A Search for Infrared Dark Clouds at 70 µm A thesis submitted to The University of Manchester for the degree of Master of Science By Research in the Faculty of Science and Engineering 2016 Hazel Blake School of Physics and Astronomy Contents List of Figures 3 Abstract 8 Declaration 9 Copyright Statement 10 Acknowledgements 11 1 Introduction 12 1.1 Star Formation . 13 1.2 Low Mass Stars . 14 1.3 High Mass Stars . 16 1.3.1 Formation Models . 17 1.4 This Study . 20 2 Infrared Dark Clouds 22 2.1 Evolution . 23 2.2 Star Formation in Infrared Dark Clouds . 24 3 Previous Work 28 3.1 MSX Dark Clouds . 28 3.2 Spitzer GLIMPSE Dark Clouds . 30 1 CONTENTS 2 3.2.1 Follow Up Study . 33 3.3 Column Densities and Dust Temperature Maps of IRDCs . 33 3.4 Herschel Counterparts of the Spitzer Dark Cloud Catalogue . 35 4 A Search for IRDCs at 70 µm 38 4.1 Method . 38 4.2 Results . 46 5 Discussion 56 5.1 Further Work . 58 6 Conclusions 61 Bibliography 62 Word Count = 11,777 List of Figures 1.1 A brief overview of star formation. Gas and dust are influenced by a nearby event, sending shock waves through the clouds. This causes small pockets of dense gas and dust to form, eventually collapsing in on itself, forming a star. (http://science.howstuffworks.com/how- are-stars-formed.htm) . 15 1.2 A diagram of the four main stages of star formation as outlined by Shu et al. (1987). (a) Molecular clouds form cores. (b) In the centre of a core, a protostar will form with a circumstellar disk. (c) Bipolar flows are created by stellar winds along the rotational axis. (d) A star is formed with a circumstellar disk. 19 2.1 Three random clouds from a catalogue by Peretto and Fuller (2009), with images from GLIMPSE Spitzer 8 µm. These indicate how varied IRDC shapes and sizes can be. 22 2.2 Cloud G0.253+0.016, located within 100 pc of the Galactic centre. This cloud has a high average density, and therefore should be form- ing numerous stars. As of yet, there are no visible stars seen within the structure. The Submillimetre Array (SMA) reveals a few star- forming cores, suggesting it might be a young cloud. The Combined Array for Research in Millimetre-wave Astronomy (CARMA) shows the cloud is full of silicon monoxide (SiO), suggesting the cloud is a collision between two clouds and being compressed (Kauffmann et al., 2013). 25 3 LIST OF FIGURES 4 3.1 A schematic view of a typical IRDC flux density profile. Ifore has been set to a specific value in this figure, but in reality, Ifore can be anywhere between Izl and Imin.IMIR is the observed mid-infrared radiation field. (Peretto and Fuller, 2009) . 31 3.2 Substructures of the three IRDCs shown in figure 2 as 8 µm opacity maps. Contours range from 0.4 to 0.8 in steps of 0.2 for the first and last image, whilst the contours for the middle figure are from 0.4 to 1.9 in steps of 0.3. Peretto and Fuller (2009) . 32 3.3 An example of a temperature map. The contours show the H2 col- umn densities. As can be seen, the temperature minima are asso- ciated with the column density peaks, but not one-to-one. (Peretto et al., 2010) . 34 4.1 The original HIGAL image at 70 µm . Within this image are stars, gas, dust and IRDCs. To detect the IRDCs, the background and stars need to be removed from the image. The z-axis represents tem- perature, where 0 defines the coolest objects, and 21000 represents the warmest objects. 39 4.2 The stars are removed from the original HIGAL image, comparing the original image with image after the stars are removed. After calculating the peak values in the HIGAL image, these are removed, leaving the background image. SOme of the background emission is left behind, but will be smoothed with a large median filter to remove the small scale structures, leaving a large scale background image from which to detect the clouds. The z-axis represents temperature, where 0 defines the coolest objects, and 21000 represents the warmest objects. 40 LIST OF FIGURES 5 4.3 After the stars have been removed, the image is smoothed with a large median filter to create an average background from which to extract the clouds. The z-axis represents temperature, where 0 de- fines the coolest objects, and 21000 represents the warmest objects. 42 4.4 The optical depth image which then has the detection process applied to it. This is the background after the stars have been removed and a large median filter applied.The z-axis represents optical depth . 43 4.5 A compilation of the sources found using DAOFIND. Each segment is each detected source above the threshold. Some sources may be over- lapping but represented as a single source.The z-axis represents an arbitrary counting system that numbers each source with a chrono- logical order. 