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  • tnithyanandan 7:08 pm on March 21, 2014 Permalink | Reply
    Tags: , Cosmology, , , low frequency, , power spectra, , , , reionization   

    Joining ASU and a peek into my research 

    My name is Nithyanandan Thyagarajan. I joined the LoCo (Low frequency Cosmology) lab group at ASU SESE headed by Prof. Judd Bowman, in September 2013 as a postdoctoral research scholar. I did my bachelor’s in Electrical Engineering from IIT Madras, India. For my PhD thesis at Columbia University, I worked on identifying and characterizing variable and transient radio objects by conducting one of the biggest searches of its kind in the radio sky. I then moved to Raman Research Institute in Bangalore, India as a postdoc and worked on statistical characterization of foreground contamination in the power spectrum of redshifted 21 cm line emission of neutral hydrogen during the epoch of reionization (EoR). During this period I got associated with the Murchison Widefield Array (MWA) project.

    The LoCo group has members involved in a variety of interesting projects. Besides having a strong presence in the MWA project, the members are also involved in other EoR experiments using the Experiment to Detect the Global EoR Step (EDGES), Precision Array for Probing the Epoch of Reionization (PAPER), Dark Ages Radio Explorer (DARE), Long Wavelength Array (LWA) and other theoretical and modeling projects. I am excited to be a part of this diverse group which provides enormous opportunities to learn science through the many perspectives from these different experiments.

    Currently, I am focusing on setting up simulations to predict the response of the MWA telescopes to all-sky radio emission. My aim is to isolate and characterize the signatures of different spatial structures of foreground objects such as the Milky Way, and other extragalactic objects besides the instrument’s own systematic effects on the observed power spectrum that contains information about the spatial distribution of redshifted 21 cm line emission from neutral hydrogen from the EoR. An understanding of the radio foreground objects and that of the telescope is extremely significant because the expected signatures from the neutral hydrogen emission during the EoR are extremely faint compared to the contamination from radio foregrounds and instrumental artifacts. Detecting EoR signal may be impossible without a precise removal of such contamination and artifacts.

    Here’s an approximate simulation of the radio foreground and instrumental signatures we expect to see in the power spectrum when the entire hemisphere of the sky is observed by the MWA telescope. The simulations are found to match well with results from analysis of data from the MWA telescopes.

    Predicted spatial power spectra of a an all-sky model as seen by MWA telescopes.

    Predicted spatial power spectra of an all-sky radio model of foreground objects as seen by MWA telescopes. The all-sky radio emission model is shown in the central panel. The peripheral panels show the power spectra recorded by different antenna pairs (x-axis) grouped by orientation of the lines joining them (EW at bottom right, NE at top right, NS at top center, and NW at top left). The x-axes in all the peripheral panels represent the different antenna pairs which sample the transverse spatial information from emission from the plane of the sky while the y-axes sample spatial structures into the plane of the sky. Since the sky model contains heterogeneous spatial structures, these different antenna pairs record different spatial information. The wedge/fork shaped feature prominent in the top center panel and the bright horizontal feature in all the peripheral panels arise out of the emission from our galaxy and other extragalactic radio emission (all the bright features enclosed by the forked black lines). The periodically repeated horizontal structures are caused by the frequency characteristics of the MWA telescopes.

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  • Boom 4:43 pm on February 22, 2013 Permalink | Reply
    Tags: , , reionization   

    Swiss Cheese, Statistics and the Early Universe 

    How could a fermented milk product riddled with holes relate to the cold space filled with hydrogen gas and stars, and to a branch of  mathematics that no one understands? The answer depends on how you look at the Universe. Regular readers may know that our colleagues in the Low-frequency Cosmology (LoCo) group here at ASU are building instruments to observe 21 cm spectrum of hydrogen from the early Universe. In a non-scientific description, we are trying to look at “rainbows” emitted by hydrogen gas using radio telescopes. The “rainbows” from different periods of time in the Universe also happen to fall into different frequencies of radio signal. Observing them at various radio frequencies will let us construct a cube showing the distribution of hydrogen in the early universe as a function of time. Now, emission from stars and galaxies breaks up hydrogen atoms surrounding them into nuclei and electrons, creating “bubbles” in which hydrogen gas is ionized, and there will be no 21 cm spectrum from within the “bubbles.” As a result you will see holes in the cube, like a block of Swiss cheese! I should also point out that the size of these “bubbles” can tell you what the stars that produce them look like!

    Unfortunately, our current generation of instruments is not good enough to construct a clean data cube that will let us directly look at the “bubbles” and measure them, and we will have to learn from statistics. Think about it this way: You count all the holes with a particular size or volume in your block of Swiss cheese. Then you chop up the cheese into pieces to “contaminate” them (be careful not to cut through the holes too much), then mix in small pieces of another type of cheese with tiny holes, like Tilsit, and randomly put all the pieces back into a block. If you then count the holes and measure their sizes again, the number should be relatively the same. (Remember that holes in Swiss cheese are big!)  This analogy does not exactly describe what  we will be seeing in our data, but it roughly explains what I meant by statistics. The bottom line is that you can still learn something about the Universe from bad data by using statistics.

    Figuring our what type of statistics to use and the best way to use them on the 21 cm data will be my Ph.D. thesis.  Please cheer and support me!

    Piyanat Kittiwisit, or Boom (as he likes to be called), is a graduate student in the Low-frequency Cosmology group in the School of Earth and Space Exploration at ASU. 

     
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