My Python environment.

RIP to Bill Paxton, lead developer of MESA. I feel privileged to have learned from the man himself at the 2012 MESA Summer School. #stellarastro #astrocode

Also another notebook showing how to automate prewhitening analysis (I will try to build more convenience functions into Pyriod for this soon). github.com/keatonb/Pyri...

For this presentation, I have also uploaded a demonstration of how to use Pyriod to measure O-C diagrams to track timing variations of a signal. github.com/keatonb/Pyri...

At the 9th TESS/16th Kepler Asteroseismic Science Consortium Workshop this week in Vienna. I'm presenting this poster on my code Pyriod for pre-whitening frequency analysis of astronomical time series data. #astromethods

Our reward for completing this process is a table of signal frequencies, amplitudes, and phases, with estimated uncertainties. These measurements of resonant frequencies of a white dwarf star are published and interpreted in Bell et al. (2019, ui.adsabs.harvard.edu/abs/2019A%26A...632A..42B).

The fit to the light curve reveals the complex variability that we otherwise couldn't visibly see for all the measurement noise, shown here for one day of the TESS light curve.

Pyriod can enforce strict relationships between combination frequencies and independent frequencies when they are identified by their arithmetic relations. We proceed to pre-whiten all significant signals, with combinations marked with gold diamonds.

Three signals down, but the next three are "combination frequencies" that appear at precise sums, multiples, and differences of frequencies. If the first three signals are f0, f1, and f2, this next cluster of peaks are f0+f1, 2*f0, and f0+f2.

We then identify additional signals from the periodogram of fit residuals (the "pre-whitened" data). Pyriod displays the periodogram of the residuals in blue (highest peak marked). The model is displayed in green. In practice, we move significant peaks from blue to green.

We "pre-whiten" signals by fitting and subtracting sinusoids from the light curve. We currently fit the frequency, amplitude, and phase of one sinusoidal signal. The data may be noisy, but TESS collected enough that we detect this signal to high significance.

The pre-whitening algorithm is a method for measuring sinusoidal signals in time series data. It is best suited for signals that are coherent for the duration of the observations. We start with the periodogram of the TESS Sector 3 light curve of the pulsating white dwarf WD 0158-160.

Had to withdraw my #AAS246 poster due to COVID, but let me demo "Pyriod: Interactive Pre-Whitening Frequency Analysis in Python." Here is a quick guide to reproducing the analysis of TESS data on a pulsating white dwarf from Bell et al. (2019, ui.adsabs.harvard.edu/abs/2019A%26A...632A..42B).

Disappointed to be missing #AAS246 this week, but I gotta keep y'all safe.

Stand Up For Science!

Had a great time at Cosmic Pathways today representing Queens College Physics. Thanks for organizing this fantastic event @wrightphyshop.bsky.social !

NYC local rally will be in Washington Square Park from 12-3 PM.

A nice break from the usual work week at the one-day ExoNYC local exoplanets meeting today at the Flatiron Institute/CCA.