{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Exploring Optical Spectra of Black Holes\n",
    "\n",
    "## Learning Goals\n",
    "By the end of this tutorial, you will:\n",
    "- Understand how to read in SDSS BOSS spectra of quasars\n",
    "- Become familiar with computed parameters of quasar spectra\n",
    "- Shift spectra to rest wavelength\n",
    "\n",
    "## Introduction\n",
    "<p>In this notebook we are going to take a look at a type of astronomical obsects known as quasars. Quasars are powered by supermassive black holes that lie in the heart of distant galaxies. They are visible as gas falling towards the black hole forms a fast-moving, hot disk that shines so brightly it can be seen in the furthest reaches of the universe.  </p>\n",
    "<p>We will study these quasars by looking at their spectra. A spectrum measures the intensity of light in many different wavelengths (colors of light). We will be using data from the Sloan Digital Sky Survey which has measured the spectra of millions of astronomical objects.</p>\n",
    "<p>You will need to download spectra for the three objects in this tutorial. Here we have assumed they are saved in a subdirectory/folder called \"BHM_spectra\", but you may choose to point to your Downlaods folder or move the spectra to the same directory as this notebook for simplicity.</p>\n",
    "<ul>\n",
    "<li><a href=\"https://data.sdss.org/sas/dr19/spectro/boss/redux/v6_1_3/spectra/lite/015173/59381/spec-015173-59381-4351098892.fits\">Object 1</a></li>\n",
    "<li><a href=\"https://data.sdss.org/sas/dr19/spectro/boss/redux/v6_1_3/spectra/lite/015301/59314/spec-015301-59314-4602374937.fits\">Object 2</a></li>\n",
    "<li><a href=\"https://data.sdss.org/sas/dr19/spectro/boss/redux/v6_1_3/spectra/lite/015023/59232/spec-015023-59232-4555307714.fits\">Object 3</a></li>\n",
    "</ul>\n",
    "\n",
    "## Imports\n",
    "This tutorial requires two commonly used python packages, and an SDSS specific package\n",
    "- _numpy_ for doing math\n",
    "- _matplotlib_ for plotting\n",
    "- _astropy_ for reading fits table\n",
    "\n",
    "Missing packages can be installed via `pip install numpy matplotlib astropy` \n",
    "\n",
    "<p>Let's start by importing some libraries.</p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b965d093",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from astropy.io import fits\n",
    "from astropy.table import Table\n",
    "# for plots\n",
    "from matplotlib import rc"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9127ae96",
   "metadata": {},
   "source": [
    "<p>We will need to load the data from files for individual spectra of objects. Here we load our first object.</p>\n",
    "\n",
    "<p>If you are running this notebook on sciserver, uncomment the longer pathname</p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c155dc1c",
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')\n",
    "\n",
    "current_path=os.getcwd()\n",
    "object1_filename=current_path+'/BHM_spectra/spec-015173-59381-4351098892.fits'\n",
    "\n",
    "# object1_filename=\"/home/idies/workspace/sdss_sas/dr19/spectro/boss/redux/v6_1_3/spectra/lite/015173/59381/spec-015173-59381-4351098892.fits\"\n",
    "\n",
    "object1_data = Table.read(object1_filename, format='fits',hdu=1)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8ab2f008",
   "metadata": {},
   "source": [
    "<p>Now let's look at our data for our first object.</p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4126aa14",
   "metadata": {},
   "outputs": [],
   "source": [
    "object1_data"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "70347369",
   "metadata": {},
   "source": [
    "<p>You can see we have multiple columns. The two we are most interested in are:\n",
    "<ul>\n",
    "    <li>The flux which measures the intensity of light received from this object at a particular wavelength</li>\n",
    "    <li>The log of the wavelength (LOGLAM).</li>\n",
    "</ul>\n",
    "We can convert the second of these to make a new wavelength column as it's often easier to think in linear scales.</p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c82249ee",
   "metadata": {},
   "outputs": [],
   "source": [
    "object1_data['WAVELENGTH']=10.0**object1_data['LOGLAM']"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cac88501",
   "metadata": {},
   "source": [
    "<p>We can now make a plot of our first object</p>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "41c05692",
   "metadata": {},
   "source": [
    "<p>This is the spectrum of your object. On the left side is the flux in the bluest color your eye can see. The color of the light gets redder as we move with increasing wavelength to the right. On the furthest right end of the spectrum we have light too red for our eyes to see (the start of the infrared). </p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0b5b1a6d",
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.figure(figsize=(15,7.5))\n",
