Astronomy 142 — Project Manual Spring 2021
1 RR Lyrae stars and the distance to globular cluster M3 1.1 Introduction In the following, we repeat a classic experiment: detect the periodically-varying stars in a globular cluster and thereby measure its distance, by considering the stars to be standard candles. Specifi- cally, we will measure the time-average luminosity of the nearby star RR Lyrae and the time-average flux of stars in M3 that vary with the same period as RR Lyr, combining these measurements to determine M3’s distance.
This observing project will involve frequent remote observation sessions with the tele- scope over the course of 1–2 weeks, hopefully including a few nights in a row. Everyone who opts for this project will share their data and receive everyone else’s in return. Each student will perform his or her own analysis and write an independent report on the results. Stars in the instability strip of the HR diagram have been fundamental in the determination of the distance scale of the Universe. These stars radially pulsate, often in their fundamental acoustic mode. As we have seen in class, their pulsation periods Π vary inversely with the mass density ρ of the star: Z R dr r 6π Π = 4 =∼ (uniform density star) (1) 0 vs γGρ Lower average density leads not only to longer periods, but also to larger luminosities L, in part because lower-density stars are much larger than higher-density stars of the same mass. Thus, a given type of pulsating star exhibits a strict relation, often linear, between Π and L. Such relations can be determined by observation of the periods and fluxes for stars whose distances are accurately known, for example, by trig. parallax. Once the Π–L relation is determined, it can be used as a standard candle to measure much greater distances to faint stars of the same type and period. The measured period Π tells us what the star’s luminosity is, and the measurement of the star’s flux f yields the distance r, s L r = (2) 4πf Henrietta Leavitt invented standard candles in the course of her observations, during 1908–12, of thousands of periodic variables in the Magellanic Clouds. Her variables are classical Cepheids, the highest-luminosity Population I inhabitants of the instability strip; the Π-L relation for classical Cepheids is called Leavitt’s Law in her honor. The instability-strip variables in globular clusters include supergiants, giants, and stars close to the Main Sequence: W Vir stars, RR Lyr stars, and SX Phe stars, respectively. RR Lyr stars are by far the most numerous. Few of these stars lie in the solar neighborhood; it has been possible to measure trig parallax for only a handful of RR Lyr stars.1 One of these is RR Lyrae itself, for which such variability was discovered by Williamina Flemming in 1901. Taking RR Lyrae to be a standard candle, we can measure accurate distances to globular clusters, the distribution of which is a good tracer of the global structure of the Milky Way.
1The ESA Gaia mission will provide parallaxes for many more field RR Lyr stars. It will not, however, be able to measure parallax for stars in many globular clusters; the RR Lyr standard-candle technique used in this project will remain the best way to measure globular-cluster distances for a long time.
1 1.2 Experimental procedure 1.2.1 Planning 1. As a stretch of clear weather approaches, choose your observing night. Look up or calculate the times of sunset and sunrise, and the length of the night. Also look up or calculate the times during which M3 and RR Lyrae will be high enough in the sky to observe (> 20◦ elevation), and the times at which each object transits. 2. Unlike the observing project in ASTR 111, this one takes all night. Plan accordingly by packing for an overnight stay in B&L, including the all-important requirement of packing sufficient food. 3. Bring your notebooks, and you would do well to also bring your personal laptop or tablet computer. Paper copies of the telescope checklist and CCD-camera observing guide will also prove useful, though these will also be accessible to you online. 4. Arrive around sunset. The telescope and camera must be ready to observe, and your team must be ready to work, no later than sunset.
1.2.2 Remote observing One team member should be stations at the workstation in B&L 203H at all times throughout the night. Be sure to rotation the team members through this position frequently so that no one gets bored.
1. Start the telescope and initialize its pointing by following the steps in Section I of the Mees Observatory remote-observing checklist. This leaves you with TCSGalil, TheSkyX, and Firefox running on the TCS computer.
2. Start the CCD camera, and focus the telescope by following the steps in Section I of the remote-observing checklist. Both the camera and telescope should now be ready to observe.
3. On TheSkyX, search for M3 (Cntl-F for the search window), click on it to bring up its information window, and check to see if it is above the telescope’s artificial horizon (elevation > 20◦). If so, you are ready to start observing!
