Hugh GarsdenFrom 2015 I work at the Harvard-Smithsonian Center for Astrophysics on the LEDA project. I work on aspects of the software pipeline for the LEDA telescope, including the correlator, and real time calibrating/imaging software, all of which use GPGPUs. I work on visualization software that is used to display, in a meaningful fashion, the vast amount of data that is collected.
From 2012-2014 I was a postdoc at CEA, south of Paris, in the CosmoStat Laboratory. I was employed by the Université-Paris-Diderot.I implemented compressed sensing for radio astronomy imaging in the LOFAR Radio Telescope. I also worked on LOFAR source finders and the LOFAR transients pipeline.
Compressed sensing is a new theory that allows reconstruction of images when they have been undersampled. I have implemented this in the LOFAR Radio Telescope imaging pipeline (software). I have run tests on simulated and real data to determine the correctness of the implementation and evaluate how it performs. A paper is in press summarizing the entire work and will be a reference paper for compressed sensing in radio imaging.
I am a member of the LOFAR Slow Transients Software Team and the LOFAR Source Finder Working Group. Finding transients involves searching radio images for astronomical sources and comparing them against known sources. This has to be done in an automated way using software, due to the huge number of images generated. I worked mainly on source finding software and testing. A paper is in preparation on the implementation, performance, and accuracy, of the PySE sourcefinder.
PhDI developed a parallelized, gravitational microlensing software simulator for huge microlensing simulations. I used this to conduct research into quasar microlensing.
Prior EmploymentThis is my first postdoc, at CEA. Prior to that I worked in industry as a software engineer and at universities in research groups in physics, computing, speech synthesis, and biomedicine.
PostdocThe following were all on the compressed sensing implementation for LOFAR, with increasing detail and results as the implementation and testing progressed. I've included one representative set of slides.
This is a talk I gave on my work on source finders.
Garsden, H.; Carbone, D.; Swinbank, J.; van der Horst, A., 2014, Astronomy and Computing (in prep.). PySE: Software for Extracting Sources from Radio Telescope Images
Garsden, H.; Girard, J.; Starck, J-L.; Corbel, S.; Tasse, C.; Woiselle, A.; McKean, J. et al., 2014, Astronomy and Astrophysics (in press). LOFAR Sparse Image Reconstruction
Garsden, H.; Starck, J-L.; Corbel, S et al., 2013, Proceedings of SPIE Optics+Photonics Conference, Compressed sensing imaging reconstruction for the LOFAR Radio Telescope
Garsden, H.; Bate, N. F.; Lewis, G. F., 2012, MNRAS. Probing planetary mass dark matter in galaxies: gravitational nanolensing of multiply imaged quasars
Garsden, H.; Bate, N. F.; Lewis, G. F., 2012, MNRAS. Gravitational microlensing of a reverberating quasar broad-line region - I. Method and qualitative results
Kedziora, D. J.; Garsden, H.; Lewis, G. F., 2011, MNRAS. Gravitational microlensing as a probe of the electron-scattering region in Q2237+0305
Garsden, H.; Lewis, G. F.; Harvey-Smith, L., 2011, MNRAS. The water maser in MG 0414+0534: the influence of gravitational microlensing
Bate, N. F.; Fluke, C. J.; Barsdell, B. R.; Garsden, H.; Lewis, G. F., 2010, MNRAS. Computational advances in gravitational microlensing: A comparison of CPU, GPU, and parallel, large data
Garsden, H.; Lewis, G. F., 2010, NewA. Gravitational microlensing: A parallel, large-data implementation
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