{ "cells": [ { "cell_type": "markdown", "id": "4e111ad9-5599-451c-83a5-f89a79b0dd42", "metadata": {}, "source": [ "# Polarization example (GRB) - Stokes parameters method" ] }, { "cell_type": "markdown", "id": "f9b8addd-aaa4-488c-8041-385881689986", "metadata": {}, "source": [ "This notebook fits the polarization fraction and angle of a Data Challenge 3 GRB (GRB 080802386) simulated using MEGAlib and combined with albedo photon background. It's assumed that the start time, duration, localization, and spectrum of the GRB are already known. The GRB was simulated with 80% polarization at an angle of 90 degrees in the IAU convention, and was 20 degrees off-axis. A detailed description of the Stokes method, which is the approach used here to infer the polarization, is available on the [Data Challenge repository](https://github.com/cositools/cosi-data-challenges/tree/main/polarization). " ] }, { "cell_type": "code", "execution_count": 1, "id": "26c12d83-7afc-4000-8b8f-d353e0b08d12", "metadata": {}, "outputs": [], "source": [ "%%capture\n", "from cosipy import UnBinnedData\n", "from cosipy.spacecraftfile import SpacecraftHistory\n", "from cosipy.polarization_fitting.polarization_stokes import (PolarizationStokes)\n", "from cosipy.threeml.custom_functions import Band_Eflux\n", "from cosipy.util import fetch_wasabi_file\n", "from astropy.time import Time\n", "import numpy as np\n", "from astropy.coordinates import Angle, SkyCoord\n", "from astropy import units as u\n", "from scoords import SpacecraftFrame\n", "from pathlib import Path\n", "\n", "%matplotlib inline" ] }, { "cell_type": "markdown", "id": "4b292969", "metadata": {}, "source": [ "### Download and read in data" ] }, { "cell_type": "markdown", "id": "3ed39150", "metadata": {}, "source": [ "This will download the files needed to run this notebook. If you have already downloaded these files, you can skip this." ] }, { "cell_type": "markdown", "id": "20c63edc", "metadata": {}, "source": [ "Download the unbinned data (660.58 KB), polarization response (1.35 GB), and orientation file (1.10 GB)" ] }, { "cell_type": "code", "execution_count": 2, "id": "b4769d25", "metadata": {}, "outputs": [], "source": [ "fetch_wasabi_file('COSI-SMEX/cosipy_tutorials/polarization_fit/grb_background.fits.gz', checksum = '21b1d75891edc6aaf1ff3fe46e91cb49')\n", "fetch_wasabi_file('COSI-SMEX/develop/Data/Responses/ResponseContinuum.o3.pol.e200_10000.b4.p12.relx.s10396905069491.m420.filtered.binnedpolarization.11D.h5', checksum = '46b006a6b397fd777dc561d3b028357f')\n", "fetch_wasabi_file('COSI-SMEX/develop/Data/Orientation/DC3_final_530km_3_month_with_slew_1sbins_GalacticEarth_SAA.fits', checksum = '1b851c042acf4c909798e2401e9d2e38')" ] }, { "cell_type": "markdown", "id": "ce33b697", "metadata": {}, "source": [ "Read in the data (GRB+background) and get the background by reading the files containting background before and after the GRB" ] }, { "cell_type": "code", "execution_count": 3, "id": "ac0ad83d", "metadata": {}, "outputs": [], "source": [ "data_path = Path(\"\") # Update to your path\n", "\n", "grb_plus_background = UnBinnedData(data_path/'grb.yaml')\n", "grb_plus_background.select_data_time(unbinned_data=data_path/'grb_background.fits.gz', output_name=data_path/'grb_background_source_interval') \n", "grb_plus_background.select_data_energy(200., 10000., output_name=data_path/'grb_background_source_interval_energy_cut', unbinned_data=data_path/'grb_background_source_interval.fits.gz')\n", "data = grb_plus_background.get_dict_from_fits(data_path/'grb_background_source_interval_energy_cut.fits.gz')\n", "\n", "background_before = UnBinnedData(data_path/'background_before.yaml')\n", "background_before.select_data_time(unbinned_data=data_path/'grb_background.fits.gz', output_name=data_path/'background_before')\n", "background_before.select_data_energy(200., 10000., output_name=data_path/'background_before_energy_cut', unbinned_data=data_path/'background_before.fits.gz')\n", "background_1 = background_before.get_dict_from_fits(data_path/'background_before_energy_cut.fits.gz')\n", "\n", "background_after = UnBinnedData(data_path/'background_after.yaml') # e.g. background_after.yaml\n", "background_after.select_data_time(unbinned_data=data_path/'grb_background.fits.gz', output_name=data_path/'background_after')\n", "background_after.select_data_energy(200., 10000., output_name=data_path/'background_after_energy_cut', unbinned_data=data_path/'background_after.fits.gz')\n", "background_2 = background_after.get_dict_from_fits(data_path/'background_after_energy_cut.fits.gz')\n", "\n", "background = [background_1, background_2]\n", "# Save background_1 dictionary to a file npz\n", "np.savez(data_path/'background_1.npz', **background_1)" ] }, { "cell_type": "markdown", "id": "2cc0300a", "metadata": {}, "source": [ "Read in the response files and the orientation file. Here, the spacecraft is stationary, so we are only using the first attitude bin ( The orientation is cut down to the time interval of the source.)" ] }, { "cell_type": "code", "execution_count": 4, "id": "ecb484f2", "metadata": {}, "outputs": [], "source": [ "response_file = data_path/'ResponseContinuum.o3.pol.e200_10000.b4.p12.relx.s10396905069491.m420.filtered.binnedpolarization.11D.h5'\n", "\n", "sc_orientation = SpacecraftHistory.open(data_path/'DC3_final_530km_3_month_with_slew_1sbins_GalacticEarth_SAA.fits',\n", " tstart = Time(1835493492.2, format = 'unix'), tstop = Time(1835493492.8, format = 'unix')) # e.g. DC3_final_530km_3_month_with_slew_1sbins_GalacticEarth_SAA.fits" ] }, { "cell_type": "markdown", "id": "c6951d6c", "metadata": {}, "source": [ "Define the GRB spectrum. This is convolved with the response to calculate the ASADs of an unpolarized and 100% polarized source" ] }, { "cell_type": "code", "execution_count": 5, "id": "26cec39d", "metadata": {}, "outputs": [], "source": [ "source_direction = SkyCoord(l=23.53, b=-53.44, frame='galactic', unit=u.deg)\n", "\n", "a = 100. * u.keV\n", "b = 10000. * u.keV\n", "alpha = -0.7368949\n", "beta = -2.095031\n", "ebreak = 622.389 * u.keV\n", "K = 300. / u.cm / u.cm / u.s\n", "\n", "spectrum = Band_Eflux(a = a.value,\n", " b = b.value,\n", " alpha = alpha,\n", " beta = beta,\n", " E0 = ebreak.value,\n", " K = K.value)\n", "\n", "spectrum.a.unit = a.unit\n", "spectrum.b.unit = b.unit\n", "spectrum.E0.unit = ebreak.unit\n", "spectrum.K.unit = K.unit" ] }, { "cell_type": "markdown", "id": "39c52ea7", "metadata": {}, "source": [ "Define the source position and polarization object" ] }, { "cell_type": "code", "execution_count": 6, "id": "41cbf55e", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "This class loading takes around 30 seconds... \n", "\n", "Number of azimuthal angle bins used: 12\n", ">>> Convolving spectrum in ICRS frame...\n", "Energy range considered (by responses design): 200.0 - 10000.0 keV\n", "Background provided. Make sure there is enough statistics.\n", "Creating the 100% polarized ASADs (this may take a minute...)\n", "Creating the unpolarized ASAD...