4. As a guide star, we recommend a 12.5 magnitude star which is known to TheSkyX as GSC 2004:639. Find it by bringing up the search window (Cntl-F) in TheSkyX and entering its name. Follow the steps in Step 16 of Section I in the remote-observing checklist to commence autoguiding. 5. As in Section III, Step 3 of the Mees Observatory CCD camera checklist: set up for G and B observations of M3:
LRGB Exposure length – – 5 min 5 min Binning – – 1x1 1x1 Number of exposures – – 1 2
This three-image, approximately 15-minute sequence will be repeated over and over throughout the experiment.
6. Observe M3 continuously until RR Lyrae rises into view (around 1:15am ET). On Camera > Take Series, set Repeat: accordingly (e.g. repeat 8 times for two hours). Then push the Take Series button.
2 7. Relax for awhile. Watch the imaging results attentively for the first cycle to make sure the autoguiding remains stable through the filter changes. After that, check every several minutes to make sure that the guide star is staying in the middle of the box. And check on TheSkyX now and then toward the end of this segment, to see when RR Lyrae will become available. RR Lyrae is known to TheSkyX as SAO 48421.
8. As soon as RR Lyrae is viewable, let the current M3 GB cycle finish — pushing Abort after the second B if necessary. Back on Autoguider, push Abort to turn off the autoguider. Then point the telescope at RR Lyrae = SAO 48421. On Camera > Take Series, click the AutoSave button and change to the appropriate file name prefix. (Do not reset the starting number. TheSkyX does not ask permission before overwriting files!) On Camera > Take Photo, take a 2-second image with the L-filter to make sure that the star is reasonably close to the center of the CCD; move it and take another image if necessary.
9. Observe RR Lyrae. The parameters in Camera > Take Series should be the same as before except for exposure time:
LRGB Exposure length –– 2 sec 2 sec Binning – – 1x1 1x1 Number of exposures – – 1 2
Set Repeat: to 8 and push the Take Series button. This will be done in a few seconds; there is no need to autoguide. 10. From now until dawn, alternate between three-frame, 15-minute M3 sequences as in Step 5 and bursts of short images of RR Lyrae as in Step 9. Do not forget to keep changing the file name prefix as you do! 11. When the Sun comes up, shut down the telescope and CCD camera by following the steps in Section II of the remote-observing checklist. 12. Go home and get some sleep.
1.3 Data reduction Each team will carry out the first stages of processing on their data before we merge data from all the teams. These stages will include calibration of your M3 and RR Lyrae data: bias and dark subtraction and bad-pixel correction. This work breaks into two roughly equal size parts, one for each filter. Make sure your team divides the data reduction workload equally among the members. Set aside a few hours for your team to meet on Zoom and remotely log into your team’s account on the workstation in B&L. Find the directory on this computer’s desktop in which the Master Dark and Bias frames are kept. Then:
1. Start CCDStack, using the icon in the Windows taskbar.
2. Open all of the G images of M3, using File > Open and navigating to your working directory where all of your files live. This will present you with the full stack of these images, which you can page through and examine with the tools on the left side of the window.
3. Calibrate these images. Choosing Process > Calibrate evokes the Calibration Manager dialog. Using the two tabs and three buttons, specify the master dark frame and bias frame appropriate to CCD temperature (-20◦C) and binning (1×1). Leave the flat field frame blank. Then click Apply to All.
