Astro RPS

The main goal this week is to get familiar with importing (and using) three really useful packages: numpy, astropy and matplotlib. Throughout the assignment we will also write some for-loops and practice logic statements This assignment is meant to be done in groups of 2-3 people.

Part 1: Loading in the SubHalo Merger Tree Data (10 - 15 minutes)¶

All galaxies live inside large accumulations of dark matter. These accumulations can be thought of as clouds or “halos”. A “merger tree” is a way of understanding the accretion history of a dark matter host halo. The trunk represents the present day host halo, and every branch is a merger event (a smaller halo being eaten up). The higher up the tree you go, the further back in time you look! I work with a code named SatGen that can create these merger trees and today you will be handling the output of the SatGen code.

The code outputs several numpy arrays that are compressed together into a single .npz file. (See this link https://numpy.org/doc/stable/reference/generated/numpy.savez.html)

Step 1

Download the tree_0.npz file from slack (or however we share it with you). Create a new script in your IDE (VSCode, PyCharm, etc). You will want to be saving your code in this script throughout this assignment, but you may also want to have an ipython instance open, for the purposes of writing and testing code quickly before copying it into your script.

Open the .npz file in your code.

How many arrays are contained in the compressed data file?
Select the mass array and print out its dimensionality.
What about the time array?

Hint: Opening the File + Looking Inside

An .npz file is a file type defined by the numpy package. Look into the numpy package to see how you can open that file type in python. Once you have the file open in python, you need some way to figure out what it contains. Recall that in dictionaries data is stored in key: value pairs, where keys represent that names. This type of numpy file is similar. In order to figure out what the names of our arrays are, we need to use the .keys() method.

Hint: Figuring out Dimensionality

Look into using the shape attribute to figure out the dimensionality of a numpy array.

Part 2: Playing around with halo mass (10 - 15 minutes)¶

Now that you have opened up the data, I can tell you that the host halo is saved in the first index of the mass array. The rest of the indices correspond to the subhalos that were accreted by the host during the “simulation”.

Step 4

Find the maximum mass of every subhalo across cosmic time! To start, you can try just finding the maximum mass for one subhalo (for ex. the first subhalo stored as the first element of the mass array).

Try this using a for-loop, then disuss with your group if there is a more efficient way accomplish the same thing.

TIP

Dark matter halos are REALLY massive! The SatGen code saves these mass values in units of solar masses and as you see, most halos are larger than 1 million solar masses.

It might make more sense to work with these numbers in log10 space. When you try to convert these values into log10 space, you might encounter a UnitTypeError. See if you can figure out what this error is telling you by referencing the astropy units documentation.

Hint: Debugging UnitTypeError

When using astropy.units we are actually converting our data from float datatype to what’s called an astropy Quantity datatype. In order to do mathematical operaitons, we usually need to convert our data back to a regular type like float. The way we can do this is by using the .value attribute of an astropy Quantity. So, we can convert our entire mass array back into regular old floats using mass.value.

SideNote: if you do some unit conversions to your mass array while it is in Quantity datatype form, then convert it back to a regular numpy array, the actual values are still converted! You can see this for yourself by using astropy to convert to kg, then using .value to convert that back to floats. The values will still be changed! This is why the astropy.units module is so useful. You will never have to worry about unit conversions again.

WOW! There are so many more low mass subhalos than there are high mass subhalos!! LCDM predicts a steep mass function!

Part 3: Plotting the merger tree! (20-25 minutes)¶

Okay so as we know, there are a bunch of subhalos in this merger tree. If we wanted plot all of them with respect to time, the figure would be a bit crowded. Instead lets only pick the ones that are above a given mass at present day.

Can you see the little dips in the accretion histories? That is when the subhalo is accreted onto the host! Notice there is no such dip for the red line!

Week 3 Assignment

Part 1: Loading in the SubHalo Merger Tree Data (10 - 15 minutes)¶

Part 2: Playing around with halo mass (10 - 15 minutes)¶

Part 3: Plotting the merger tree! (20-25 minutes)¶