Stellar Spectra – Voyages

Stellar Spectra: Comparing Curves

NGSS connections

Supports PE HS-ESS1-2 and HS-ESS1-3 : Earth’s Place in the Universe

Engages in SEP 4: Analyzing and interpreting data

Engages in CCC 1: Patterns: Elements emit and absorb characteristic frequencies/wavelengths of light

When people encounter something new, one of the first things they do to build understanding is to look for differences and patterns. Whether it is for rocks, people, animals, or stars, humans love to use what we observe to divide things into groups. And we are good at it, too! Nothing else compares to the human brain as a pattern-making machine. Millennia ago people first looked up and created patterns of stars they called constellations. Still today, each time we invent a new technology to aid in our observations, we expand our time-tested ability to look for patterns and group objects.

In the case of stars, the spectrograph was the break-through invention that allowed astronomers to understand the differences between stars and develop hypotheses about their structure, lives, and distribution in the Milky Way. Although it is possible to study some individual stars in distant galaxies, all of the stars you will encounter in this activity are inside our own galaxy, the Milky Way.

Spectra are the primary product of the SDSS spectrograph. Although there are dozens of different measurements that can be taken from a single spectrum, we will begin our exploration by looking for patterns in the overall shape of the spectrum. If you are curious about the details of the features you see, there will be numerous resources available along the way for you to consult. Let’s begin.

Introducing the SDSS Science Archive Server

If you want to look at a lot of spectra at one time, the easiest place to encounter them is through the Science Archive Server (SAS). SAS is the latest image and spectrum service for the SDSS. But before you can use SAS, you need a starting place. Choose one of the paths below. If you already have a Special Place in the Database, great. Start there. If you don’t, choose one from the SDSS Constellations Notebook. Record the RA and Dec of your starting location.

I have a starting place

Use constellations notebook

When you arrive at a SAS Spectra List page, bookmark the location. Next, notice that each row represents a different object that was captured by the spectrograph. The Survey, Plate ID, and MJD columns are identical. This set of data was gathered under the same observing goals (Survey) using the same spectroscopic plate (Plate) on the same day (MJD). It isn’t until you get to the fourth column (Fiber #) that the information becomes unique. Scroll down and notice that there are either 640 or 1000 objects in the list depending upon the survey. Observe that you can reorder the column by clicking the up-down arrows on the column heading.

Explore SAS

Remember, our goal is to look for patterns in the overall shape of stellar spectra. We have a lot of spectra to observe from our starting point in SAS. The SDSS divides all objects in the database into one of three classes: star, galaxy, or QSO (quasar). This classification is reported in the Class column.

DO: Click the up-down arrows for the Class column twice so that all objects that are stars sort to the top of the page.

For this investigation, it is useful to observe graphs that are not extremely jagged. To do this, we use spectra with a high signal to noise ratio, r(S/N)2. You can learn more about this measurement in the Launch activity, Signal to Noise. For now, let’s observe the difference between low and high signal to noise measurements.

Choose two stellar spectra that have very different S/N ratios to observe.
Click the plot link in the Plot Spectrum Column.
Click the plot link in the Plot Spectrum Column.

Choosing Spectra

For this activity, we need spectra of stars, AND it would be helpful to have spectra that have a high signal-to-noise ratio. We can sort the list to show just the spectra we want using the empty boxes at the top of each column.

Type >10 in the blank box at the top of the signal-to-noise ratio column.
Type STAR in the box at the top of the Class column.
The column automatically sorts to match the commands you insert.

Observe and Sort

Using the Plot link in the Plot Spectrum column, open 10 – 20 spectra. For this first step concentrate on the graph itself. Focus on all of the parts as you understand them from Preflight Training. Look at the shape, features, and intensity. Try to group your spectra. There are many ways that you can compare one spectrum to another:

Each spectrum opens in a new tab. Drag to reorder the spectra so that similar spectra are located next to one another.
Print each spectrum and sort.
Screen capture each spectrum as an image. Images can be inserted into a document and dragged around to form groups.

Look for Patterns

Now it’s time to go beyond Preflight Training. You have grouped your objects in some way based upon real physical features of the spectra. With your sorting in mind, look at what other information is available about your object on the spectrum plot page. This is actual data that scientists use. If you find it a bit scary, start with the picture of the star. Can you find any patterns?

If you want to consider additional information from the Spectrum Plot pages, check out the SAS Help pages.