3 4. Next, remove hot pixels: those with (permanently) high and variable dark current that does not subtract out in calibration. Choose Process > Data Reject > Procedures. In the re- sulting dialog choose reject hot pixels from the dropdown menu, specify a strength of 50, check clear before apply, then click Apply to All. Then choose interpolate rejected pixels from the dropdown menu, and again click Apply to All. 5. Then cold pixels: also with permanent dark-current problems, if not completely dead. Repeat Step 6, substituting cold for hot in the first dialog. 6. Align all of these images so the stars are in precisely the same places. First, page through the images until the one taken when M3 was closest to transit is on top. Choose Stack > Register, which brings up the Registration dialog. 7. On the Star Snap tab, click remove all reference stars, then select/remove reference stars. Double-click to select 6–8 stars which do not have any particularly close neighbors, are not close to the edge of the image, do not include extremely bright looking stars, and are spread uniformly around the cluster. Page through the stack of images to see how close to being in alignment they already are. Drag any misaligned ones into closer alignment. Then click align all to shift the frames into rough alignment. 8. Switch to the Apply tab, choose Bicubic B-Spline from the dropdown box, and click Apply to All to shift the frames very accurately into alignment. Page through the images to make sure it worked. It should now be difficult to tell when you page from one image to the next. 9. Adjust all the images to remove atmospheric extinction. Again, page through the images until the one taken when M3 was closest to transit is on top. Choose Stack > Normalize > Control > Both. In response to the subsequent instructions, drag a rectangle well off the cluster’s center to represent background, and click OK. Then drag a rectangle encompassing the densest part of the cluster to represent the highlights, again clicking OK. 10. Now that the stack of images is registered and normalized, it can be corrected for cosmic- ray hits and satellite trails. Choose Stack > Data Reject > Procedures. In the resulting dialog pick STD sigma reject from the dropdown box, specify a factor of 2.2 (sigma) and an iteration limit of 8, and click Apply to All. Then select interpolate rejected pixels from the dropdown menu, and again click Apply to All. 11. Choose File > Save > All. In the File name box of the resulting dialog, enter a suffix indicating the degree of processing the images have had, e.g. CalRegNormFix. Set the file format to FITS. Then click Save. 12. The Red images are now tidied up; choose File > Remove all images - Clear. 13. Repeat Steps 2–12 for the B images of M3, except: do not clear the stack at the end of the image reduction. 14. Only if you are the first group analyzing the data, use the stack of B images in a quick search for variable stars. Page to the first M3 image of the night, then use the Navigate Back and Navigate Forward buttons to toggle between the first and last blue images. How many stars can you find that substantially changed brightness between the beginning and end of the night? Keep a list of their pixel coordinates, noting that what is under the cursor is displayed at bottom right of the CCDStack window. Repeat this with image pairs separated by different time intervals, such as beginning/halfway and halfway/end. Note that the Blink button results in continuously and automatically paging through the contents of the stack with approximately half-second intervals between images. 15. Now clear the stack and repeat this procedure on the RR Lyrae images, with two differences: (a) Do not normalize the images to correct for atmospheric extinction (Step 11), and do not fix cosmic ray hits (Step 12) just yet.
4 (b) Instead, save the stack after registration, with file name suffix CalReg, and clear the stack. Then open, one at a time, each series of eight consecutive two-second exposures. As in Step 10, choose Stack > Data Reject > Procedures, pick STD sigma reject with a factor of 2.2 (sigma) and an iteration limit of 8, and click Apply to All. Then select interpolate rejected pixels from the dropdown menu, and again click Apply to All. Save the series with the suffix Fix. Choose Stack > Combine > Mean to produce an average of the series. Save this new image as a FITS file, accepting CCDStack’s suggested prefix of Mean. Then clear the stack and proceed to the next series. (c) After processing all the individual series, clear the stack and load all of the blue RR Lyrae Mean images. Put them on Blink, and note that the brightness of RR Lyrae changes by quite a bit from the beginning to the end, while the rest of the stars in the field change by much less. Thus, RR Lyrae varies like many of the variables in M3. The small changes in the rest of the stars turn out to be the systematic effect of atmospheric transmission; this was taken out of the M3 data in the Normalize step, but in the case of RR Lyrae, which is the brightest object in a frame with few stars, normalization has to be done more carefully, in the next set of tasks.
1.4 Analysis Next you will measure the fluxes of the M3 variable stars and of RR Lyrae as functions of time through your observing night. Using these data, you will measure the distance to M3.
1. Only if you are the first group analyzing the data, open one of the blue M3 frames in SAOImageDS9. Find the best scaling for the image by adjusting the settings in the Scale drop-down menu (ASINH at 99.5% is a good place to start). Select Region from the Edit menu and click on the image to draw a circle region around each of your identified variable stars. To change the location and size of the drawn region, double-click on the region. In the resulting pop-up window, specify the center position and radius of the region, and label the star with a number in the Text block. Save this annotated image as a EPS file (File > Save Image > EPS) and send it to Prof. Douglass so that it can be uploaded to Blackboard for reference.
