kim, J. G., “Electronic-state-resolved analysis of high-enthalpy air plasma flows,” Physical Review E, Vol. 100, No. 3, 2019, p. 033203

  27. [27]

    Empirical fits to the Voigt line width: A brief review,

    Olivero, J., and Longbothum, R., “Empirical fits to the Voigt line width: A brief review,” Journal of Quantitative Spectroscopy and Radiative Transfer, Vol. 17, No. 2, 1977, pp. 233–236

  28. [28]

    Modelling of radiating shock layers for atmospheric entry at Earth and Mars,

    Potter, D., “Modelling of radiating shock layers for atmospheric entry at Earth and Mars,” Ph.D. thesis, University of Queens- land, 2011

  29. [29]

    Calculation of radiation from argon shock layers,

    Park, C., “Calculation of radiation from argon shock layers,” Journal of Quantitative Spectroscopy and Radiative Transfer , Vol. 28, No. 1, 1982, pp. 29–40

  30. [30]

    Plato: A High-Fidelity Library for Multicomponent Gases and Plasmas,

    Munafò, A., and Panesi, M., “Plato: A High-Fidelity Library for Multicomponent Gases and Plasmas,” Journal of Thermo- physics and Heat Transfer, 2025, pp. 1–21. 31

  31. [31]

    A computational model for nanosecond pulse laser-plasma interactions,

    Munafò, A., Alberti, A., Pantano, C., Freund, J. B., and Panesi, M., “A computational model for nanosecond pulse laser-plasma interactions,” Journal of Computational Physics , Vol. 406, 2020, p. 109190

  32. [32]

    Multi-fidelity modeling framework for radiative transfer in hypersonic atmospheric entry,

    Jo, S. M., Kumar, S., Le Maout, V ., Munafò, A., and Panesi, M., “Multi-fidelity modeling framework for radiative transfer in hypersonic atmospheric entry,” AIAA Scitech 2023 Forum, 2023, p. 1730

  33. [33]

    Uqpy v4. 1: Uncertainty quantification with python,

    Tsapetis, D., Shields, M. D., Giovanis, D. G., Olivier, A., Novak, L., Chakroborty, P ., Sharma, H., Chauhan, M., Kontolati, K., Vandanapu, L., et al., “Uqpy v4. 1: Uncertainty quantification with python,” SoftwareX, Vol. 24, 2023, p. 101561

  34. [34]

    Uncertainty analysis and validation of radiation measure- ments for Earth reentry,

    Brandis, A., Johnston, C., Cruden, B., Prabhu, D., and Bose, D., “Uncertainty analysis and validation of radiation measure- ments for Earth reentry,” Journal of Thermophysics and Heat Transfer , Vol. 29, No. 2, 2015, pp. 209–221

  35. [35]

    Analysis of air radiation measurements obtained in the EAST shocktube facility,

    Brandis, A., “Analysis of air radiation measurements obtained in the EAST shocktube facility,” Center of Turbulence Research, Annual Research Briefs, 2010, pp. 105–116

  36. [36]

    Security requirements for cryptographic modules,

    National Institute of Standards and Technology, “Security requirements for cryptographic modules,” Tech. Rep. Federal Infor- mation Processing Standards Publications (FIPS) 140-2, Change Notice 2 December 03, 2002, U.S. Department of Commerce, 2001

  37. [37]

    Atomic transition probabilities,

    Wiese, W. L., “Atomic transition probabilities,” Tech. Rep. NSRDS-NBS, National Bureau of Standards, 1969

  38. [38]

    Atomic data for opacity calculations. I. General description,

    Seaton, M., “Atomic data for opacity calculations. I. General description,” Journal of Physics B: Atomic and Molecular Physics, Vol. 20, No. 23, 1987, pp. 6363–6378

  39. [39]

    Atomic data for opacity calculations. II. Computational methods,

    Berrington, K., Burke, P ., Butler, K., Seaton, M., Storey, P ., Taylor, K., and Y an, Y ., “Atomic data for opacity calculations. II. Computational methods,” Journal of Physics B: Atomic and Molecular Physics , Vol. 20, No. 23, 1987, pp. 6379–6397

  40. [40]

    Atomic data for opacity calculations. III. Oscillator strengths for C II,

    Y an, Y ., Taylor, K., and Seaton, M., “Atomic data for opacity calculations. III. Oscillator strengths for C II,” Journal of Physics B: Atomic and Molecular Physics , Vol. 20, No. 23, 1987, pp. 6399–6408

  41. [41]

    Atomic data for opacity calculations. VII. Energy levels, f values and photoionisation cross sections for He-like ions,