44 4.6 Overlaying the peak longitude and latitude of the 8 µm clouds (cyan circles) on top of the 70 µm image gives a quick visual comparison between the two. At quick glance, many of the structures seen in 8 µm are not necessarily seen at 70 µm. However, there is some correlation between the two when viewed by eye. Many clusters of peaks in 8 µm are around the same area as clusters of 70 µm clouds. 45 4.7 A comparison of the HIGAL image with column densities and dust temperatures as described by Peretto et al. (2016). Comparing these images to the segmentation image can confirm if the sources detected correspond to true peaks in column density, and so are 'true' clouds. 46 4.8 An example of sources from the segmentation process as compared to the other images.The first image shows a structure seen by the detec- tion process, compared with the original image (top right), the dust temperature (bottom left) and the column density (bottom right). The structure is barely visible in the HIGAL image. The image is not traced in the bottom images, although there is a different structure seen. 47 LIST OF FIGURES 6 4.9 In this image, some small points are seen by the detection process, but not necessarily seen in the other maps. Structures can be seen in the column density and temperature maps, but not in the original image. Some points from the segmentation image may correlate to the structures, but it is difficult to confirm outright. 48 4.10 The structure described by the detection process can clearly be seen in all three of the other images. This is more than likely a real cloud. 49 4.11 The detection process found a lot of points above the threshold, classing them as clouds. These points are not seen in the original HIGAL image, with limited points seen in the column density map or the dust temperature map. This suggests these points are artefacts of the manipulation process. 50 4.12 As can be seen in the original HIGAL image, this area has a large amount of noise in the region. This will have skewed the manipu- lation process, as not all the noise will have been removed prior to the median filter. This may be the reason for many points being de- tected. There is some structure here, as seen in the dust temperature and column density maps, but nothing has been identified clearly by the detection process. 51 4.13 This ring that has been detected by the segmentation process is clearly identifiable in all three other images. This is therefore a real cloud. Most of the cloud has been detected by the segmentation process, meaning a large proportion of this cloud is visible in 70 µm. 52 4.14 An example of structures seen in most of the images. There are some filamentary structures seen in the column density and dust temperature maps, but hidden by clouds and noise in the HIGAL image. Some of these structures are seen by the detection process. 53 4.15 A very obvious square structure seen by HIGAL and seen in the column density and dust temperature maps, but not picked up in in the segmentation process. 54 List of Abbreviations IRDCs - Infrared Dark Clouds IMF - Initial Mass Function SPH - Smoother Particle Hydrodynamics IR - Infrared EGO - Extended Green Object MSX - Midcourse Space Experiment PAHs - Polyaromatic Hydrocarbons PBCD - Post-basic Callibrated Data FWHM - Full Width at Half Maximum SDCs - Spitzer Dark Clouds 7 Abstract Abstract of Dissertation submitted by Hazel Blake for the degree of Masters of Science by Research to The University of Manchester, September 2016 A Search for Infrared Dark Clouds at 70 µm Peretto and Fuller (2009) produced a catalogue of infrared dark clouds at 8 µm seen in the Galactic longitude and latitude 10◦ < jlj < 65◦ and jbj < 1◦ By constructing a catalogue of infrared dark clouds at 70 µm, this study detected over 1,000 individual points. Visual inspection of these points, compared with the temperature map and column density map described in Peretto et al. (2016), produced at least 10 areas with confirmed cloud candidates, and at least three regions of definitive overlap between the two studies. This study discusses the methods used to detect clouds at 70 µm using HIGAL data, and a comparison between the two catalogues. 8 Declaration No portion of the work referred to in the thesis has been submitted in support of an application for another degree or qualification of this or any other university or other institute of learning.