Spring 2024 updates

Lab_1/Lab_1.ipynb

@@ -57,7 +57,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Download _object.fits_ and _object.cat_ from Gauchospace.  You may right-click _object.fits_ (if you associated fits files with ds9) and open with ds9, or you my load ds9 by clicking on the icon pinned to the taskbar and then using the open function (you can do this with both the GUI button and from the \"File\" menu) to find the file _object.fits_.\n",
+    "Download _object.fits_ and _object.cat_ from the Canvas Week 2 Module.  You may right-click _object.fits_ (if you associated fits files with ds9) and open with ds9, or you my load ds9 first and then using the open function (you can do this with both the GUI button and from the \"File\" menu) to find the file _object.fits_.\n",
     "\n"
    ]
   },

Lab_2/Lab_2.ipynb

@@ -4,14 +4,14 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# <p style=\"text-align: center;\">PHYS 134L Spring 2022 Lab 2</p>"
+    "# <p style=\"text-align: center;\">PHYS 134L Spring 2024 Lab 2</p>"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "<div class=\"alert alert-block alert-danger\"><b>Due date:</b> Sunday, April 17th, 2022 by 11:59pm, submitted through Gradescope.</div>"
+    "<div class=\"alert alert-block alert-danger\"><b>Due date:</b> Sunday, April 21th, 2024 by 11:59pm, submitted through Gradescope.</div>"
    ]
   },
   {
@@ -92,7 +92,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "**On a sheet of paper, sketch a map of the part of the sky where the image was taken large enough to include a couple of bright, named stars (please label them).  Check out the [Stellarium website](https://stellarium-web.org/) if you need some help. Note that RA is defined so that as the Earth turns, the RA of objects on the meridian increases with time. Draw your map with N up and E to the left (as it would appear if you were facing the southern horizon). Attach the drawing to the end of this lab report before you submit it to gradescope**"
+    "**On a sheet of paper, sketch a map of the part of the sky where the image was taken large enough to include a couple of bright, named stars (please label them).  Check out the [Stellarium website](https://stellarium-web.org/) if you need some help. Note that RA is defined so that as the Earth turns, the RA of objects on the meridian increases with time. Draw your map with N up and E to the left (as it would appear if you were facing the southern horizon). Attach the drawing to the end of this lab report before you submit it to gradescope.**"
    ]
   },
   {
@@ -130,7 +130,7 @@
    "source": [
     "The word ''sidereal'' means ''with respect to the stars.'' The current Local Sidereal Time (LST) is the value of the RA in the equatorial\n",
     "coordinate system that is crossing your meridian at the moment. Since the coordinates of stars are essentially constant over very long times,\n",
-    "at a given LST you will always find the stars in the same apparent positions in the sky. Sidereal time is not the same as solar time (which we normally use) -- at a given solar time (such as noon), we find the {\\it Sun} in the same position, not the stars. Because the Earth orbits the Sun once per year, the sidereal day is about 4 minutes shorter than the solar day. Thus, measuring by solar time, a given star rises and sets about 4 minutes earlier every day."
+    "at a given LST you will always find the stars in the same apparent positions in the sky. Sidereal time is not the same as solar time (which we normally use) -- at a given solar time (such as noon), we find the _Sun_ in the same position, not the stars. Because the Earth orbits the Sun once per year, the sidereal day is about 4 minutes shorter than the solar day. Thus, measuring by solar time, a given star rises and sets about 4 minutes earlier every day."
    ]
   },
   {
@@ -511,7 +511,7 @@
    "metadata": {},
    "source": [