    Fernley, J., Taylor, K., and Seaton, M., “Atomic data for opacity calculations. VII. Energy levels, f values and photoionisation cross sections for He-like ions,” Journal of Physics B: Atomic and Molecular Physics , Vol. 20, No. 23, 1987, pp. 6457–6476

  42. [42]

    Atomic data for opacity calculations. XI. The carbon isoelectronic sequence,

    Luo, D., and Pradhan, A., “Atomic data for opacity calculations. XI. The carbon isoelectronic sequence,” Journal of Physics B: Atomic, Molecular and Optical Physics , Vol. 22, No. 21, 1989, pp. 3377–3395

  43. [43]

    Atomic data for opacity calculations. XIV . The beryllium sequence,

    Tully, J. A., Seaton, M. J., and Berrington, K. A., “Atomic data for opacity calculations. XIV . The beryllium sequence,” Journal of Physics B: Atomic, Molecular and Optical Physics , Vol. 23, No. 21, 1990, pp. 3811–3837

  44. [44]

    Accurate f values of astrophysical interest for neutral carbon,

    Hibbert, A., Biémont, E., Godefroid, M., and Vaeck, N., “Accurate f values of astrophysical interest for neutral carbon,” Astronomy and Astrophysics Supplement Series (ISSN 0365-0138) , Vol. 99, 1993, pp. 179–204

  45. [45]

    New accurate transition probabilities for astrophysically important spectral lines of neutral nitrogen,

    Hibbert, A., Biemont, E., Godefroid, M., and Vaeck, N., “New accurate transition probabilities for astrophysically important spectral lines of neutral nitrogen,” Astronomy and Astrophysics Supplement Series (ISSN 0365-0138)., Vol. 88, 1991, pp. 505– 524. 32

  46. [46]

    E1 transitions of astrophysical interest in neutral oxygen,

    Hibbert, A., Biémont, E., Godefroid, M., and Vaeck, N., “E1 transitions of astrophysical interest in neutral oxygen,” Journal of Physics B: Atomic, Molecular and Optical Physics , Vol. 24, No. 18, 1991, pp. 3943–3958

  47. [47]

    Oscillator strengths for optically allowed transitions in singly ionized nitrogen,

    Bell, K., Ramsbottom, C., and Hibbert, A., “Oscillator strengths for optically allowed transitions in singly ionized nitrogen,” Journal of Physics B: Atomic, Molecular and Optical Physics , Vol. 25, No. 8, 1992, pp. 1735–1744

  48. [48]

    Accurate transition probabilities for some spectral lines of singly ionized oxygen,

    Bell, K., Hibbert, A., Stafford, R., and McLaughlin, B., “Accurate transition probabilities for some spectral lines of singly ionized oxygen,” Physica Scripta, Vol. 50, No. 4, 1994, pp. 343–353

  49. [49]

    Transition probabilities for some spectral lines of N III,

    Bell, K., Hibbert, A., Stafford, R., and Brage, T., “Transition probabilities for some spectral lines of N III,” Monthly Notices of the Royal Astronomical Society, Vol. 272, No. 4, 1995, pp. 909–912

  50. [50]

    D., The theory of atomic structure and spectra , Vol

    Cowan, R. D., The theory of atomic structure and spectra , Vol. 3, Univ of California Press, 2023

  51. [51]

    W., Astrophysical Quantities, 3rd ed., Athlone Press, 1973

    Allen, C. W., Astrophysical Quantities, 3rd ed., Athlone Press, 1973

  52. [52]

    Improved critical compilations of selected atomic transition probabilities for neutral and singly ionized carbon and nitrogen,

    Wiese, W. L., and Fuhr, J. R., “Improved critical compilations of selected atomic transition probabilities for neutral and singly ionized carbon and nitrogen,” Journal of Physical and Chemical Reference Data , Vol. 36, No. 4, 2007, pp. 1287–1345

  53. [53]

    Breit-Pauli energy levels and transition rates for nitrogen-like and oxygen-like sequences,

    Tachiev, G., and Fischer, C. F., “Breit-Pauli energy levels and transition rates for nitrogen-like and oxygen-like sequences,” Astronomy & Astrophysics, Vol. 385, No. 2, 2002, pp. 716–723

  54. [54]

    Regularities and similarities in plasma broadened spectral line widths (Stark widths),

    Wiese, W., and Konjevic, N., “Regularities and similarities in plasma broadened spectral line widths (Stark widths),” Journal of Quantitative Spectroscopy and Radiative Transfer, Vol. 28, No. 3, 1982, pp. 185–198

  55. [55]

    R., Spectral line broadening by plasmas , Academic Press, 1974

    Griem, H. R., Spectral line broadening by plasmas , Academic Press, 1974

  56. [56]