2. Run IDL using the icon in the Windows taskbar. Then type ATV
5 7. In the aperture photometry window, click Write results to file... and enter a file name in which to store star fluxes. It will be useful to have the observation date and time as all or part of the file name. While this file is open, a click on a star will write its centroid position, flux (as “counts”), and FWHM diameter in pixels. 8. Click on each of the variable stars in this image. Note any cases in which the radial profile indicates that nearby stars are influencing the measurement of the variable. Throw the star off the list and choose a different one if there is not a good way to exclude too-bright stars from the sky annulus. When you are finished, click Close photometry file. 9. Repeat Steps 3-8 for each of the G images of M3 you acquired.
10. Repeat Steps 3-8 for each of the Mean G images of RR Lyrae you acquired. In this case there is only one variable star, RR Lyrae itself, but click the next four brightest stars as well to enable the correction for atmospheric extinction that we postponed from Data Reduction, Step 17. 11. From the information in your photometry files, fill in the class’s Google spreadsheet which lists the flux, in Counts, as a function of time for each of the M3 variables.
12. After other groups have added their data to the spreadsheet, download the file (or copy the data into your own spreadsheet). Use this to calculate the average and standard deviation for the flux of each variable star, and to plot the flux vs time — i.e. the light curve — for each of the variables. Traditionally, these plots use the Day as the unit of time. Have these plots and the table of averages available for use in your lab report.
13. Repeat Steps 11 and 12 for your RR Lyrae data, with one difference. For each image, calculate the ratio of fluxes for the non-RR Lyrae stars to the fluxes these stars have in the image taken closest to transit. Average these ratios for each image. Then create new columns containing stellar fluxes divided by the average ratio for their images. Use these new columns to calculate RR Lyrae’s average flux and standard deviation, and plot the light curve for RR Lyrae. Again, have these data available for use in your lab report.
14. Discuss the light curves for M3’s variables and RR Lyrae. Which M3 light curves resemble RR Lyrae’s most closely? Are there light curves in which you see clear minima and maxima? Are there light curves in which you see two maxima or minima, and can thereby measure the pulsation period?
15. Assume that RR Lyrae and the M3 variables with similar light curves all have the same luminosity. The distance to RR Lyrae has been measured by trig parallax; it is r = 270±20 pc (Gaia Collaboration 2016). So what is the distance to M3, and what is the uncertainty in this distance? Use the average fluxes and uncertainties obtained in Steps 11 and 12 in this determination.
16. Before Gaia, the largest stellar distance we knew from trig parallax was about 500 pc. By what factor is the distance to M3 larger than this?
1.5 Lab reports Each student must write their own report, in which they explain the purpose, methods, and outcomes of the observations, and answer all of the questions raised in the sections above. We offer a sample lab report on Blackboard, to give an idea of the length and level of detail expected.
6 2 The Messier Marathon 2.1 Introduction The first interesting catalog of non-stellar objects that do not belong to the Solar system was that compiled by Charles Messier in the late eighteenth century. In the era of Messier’s activity, solar- system astronomy seemed the most exciting frontier, exemplified by Herschel’s (1781) discovery of Uranus and the realization that the orbital anomalies of the new planet could be explained most easily by another planet, or planets, further away. Within this rubric was the study of minor solar system bodies, which in those days meant comets, as asteroids were not discovered until 1801. Messier was a hunter of comets. In his hunt, he and his assistant Pierre M´echain also discovered many fuzzy, extended objects that could be mistaken for comets at a glance, but which seemed not to move with respect to the fixed stars. Messier published this list (1781) as a warning to fellow comet- hunters. Originally containing 103 objects2, the catalog expanded slightly during the 20th century as astronomers, notably Camille Flammarion and Helen Sawyer Hogg, re-read additional notes and descriptions of observations kept by Messier and M´echain. There are now officially 110 Messier objects. The catalog includes most of the brightest examples of stellar clusters, gaseous nebulae, and galaxies visible from the northern hemisphere. Very influential in its day, the M catalog spawned many more collections of extended celestial objects, starting with the General Catalogue of Nebulae and Clusters of Stars (GC; 1864), the New General Catalogue (NGC; 1888), and its appendices the Index Catalogues (IC; 1896, 