     "The size of an astronomical image on the CCD detector depends on the effective focal length (usually abbreviated ''focal length'') of\n",
-    "the telescope. Here is a link to a quick primary on focal length: [Focal length and f/# explained](https://www.paragon-press.com/lens/lenchart.html). This part of the lab will use a fits file called ```cluster.fits``` that should have been downloaded to your JupyterHub account when you clicked the link for this notebook, but it can also be found on the Lab 2 tab on the Gauchospace site. "
+    "the telescope. Here is a link to a quick primary on focal length: [Focal length and f/# explained](https://www.paragon-press.com/lens/lenchart.html). This part of the lab will use a fits file called ```cluster.fits``` that should have been downloaded to your JupyterHub account when you clicked the link for this notebook, but it can also be found on the Lab 2 tab on the Canvas site. "
    ]
   },
   {
@@ -641,19 +641,33 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Now open a browser and go to [http://www.sky-map.org](http://www.sky-map.org). This is a nice piece of planetarium software (similar to the Stellarium page we used earlier). Go to ''Home,'' and enter the name of the cluster in the ''Find Object'' window. When the map comes up, point to the small elliptical icon in the upper left called ``DSS,'' and\n",
-    "select ``DSS2 All Sky Survey.'' These data come from various releases of the [Digital Sky Survey](https://irsa.ipac.caltech.edu/data/DSS/). Zoom in 3 or 4 clicks on the size scale, and you should see a familiar star cluster (a bit off center). Drag it\n",
-    "to the center of the window, and zoom it to whatever degree makes you comfortable. Now when you drag the cursor over a star image you\n",
-    "will see lots of information about each star, including a long catalog number, and (most importantly) the star’s equatorial coordinates."
+    "Now open a browser and go to the [Aladin Lite](https://aladin.cds.unistra.fr/AladinLite/) online tool. This is a nice professional tool that contains a little more astronomical data than Stellarium. From it's website: \"Aladin is an interactive sky atlas allowing the user to visualize digitized astronomical images or full surveys, superimpose entries from astronomical catalogues or databases...\". The website provides a simple interface to access some of Aladin's most basic features. If you'd like to explore the tool more I recommend downloading the desktop version. \n",
+    "\n",
+    "**In the search bar enter the name of the cluster pictured above and zoom in. Underneath the search bar there is a selection of different Astronomical image Catalogs that you can display. Select 5 different catalogs and do some internet sleuthing to find out about them. For each catalog find out: At what telescope were these data taken? What is the wavelength of the data being displayed? When was the data taken (or published)?**\n",
+    "\n"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Identify the 4 numbered stars in the image above on the ```sky-map.org``` site, and list their RA, $\\delta$ values in the table below, 1 row per star. Also measure the $\\{x,y\\}$ coordinates\n",
-    "of each star on ```cluster.fits```, using the cursor to pick out the brightest point in each star. Do this carefully, zooming so that setting the cursor is\n",
-    "easy, and adjusting the ``scale'' options so you can easily see the brightness variations inside the star images.  Make a subjective guess about the error (in pixel units) with which you can measure the star positions. Put this in the table too, under error\\_g."
