We present the first astrophysical detection of methanol (CH3OH) in the torsional band near 25 um. Using high resolution mid-infrared (MIR) spectroscopy, we identified over seventy gas-phase CH3OH absorption lines between 20 and 28 um towards the massive protostar NGC 7538 IRS 1 with SOFIA/EXES. We derive a temperature of 180 K and a total column density of 2 x 10^17 cm-2, comparable to sub-mm measurements. Complementary analysis of acetylene (C2H2) absorption lines is also included. Both CH3OH and C2H2 reveal an unresolved second velocity component. These MIR absorption lines likely probe the molecular material in two edge-on disks, supporting the scenario that NGC 7538 IRS 1 consists of multiple protostars. We provide an updated line list for the torsional band of CH3OH, which was generated from lab work and model calculations. This discovery and the updated line list will enable the search for CH3OH in JWST/MIRI spectra.
We investigate how dust foreground complexity can affect measurements of the tensor-to-scalar ratio, $r$, in the context of the Simons Observatory, using a cross-spectrum component separation analysis. Employing a suite of simulations with realistic Galactic dust emission, we find that spatial variation in the dust frequency spectrum, parametrized by $\beta_d$, can bias the estimate for $r$ when modeled using a low-order moment expansion to capture this spatial variation. While this approach performs well across a broad range of dust complexity, the bias increases with more extreme spatial variation in dust frequency spectrum, reaching as high as $r\sim0.03$ for simulations with no primordial tensors and a spatial dispersion of $\sigma(\beta_d)\simeq0.3$ -- the most extreme case considered, yet still consistent with current observational constraints. This bias is driven by changes in the $\ell$-dependence of the dust power spectrum as a function of frequency that can mimic a primordial $B$-mode tensor signal. Although low-order moment expansions fail to capture the full effect when the spatial variations of $\beta_d$ become large and highly non-Gaussian, our results show that extended parametric methods can still recover unbiased estimates of $r$ under a wide range of dust complexities. We further find that the bias in $r$, at the highest degrees of dust complexity, is largely insensitive to the spatial structure of the dust amplitude and is instead dominated by spatial correlations between $\beta_d$ and dust amplitude, particularly at higher orders. If $\beta_d$ does spatially vary at the highest levels investigated here, we would expect to use more flexible foreground models to achieve an unbiased constraint on $r$ for the noise levels anticipated from the Simons Observatory.