Extremely low metallicity HII regions have been observed with the goal of determining the primordial helium abundance ($Y_{\rm p}$). $Y_{\rm p}$, combined with standard big bang nucleosynthesis and the half-life of the neutron, provides a direct measurement of the number of neutrino families, but $Y_{\rm p}$ must be measured very precisely to provide meaningful constraints on physics beyond the Standard Model. Here we describe a program to combine new Large Binocular Telescope (LBT) observations with a new analysis methodology to significantly improve the determination of $Y_{\rm p}$. The LBT, with its MODS and LUCI instruments, produces spectra, which, when combined with our new analysis methodology, are capable of delivering He abundances in individual HII regions with uncertainties of approximately 2% or less. Archival LBT/MODS spectra of standard stars over a four-year period enable the determination of a wavelength-dependent uncertainty in the MODS spectral response, resulting in improved relative emission line uncertainties. An optimized sample of low-metallicity galaxies has been selected with the goal of producing a determination of $Y_{\rm p}$ with a precision of $\sim$ 0.5%, sufficient to provide an independent constraint on the effective number of neutrino families of $\sim$ 3%.
Accurately determining the elemental abundances of a low metallicity nebula strongly depends on measuring the density (n$_e$) and temperature (T$_e$) of the gas. Because these two parameters are inherently degenerate when derived solely from H and He recombination lines, we rely on the density-sensitive HeI $\lambda$10830 line to assist in resolving this issue, especially for accurate He abundances. To facilitate this, we present near-IR (NIR) LUCI spectra of 48 low-metallicity targets from the Large Binocular Telescope (LBT) and homogeneously reduce them using Pypeit as part of the LBT $Y_{\rm p}$ Project. IR spectra require special care, and we wavelength calibrate by-hand using the bright OH emission lines, carefully apply proper telluric corrections, and co-add the spectra of LUCI1 and LUCI2 on a resampled grid to ensure accurate results. We use a Gaussian profile to fit the emission lines and measure the fluxes relative to Paschen-gamma (P$\gamma$), resulting in HeI $\lambda$10830 to P$\gamma$ ratios consistent with previous studies. As a result, this work significantly expands the available dataset of NIR HeI $\lambda$10830 fluxes in low metallicity galaxies. These high-quality measurements, where we find a median flux ratio uncertainty of $\widetilde{\sigma} = 0.08$, reduce the overall uncertainties in helium abundance estimates for individual targets. The increased size of the high-quality sample enables searching for systematic uncertainties and improves the reliability of the helium abundance determinations used to infer the primordial helium abundance ($Y_{\rm p}$).
The size-velocity dispersion ($\sigma$) relation, while well established for giant HII regions, remains uncertain for their smaller counterparts (physical radii R < 20 pc). Thanks to the LAMOST MRS-N dataset's large sky coverage and high spatial/spectral resolution, we examined this relationship using 10 isolated Galactic HII regions with R < 20 pc. Our results reveal two key findings: (1) these small-size HII regions remarkably follow the same size-$\sigma$ relation as giant HII regions, suggesting this correlation could serve as a novel distance indicator for Galactic HII regions; and (2) we find distinct dynamical behaviors between younger and older HII regions. Specifically, in younger (< 0.5 Myr), ionization-bounded HII regions, the velocity dispersion shows no correlation with expansion velocity, indicating that turbulence is driven primarily by stellar winds and ionization processes. In contrast, in older (> 0.5 Myr), matter-bounded HII regions, a clear correlation emerges, implying that expansion-driven processes begin to play a significant role in generating turbulence. We therefore propose an evolutionary transition in the primary turbulence mechanisms, from being dominated by stellar winds and radiation to being increasingly influenced by expansion-driven dynamics, during the evolution of HII regions. Considering the small sample size used in this work, particularly the inclusion of only two young HII regions, which also have large uncertainties in their expansion velocities, further confirmation of this interpretation will require higher-resolution 2D spectroscopy to resolve blended kinematic components along the line of sight for more accurate estimation of expansion velocities, along with an expanded sample that specifically includes more young HII regions.
This study focuses on forecasting major (>=M-class) solar flares that can severely impact the near-Earth environment. We construct two types of datasets using the Space Weather HMI Active Region Patches (SHARP), and develop a flare prediction network based on large language model (LLMFlareNet). We apply SHapley Additive exPlanations (SHAP) to explain the model predictions. We develop an operational forecasting system based on the LLMFlareNet model. We adopt a daily mode for performance comparison across various operational forecasting systems under identical active region (AR) number and prediction date, using daily operational observational data. The main results are as follows. (1) Through ablation experiments and comparison with baseline models, LLMFlareNet achieves the best TSS scores of 0.720 +/- 0.040 on the ten cross-validation (CV) dataset with mixed ARs. (2) By both global and local SHAP analyses, we identify that R_VALUE is the most influential physical feature for the prediction of LLMFlareNet, aligning with flare magnetic reconnection theory. (3) In daily mode, LLMFlareNet achieves TSS scores of 0.680/0.571 (0.689/0.661, respectively) on the dataset with single/mixed ARs, markedly outperforming NASA/CCMC (SolarFlareNet, respectively). This work introduces the first application of a large language model as a universal computation engine with explainability method in this domain, and presents the first comparison between operational flare forecasting systems in daily mode. The proposed LLMFlareNet-based system demonstrates substantial improvements over existing systems.
We present the on-sky performance of a Radio-Transparent Multi-Layer Insulation filter (RT-MLI) that uses Styroace-II styrofoam to reject ambient thermal radiation from entering a 0.42 m diameter aperture to a sub-100 mK bolometric detector array cooled by a dilution-refrigerator. We find that greater than 90% of the expected incident infra-red (IR) radiation is rejected, resulting in $<$12 W of measured transmitted power. Transmitted power in the detector passbands is consistent with a lower bound of 95%. We address filter design and placement, thermal loading, and mm-wave transmission.
We investigate the evolution of the PAH population's charge state and size across key physical zones in the Orion Bar, which include the HII region, the atomic PDR (APDR), and three HI/H2 dissociation fronts (DF1, DF2, and DF3). Utilising the NASA Ames PAH Infrared Spectroscopic Database (PAHdb) and the pyPAHdb spectral modelling tool, we analysed the MIRI-MRS observations of the Orion Bar from the "PDRs4All" ERS Program. pyPAHdb modelling reveals the fractional contribution of the different PAH charge states and sizes to the total PAH emission across the Orion Bar. Cationic PAH emission peaks in the APDR region, where neutral PAHs have minimal contribution. Emission from neutral PAHs peaks in the HII region that consists of emission from a face-on PDR associated to the background OMC-1 molecular cloud, and in the molecular cloud regions past DF2. PAH anions are observed deep within the DF2 and DF3 zones. The average PAH size ranges between ~$60-74$ Nc. The modelling reveals regions of top-down PAH formation at the ionisation front, and bottom-up PAH formation within the molecular cloud region. The PAH ionisation parameter $\gamma$ ranges between ~$2-9 x 10^4$. Intensity ratios tracing PAH ionisation scale well with $\gamma$ in regions encompassing edge-on or face-on PDR emission, but their correlation weakens within the molecular cloud zone. Modelling of the $5-15$ $\mu$m PAH spectrum with pyPAHdb achieves comprehensive characterization of the net contribution of neutral and cationic PAHs across different environments, whereas empirical PAH proxy intensity ratio tracers can be highly variable and unreliable outside regions dominated by PDR emission. The derived average PAH size in the different physical zones is consistent with a view of PAHs being more extensively subjected to ultraviolet processing closer to the ionisation front, and less affected within the molecular cloud.