PPV maps details

Equations for the position to velocity (PPV) cubes were computed for a 3-D cube of density with its center (point P) at a given distance (d) from Sun (S). Here, by data convention, Y axis is along the line of site (SP).

For any pixel in the cube (point Q), the line of site SQ would then subtend an angle wrt the center (SP). Let Q' be the projection of Q on X-Y plane, therefore, SQ' has projections of x & y along the two axes.

We can then relate R0 (= CS = distance of Sun from Galaxy's center), R ( = distance CQ'), distance d (SP), and distance d' (SQ') through other quantities and angles (such as longitude= angle CSP).

The projection of relative velocity between S & Q' (due to galactic rotation) is added to the projections of the pixel velocities (vxx, vyy and vzz). Doing this for each pixel creates the cube "v_los". We sort the pixel values falling in different velocity bins, and make velocity maps of width 1 km/s.

Simulations: PPV maps ready

1. Testing with 10x10x20 cubes
2. PPV maps seem to be all right.
3. Will now test on the desktop with full limits put in.
   

MHD Simulations: PPV maps

1. Read density, vxx, vyy,vzz cubes
2. Compute pixel (radial) velocities due galactic rotation
3. Add components of vxx,vyy,vzz from individual pixel values.
   
4. ERROR in writing the files in PPV files

flucatuation analysis: easyGUI

1. The program menu now has a comprehensive logical structure. There will be text files holding menu data.
2. Program reads menu (text) files and records pulsar parameters as read from the data file. These can be later used for various analyses.
   
3. The main menu leading to average profile in a sub-menu "fold menu". There wiill be plot menu on all such sub-menus.
4. I can now display pulse sequence and zoom in on the chosen sequence area.

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fluctuation analysis: EasyGUI

EasyGUI is god-sent

1. I can display various options in a menu window and ask the user to click and choose.
2. I can choose the data file and read it.
   
3. I can plot the average profile

All this in 3 days work. Python is getting better every day.

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fluctuation spectral analysis

1. We can now read PPR data from Gauribidanur and UTR-2, YEY!!!
2. The problems in LRFLUC are ignored for the moment.
3. We will now consider to write a suitable GUI. The only candidate (simplest to work with, and most basic to be found on all Python installations) is 'easyGUI'

easygui.sourceforge.net
you try it too.


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fluctuation spectral analysis

1. We read Arecibo data
2. We obtain a 2-D zoomed single pulse data as an image (intensity on 3rd axis)
3. We take 2-D FFT
4. We fold the FFT to obtain an equivalent of LRFLUC, and it does not work properly.

fluctuation analysis

1. Average profile zoom works:

we use Matplotlib window (ginput) to read click location.
two clicks are used to mark pulse window.

fluctuation spectrum analysis

I am writing Python code to analyse single-pulse data from radio pulsars. The idea is to make polar maps from fluctuation analysis.

1. I can read data from Arecibo
2. display average profile, and
3. plot single-pulse sequences from the file.
   

Oven Controlled Crystal Oscillator MCOCXOW

I looked for crystal controlled COs. Here is one data sheet from Golledge. Excellent stability, we do not know the price. It is their featured product, from price and availability point of view.

AIPS : initial calib idea

Initial Calibration steps in AIPS

1. INDXR
   
2. First clip source for arbitrarily high points (100 KJy), due to correlator errors. (CLIPM)


3. SETJY to set fluxes of prim calib sources in SU table
   
4. CALIB on prim calib to find antenna solutions, SN tab 1
   
5. CALIB on second calib : SN tab 2
   
6. GETJY to calculate second calib fluxes to second calib (using SN and SU tables)
   
7. CLCAL apply second calib source calibration to target sources: CL tab 2
   

Now, one is free to excise interference. once one has cleaned all the data, return to step 4 above to redo the calibration process (after deleting all SN and CL tables generated above).

fruitful day!

things done:

1. AIPS processing tutorial by Chiranjeevi, it has given a new perspective about GMRT interference removal and calibration.


2. ms for SAX 1808 paper is ready for desh's view.



3. there has been tons of discussion about radio telescope.
   
   
   • the 2-bit samples from 4 elements could combined in one byte per sample rate.
   
   
   • Cross-correlations of each two-element pairs (total 6 pairs, called 'baselines') can be done for N delays. Resultant array of N correlations can be passed over to FFT, resulting in amplitudes and phases for N/2 spectral channels. (This job can be simplified by using tabulated results for all 8-byte combinations).
   
   
   • The value N above is decided by delta-u and delta-v that we can have, using 1/imsize for our map (possibly 1/60 deg).
   
   
   • We need to keep computing such cross-correlations over a large time, integrating amplitude and phases over a large time (about 8 seconds or so).
   
   
   • These integrated amp and phases are the output (dynamic spectrum) of an effective software correlator.
   
   
   
   
   

Human Tracking on Campus (update)

Students returned here again. This time they had prepared a lot more for display. They have now decided, as I suggested, to reduce the size of the gadget that everyone would carry with them.

As per the original design, the signal generator gadget sends digital codes as an identification for an individual sender. The transmission is at a given higher frequency, using FM. This would mean that all receiving stations (which are used in triangulation) operate at one frequency, and a person's id is the digital signal sent at that frequency.

Now, we will use individual frequency transmission as an id. we may have to do further tricks, since this might mean very narrow bands and FM using highly accurate filters, etc. one could explore if we could do a crude digital signaling. One could just change the ON/OFF frequency of individual receivers, providing another way of identification...

This circuitry could work close to 65 MHz, providing most of the amplifiers and filters that we need for our radio telescope ;-)

Making A Human Tracker

Students are eager to build a human tracker system in the campus. They want each person to carry a transmitter wherever s/he goes. Multiple towers will receive their signals and convey this reception to the central computer. The computer will time the arrivals with GPS unit, and locate the emitter by simple triangulation. The computer can track the location on a map for an easy display.

Students wanted to know if this was feasible. They had ideas of using high-freq dishes, radio-id tags, etc. However, I suggested them to build a system at low frequencies, which will be less prone to blockage. This is of concern, since the system will otherwise fail if the person reaches in a classroom.

We are not sure about how much of signal is needed to make it detectable at the receiving stations, but we are initially going to play with a system working over less than 300 mtrs, using simple yaggi antennas.

Making an Amateur Radio Telescope

Radio Interferrometer

Today I detailed the entire telescope project with Anita. The standard components will be:

1. Two antennas, separated by about 100 meters. To begin with, of course, we will start with one antenna. Signal frequency of 40/60 MHz +- 5 MHz
   
2. Pre-amplifier will be required in at least one case, to boost the signal by 20 dB and carry it over 100 meters. Signal freq 40/60 MHz +- 5 MHz.
   
3. RF to IF conversion followed by an appropriate filter: 0-2 MHz band chosen.
4. IF amplification, possibly two amplifiers back to back for 40 dB or so gain: signal freq. 0-2 MHz.
5. Phase shifter and adder (with 90 degrees phase difference), followed by a detector. The output is a amplitude time series at the rate of 1/16 second.

This kind of project requires a team of students, possibly 8 students working on different aspects simultaneously. Complex job, but it will be fun if we invest their time in it...