Search arXivSearch

arXiv · 0904.2748

Star formation in extremely faint dwarf galaxies

Abstract

We study the relationship between the gas column density (derived from GMRT 21 cm data) and the star formation rate surface density (derived from publicly available GALEX data) for a sample of 23 extremely faint dwarf irregular galaxies drawn from the Faint Irregular Galaxy GMRT Survey (FIGGS). Our sample galaxies have a median HI mass of 2.8e07 solar masses and a median blue magnitude -13.2. We find that gas column density averaged over the star forming region of the disk lies below most estimates of the "threshold density" for star formation, and that the average star formation rate surface density for most of the galaxies is also lower than would be expected from the "Kennicutt-Schmidt" law (Kennnicutt 1998}. We also use our data to look for small scale (400 pc and 200 pc) correlations. At 400 pc linear resolution, for 18 of our 23 galaxies, we find that star formation rate surface density can be parametrized as having a power law dependence on gas column density, which varies accross the sample and is in general steeper than "Kennicutt-Schmidt" law. The power law relation holds until one reaches the sensitivity limit of the GALEX data, i.e. we find no evidence for a "threshold density" below which star formation is completely cut off. For the 5 galaxies for which a power law does not provide a good parametrization, there are substantial offsets between the UV bright regions and the HI high column density maps. At 200 pc resolution, the offsets between the peaks in the HI and UV images are more pronounced, and a power law parametrization is possible for only 5 of 10 galaxies.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Sambit Roychowdhury, Jayaram N. Chengalur, Ayesha Begum, Igor D. Karachentsev. 2009-04-17. Star formation in extremely faint dwarf galaxies. https://doi.org/10.1111/j.1365-2966.2009.14931.x

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

Constraints on the Thomson optical depth to the CMB from the Lyman-$α$ forest

We present the first constraints on the electron optical depth to reionization, $τ_{\mathrm{e}}$, from the Lyman-$α$ forest alone for physically motivated reionization models that match the reionization's end-point, $z_{\rm{end}}$, required by the same astrophysical probe, and for symmetric reionization models with fixed duration, $Δz$, commonly adopted in CMB reionization analyses. Compared to traditional estimates from the latter, the Lyman-$α$ forest traces the ionization state of the IGM through its coupling with the thermal state. We find an explicit mapping between the two solving the chemistry and temperature evolution equations for hydrogen and helium. Our results yield $τ_{\mathrm{e}}$=$0.040^{+0.042}_{-0.018}$ (95\% C.L) and $τ_{\mathrm{e}}$=$0.041^{+0.028}_{-0.017}$ for reionization models with $z_{\rm{end}}$ and $Δz$-fixed, respectively. With mock Lyman-$α$ forest data that mimics the precision of future larger quasar sample datasets, we would potentially obtain tighter $τ_{\mathrm{e}}$ constraints, paving the way for CMB-independent constraints on the epoch of reionization from a large-scale structure probe.

astro-ph.CO

Non-minimally Coupled Running Curvaton for DESI-motivated Dynamical Dark Energy

Recent DESI BAO data combined with CMB and supernova measurements suggest a dynamical dark energy that can cross the phantom divide. We show that introducing a non-minimal coupling $ξχ^2R$ to the running-curvaton framework allows a single field to drive early-universe curvature perturbations and late-time phantom-crossing cosmic acceleration without ghost instabilities. Using MCMC background likelihoods with DESI DR2 BAO, Pantheon+ SNe, and a reduced CMB prior, we constrain the cosmological parameters: $H_0 = 67.88^{+0.53}_{-0.61}\,{\rm km\,s^{-1}\,Mpc^{-1}}$, $Ω_m = 0.3072^{+0.0059}_{-0.0054}$, $w_0 = -0.922^{+0.055}_{-0.063}$, and $w_a = -0.205^{+0.173}_{-0.182}$. Parameter degeneracies leave the coupling constants weakly constrained, highlighting the need for full perturbation-level analysis using CMB spectra and lensing.

astro-ph.CO

On the Relation Between Field-Level Posteriors, Correlators, and their Likelihoods

We develop a field-level posterior for cosmological data by marginalizing over initial conditions and noise in a general forward model. While our focus is on large-scale structure data, the results generalize to any weakly non-Gaussian observable. Moreover, the construction is non-perturbative with respect to the forward model and applies equally well to perturbative calculations, simulation-based predictions, and more general effective descriptions. Expanding the FLP around its Gaussian limit, we derive a general expression for the Fisher matrix and reorganize the field-level information into contributions associated with the connected correlators of the evolved field. This makes explicit which terms are captured by likelihood analyses based on the power spectrum, the bispectrum, or finite sets of summary statistics, and which are lost under compression. We recover the standard Gaussian-covariance result for the power spectrum, show that the Gaussian bispectrum likelihood reproduces the corresponding field-level contribution, and show how cross-covariances among summaries progressively reconstruct more of the full field-level information. As an application to the BAO scale, we show how the field contains all the information required for its optimal reconstruction in the presence of noise, and identify the contributions in the FLP needed to attain this limit. We also show that the reconstruction of the initial field arises naturally as a byproduct of our approach, yielding the optimal estimate of the initial conditions given the data and the noise. Our results provide a unified framework to compare field-level and correlator-based inference, to quantify the information loss induced by compression, and to explore the role of stochasticity.

astro-ph.CO