    Spectral absorption coefficients of carbon, nitrogen and oxygen atoms,

    Wilson, K., and Nicolet, W., “Spectral absorption coefficients of carbon, nitrogen and oxygen atoms,” Journal of Quantitative Spectroscopy and Radiative Transfer, Vol. 7, No. 6, 1967, pp. 891–941

  57. [57]

    Nonequilibrium shock-layer radiative heating for Earth and Titan entry,

    Johnston, C. O., “Nonequilibrium shock-layer radiative heating for Earth and Titan entry,” Ph.D. thesis, Virginia Polytechnic Institute and State University, 2006

  58. [58]

    Validation of high speed Earth atmospheric entry radiative heating from 9.5 to 15.5 km/s,

    Brandis, A., Johnston, C., Cruden, B., Prabhu, D., and Bose, D., “Validation of high speed Earth atmospheric entry radiative heating from 9.5 to 15.5 km/s,” 43rd AIAA thermophysics conference, 2012, p. 2865

  59. [59]

    D., Hypersonic and high temperature gas dynamics , AIAA, 1989

    Anderson, J. D., Hypersonic and high temperature gas dynamics , AIAA, 1989

  60. [60]

    Electron density measurement in reentry shocks for lunar return,

    Cruden, B. A., “Electron density measurement in reentry shocks for lunar return,” Journal of Thermophysics and Heat Transfer, Vol. 26, No. 2, 2012, pp. 222–230

  61. [61]

    A comparison of three methods for selecting values of input variables in the analysis of output from a computer code,

    McKay, M. D., Beckman, R. J., and Conover, W. J., “A comparison of three methods for selecting values of input variables in the analysis of output from a computer code,” Technometrics, Vol. 42, No. 1, 2000, pp. 55–61. 33

  62. [62]

    Saltelli, A., Ratto, M., Andres, T., Campolongo, F., Cariboni, J., Gatelli, D., Saisana, M., and Tarantola, S., Global sensitivity analysis: the primer , John Wiley & Sons, 2008

  63. [63]

    Generalized polynomials and associated operational identities,

    Dattoli, G., Lorenzutta, S., Mancho, A., and Torre, A., “Generalized polynomials and associated operational identities,” Jour- nal of computational and applied mathematics , Vol. 108, No. 1-2, 1999, pp. 209–218

  64. [64]

    Equation of state calculations by fast computing machines,

    Metropolis, N., Rosenbluth, A. W., Rosenbluth, M. N., Teller, A. H., and Teller, E., “Equation of state calculations by fast computing machines,” The journal of chemical physics , Vol. 21, No. 6, 1953, pp. 1087–1092

  65. [65]

    DRAM: efficient adaptive MCMC,

    Haario, H., Laine, M., Mira, A., and Saksman, E., “DRAM: efficient adaptive MCMC,” Statistics and computing , Vol. 16, No. 4, 2006, pp. 339–354

  66. [66]

    Combining field data and computer simulations for calibration and prediction,

    Higdon, D., Kennedy, M., Cavendish, J. C., Cafeo, J. A., and Ryne, R. D., “Combining field data and computer simulations for calibration and prediction,” SIAM Journal on Scientific Computing , Vol. 26, No. 2, 2004, pp. 448–466

  67. [67]

    Power prior distributions for regression models,

    Ibrahim, J. G., and Chen, M.-H., “Power prior distributions for regression models,” Statistical Science, 2000, pp. 46–60

  68. [68]

    A general framework for updating belief distributions,

    Bissiri, P . G., Holmes, C. C., and Walker, S. G., “A general framework for updating belief distributions,” Journal of the Royal Statistical Society Series B: Statistical Methodology , Vol. 78, No. 5, 2016, pp. 1103–1130

  69. [69]

    Absolute radiation measurements in Earth and Mars entry conditions,

    Cruden, B. A., “Absolute radiation measurements in Earth and Mars entry conditions,” Tech. Rep. ARC-E-DAA-TN13965, NASA Ames Research Center, 2014

  70. [70]

    Review of chemical-kinetic problems of future NASA missions. I-Earth entries,

    Park, C., “Review of chemical-kinetic problems of future NASA missions. I-Earth entries,” Journal of Thermophysics and Heat transfer, Vol. 7, No. 3, 1993, pp. 385–398

  71. [71]

    Hegel: a high-fidelity flexible software for hypersonics and plasma simu- lations,

    Munafò, A., Kumar, S., Jo, S. M., and Panesi, M., “Hegel: a high-fidelity flexible software for hypersonics and plasma simu- lations,” AIAA SciTech 2024 Forum, 2024, p. 0449. 34 Supplementary Material: Bayesian Estimation of Spectroscopic Parameters: Application to the Atomic Nitrogen Bound-Bound System Tae Woong Jeong 1 and Sung Min Jo 2,a) 1Korea Advanc...