I know. Serious bees wax sounds pretty serious. Unfortunately, on occasion I am forced to face reality and be (a bit) serious. Fortunately, the serious bees wax is also fun. If you were unaware, I do science. Specifically physics. More specifically astrophysics. Or is it astonomy... Once of those two. I should probably find out which... At least my supervisor doesn't know either...

Anyway. As a byproduct of being serious, I have some papers full of useful science. I deal with galaxy evolution and have "experties" in far-infrared observation, SED modelling with multi- wavelength data, Bayesian statistics and forward modelling. My papers will tell you more.

Main sequence of star forming galaxies beyond the Herschel confusion limit

W. J. Pearson et al., A&A, 615, 146 (2018)

Context: Deep far-infrared (FIR) cosmological surveys are known to be affected by source confusion, causing issues when examining the main sequence (MS) of star forming galaxies. In the past this has typically been partially tackled by the use of stacking. However, stacking only provides the average properties of the objects in the stack.

Aims: This work aims to trace the MS over 0.2 ≤ z < 6.0 using the latest de-blended Herschel photometry, which reaches ≈ 10 times deeper than the 5σ confusion limit in SPIRE. This provides more reliable star formation rates (SFRs), especially for the fainter galaxies, and hence a more reliable MS.

Methods: We built a pipeline that uses the spectral energy distribution (SED) modelling and fitting tool CIGALE to generate flux density priors in the Herschel SPIRE bands. These priors were then fed into the de-blending tool XID+ to extract flux densities from the SPIRE maps. In the final step, multi-wavelength data were combined with the extracted SPIRE flux densities to constrain SEDs and provide stellar mass (M) and SFRs. These M and SFRs were then used to populate the SFR-M plane over 0.2 ≤ z < 6.0.

Results: No significant evidence of a high-mass turn-over was found; the best fit is thus a simple two-parameter power law of the form log(SFR) = α[log(M) - 10.5] + β. The normalisation of the power law increases with redshift, rapidly at z ≲ 1.8, from 0.58 ± 0.09 at z ≈ 0.37 to 1.31 ± 0.08 at z ≈ 1.8. The slope is also found to increase with redshift, perhaps with an excess around 1.8 ≤ z < 2.9.

Conclusions: The increasing slope indicates that galaxies become more self-similar as redshift increases. This implies that the specific SFR of high-mass galaxies increases with redshift, from 0.2 to 6.0, becoming closer to that of low-mass galaxies. The excess in the slope at 1.8 ≤ z < 2.9, if present, coincides with the peak of the cosmic star formation history.

De-blending Deep Herschel Surveys: A Multi-wavelength Approach

W. J. Pearson et al., A&A, 603, 102 (2017)

Aims: Cosmological surveys in the far-infrared are known to suffer from confusion. The Bayesian de-blending tool, XID+, currently provides one of the best ways to de-confuse deep Herschel SPIRE images, using a flat flux density prior. This work is to demonstrate that existing multi-wavelength data sets can be exploited to improve XID+ by providing an informed prior, resulting in more accurate and precise extracted flux densities.

Methods: Photometric data for galaxies in the COSMOS field were used to constrain spectral energy distributions (SEDs) using the fitting tool CIGALE. These SEDs were used to create Gaussian prior estimates in the SPIRE bands for XID+. The multi-wavelength photometry and the extracted SPIRE flux densities were run through CIGALE again to allow us to compare the performance of the two priors. Inferred ALMA flux densities (FinferALMA), at 870 μm and 1250 μm, from the best fitting SEDs from the second CIGALE run were compared with measured ALMA flux densities (FmeasALMA) as an independent performance validation. Similar validations were conducted with the SED modelling and fitting tool MAGPHYS and modified black-body functions to test for model dependency.

Results: We demonstrate a clear improvement in agreement between the flux densities extracted with XID+ and existing data at other wavelengths when using the new informed Gaussian prior over the original uninformed prior. The residuals between (FmeasALMA) and (FinferALMA) were calculated. For the Gaussian priors these residuals, expressed as a multiple of the ALMA error (σ), have a smaller standard deviation, 7.95σ for the Gaussian prior compared to 12.21σ for the flat prior; reduced mean, 1.83σ compared to 3.44σ and have reduced skew to positive values, 7.97 compared to 11.50. These results were determined to not be significantly model dependent. This results in statistically more reliable SPIRE flux densities and hence statistically more reliable infrared luminosity estimates.