# LunarSynchrotronArray This is the README for the LunarSynchrotronArray package, maintained by Dr. Alex Hegedus alexhege@umich.edu I am currently a post-doctoral research fellow at University of Michigan looking to branch out and make connections with people interested in designing distributed sensor arrays. This code repository corresponds to the Hegedus et al. 2019 (in review) Radio Science paper, "Measuring the Earth's Synchrotron Emission from Radiation Belts with a Lunar Near Side Radio Array". The arxiv link for the paper is https://arxiv.org/abs/1912.04482 The DOI link is https://doi.org/10.1029/2019RS006891 This set of codes should guide you through making the figures in the paper, as well as hopefully being accessible enough for changing the code for your own array. I would encourage you to please reach out to collaborate if that is the case! Requirements: CASA 4.7.1 (or greater?) built on python 2.7 Example link for Red Hat 7 https://casa.nrao.edu/download/distro/casa/release/el7/casa-release-4.7.1-el7.tar.gz Users may follow this guide to download and install the correct version of CASA for their system https://casa.nrao.edu/casadocs/casa-5.5.0/introduction/obtaining-and-installing CASA executables should be fairly straightforward to extract from the untarred files. gcc 4.8.5 or above (or below?) GCC installation instructions can be found here https://gcc.gnu.org/install/ SPICE (I use cspice here) https://naif.jpl.nasa.gov/naif/toolkit_C.html As seen in lunar_furnsh.txt which loads the SPICE kernels, you also must download KERNELS_TO_LOAD = ( '/home/alexhege/SPICE/LunarEph/moon_pa_de421_1900-2050.bpc' '/home/alexhege/SPICE/LunarEph/moon_080317.tf' '/home/alexhege/SPICE/LunarEph/moon_assoc_me.tf' '/home/alexhege/SPICE/LunarEph/pck00010.tpc' '/home/alexhege/SPICE/LunarEph/naif0008.tls' '/home/alexhege/SPICE/LunarEph/de430.bsp' ) All of which can be found at https://naif.jpl.nasa.gov/pub/naif/generic_kernels/ SLDEM2015_128_60S_60N_000_360_FLOAT.IMG for the lunar surface data by LRO LOLA Found at http://imbrium.mit.edu/DATA/SLDEM2015/GLOBAL/FLOAT_IMG/ Codes within this package in order of use in pipeline: 0. snrCalc.py This regular python script creates the noise budget plots with frequency, not necessary for pipeline. Information about the frequency dependence of the November 1st 2016 stormy synchrotron brightness as a function of frequency is also contained here. 1. createArrayConfig.py This regular python script sets your array configurations (currently log spaced circular for 1024 elements). Reads the SLDEM data and saves the longitude, latitude, and altitude of each antenna. Also you must update the variable lunarPath to the current location of the SLDEM file 2. eqArrOverTimeEarth.c This is runs the SPICE kernel, taking in the Long Lat and Alt data from the first script, as well as the period of time you want to observe. This will align the frame of the antenna on the Lunar Surface to the area of the sky containing the targeted Earth overhead. This saves a number of variables as output files, most important being the XYZ position of each antenna in J2000 coordinates, and the J2000 coordinates of the Earth from the Moon’s perspective. You also must update lunar_furnsh.txt with the new path names for the required frame and ephemeris files. Update below in lunar_furnsh.txt with the directory you installed the files to. KERNELS_TO_LOAD = ( '/home/alexhege/SPICE/LunarEph/moon_pa_de421_1900-2050.bpc' '/home/alexhege/SPICE/LunarEph/moon_080317.tf' '/home/alexhege/SPICE/LunarEph/moon_assoc_me.tf' '/home/alexhege/SPICE/LunarEph/pck00010.tpc' '/home/alexhege/SPICE/LunarEph/naif0008.tls' '/home/alexhege/SPICE/LunarEph/de430.bsp' ) Currently, you also must copy paste any new Long Lat Alt data into the C script manually, as I have not implemented a dynamic routine for C that can read in variable length arrays from a file. Currently has 10 km logarithmic circular array loaded in. Then compile the script with gcc eqArrOverTimeEarth.c -o eqArrOverTimeEarth -I/home/alexhege/SPICE/cspice/include /home/alexhege/SPICE/cspice/lib/cspice.a -lm -std=c99 update the included directories to wherever you have installed the SPICE libraries This will create the executable file eqArrOverTimeEarth Then run with ./eqArrOverTimeEarth which will create the output files: RAs.txt - List of Right Ascension coordinates of the Earth's position in the sky as seen form the Lunar Surface. Currently at a nearly weekly cadence with 48 points over a year. Decs.txt - List of Declination coordinates of the Earth's position in the sky as seen form the Lunar Surface. Currently at a nearly weekly cadence with 48 points over a year. eqEarthAngs.txt - Angle between the surface normal vector (zenith) and vector to the Earth. Currently at a nearly weekly cadence with 48 points over a year. eqSolAngs.txt - Angle between the surface normal vector (zenith) and vector to the Sun. Currently at a nearly weekly cadence with 48 points over a year. eqXYZ_EarthCentered.txt - (x,y,z) meters in earth centered j2000 frame for each receiver for each time. Currently 1024x48x3 values. Later reshaped into an np array with dimensions (1024, 48, 3) The files in the repository currently are the output for the 1024 element array with a 10 km diameter, centered at its corresponding lowest variance altitude location near the sub-Earth point, (Long, Lat) = (-1.04, -0.43). 3. Run LunarEarthPicFreqIntegration.py This is the CASA script that does the work of simulating the radio array now that everything is defined. It reads in the array position data and the position of the target in the sky. To run within casa run this command: %run LunarEarthPicFreqIntegration.py -outDir . -correlate True -numSC 1024 or in terminal casa --nologger --nologfile --nogui --agg -c LunarEarthPicFreqIntegration.py -outDir . -correlate True -numSC 1024| tee out.out nohup casa --nologger --nologfile --nogui --agg -c LunarEarthPicFreqIntegration.py -outDir . -correlate True -numSC 1024 | tee earth.out & It reads in the .dat files of the synchrotron emission maps in the EarthSynchrotronMapVsFrequency subfolder and converts them into a CASA ground truth file that is given to the virtual array. Currently, only the ~0.75 MHz image is used as an average for the 0.5 – 1.0 MHz range. It uses CASA routines to create a synthetic array using the J2000 data calculated from the SPICE kernel in the previous script. It then feeds the truth image into the simulated array to create the visibility data and puts it into a Measurement Set (MS) file. This MS file is the main output of this script. 4. Run noiseCopies.py This file takes the newly created MS file and creates a noiseless image of the recovered emission. It then makes copies of the MS file and adds noise according to the set integration time and SEFD noise level. Currently makes images for a range of integration times up to 24 hours and over several robust weighting scheme values.