Beryl Hovis-Afflerbach

Astronomy PhD candidate
Photo of Beryl Hovis-Afflerbach

Beryl Hovis-Afflerbach

(she/they)

I am a PhD candidate and NSF graduate research fellow working with Professor Allison Strom at Northwestern University. My research focuses on massive stars in galaxies across cosmic time.

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Massive stars

I am interested the evolution and properties of massive stars across cosmic time. Massive stars dominate the ionizing spectra of star forming galaxies, influence chemical abundances, and provide feedback that links galaxies to their environments.

High-z galaxies

Massive stars at high redshift are observationally distinct from those in the local universe, and accurately modeling their radiation is crucial to interpreting observations of high-redshift galaxies from JWST.

Models

I work with the stellar evolution code MESA and a variety of stellar population synthesis codes. Existing models can vary significantly in their assumptions and treatments of binary evolution, with large implications for the conclusions drawn from observations.

Observations

I use rest-UV-optical observations of high-z galaxies and their local analogs to better understand their massive stars. I am working on comparing multiple different existing models to observations and investigating how we can improve these models to better reproduce observations.

Latest

Publications

All publications on SciX

The mass distribution of stars stripped in binaries: The effect of metallicity

Hovis-Afflerbach, B., Götberg, Y., Schootemeijer, A., Klencki, J., Strom, A. L., Ludwig, B. A., Drout, M. R., 2025, A&A, 697, A239

Stars stripped of their hydrogen-rich envelopes through binary interaction are thought to be responsible for both hydrogen-poor supernovae and the hard ionizing radiation observed in low-Z galaxies. A population of these stars was recently observed for the first time, but their prevalence remains unknown. In preparation for such measurements, we estimate the mass distribution of hot, stripped stars using a population synthesis code that interpolates over detailed single and binary stellar evolution tracks. We predict that for a constant star-formation rate of 1 Msun/yr and regardless of metallicity, a scalable model population contains ~30,000 stripped stars with mass Mstrip >1Msun and ~4,000 stripped stars that are sufficiently massive to explode (Mstrip >2.6Msun). Below Mstrip = 5Msun, the distribution is metallicity-independent and can be described by a power law with the exponent alpha~-2. At higher masses and lower metallicity (Z = 0.002), the mass distribution exhibits a drop. This originates from the prediction, frequently seen in evolutionary models, that massive low-metallicity stars do not expand substantially until central helium burning or later and therefore cannot form long-lived stripped stars. With weaker line-driven winds at low metallicity, this suggests that neither binary interaction nor wind mass loss can efficiently strip massive stars at low metallicity. As a result, a “helium-star desert” emerges around Mstrip = 15 Msun at Z = 0.002, covering an increasingly large mass range with decreasing metallicity. We note that these high-mass stars are those that potentially boost a galaxy's He+-ionizing radiation and that participate in the formation of merging black holes. This "helium-star desert" therefore merits further study.

The results of our population synthesis model runs can be downloaded here and the code to reproduce all of the results and figures in the paper can be found here.

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Identifying and Repairing Catastrophic Errors in Galaxy Properties Using Dimensionality Reduction

Hovis-Afflerbach, B., Steinhardt, C. L., Masters, D., & Salvato, M. 2021, ApJ, 908, 148

Modern surveys are able to observe large numbers of galaxies because they use photometry, observing a few bands for each galaxy, rather than the more time-consuming spectroscopy, observing the galaxy's entire spectrum.

Typically, a template fitting code is used to determine each galaxy's properties from its photometry. However, for a few percent of galaxies in every survey, the derived properties can be catastrophically wrong, such as labeling relatively nearby galaxies as some of the farthest in the universe. Because there is no way to know which galaxies have these catastrophic errors in their derived properties, the errors contaminate all studies of galaxy properties based on photometric surveys.

To determine which galaxies have these catastrophic errors, we develop an augmented algorithm as follows:

  1. Run a template fitting code, EAZY, to determine a photometric redshift for each galaxy.
  2. Use the dimensionality reduction algorithm t-SNE to group objects with similar photometry. Color the t-SNE map by photometric redshift, as seen in the figure above.
  3. Galaxies with similar photometry should have similar redshift, so any object which has a very different photometric redshift than its nearest neighbors on the t-SNE map gets flagged as a potential catastrophic error.