\n", "A = 0.72, B = 0.57, C = 1.53\n", "Rmax, Rmin: 1.2827367006245693 0.7181276431368199\n", "Modulation mu = 0.28218257736871405\n", "A = 0.71, B = 0.58, C = 1.24\n", "Rmax, Rmin: 1.284622321399381 0.7145058020894187\n", "Modulation mu = 0.2851825816521541\n", "A = 0.71, B = 0.58, C = 0.99\n", "Rmax, Rmin: 1.2794216149597286 0.7123734684134967\n", "Modulation mu = 0.2846920103778455\n", "A = 0.71, B = 0.58, C = 0.73\n", "Rmax, Rmin: 1.2823360713534138 0.7078568845720508\n", "Modulation mu = 0.28865501964065743\n", "A = 0.71, B = 0.59, C = 0.48\n", "Rmax, Rmin: 1.2856339600280398 0.7071225736365377\n", "Modulation mu = 0.2903071080778991\n", "A = 0.71, B = 0.58, C = 0.21\n", "Rmax, Rmin: 1.2853837198507168 0.7078525333056281\n", "Modulation mu = 0.2897454757962344\n", "A = 1.28, B = -0.56, C = 1.52\n", "Rmax, Rmin: 1.2774932586981842 0.7207764823973882\n", "Modulation mu = 0.2785994127077009\n", "A = 1.28, B = -0.57, C = 1.26\n", "Rmax, Rmin: 1.281431276325245 0.721439446355475\n", "Modulation mu = 0.2795945957112275\n", "A = 1.29, B = -0.58, C = 0.99\n", "Rmax, Rmin: 1.2896296477209535 0.7198603933983151\n", "Modulation mu = 0.2835392276964368\n", "A = 1.30, B = -0.59, C = 0.72\n", "Rmax, Rmin: 1.2976477509374849 0.7140224843592645\n", "Modulation mu = 0.29011975041333127\n", "A = 1.29, B = -0.58, C = 0.47\n", "Rmax, Rmin: 1.2911649168710433 0.7164309051392445\n", "Modulation mu = 0.2862797408874333\n", "A = 0.71, B = 0.58, C = 1.79\n", "Rmax, Rmin: 1.2879885426880395 0.7165586766198688\n", "Modulation mu = 0.28506680240012655\n" ] } ], "source": [ "source_photons = PolarizationStokes(source_direction, spectrum, data, response_file, sc_orientation, \n", " background=background, response_convention='RelativeX', show_plots=False)" ] }, { "cell_type": "markdown", "id": "54defb88", "metadata": {}, "source": [ "Let's check some numbers:" ] }, { "cell_type": "code", "execution_count": 7, "id": "57c9a289", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "Data duration: 0.541 s\n", "Data counts: 8114\n", "Count rate: 15006.507 counts/s\n", "\n", "Background duration: 378.9 s\n", "\n", "MDP_99: 16.646 %\n" ] } ], "source": [ "data_duration = source_photons.get_data_duration()\n", "data_count = source_photons.get_data_counts()\n", "print('\\nData duration:', str(round(data_duration, 3)), 's')\n", "print('Data counts:', str(data_count))\n", "print('Count rate:', str(round(data_count / data_duration, 3)), 'counts/s')\n", "\n", "background_duration = source_photons.get_background_duration()\n", "print('\\nBackground duration:', str(round(background_duration, 3)), 's')\n", "\n", "MDP99 = source_photons._mdp99 * 100\n", "print('\\nMDP_99:', str(round(MDP99, 3)), '%')" ] }, { "cell_type": "markdown", "id": "1e5cb5b3", "metadata": {}, "source": [ "Derive the modulation factor. This depends on the source spectrum and the instrument polarization response averaged over polarization angles. This steo needs to be re-computed for every source." ] }, { "cell_type": "code", "execution_count": 8, "id": "2db5d9d4", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "modulation factor: 0.286 +/- 0.000\n" ] } ], "source": [ "average_mu = source_photons._mu100\n", "mu = average_mu['mu']\n", "mu_err = average_mu['uncertainty']\n", "\n", "print('modulation factor: %.3f +/- %.3f'%(mu, mu_err))" ] }, { "cell_type": "markdown", "id": "eb4a7306", "metadata": {}, "source": [ "Get the azimuthal angles for each photons and calculate the Pseudo Stokes parameters from the scattering angle for each photon in the data and background simulation" ] }, { "cell_type": "code", "execution_count": 9, "id": "5db15edd", "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "qs, us = source_photons.compute_data_pseudo_stokes(show_plots=True)" ] }, { "cell_type": "markdown", "id": "26df3de8", "metadata": {}, "source": [ "Now get the stokes parameters for the background observations" ] }, { "cell_type": "code", "execution_count": 10, "id": "c69dae6c", "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "bkg_qs, bkg_us = source_photons.compute_background_pseudo_stokes(show_plots=True)" ] }, { "cell_type": "markdown", "id": "5bced9c7", "metadata": {}, "source": [ "The background is rate is estimated over a longer time period and therefore its flux needs to be rescaled to the expected flux during the GRB.\n", "\n", "This factor is simply computed as the ration of GRB duration / background duration." ] }, { "cell_type": "code", "execution_count": 11, "id": "da3b6513", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Background scale factor: 0.0014270214696478288\n", "Consistency check : True\n" ] } ], "source": [ "backscal = source_photons.get_backscal()\n", "\n", "print('Background scale factor:', backscal)\n", "print('Consistency check :', data_duration/background_duration == backscal)" ] }, { "cell_type": "markdown", "id": "b3417867", "metadata": {}, "source": [ "Compute the expected MDP assuming " ] }, { "cell_type": "code", "execution_count": 12, "id": "f19a7f75", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "I, Q, U, mu 8114 -6748.662921595113 679.1013368480847 0.286103474003816\n", "Q, U (unsubtracted:) -0.831730702686112 0.08369501316836143\n", "Unpolarized bkg (or simulation) provided, subtracting its contribution.\n", "check I(src+bkg) vs I(src): 8114 8111.672527983004\n", "Q, U unpolarized: 0.30927296257871145 0.1280049674500421\n", "Q, U unpolarized uncertainty: 323.2597643589276 %\n", "Q, U, subtracted: -0.8312893635285307 0.08387767900513422\n", "Q/I, U/I, uncertainty: 0.044400158330688354 0.05478623413101503 0.2107134507588169\n", "\n", " ############################## \n", "\n", " PD: 83.55 +/- 5.41 %\n", " PA: 87.12 +/- 1.88 deg\n", "\n", " ############################## \n", "\n" ] }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "polarization = source_photons.calculate_polarization(qs, us, mu, bkg_qs=bkg_qs, bkg_us=bkg_us, show_plots=True, ref_pdpa=(0.8, 90), ref_label='Simulated', mdp=MDP99/100)" ] }, { "cell_type": "markdown", "id": "bc5136dd", "metadata": {}, "source": [ "Extracting the informations from the polarization dictionary:" ] }, { "cell_type": "code", "execution_count": 13, "id": "5447d326", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Polarization degree: (83.55 +/- 5.41) %\n", "Polarization angle: (87.12 +/- 1.88) deg\n", "Normalized Q: -0.831 +/- 0.044\n", "Normalized U: 0.084 +/- 0.055\n" ] } ], "source": [ "Pol_frac = polarization['fraction'] * 100\n", "Pol_frac_err = polarization['fraction_uncertainty'] * 100\n", "print('Polarization degree: (%.2f +/- %.2f) %%'%(Pol_frac, Pol_frac_err))\n", "\n", "Pol_angle = polarization['angle'].angle.degree\n", "Pol_angle_err = polarization['angle_uncertainty'].degree\n", "print('Polarization angle: (%.2f +/- %.2f) deg'%(Pol_angle, Pol_angle_err))\n", "\n", "Normalized_Q = polarization['QN']\n", "Normalized_U = polarization['UN']\n", "QN_ERR = polarization['QN_ERR']\n", "UN_ERR = polarization['UN_ERR']\n", "print('Normalized Q: %.3f +/- %.3f'%(Normalized_Q, QN_ERR))\n", "print('Normalized U: %.3f +/- %.3f'%(Normalized_U, UN_ERR))\n", "\n" ] } ], "metadata": { "kernelspec": { "display_name": "Python [conda env:cosipy]", "language": "python", "name": "conda-env-cosipy-py" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.12.12" } }, "nbformat": 4, "nbformat_minor": 5 }