+    "*Your answer here*"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "On the right-hand side of the screen you'll see the option to display data from several different catalogs. When you select one (it may take a second for the data to load), each star in the image that is in that database will show up with a symbol on it. If you click on that symbol you will be shown some of the main identifying information about that star. For the purposes of this lab using the SIMBAD catalog is probably most appropriate. "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**Identify the 4 numbered stars in the image above on the Aladin Lite site, and list their RA, $\\delta$ values in the table below, 1 row per star. Also measure the $\\{x,y\\}$ coordinates\n",
+    "of each star on ```cluster.fits``` in DS9, using the cursor to pick out the brightest point in each star. Do this carefully, zooming so that setting the cursor is\n",
+    "easy, and adjusting the ''scale'' options so you can easily see the brightness variations inside the star images.  Make a subjective guess about the error (in pixel units) with which you can measure the star positions. Put this in the table too, under _error\\_g_.**"
    ]
   },
   {
@@ -673,7 +687,7 @@
    "metadata": {},
    "source": [
     "What do you think is your largest source of error (the one that dominates your estimate of\n",
-    "error g)?"
+    "error\\_g)?"
    ]
   },
   {
@@ -688,8 +702,8 @@
    "metadata": {},
    "source": [
     "Now compute the distances between various pairs of stars, as given below. Do this first by using the difference in RA and d that you obtained\n",
-    "from ```sky-map.org```. Formally this is an exercise in spherical trigonometry, but because all of these stars are very close together on the sky, we\n",
-    "may use small-angle approximations. In this case we get sufficient accuracy by taking}\n",
+    "from Aladin. Formally this is an exercise in spherical trigonometry, but because all of these stars are very close together on the sky, we\n",
+    "may use small-angle approximations. In this case we get sufficient accuracy by taking\n",
     "$$\n",
     "\\Delta r = \\sqrt{(\\Delta \\delta)^2 + \\left(\\Delta {\\rm RA} \\cos \\delta \\right)^2},\n",
     "$$\n",
@@ -719,9 +733,9 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "**Also compute the separation between these pairs of stars in units of pixels, using your measured values of $x$ position and $y$ position. In this case the\n",
+    "**Now compute the separation between these pairs of stars in units of pixels, using your measured values of $x$ position and $y$ position. In this case the\n",
     "normal Pythagorean law may be used, with no $\\cos(\\delta)$ factor. (Think about why.) Use your estimates of error\\_g and standard propagation-of-error\n",
-    "rules (see the textbook by ***Taylor*** linked on the Lab 2 tab in Gauchospace for a refresher) to estimate the errors in these separations which we will call error $_p$. In the space below, show the formula(s) you used for calculating the error $_p$ values. Then put all of the data into the table below. Expand the number of rows as necessary.**"
+    "rules to estimate the errors in these separations which we will call error $_p$. In the space below, show the formula(s) you used for calculating the error $_p$ values. Then put all of the data into the table below. Expand the number of rows as necessary.**"
    ]
   },
   {
@@ -742,7 +756,7 @@
    "metadata": {},
    "source": [
     "**For each star pair, compute the image scale $\\Delta r/\\Delta p$ in units of arcsec/pixel, and enter this value in the table. Use Taylor’s error propagation rules, starting from your estimates of error $_p$, to estimate the error in your derived value for the image scale (which we will call error $_s$).\n",
-    "Assume that the star separations derived from ```www.sky-map.org``` positions have negligible errors. Put your error $_s$ values in the table.**\n"
+    "Assume that the star separations derived from Aladin positions have negligible errors. Put your error $_s$ values in the table.**\n"
    ]
   },
   {
@@ -776,11 +790,6 @@
    "source": [
     "*You answer here*"
    ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": []
   }
  ],
  "metadata": {