    "plt.plot(object1_data['WAVELENGTH'],object1_data['FLUX'])\n",
    "plt.title(object1_filename)\n",
    "plt.xlabel('wavelength (Angstroms)')\n",
    "plt.ylabel('Flux')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a4500383",
   "metadata": {},
   "source": [
    "<p>Sometimes a spectrum comes with regions of bad data caused by things like cosmic rays hitting the detector or for reasons related to the spectrograph. Luckily, the SDSS pipeline marks pixels that may have been affected by issues like this. We can mask out the worst of this data by doing filtering for pixels which are marked as having no issues. </p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "577d9c57",
   "metadata": {},
   "outputs": [],
   "source": [
    "object1_mask_pixels =(object1_data['AND_MASK']==0)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ca1fb04d",
   "metadata": {},
   "source": [
    "<p>Now let's redo our plot showing only pixels that we didn't mask out.</p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "dbb107ce",
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.figure(figsize=(15,7.5))\n",
    "plt.plot(object1_data[object1_mask_pixels]['WAVELENGTH'],object1_data[object1_mask_pixels]['FLUX'])\n",
    "plt.title(object1_filename)\n",
    "plt.xlabel('wavelength (Angstroms)')\n",
    "plt.ylabel('Flux')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7958cdec",
   "metadata": {},
   "source": [
    "**Exercise:**\n",
    "Do you notice any changes between the masked and the unmasked spectra?"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3c0970f4",
   "metadata": {},
   "source": [
    "#answer"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bcf834fd",
   "metadata": {},
   "source": [
    "**Exercise:**\n",
    "Have a look at your masked spectrum and answer the following questions:\n",
    "<ul>\n",
    "    <li>What is the overall shape of the spectrum?</li>\n",
    "    <li>Where do you find the biggest deviations from this overall shape?</li>\n",
    "    <li>What is the biggest of these deviations from the overall shape?</li>\n",
    "</ul>\n",
    "</p>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "220ed6c9",
   "metadata": {},
   "source": [
    "#answers"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "adcc4f6d",
   "metadata": {},
   "source": [
    "<p>In spectroscopy we typically talk an object having \"continuum\" that marks the general shape of the object's spectrum. Peaks above this continuum are known as emission lines and valleys below continuum are known as absorption lines.<br/>\n",
    "\n",
    "**Exercise**\n",
    "<ul>\n",
    "<li>What do you think is the continuum in your spectrum?</li>\n",
    "<li>Can you see emission or absorption lines?</li>\n",
    "</ul>\n",
    "</p>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "25e7dc31",
   "metadata": {},
   "source": [
    "#answers"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b5af7e4f",
   "metadata": {},
   "source": [
    "**Exercise:**\n",
    "Load the data for the following files using similar code the what we used for the first object. Create pixel masks for both of these objects to remove bad data.\n",
    "\n",
    "If you're running this notebook on SciServer, uncomment the longer paths to access the local files."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a96ae5dc",
   "metadata": {},
   "outputs": [],
   "source": [
    "object2_filename=current_path+'/BHM_spectra/spec-015301-59314-4602374937.fits'\n",
    "\n",
    "# object2_filename = \"/home/idies/workspace/sdss_sas/dr19/spectro/boss/redux/v6_1_3/spectra/lite/015301/59314/spec-015301-59314-4602374937.fits\"\n",
    "\n",
    "object3_filename=current_path+'/BHM_spectra/spec-015023-59232-4555307714.fits'\n",
    "\n",
    "# object3_filename = \"/home/idies/workspace/sdss_sas/dr19/spectro/boss/redux/v6_1_3/spectra/lite/015023/59232/spec-015023-59232-4555307714.fits\"\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f738dc4e",
   "metadata": {},
   "source": [
    "<p>Now make three plots of the three spectra. You can put your plotting code in the cell below.</p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "74b41904",
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.figure(figsize=(15,20))\n",
    "plt.subplot(3,1,1)\n",
    "#object1 plotting code goes here\n",
    "\n",
    "\n",
    "\n",
    "plt.subplot(3,1,2)\n",
    "#object2 plotting code goes here\n",
    "\n",
    "\n",
    "\n",
    "plt.subplot(3,1,3)\n",
    "#object3 plotting code goes here\n",
    "# there is an issue with this spectrum at the very blue end, we can ignore it and manually change the y axis\n",
    "plt.ylim(-10,80) \n",
    "\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ea300166",
   "metadata": {},
   "source": [
    "<p>Let's take a look at some of the features of the three spectra.</p>\n",
    "<p>Take the biggest emission line in each spectrum. This should be the triangular-shaped line that is the highest above the continuum. What differs between the stongest emisson line in each spectrum?</p>\n",
