The effects of He I 10830 on helium abundance determinations

TL;DR

This study shows that incorporating He I $\lambda$10830$ into helium abundance analyses of metal-poor H II regions dramatically improves constraints on density and related parameters, reducing the uncertainty in the primordial helium abundance $Y_p$ by more than a factor of two overall. Using an MCMC framework to fit $y^+$, $n_e$, $T$, and other factors to both optical and infrared helium lines, the authors demonstrate that $\lambda$10830$ provides a strong density diagnostic that helps break the density–temperature degeneracy. Synthetic tests and a carefully curated dataset (ITG14 scaling of Paschen gamma to optical data) yield a final $Y_p = 0.2449 \pm 0.0040$, consistent with Planck/BBN expectations, while also achieving a substantial reduction in the intercept uncertainty and slope variability in the helium–metallicity regression. The results underscore the value of simultaneous optical and infrared spectroscopic observations to minimize systematics and push toward higher-precision cosmological inferences from primordial element abundances.

Abstract

Observations of helium and hydrogen emission lines from metal-poor extragalactic H II regions provide an independent method for determining the primordial helium abundance, Y_p. Traditionally, the emission lines employed are in the visible wavelength range, and the number of suitable lines is limited. Furthermore, when using these lines, large systematic uncertainties in helium abundance determinations arise due to the degeneracy of physical parameters, such as temperature and density. Recently, Izotov, Thuan, & Guseva (2014) have pioneered adding the He 10830 infrared emission line in helium abundance determinations. The strong electron density dependence of He 10830 makes it ideal for better constraining density, potentially breaking the degeneracy with temperature. We revisit our analysis of the dataset published by Izotov, Thuan, & Stasinska (2007) and incorporate the newly available observations of He 10830 by scaling them using the observed-to-theoretical Paschen-gamma ratio. The solutions are better constrained, in particular for electron density, temperature, and the neutral hydrogen fraction, improving the model fit to data, with the result that more spectra now pass screening for quality and reliability, in addition to a standard 95% confidence level cut. Furthermore, the addition of He 10830 decreases the uncertainty on the helium abundance for all galaxies, with reductions in the uncertainty ranging from 10-80%. Overall, we find a reduction in the uncertainty on Y_p by over 50%. From a regression to zero metallicity, we determine Y_p = 0.2449 +/- 0.0040, consistent with the BBN result, Y_p = 0.2470 +/- 0.0002, based on the Planck determination of the baryon density. The dramatic improvement in the uncertainty from incorporating He 10830 strongly supports the case for simultaneous (thus not requiring scaling) observations of visible and infrared helium emission line spectra.

Figures (6)

• Figure 1: Comparison of the pfsdc emissivities, including the collisional correction, versus density, using a temperature of 18,000 K, for He I $\lambda\lambda$3889, 4026, 4471, 5876, 6678, 7065, 10830. The much stronger density dependence of He I $\lambda$10830 is apparent.
• Figure 2: Comparison of the pfsdc emissivities, including the collisional correction, versus temperature, using a density of 100 cm$^{-3}$, for He I $\lambda\lambda$3889, 4026, 4471, 5876, 6678, 7065, 10830.
• Figure 3: Comparison of 1000 MC solutions for analysis with and without He I $\lambda$10830, as well as with and without the [O III] temperature prior. For each of these four cases, the helium abundance is plotted separately versus density and temperature. On each of these eight panels the average MC best-fit value is plotted with its dispersion. From top to bottom the progression of the panels is as labeled: w/ He I $\lambda$10830 & w/ T(O III), w/o He I $\lambda$10830 & w/ T(O III), w/ He I $\lambda$10830 & w/o T(O III), and w/o He I $\lambda$10830 & w/o T(O III). The panels on the left are $y^+$ vs. $n_e$, while those on the right are $y^+$ vs. $T$, and, except for the inset in the bottom left panel, all of the axes are shared and show the same domain and range.
• Figure 4: Plot comparing the parameter solutions for $y^+$, $n_e$, and $T_4$ ($T_e/10^4$) for the 11 qualifying objects in AOPS with He I $\lambda$10830 values in ITG14. The lighter, thinner lines show the results given in AOPS. The results after the inclusion of He I $\lambda$10830 are given in the darker, thicker bars. The uncertainty in $n_e$ is dramatically reduced by the addition of He I $\lambda$10830 with a corresponding reduction in the uncertainty in $y^+$.
• Figure 5: Plot comparing the parameter solutions for $y^+$, $n_e$, and $T_4$ ($T_e/10^4$) for the 11 qualifying objects in AOPS with He I $\lambda$10830 values in ITG14. The lighter, thinner lines show the results where He I $\lambda$10830 is included but the T(O III) prior is removed. The results including both He I $\lambda$10830 and the T(O III) prior are given in the darker, thicker bars. Because including the T(O III) prior does not significantly bias the values of $y^+$, and because its inclusion results in a greater yield of qualifying points, the T(O III) prior is applied in the final analysis.