Lab_3/Lab_3.ipynb

@@ -4,14 +4,14 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# <p style=\"text-align: center;\">PHYS 134L Spring 2022 Lab 3</p>"
+    "# <p style=\"text-align: center;\">PHYS 134L Spring 2024 Lab 3</p>"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "<div class=\"alert alert-block alert-danger\"><b>Due date:</b> Sunday, April 24th, 2022 by 11:59pm, submitted through Gradescope.</div>"
+    "<div class=\"alert alert-block alert-danger\"><b>Due date:</b> Sunday, April 28th, 2024 by 11:59pm, submitted through Gradescope.</div>"
    ]
   },
   {
@@ -32,7 +32,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Read through this entire lab before you start. In this lab, we will look at the brightness of stars as measured in astronomical units called ''magnitudes.'' To complete this lab you should have already read textbook Chapter 3 and Sections 2.3 and 2.4. In this lab, you will be asked to type out some equations. In a jupyter notebook you can do this using standard LATEX math notation. If you're new to LATEX you can use [this online equation editor](https://latex.codecogs.com/) to help you along to start. Later in this course you'll be using La"
+    "Read through this entire lab before you start. In this lab, we will look at the brightness of stars as measured in astronomical units called ''magnitudes.'' To complete this lab you should have already read textbook Chapter 3 and Sections 2.3 and 2.4. In this lab, you will be asked to type out some equations. In a jupyter notebook you can do this using standard LaTeX math notation. If you're new to LaTeX you can use [this online equation editor](https://latex.codecogs.com/) to help you along to start. Later in this course you'll be using LaTeX for your final report. "
    ]
   },
   {
@@ -304,7 +304,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Last lab, you estimated the angular sizes of a few stars; the largest size you should have computed was around 2~mas.  You also computed the pixel scale in these images; you should have gotten a scale of around $0.\\!\\!^{\\prime \\prime}58$ arcsec/pixel. **Use these two numbers to estimate the angular size of a star in units of pixels.  Please show your work for the unit conversion.**"
+    "Last lab, you estimated the angular sizes of a few stars; the largest size you should have computed was around 2~mas.  You also computed the pixel scale in these images; you should have gotten a scale of around $0.^{\\prime \\prime}58$ arcsec/pixel. **Use these two numbers to estimate the angular size of a star in units of pixels.  Please show your work for the unit conversion.**"
    ]
   },
   {
@@ -355,7 +355,14 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "For telescopes on the ground, the FWHM is usually set by atmospheric turbulence and is called ''seeing.''  A better site gives a shaper image. \n"
+    "For telescopes on the ground, the FWHM in an image is set either  by:  a) the atmospheric turbulence, where the atmosphere blurs out light passing through it, or b) the telescope primary mirror diameter, which introduces diffraction and limits the FWHM of the point spread function to be ~$\\lambda/D$ (in radians). When limited by the atmosphere, a better site gives a shaper image; the size of the atmospheric FWHM we call the ''seeing'' (typically expressed in arcseconds). Try to find on the internet the typical seeing for a few different astronomical telescope sites: Mauna Kea, Paranal and one site of your choice. Compare this to the diffraction limit of a couple telescopes at each those sites, when observing at 600nm. \n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "*Your answer here*"
    ]
   },
   {
@@ -484,7 +491,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "**Now use the flux-vs-magnitude expression from page 2 to write an expression for $N_{\\rm phot}$ as a function of ```MAG_ISOCOR```.**"
+    "**Now use the flux-vs-magnitude expression from Part 1 to write an expression for $N_{\\rm phot}$ as a function of ```MAG_ISOCOR```.**"
    ]
   },
   {
@@ -499,7 +506,7 @@
    "metadata": {},
    "source": [
     "The expected counting error (measured in photo-electrons) is the square root of $N_{\\rm phot}$. To get the noise in units of counts, we must\n",
-    "divide by the ```GAIN```. **Write an expression for this counting error as a function of MAG_ISOCOR}.**\n"
+    "divide by the ```GAIN```. **Write an expression for this counting error as a function of MAG_ISOCOR.**\n"
    ]
   },
   {
@@ -554,7 +561,23 @@
     "\n",
     "```x = np.arange(int(np.amin(mags)), int(np.amax(mags)) + 1)```\n",
     "\n",
-    "**and evaluate your expression for magnitude uncertainties at these integer ```x``` values.  Overplot this on your plot of ```MAGERR_ISOCOR``` vs.~```MAG_ISOCOR``` using a thick, red line.**"
+    "**and evaluate your expression for magnitude uncertainties at these integer ```x``` values.  Overplot this on your plot of ```MAGERR_ISOCOR``` vs.~```MAG_ISOCOR``` using a thick, red line. Comment on whether they match or not**"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#Your Code here"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "*Your answer here*"
    ]
   },
   {
@@ -569,7 +592,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Now we know how to use Source Extractor output to estimate the fluxes and magnitudes of stars, and also the precision that simple physics says we should be achieving. But how well do we know our errors, really? Might effects other than photon counting statistics be dominant? And what about systematic errors, which give us consistent and repeatable wrong answers? How can we test for these?\n",
+    "Now we know how to use the data from Source Extractor to estimate the fluxes and magnitudes of stars, and also the precision that simple physics says we should be achieving. But how well do we know our errors, really? Might effects other than photon counting statistics be dominant? And what about systematic errors, which give us consistent and repeatable wrong answers? How can we test for these?\n",
     "\n",
     "\n",
     "Source Extractor can estimate source fluxes in several ways – two of these are isophotal photometry (which deals well with objects having funny shapes) and aperture photometry (which works well for perfectly round objects, as star images are supposed to be). Check section 7.4 of *Source Extractor for Dummies* for an explanation of what these things mean. The picture on p.~41 is particularly helpful.\n",