1905), compiled by John Herschel and John Dreyer, from observations by William, Caroline and John Herschel. Professional and amateur astronomers alike remain fascinated by the wide variety of astrophysical processes which can be studied in detail in the Messier objects. The Messier catalog has two features that many find particularly interesting. First, there are two brief intervals each year in which every object in the catalog could in principle be observed between sunset and sunrise. Second, the number of objects is sufficiently small that a good observer can point a telescope at each object during the course of one clear dark night, but sufficiently large to make it a challenge. This observing program — all, or at least nearly all, the M objects in a single night — is called the Messier Marathon. The Marathon is very popular among amateur astronomers. The longer of the two Messier-catalog visibility windows lies in the last couple of weeks of March and the first couple of weeks of April, and thus falls within the prime ASTR 142 observing season. In this experiment, we will run the Messier Marathon, recording CCD images of the M objects, or at least their centers.3
2.2 Experimental procedure 2.2.1 Planning your Messier Marathon There are 110 objects in the catalog and less than 12 hours of darkness in which to observe them, so each object needs to be acquired and imaged in less than six and a half minutes. Thus no one succeeds at the Messier Marathon without carefully planning the sequence of observations. It is not possible to simply go through the list in right-ascension or catalog-number order. Instead, you need to take account of the times at which objects set and rise, noting the constraints imposed by the
2Some of the objects were known to be non-stellar and non-planetary for a long time before Messier. For example, of the first 45 catalog objects he published, the last four are naked-eye nebulosities known to the ancients, which Messier added for completeness: the middle “star” of Orion’s sword (M42 and M43), the Beehive Cluster in Cancer (M44) and the Pleiades in Taurus (M45). The Andromeda Nebula (M31), also visible to the naked eye, was known at least 800 years before Messier’s time. Several other M objects were discovered within the generation or two before Messier: for instance, the Great Hercules Cluster (M13), which is barely visible to the naked eye under perfect conditions, was described by Halley, and the Crab Nebula (M1) by Bevis, early in the 1700s. But Messier was the first to collect these scattered observations, add many other examples systematically, and publish the results, so his work had more impact than that of his predecessors. 3Serious amateur astronomers usually consider the use of computer-controlled telescopes to be against the rules of the Messier Marathon. Beware of thinking that completion of this project entitles you to stand in the august company of those who have done it with Dobsonians pointed by hand; they will consider you a cheater. On the other hand, most of them do not record images of the targets while they are running the Marathon, and you will.
7 southernmost objects that are not above the horizon for very long, and use the flexibility of the long observing windows for the northernmost objects. During the past few weeks of Learn Your Way Around The Sky lessons in recitation, you have learned everything you need to know to calculate the rising and setting times of each object and the Sun, to the required, better-than-a-few-minutes accuracy. First, there is the relation between zenith angle ZA and hour angle HA, in terms of an object’s declination δ and the observer’s latitude λ:
ZA = cos−1 (cos HA cos δ cos λ + sin δ sin λ) (3) which you derived in Recitation 5. Then there is local sidereal time, ST , which depends upon the observer’s longitude L, time t (in UT) since the Vernal equinox (at t1), longitude L1 at which it was noon at the Vernal equinox, and Earth’s orbital parameters, including the sidereal rotation period P⊕, the length of the day, the semimajor axis length a, eccentricity ε, and ecliptic obliquity Ψ. In Recitations 4, 6, and 8, you derived the components of sidereal time, which expressed in sidereal days is 1 1 1 t − t1 ST = (t − t1) − + [L − L1 + ∆θε(t) + ∆θ0(t)] + mod , 1 (4) P⊕ day 2π day where by mod(x, 1) we mean the part of x in excess of the largest integer smaller than x, or in this case time of day on a 24-hour clock, with the integer number of previous days subtracted off, and where ∆ω 1 − cos ψ ∆θ (t) = 0 sin ω(t − t ) ∆θ (t) = sin 2ω(t − t ) (5) ε ω 0 0 2 1 Here ω is the angular frequency of the mean Sun, ∆ω0 is the difference in Solar angular frequency between perihelion and aphelion, t0 is the time of perihelion, and ψ is the obliquity of the ecliptic. Finally, there is the celestial position of the Sun, for which you obtained the declination in Recitation 9, and for which the right ascension is only slightly different from sidereal time: 1 1 α = mod 2π(t − t1) − + ∆θε(t) + ∆θ0(t), 2π P⊕ day
