Izabela Pavel posing in front of a poster that was written by her, Alex Siebenmorgen, and Bret Lehmer. The poster contains the preliminary results of Izabela Pavel’s research.

Author: Izabela Pavel | Major: Physics | Semester: Spring 2023

Hello, my name is Izabela Pavel, and I am a physics major with an astronomy concentration.

I have been working with Dr. Bret Lehmer since Fall of 2021, but I received the Honors College Grant for the Spring 2023 semester. My on-going project, which was at the heart of my honors thesis, focuses on developing a new method of analyzing X-ray spectra of high-mass X-ray binaries (HMXBs) of different host-galaxy properties by using X-ray colors and count-rate. By developing a different method, astronomers can analyze X-ray spectra of different galaxies at high redshifts. My project specifically focuses on one particular galaxy, NGC3310, and uses that galaxy as a guinea pig for developing the different method.

This project was broken up into multiple steps. From the Fall 2021 semester to the Fall 2022 semester, I was focused on learning the background information, how to manipulate X-ray data in Python, and using the current method to analyze the X-ray spectra. I did start to touch upon using the X-ray color to find another way to analyze X-ray spectra, but I only got to that step this semester. For the X-ray spectra, we assumed a power-slope model which has three parameters: hydrogen column density, photon index (aka gamma), and a normalization constant. The goal of the project is to use X-ray colors and count-rate to find those three parameters. Once we have those parameters, then we have the X-ray spectral shape.

This semester, I started off by creating a basic color-color map, which had the soft-colors on the x-axis and the hard-colors on the y-axis. I then was able to plot the sources onto the graph. The biggest challenge was creating a grid of the varying hydrogen column density and gamma. To create one axis grid, I would keep the hydrogen column density constant, and find the predicted gamma values. To create the other axis, I would keep the gamma value constant, and find the predicted hydrogen column density. I repeated this process a few more times in order to create a 10×10 grid.

Once I have the color-color map, I then added two more plots to create a corner plot. These two plots are color-count rate plots, with one being soft-color vs count-rate, and the other being hardcolor vs count-rate. I had to recreate the grid from the color-color map, but instead of mapping it in a color-color space, I got to map it in a color-intensity space. I also had to factor another parameter called normalization. With the color-color map, the normalization parameter had no effect, since it has no effect on the color. Since I am now using count-rate, which normalization does effect, I also have factor in that parameter. To do this, I created two grids for the color-intensity space, with each grid having a different normalization constant. All the normalization constant does is changes the vertical position of the grids, but it does not change the shape of the grids at all.

This corner-corner plot is the new method that I was working on. To utilize it, say we have a theoretical source, we can use the data already gathered by an X-ray observatory to find the colors and count-rate. We can then plot those values onto the plots we created. We then can see what values of gamma, hydrogen column density, and normalization constant by looking at where our point lands on the grid. Once we have those parameter values, then we have our X-ray spectral shape.

This is where I ended for the honors thesis. I am lucky enough to continue working on research on a similar project over the summer. I will still be working with Dr. Lehmer, but I will also be working co-currently with another graduate student, who will be fully taking over the project. This project is similar to the one I was working on, except we will be adding another layer by considering how an absorption factor (the hydrogen column density) changes due to extinction.