Lab_4/Lab_4.ipynb

@@ -4,14 +4,14 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# <p style=\"text-align: center;\">PHYS 134L Spring 2022 Lab 4</p>"
+    "# <p style=\"text-align: center;\">PHYS 134L Spring 2024 Lab 4</p>"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "<div class=\"alert alert-block alert-danger\"><b>Due date:</b> Sunday, May 1st, 2022 by 11:59pm, submitted through Gradescope.</div>"
+    "<div class=\"alert alert-block alert-danger\"><b>Due date:</b> Sunday, May 5th, 2024 by 11:59pm, submitted through Gradescope.</div>"
    ]
   },
   {
@@ -93,7 +93,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Read the photutils background estimation [documentation](https://photutils.readthedocs.io/en/stable/background.html) to determine the best method to use on this data. Play with image scaling and colorbars to help determine if a 2D background estimation is needed. Describe below your final decision on the best method here and why"
+    "Read the photutils background estimation [documentation](https://photutils.readthedocs.io/en/stable/background.html) and test out several methods of background subtraction. Determine the best method to use on this data. Play with image scaling and colorbars to help you decide the best method. Show your work below. Describe below your final decision on the best method here and why. "
    ]
   },
   {
@@ -201,7 +201,9 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Now we're moving on to extracting the photometry. Here we'll be carrying out photometry using a technique called \"aperture photometry\", where we simply add up all the counts within a circular aperture. See the ```photutils``` documentation [here](https://photutils.readthedocs.io/en/stable/aperture.html). **Read up on the documentation and try it out yourself.** There are other types of photometry, such as \"weighted PSF\" photometry, that may be useful in your final project. \n",
+    "Now we're moving on to extracting the photometry. Here we'll be carrying out photometry using a technique called \"aperture photometry\", where we simply add up all the counts within a circular aperture. There are other types of photometry, such as \"weighted PSF\" photometry, that may be useful in your final project. Another type of photometry is \"Isophotal photometry\", which we encountered earlier in the course. You can read about that in the Sextractor documentation or elsewhere online. \n",
+    "\n",
+    "See the ```photutils``` documentation [here](https://photutils.readthedocs.io/en/stable/aperture.html) on aperture photometry. **Read up on the documentation and try it out yourself.**\n",
     "\n",
     "To get started quickly you can ignore some of these sections in the documentation: sky apertures, pixel masking, aperture masks, aperture photometry using Sky Coordinates. \n",
     "\n",
@@ -251,7 +253,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Play with the various input parameters to the photometric extraction funtion until you get the two catalogs to match as well as you can. One key parameter you can change is the aperture radius, especially if the background isn't sufficiently subtracted. What radius did you have to choose to match the two catalogs? "
+    "Play with the various input parameters to the photometric extraction funtion until you get the two catalogs to match as well as you can. One key parameter you can change is the aperture radius, which can make a difference especially if the background isn't sufficiently subtracted. What radius did you have to choose to match the two catalogs? "
    ]
   },
   {
@@ -299,7 +301,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Using that equation create an error map for the whole data array and pass that into the ```aperture_photometry``` function so that you can get an estimate of the flux error on each star. "
+    "Using that equation to create an error map for the whole data array and pass that into the ```aperture_photometry``` function so that you can get an estimate of the flux error on each star. "
    ]
   },
   {
@@ -385,7 +387,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Use the website [sky-map](http://www.sky-map.org/) to determine the magnitudes of the same 4 stars that you used for the image-scale calculation in the previous lab. Make a table below that shows the star number from the Figure in Lab 3, its magnitude from *sky-map*, and (by matching $\\{x,y\\}$ coordinates) the magnitude that you calculated with ```photutils```. Calculate the average difference between your magnitudes and those from *sky-map*, and the standard deviation of this difference:"
+    "Use the [Aladin Lite](https://aladin.cds.unistra.fr/AladinLite/) online tool to determine the magnitudes of the same 4 stars that you used for the image-scale calculation in the previous lab. Find your stars in Aladin, and then use the \"SIMBAD\" catalog (the little box on the right-hand side) to find the magnitude of your targets. You'll have to pick the appropriate filter (either the same one as the data, or not that covers similar wavelengths). Make a table below that shows the star number from the Figure in Lab 3, its magnitude from *Aladin*, and (by matching $\\{x,y\\}$ coordinates) the magnitude that you calculated with ```photutils```. Calculate the average difference between your magnitudes and those from *Aladin*, and the standard deviation of this difference:"
    ]
   },
   {
@@ -401,7 +403,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Star| sky-map Mag | ```photutils``` Mag | difference \n",
+    "Star| Aladin Mag | ```photutils``` Mag | difference \n",
     "---|---|---|---\n",
     "1 |---|---|---\n",
     "2 |---|---|---\n",
@@ -420,7 +422,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "**Write an expression for magnitudes in the *sky-map* system (assumed here to be the true on-sky magnitudes) in terms of your derived magnitudes.**  This expression will convert your measured magnitudes  (based on image counts) into on-sky magnitudes. "
+    "**Write an expression for magnitudes in the *Aladin/SIMBAD* catalog (assumed here to be the true on-sky magnitudes) in terms of your derived magnitudes.**  This expression will convert your measured magnitudes (based on image counts) into on-sky magnitudes. "
    ]
   },
   {
@@ -432,7 +434,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Assume the brightest of the stars in your list of 4 has an **absolute** magnitude of 2.75.  What is its distance (in parsecs) based on its apparent magnitude? What uncertainty do you assign to this distance estimate, given only the uncertainty that you just calculated in estimating *sky-map* magnitudes from the magnitudes you calculated? Justify your answers."
+    "Assume the brightest of the stars in your list of 4 has an **absolute** magnitude of 2.75.  What is its distance (in parsecs) based on its apparent magnitude? What uncertainty do you assign to this distance estimate, given only the uncertainty that you just calculated in estimating *Aladin* magnitudes from the magnitudes you calculated? Justify your answers."
    ]
   },
   {