δ = −ψ cos [ω(t − t2) − ∆θε(t) − ∆θ0(t)]
Here the results would be in radians, t2 is the time of the last winter equinox, and (mod x, 2π) again means that the largest integer multiple of 2π is subtracted off, that can still leave a positive result. “All” that needed to be done, then, to obtain the rising and setting times of each Messier object and the Sun for any arbitrary night of the year, is to solve for the times t on that night which satisfy
cos ZAmax = cos (ST (t, L) − α) cos δ cos λ + sin δ sin λ (6) for each target’s α and δ. Then take the rising and setting times and arrange the order of obser- vation, such that the average pace of the observations — say, one every five or six minutes — can accommodate observation of each object after it rises and before it sets. In Figure 1, the results of such a calculation are rearranged into one practical realization of the Messier Marathon. Fortunately, you will not have to go to this much trouble. The popularity of Messier Marathons among amateur astronomers has led to the presence online of several Messier Marathon planners which can be customized for any observing date: just google “Messier Marathon planner.” But you do know how to do the calculations which these planners do, and you could do them if you wanted to. We will not ask for them in this project, because they involve the use of numerical root-finding routines which are not easily implemented. With all this in mind, here is the pre-observing procedure to be followed: 1. As you will see, there is very little down time for anyone on the observing team during the course of this project. There are three tasks that must be performed constantly through the night, and we presume that team members will rotate periodically so that everybody gets to enjoy each different task.
8 Figure 1: Rising and setting times for the Messier objects, organized in a sequence to aid in deter- mining the order of observations during the Messier Marathon.
9 2. Download the Messier catalog, available as either .txt or .csv file on Blackboard.
3. Calculate the amount of time each object is above the effective horizon, 2HA(ZAmax). Identify the objects which never get above the horizon and should therefore be left out of the observing list. Identify circumpolar objects and prepare to keep them handy: you must always be observing something, and these may serve if you would otherwise have to wait for an object to rise. (Please remember: The telescope at Mees cannot be slewed to a position below the North Star! Just because an object is circumpolar does NOT mean that you can observe it at any point during the night.) 4. Look up or calculate the times of sunset and sunrise, and the length of the night, for your observing night. 5. Refine your observing list by identifying the objects which rise too late or set too soon. De- termine your time budget: the number of seconds available for each object on the average. By consulting online Messier Marathon plans and Figure 1, determine the order in which the list should be observed. Make a spreadsheet list of targets and times at which you should begin observing each target. Hint: Note the position of M68 in Figure 1. Consider how this, and other objects with very narrow windows of observability, constrain the schedule. 6. Plan to take at least 2 minutes of imaging data per object with the L filter. The imaging should be in the form of a short exposure (20–30 sec) followed by centering if necessary, and either a longer exposure or a series of short ones. For faint objects (e.g. most galaxies) in a dark sky, it would be best to take one long exposure; for bright objects (e.g. M42) or bright sky conditions (twilight or moonlight) it works better to take a stack of short exposures and average them afterwards. 7. Learn enough about the Messier objects to know which are unlikely to have their interesting parts fit in the 15.4 arcminute wide camera field. Flag these objects on your observing plan spreadsheet. For these targets, you will record images of the center with the camera but will supplement these images with descriptions of the view through the finder telescope or the image-stabilized binoculars. 8. Present your list, with calculations and order appropriate for the observing night, to Prof. Douglass for review. No group gets to observe without presenting a blow-by-blow plan in advance. 9. Unlike the observing projects in ASTR 111, this one takes all night. Plan accordingly by packing for an overnight stay in B&L, and remember the all-important requirement of packing sufficient food. 10. Bring your notebooks, and you would do well to also bring your personal laptop or tablet computer. Paper copies of the remote-observing checklist and CCD-camera observing guide will also prove useful, though these will also be accessible to you online at Mees. 11. Arrive at least 45 minutes before sunset. The telescope and camera must be ready to go, and all team members must be at their stations, before the sun goes down.