    "<p>Take the group of three emission lines between 6500A and 7000A on the spectrum of object 1. Do you see a similar pattern somewhere in the spectrum of object 2, what is different about that feature?<br/>Can you find a similar feature in the spectrum of object 3?</p>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5bd6aa3f",
   "metadata": {},
   "source": [
    "<p>The SDSS pipeline doesn't just produce a spectrum of the object. It also uses that spectrum to measure lots of parameters relating to the object. It's quite easy to access these. We can do this by doing the following:</p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b1ec08fa",
   "metadata": {},
   "outputs": [],
   "source": [
    "object1_pipeline_data = Table.read(object1_filename, format='fits',hdu=2)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "095321bc",
   "metadata": {},
   "source": [
    "<p>Now we can have a look at the columns.</p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1039c26b",
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "object1_pipeline_data.colnames"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9ba07851",
   "metadata": {},
   "source": [
    "<p>There are many columns, too many to go into here. They cover parameters measured from the spectrum to important bits of information about the spectrum such as the exposure time and the moon phase when it was observed.</p>\n",
    "\n",
    "<p>What we are interested in is a parameter labeled \"z\". Let's have a look at that parameter and its error.</p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9e4ac954",
   "metadata": {},
   "outputs": [],
   "source": [
    "object1_z=object1_pipeline_data[0]['Z']\n",
    "object1_z_err=object1_pipeline_data[0]['Z_ERR']\n",
    "print('z='+str(object1_z)+' +/- '+str(object1_z_err))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "99d17ea0",
   "metadata": {},
   "source": [
    "<p>This parameter is called redshift. In an expanding universe, distant objects appear to be moving away from us. The further away the object, the faster they appear to be moving away. The further away they are, the faster they appear to be moving away from us. This changes the spectrum of the objects, moving spectra features to longer, redder wavelengths (hence redshift).</p>\n",
    "\n",
    "<p>The observed wavelength of a spectral feature is related to the wavelength it had when it was emitted (the rest wavelength) by the following relation</p>\n",
    "<p>$\\lambda_{obs}=(1+z)\\lambda_{rest}$</p>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8708693c",
   "metadata": {},
   "source": [
    "**Exercise:** Extract the redshift from the pipeline data for objects 2 and 3. Then add a new column to the spectra for objects 1, 2 and 3 called \"WAVELENGTH_REST\". This should be the wavelength of that pixel corrected for the redshift. Then remake your plots of the three spectra.<br/>HINT: use plt.xlim(2000,8000) for each of your plots so they cover the same wavelength range.</p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "47ba527f",
   "metadata": {},
   "outputs": [],
   "source": [
    "# code"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c8f81890",
   "metadata": {},
   "source": [
    "**Exercise:**\n",
    "<ul>\n",
    "<li>What do you notice about the lines you previously looked at. Do you still see the same changes as before?</li>\n",
    "<li>What about the big line in object 1 that has a wavelength of roughly 9000A before correction for redshift? Do you see this in the other objects? If not why not?</li>\n",
    "</ul>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b2586507",
   "metadata": {},
   "source": [
    "#answers"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "671be9cd",
   "metadata": {},
   "source": [
    "<p>Below is an example spectrum of a quasar (credit Vanden Berk et al. 2001). On it are marked several lines that are often prominent in quasar spectra. Which lines to you see in each of your spectra?</p>"
   ]
  },
  {
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"
    }
   },
   "cell_type": "markdown",
   "id": "7183ba42",
   "metadata": {},
   "source": [
    "![fg3.gif](attachment:fg3.gif)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fb9962f8",
   "metadata": {},
   "source": [
    "<p>So you've had a look at the spectra of quasars and seen how redshift can change what they look like when we observe them. Now lets have a look at several spectra of the same quasar taken in different years.</p>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f96188b8",
   "metadata": {},
   "source": [
    "<p>Next we need to add a grab a few more spectra of object 1. Add them to the same directory as before.</p>\n",
    "<ul>\n",
    "<li><a href=\"https://dr18.sdss.org/optical/spectrum/view/data/format=fits/spec=lite?plateid=7339&mjd=56799&fiberid=611\">Object 1 spectrum B</a></li>\n",
    "<li><a href=\"https://dr18.sdss.org/optical/spectrum/view/data/format=fits/spec=lite?plateid=7339&mjd=57518&fiberid=611\">Object 1 spectrum C</a></li>\n",
