6.2.1 BaTMAn and the low signal-to noise IFS data
In Chapter4we present BATMAN (Bayesian Technique for Multi-image Analysis), a new binning tool designed to characterize and coherently tessellate simultaneously many layers
oping BATMANalgorithm arises from the need to carefully analyse the low signal-to-noise areas that appear in extended resolved observations of galaxies (e.g. outskirts of galaxies in the CALIFA sample presented in Chapter3).
This work comprises two separate parts, the mathematical formulation of the binning technique and its testing using synthetic and real data. BATMAN’s tessellation algorithm follows a different philosophy with respect to other existing binning tools, as it attempts to identify spatially-connected regions that are statistically consistent with carrying the same information (measurements and corresponding errors). BATMANis conceived to bin our data “only” if possible, with the ultimate goal of avoiding unnecessary loss of information. The posed test cases considered are specifically devised to test the performance of the seg- mentation tool and provide some guidance for its further use. This analysis allows us to conclude that:
• In all our test cases, the output tessellations successfully adapt to the spatial structures present in the input data for a wide variety of morphologies, regardless of the statis- tical properties of the noise. Nevertheless, the optimal segmentation does depend on the precise choice of the input data set. It is thus of paramount importance to investi- gate the information that should be considered relevant as a preliminary step of any scientific analysis.
• Our synthetic tests show that the mean values for the intensity within each region, estimated from the posterior probability distribution, provide a good representation of the true signal, whereas the formal errors, although indicative of the true uncer- tainties, may underestimate them by a factor of the order of two. The tests conducted with real astronomical data reveal that BATMANmay be most helpful in the low S/N
regime (e.g. reduction of the noise with respect to the original data is clearly visible in the galaxy outskirts).
• When BATMANis applied to the CALIFA datacubes prior to measuring colours and equivalent widths, the number of regions and the associated scatter are significantly reduced (specially in the outer parts). All the trends observed in the spaxel-by-spaxel analysis persist, confirming the robustness of the results and the successful perfor- mance of binning algorithm. In addition, it is now clearer that there may be different paths through the colour-equivalent width diagram and that many galaxies contain extended regions along both the “ageing” and “quenching” sequences.
To summarize, one of the main objectives of this work is to approach IFS binning in a new way, with the ultimate goal of preserving all the statistically-significant informa- tion contained in the original data. This philosophy represents a novel and much needed approach to the analysis of astronomical images, which we believe will be of crucial impor- tance in the advent of the vast amount and spatial resolution of IFS data to come.
6.2.2 Synthetic IFS observations
In Chapter5we present the “SELGIFS Data Challenge”, a project led by G. Guidi that pro- poses a pioneering approach to connect integral-field observations and state-of-the-art hy- drodynamical simulations. This project aims to set the basis for a coherent comparison between the two types of data and provide the scientific community with reliable synthetic IFS datacubes that allow testing analysis tools. The success of this work is of paramount importance. On the one hand, it will facilitate the use of simulations to interpret observa- tions and to study the effects of different physical processes that galaxies undergo on their
observable properties. On the other hand, a reliable comparison between the two datasets is crucial to test the different recipes implemented in the hydrodynamical codes (specially in the sub-resolution regime).
In this work we use three hydrodynamical simulations of galaxies re-simulated using the zoom-in technique on three Milky way-like halos selected from the Aquarius dark- matter only simulation. These simulated objects have been post-processed with the radia- tive transfer code SUNRISE in order to obtain the spectral energy distributions associated
to the stellar particles. Three different orientations are considered for every given object. This “virtual observations” attempt to mimic the properties of IFS observations from the CALIFA survey and account for stellar emission and absorption features, nebular emission, dust extinction, and line broadening due to kinematics.
We provide a final sample of 18 datacubes: 3 objects in 3 different orientations and for- matted in the two observational setups available in the CALIFA survey (V500 and V1200). To generate these datacubes we have considered the following observational properties, specific of the PMAS/PPak instrument (but the procedure is extensive to any given IFS survey):
• Physical size within the field-of-view. Objects are virtually “placed” at a certain redshift so that the characteristic PMAS/PPak FoV (∼ 7800× 7800) covers a region of approx- imately 2R50 for every simulated galaxy. The spectra generated with SUNRISE are
redshifted to match this value.
• Spatial and spectral resolution. The effects of the spatial and spectral point spread func- tions are included by convolving our datacubes first in the spatial dimensions with a 2D Gaussian kernel of 3” FWHM and later in the spectral direction with a 1D Gaus- sian with FWHM values δλ500 = 6.0Å and δλ1200 = 2.3Å for the V500 and V1200
setups, respectively.
• Detector noise. We finally include random Gaussian error in our data to account for the detector noise, using a simple model of the error variance based on the analysis a sample of 20 CALIFA galaxies (considering both setups).
A key aspect of this work is that we also generate and provide what we refer to as high-level product datacubes, i.e. 2-dimensional maps of some galactic properties computed directly from the simulations and/or measured directly from noiseless versions of the syn- thetic datacubes. These product datacubes provide observers with a “solution” to test the accuracy of their analysis pipelines and open the way for a meaningful comparison with the theoretical results provided by numerical simulations. The advent of new IFS data (MUSE, WEAVE, MANGa, SAMI, etc.) and large hydrodynamical simulations (EAGLE) makes the present time ideal to work on this synergy. We believe this type of detailed comparison is necessary, and we hope that the robustness and versatility of the methodology proposed in this work to generate mock IFS observations facilitates collaboration at the always exciting interface between theory and observation.