2.2.2 Observations Two team members should be stationed at two specific jobs: telescope and CCD camera operator and scribe: • The Scribe orders the observations, enforces the schedule, and maintains a spreadsheet in which they record the correspondence between file name and object being observed, exposure times, etc. The scribe is also in charge of quality control: making sure that the images are not saturated, and making sure that the target is centered properly, etc.; calculates the necessary offsets to center the targets.
10 • The telescope and camera operator moves the telescope to acquire the targets; offsets the telescope at the request of the scribe, in the process of centering targets, using TCSGalil Telescope > Movement > Offset; and looks for opportunities to sync the telescope coordi- nates whenever a star happens to be centered in the camera, thus to keep the pointing sharp. Rotate the team members among the jobs at least once an hour. Here is the recipe that should be followed: 1. Start the telescope and initialize its pointing by following the steps in Section I of the Mees Ob- servatory remote-observing checklist. This leaves you with TCSGalil, Firefox, and TheSkyX running on the TCS computer.
2. Start the CCD camera and focus the telescope by following Step 15 in Section I of the remote- observing checklist. Notable differences from ordinary observations: (a) Note that you can find stars near the zenith, and sometimes even focus the telescope adequately, before sunset. Give it a try. (b) You will not have time to change the file name prefix for every object. Rely on a generic prefix and the serial numbers, and the spreadsheet maintained by the scribe, to keep your targets and data sorted. (c) No time, or need, to autoguide. (d) Because you will be using only one filter, but changing targets and exposure times so frequently, it will be more convenient to take data with TheSkyX’s Camera > Take Photo tools instead of the usual Camera > Take Series. Both the camera and telescope are now ready to observe and autosave the data. 3. Begin the Marathon. The scribe is in command, enforces the following of the plan, and maintains the spreadsheet of file names and targets. Illustrations of the routine:
Scribe Move to Mxx. Telescope We’re there. Scribe Looks like a galaxy nucleus in the 20 second image, please move us 5 minutes west and 3 minutes north. Telescope Done. Two-minute exposure in progress. By the way, the 20 second image was number 147 and the current one is 148. Scribe Duly noted. Get ready for Myy next. Telescope Image 148 done and ready for next. 4. Occasionally:
Telescope 20-second image number 230 already beautiful, brightest stars barely on scale. Can we do 16 20-second images? Scribe No time for that; make it 9 20-second images. Telescope Oh, all right. 230 through 239 in progress. 5. The non-routine: Whenever an object is not clearly seen in the camera quickly point to a nearby bright star, center it in the camera, and update the TCS telescope position, then point back to the target. You will have to learn how to do this in no more than a couple of minutes. 6. When all this is done, or when the Sun comes up — whichever is first, shut down the telescope by following the steps in Section II of the remote-observing checklist.
7. Go home and get some sleep.
11 2.3 Data reduction Now we calibrate your Messier Marathon images. Since the images differ only in target and inte- gration time, this task benefits greatly from CCDStack’s automation. Make sure your team divides the data-reduction workload equitably among the members. Set aside a few hours for your team to meet on Zoom and remotely log into your team’s account on the workstation in B&L. Find the directory on this computer’s desktop in which the Master Dark and Bias frames are kept. Then: 1. Start CCDStack, using the icon in the Windows taskbar.
2. Open all your Messier Marathon images using either File > Open... or File > Open Selected... and navigating to your working directory. This will present you with the full stack of these images, which you can page through and examine with the tools on the left side of the window.
3. Calibrate the images en masse. Choosing Process > Calibrate evokes the Calibration Manager dialog. Using the two tabs and three buttons, specify the master dark frame and bias frame appropriate to CCD temperature (-20◦C) and binning (1×1). Then click Apply to All. 4. Next, remove hot pixels: those with (permanently) high and variable dark current that does not subtract out in calibration. Choose Process > Data Reject > Procedures. In the re- sulting dialog choose reject hot pixels from the dropdown menu, specify a strength of 50, check clear before apply, then click Apply to All. Then choose interpolate rejected pixels from the dropdown menu, and again click Apply to All. 5. Then cold pixels: also with permanent dark-current problems, if not completely dead. Repeat Step 6, substituting cold for hot in the first dialog. 6. Choose File > Save > All. In the File Name box of the resulting dialog, enter a suffix indicating the degree of processing the images have had, e.g. Cal. Then click Save.