The t-SNE map showing the grouping can be seen in the figure above. For a handful of objects in each of three distinct regions in the t-SNE map, the spectral energy distribution (SED) shape is shown in the boxes at left. Objects grouped close together on the t-SNE map, which are in the same box at left, have similar SED shapes. By contrast, the SED shapes are different between these three distinct regions of the t-SNE map.

This method consistently correctly identifies errors at a much higher rate than it misidentifies correct objects as errors.

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Partially Erupted Prominence Material as a Diagnostic of Coronal Mass Ejection Trajectory

Hovis-Afflerbach, B., Thompson, B. J., & Mason, E. I., 2023, Space Weather, 21, e2022SW003256

Coronal mass ejections (CMEs) are energetic releases of large-scale magnetic structures from the Sun. CMEs can have impacts on spacecraft and at Earth. This trajectory is typically assumed to be radial, but often the CME moves outward with some spatial offset from the source region where the eruption initially occurred. A CME is frequently accompanied by a prominence eruption, a movement of cool, dense material up into the corona that can be ejected or fall back down. We investigate eruptions in which some portion of the prominence material falls back to the Sun along field lines which have reconfigured in the eruption, rather than draining back to the source or escaping with the CME. Using a method called persistence mapping, 304 Å images from the Solar Dynamics Observatory (SDO), and coronagraph images from the Solar and Heliospheric Observatory, we measure and compare the offsets in latitude of 20 CMEs and their respective prominences with respect to the source region. The 20 events were chosen to sample over the first 10 years of the SDO mission. We find that the offsets are correlated. We find no difference between eruptions offset toward the equator or the poles, suggesting that the offset is a result of local changes in the eruptive field, rather than of the Sun's global magnetic field structure. These findings help us contextualize individual eruptions and highlight changes in the local magnetic field associated with the prominence eruption.

As part of this work, I wrote an implementation of persistence mapping and time convolution mapping in Python. Persistence mapping is a tool for tracking the evolution of solar prominences (or other types of time-evolving phenomena). When a pixel reaches a maximum value, that value "persists" into subsequent frames until it is exceeded, resulting in a final image which traces out the full motion of the prominence. In time convolution mapping (shown in the figure above), each pixel is colored according to the time it reaches its maximum value. The code can be found here.

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Two New Methods for Counting and Tracking the Evolution of Polar Faculae

Hovis-Afflerbach, B. & Pesnell, W. D., 2022, Sol Phys, 297, 48

Polar faculae are the footpoints of magnetic-field lines near the Sun's poles that are seen as bright regions along the edges of granules. The time variation in the number of polar faculae has been shown to correlate with the strength of the polar magnetic field and to be a predictor of the subsequent solar cycle. Due to the small size and transient nature of these features, combined with different techniques and observational factors, previous counts of polar faculae differ in magnitude. Further, there were no scalable techniques to measure the statistical properties of the faculae, such as the variation of the facular lifetime with time or solar activity.

Using data from the Helioseismic and Magnetic Imager (HMI) onboard the Solar Dynamics Observatory (SDO), we present two new methods for tracking faculae and measuring their properties.

In the first, we calculate the pixel-by-pixel standard deviation of the HMI continuum intensity images over one day, visualizing the faculae as streaks. The lifetime of the facula is found by dividing the angular length of the streaks by the latitude-dependent rotation rate. We apply this method to the more visible pole each day for a week every six months, from September 2010 to March 2021. Combining all of the measured facular lifetimes provides a statistical distribution with a mean of 6.0 hours, a FWHM of 5.4 hours, and a skew towards longer lifetimes, with some faculae lasting up to 1 day.

In the second method, we overlay images of the progressive standard deviation with the HMI magnetogram to show the close relationship between the facular candidates and the magnetic field. The results of this method allow us to distinguish between motion due to the Sun's rotation and "proper motion" due to faculae moving across the Sun's surface, confirming that faculae participate in convective motions at the poles.

Counts of polar faculae using both methods agree with previous counts in their variation with the solar cycle and the polar magnetic field. These methods can be extended to automate the identification and measurement of other properties of polar faculae, which would allow for daily measurements of all faculae since SDO began operation in 2010.

The code for the second method can be found here.

Click here for the paper