Lab_5/Lab_5.ipynb

@@ -4,14 +4,14 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# <p style=\"text-align: center;\">PHYS 134L Spring 2022 Lab 5</p>"
+    "# <p style=\"text-align: center;\">PHYS 134L Spring 2024 Lab 5</p>"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "<div class=\"alert alert-block alert-danger\"><b>Due date:</b> Sunday, May 8th, 2022 by 11:59pm, submitted through Gradescope.</div>"
+    "<div class=\"alert alert-block alert-danger\"><b>Due date:</b> Sunday, May 12th, 2024 by 11:59pm, submitted through Gradescope.</div>"
    ]
   },
   {
@@ -47,7 +47,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "The first part of this lab will be an introduction to spectra.  Astronomical data comes in two basic forms: images and spectra.  You have already seen images.  Spectra are a bit different: we lose at least some of our ability to resolve an object and see its shape, but we spread out its light into its colors, or wavelengths.  The intro slides to this lab included a spectrum as it appears on a detector.  It is a colored spectrum of the Sun, showing many black parts where there is less light.  These are absorption lines and give a whole lot of information about the physics of the Sun. \n",
+    "The first part of this lab will be an introduction to spectra.  Astronomical data typically comes in two basic forms: images and spectra.  You have already seen images.  Spectra are a bit different: we lose at least some of our ability to resolve an object and see its shape, but we spread out its light into its wavelengths.  The intro slides to this lab included a spectrum as it appears on a detector.  It is a colored spectrum of the Sun, showing many black parts where there is less light.  These are absorption lines and give a whole lot of information about the physics of the Sun. \n",
     "\n",
     "Just like Source Extractor takes the images and extracts the positions and brightnesses of stars, we can extract the flux of a star as a function of wavelength.  "
    ]
@@ -343,7 +343,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Now you can image that only using images of a star in two filters, we can learn a lot about its fundamental properties! "
+    "Now you can imagine that only using images of a star in two filters, we can learn a lot about its fundamental properties! "
    ]
   },
   {

Lab_6/Lab_6.ipynb

@@ -51,7 +51,7 @@
    "source": [
     "For a quick introduction to (or refresher on) many of the basic notions, see [here](http://www.tim-thompson.com/hr.html). \n",
     "\n",
-    "For a more quantitative picture of stellar evolution, consider the files ```evol_M0.8.dat```, ```evol_M1.0.dat```, ```evol_M1.3.dat```,```evol_M1.8.dat```, and ```evol_M2.6.dat. These contain evolutionary tracks for stars with compositions similar to the Sun's and with masses of 0.8, 1.0, 1.3, 1.8, and 2.5 times the mass of the\n",
+    "For a more quantitative picture of stellar evolution, consider the files ```evol_M0.8.dat```, ```evol_M1.0.dat```, ```evol_M1.3.dat```,```evol_M1.8.dat```, and ```evol_M2.6.dat```. These contain evolutionary tracks for stars with compositions similar to the Sun's and with masses of 0.8, 1.0, 1.3, 1.8, and 2.5 times the mass of the\n",
     "Sun. The columns of the tables contain $\\log_{10}(Temperature~(K))$, $\\log_{10}(Luminosity~(solar~units)$), and Age (in Gyr). Notice (by opening one of the files in a text editor) that the range of ages in the various tables is fairly wide -- massive stars live for much shorter times than low-mass ones, though they are much more luminous.  They burn brightly but burn out quickly."
    ]
   },