7. You are now done with the entire stack; choose File > Remove all images - Clear. 8. Now, using the scribe’s spreadsheet of observations, identify all multiple images of given ob- jects, such as those described in step 4 of Section 2.2.2.
(a) Use File > Open... to open the first set. (b) Align all of these images so that the stars are in precisely the same places. Choose Stack > Register, which brings up the Registration dialog. (c) On the Star Snap tab, click remove all reference stars, then select/remove reference stars. Double-click to select 6–8 stars which do not have any particularly close neigh- bors, are not close to the edge of the image, do not include extremely bright looking stars, and are spread uniformly around the cluster. Page through the stack of images to see how close to being in alignment they already are. Drag any misaligned ones into closer alignment. Then click Align All to shift the frames into rough alignment. (d) Switch to the Apply tab, choose Bicubic B-Spline from the dropdown box, and click Apply to All to shift the frames very accurately into alignment. Page through the images to make sure it worked. It should now be difficult to tell when you page from one image to the next. (e) Choose Stack > Normalize > Control > Both. In response to the subsequent instruc- tions, drag a rectangle well off of the cluster’s center to represent background, and click OK. Then drag a rectangle encompassing the densest part of the cluster to represent the highlights, again clicking OK.
12 (f) This registered, normalized stack of images can be corrected for cosmic-ray hits and satellite trails. Choose Stack > Data Reject > Procedures. In the resulting dialog pick STD sigma reject from the dropdown box, specify a factor of 2.2 (sigma) and an iteration limit of 8, and click Apply to All. Then select interpolate rejected pixels from the dropdown menu, and again click Apply to All. (g) Choose File > Save > All. In the File name box of the resulting dialog, enter a suffix indicating the degree of processing the images have had, e.g. RegNormFix. Then click Save. (h) Average the stack of images using Stack > Combine > Mean. Save this image as well (File > Save > This), using the first file name in the stack as a suffix, and Mean as a prefix. (i) Choose File > Remove all images { Clear. (j) Repeat steps a–i for each multiple observation. 9. Using File > Open Selected..., open all of the calibrated images (Cal suffix). 10. Page through the images and remove from the stack (Ctrl-R) all of the images which went into an average: those with suffix CalRegNormFix. 11. Using File > Open Selected... again, open all of the averages of the multiple images (Mean prefix. 12. Now comes the time consuming part. You now have as many as 110 images in the stack: your best try on each of the Messier objects you observed. Go through them one by one, and make each look as good as possible by use of the Adjust Display tools. By “good,” we should mean that the image stretch (Gamma and DDP parameters) is adjusted to show all details of the object from brightest to dimmest, that Maximum is chosen not to saturate too much of an image’s brightest parts, and that Background is chosen so that the image is black at levels below the dimmest detected part of the object: thus blotting out any sky background, but none of the stars brighter than that. 13. When you are done beautifying the images, save them all in scaled form: File > Save > All, with JPEG as the Save as Type. Leave copies of all images in the working directory you created on the observing computer.
2.4 Analysis As your main result, you have digital images of the vast majority of the Messier objects. 1. Make a master table of final images and object descriptions, with the objects listed in the order you actually observed them. Include in the descriptions a classification of each object made in accordance with its appearance. For each galaxy, this should include your estimate of the Hubble type as is consistent with the image you took. 2. Make an additional cross-reference table in which the objects are sorted according to their classification: open cluster, globular cluster, planetary nebula, Hii region/reflection nebula, supernova remnant, elliptical galaxy, spiral galaxy. Comment on the ranges of brightness and angular size observed under each of these classes. 3. Pay particular attention to the identification and classification of three objects: M40, M73, and M102.
2.5 Lab reports Each student must write their own report, in which they explain the purpose, methods, and outcomes of the observations, and your complete set of images, object descriptions, and cross references. We offer a sample lab report on Blackboard, to give an idea of the length and level of detail expected.
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