    "</ul>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "43b06b49",
   "metadata": {},
   "source": [
    "<p>First let's load in the spectra. Note one small change, with these older spectra the column names are lower case.</p>\n",
    "\n",
    "If you're running this notebook on SciServer, uncomment the longer paths to access the local files."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "bf3ba468",
   "metadata": {},
   "outputs": [],
   "source": [
    "object1b_filename=current_path+'/BHM_spectra/spec-7339-57518-0611.fits'\n",
    "\n",
    "# object1b_filename = \"/home/idies/workspace/sdss_sas/dr17/eboss/spectro/redux/v5_13_2/spectra/lite/7339/spec-7339-57518-0611.fits\"\n",
    "\n",
    "object1b_data = Table.read(object1b_filename, format='fits',hdu=1)\n",
    "\n",
    "object1c_filename=current_path+'/BHM_spectra/spec-7339-56799-0611.fits'\n",
    "\n",
    "# object1c_filename = \"/home/idies/workspace/sdss_sas/dr17/eboss/spectro/redux/v5_13_2/spectra/lite/7339/spec-7339-56799-0611.fits\"\n",
    "\n",
    "object1c_data = Table.read(object1c_filename, format='fits',hdu=1)\n",
    "\n",
    "object1b_mask_pixels =(object1b_data['and_mask']==0)\n",
    "object1b_data['WAVELENGTH']=10.0**object1b_data['loglam']\n",
    "object1c_mask_pixels =(object1c_data['and_mask']==0)\n",
    "object1c_data['WAVELENGTH']=10.0**object1c_data['loglam']"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a0b13e08",
   "metadata": {},
   "source": [
    "**Exercise:**\n",
    "    <ul>\n",
    "    <li>Plot the three spectra of object 1 (called object1, object1b and object1c) on the same axes. Give these the colors limegreen, blue and red. Add \"Epoch Comparison as the title\".</li>\n",
    "    </ul>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "bd19a86c",
   "metadata": {},
   "outputs": [],
   "source": [
    "# code"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "351a4f36",
   "metadata": {},
   "source": [
    "<p>Now let's look at when these spectra were taken. The date they were taken is actually in the file name for each. The spectrum filename has the form <code>spec-plate_number-date-fiber_number.fits</code>.</p>\n",
    "<p>But, that number doesn't look like a date. That's because it's in a slight odd formatting used by astronomers called a Modified Julian Date (MJD). This is a modification to a dating system with a rather strange origin. Put simply, that number is the number of days since the 17th of November 1858.</p>\n",
    "    <p>To make life easier here's a little function to convert MJD to a more familiar format.</p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "31b2ffa3",
   "metadata": {},
   "outputs": [],
   "source": [
    "def mjd_to_year(mjd):\n",
    "    from astropy.time import Time\n",
    "    time_tmp = Time(mjd, format='mjd') \n",
    "    return time_tmp.iso"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6b296ef7",
   "metadata": {},
   "source": [
    "**Exercise:**\n",
    "    <ul>\n",
    "    <li>Convert the Modified Julian Dates for your three spectra into a more readable format</li>\n",
    "    <li>Label each of lines on your plot with the date that spectrum was taken</li>\n",
    "    <li>Add a legend to your plot using a call to plt.legend()</li>\n",
    "    </ul>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "861e0f00",
   "metadata": {},
   "outputs": [],
   "source": [
    "# code"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3d4a35ca",
   "metadata": {},
   "source": [
    "**Exercise:**\n",
    "    <ul>\n",
    "    <li>Take a look at the three spectra. What can you say about the different spectra?\n",
    "        <ul>\n",
    "            <li>How does the level of the continuum change?</li>\n",
    "            <li>How do the positions, heights and shapes of most of the spectral lines change?</li>\n",
    "        </ul>\n",
    "    <li>Given what was mentioned at the start of this notebook about what powers quasars, what do you think could be happening?</li>\n",
    "    </ul>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b6e19c23",
   "metadata": {},
   "source": [
    "#answers"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "52bc3034",
   "metadata": {},
   "source": [
    "## About this notebook\n",
    "This notebook was created to illustrate some of the basic principles of quasar spectra from the SDSS-V BOSS\n",
    "\n",
    "**Authors**: Niall Deacon\n",
    "\n",
    "*Editing:* John Donor\n",
    "\n",
    "**Last Update**: 2025 June 26\n",
    "\n",
    "If you use `astropy`  for published research, please cite the\n",
    "authors. Follow this link for more information about citing `astropy`:\n",
    "\n",
    "* [Citing `astropy`](https://www.astropy.org/acknowledging.html)\n",
    "\n",
    "And of course, please [cite](https://sdss.org/collaboration/citing-sdss/) SDSS when you use our data."
   ]
  }
 ],
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