Floor Broekgaarden

Floor Broekgaarden

she/her

Assistant Professor of Astronomy at UC San Diego. Building a research group in Gravitational Wave Paleontology.

GROWL Task Force

The GROWL Task Force is a community of students, industry professionals, and anyone curious about gravitational waves who work with our lab on GROWL, our main research project. You can follow what we are working on, get updates from the group, and contribute to real research. You don’t need a background in astrophysics to join.

Interested? Fill out our interest form and mention the GROWL Task Force. More details are below.

What is GROWL?

GROWL stands for GRavitatiOnal Wave paLeontology. It is a framework that brings together more than 10,000 simulations of black hole and neutron star mergers across cosmic time, so that we can standardize, compare, and visualize them in one place, and make them publicly available.

When two black holes or neutron stars merge, the gravitational waves they send out carry information about the stars that formed them, often billions of years earlier. I like to think of these signals as cosmic fossils, which is why we call this field gravitational-wave paleontology. The number of detections is growing fast, from hundreds today to thousands and eventually hundreds of thousands per year, and we want to use them to learn how massive stars lived and died throughout the history of the Universe.

To do that, we need to compare the observations with simulations. The problem is that these simulations are currently stuck in “simulation silos”: models from different groups and codes use different physical assumptions, data formats, and parameter ranges, which makes it really hard to compare them or reproduce results. GROWL is our attempt to fix this. Over the next few years, we will:

  • bring together existing simulations from population synthesis codes such as COMPAS, StarTrack, SEVN, POSYDON, BPASS, and COSMIC;
  • quantify and visualize how the predictions depend on the model assumptions;
  • combine the simulations with metallicity-dependent star formation histories to predict merger populations across cosmic time; and
  • release interactive visualization and analysis tools through the GW Landscape dashboard.

In the end, we want to know which predictions (for example merger rates, delay times, and mass distributions) hold up across models, and which ones depend on uncertain stellar physics like common-envelope evolution, mass transfer, and supernovae.

GROWL is funded by the National Science Foundation (Award #2606407, Oct 2026 – Sep 2029). You can read more about the grant on the Publications page, and about our science on the Research page.

What is the GROWL Task Force?

The Task Force is the group of people who help build and use GROWL. As a member you can:

  • follow the lab and see what we are working on each week;
  • get updates, results, and behind-the-scenes stories from the group; and
  • contribute to the research by working with us on open problems in GROWL.

Everyone brings something different. Members from industry bring software and data-engineering experience that is often missing in academic groups, and help mentor students. Students get research experience, mentorship, and a better idea of the career paths open to them, and in turn help onboard new members. And everyone gets to see how publicly funded science works from the inside.

Some examples of what Task Force members work on:

  • research projects using the GROWL catalog, such as calculating and plotting binary black hole mass distributions from the simulations;
  • helping new members get started; and
  • sharing updates and stories from the lab.

Why I started the GROWL Task Force

Access to research

Every year I get more than 40 emails from students asking about research opportunities. Like most faculty, I can only take on a few of them, typically one to three students, because research mentoring is usually done through individual one-on-one meetings. This also affects who gets to do research. The spots often go to students who already have some research experience or have taken more advanced courses, while others are told to take a few more classes first.

At the same time, more and more students are majoring in astrophysics. Many of them go on to data science jobs in industry, and others continue in research, for example in a PhD program or at a national lab. Research experience is great preparation for all of these. With the Task Force, I want to create a way for at least 50 students to take part in research each year, while still giving them one-on-one mentoring.

Not everyone can do a two-year project

The usual model for undergraduate research is that a student works on their own project for one to two years, ideally leading to a first-author paper. This can be a great experience, but it is not the only way to learn from research, and many students can’t commit to it, for example because they have a job or family responsibilities. It is also harder to access for students from backgrounds that are underrepresented in astronomy, and for people outside of academia.

There is good evidence that other models work well. In the SEA-PHAGES program, 2,850 students at 67 institutions all worked on one shared research problem, and they scored much higher on measures related to staying in science than students in traditional lab courses, regardless of their academic background (Hanauer et al. 2017). At UT Austin, students in the Freshman Research Initiative, where first-year students do research as part of a course, were more likely to graduate and to finish a STEM degree (Rodenbusch et al. 2016). Course-based research like this may also be a more inclusive way into science than individual research projects (Bangera & Brownell 2014).

A network of mentors

There is also growing evidence that students do better when they have a network of mentors, rather than a single research mentor. The National Academies recommend “multiple, or ‘constellation,’ mentor models,” and say mentors should help students build relationships with people both inside and outside their own institution (NASEM 2019; see also Higgins & Kram 2001). Good mentorship and research experience help students build their confidence and identity as scientists, which in turn predicts whether students from underrepresented groups stay in STEM careers (Estrada et al. 2018). In the Task Force, members can learn from faculty, postdocs, graduate students, other students, and people working in industry, and they also have one-on-one mentoring.

Research as a team effort

Doing research is often a very individual effort. But science is increasingly done in teams: a study of nearly 20 million papers over five decades found that teams now produce most papers, and that their papers are cited more (Wuchty, Jones & Uzzi 2007). I want students to experience research like this, and to play a real role in a big project, including sharing in the leadership. For example, Maryam Ahsan led and presented the first GROWL results to the Task Force.

Working together across many institutions takes some structure. In a study of 62 NSF-funded collaborations, projects that involved more universities were harder to coordinate, and the most effective way to coordinate was direct supervision, especially by faculty and graduate students (Cummings & Kiesler 2005). People who had worked together before also had fewer problems with distance and differences between disciplines (Cummings & Kiesler 2008). So in the Task Force, lab members mentor and supervise the projects, and we try to keep people working together over a longer time.

Learning from each other

Task Force members work together and help each other, for example through our Discord. Teaching each other your tools and methods also makes a team work better together: cross-training helps team members understand each other’s roles, which improves coordination and performance (Marks et al. 2002). I also want our research to be easy to get into. Our tutorials and bootcamp are publicly available, so anyone can work through them at their own pace.

Who is involved?

The Task Force is run by the GROWL Task Force Co-I Team: Floor Broekgaarden, Marko Ristić, Julia Haynes, Tyler Smith, Steffani Grondin, Melanie Santiago, Rhea Kumar, Sofia Alvarez Lopez, Sasha Levina, and Kyle Rocha. Members join from all over the world. For example, Maryam Ahsan (Quaid-i-Azam University, Islamabad, Pakistan) presented the first GROWL results to the group in October 2026. You can meet the rest of the lab on our Research Group page.

Some milestones so far:

  • Jul 2026: we launched the GROWL Task Force.
  • Aug 2026: the lab received an NSF grant for GROWL.
  • Oct 2026: Chad and Mugdha visited UC San Diego to meet with the GROWL Task Force Co-I Team.
  • Oct 2026: Maryam Ahsan presented the first GROWL results to 10 collaborators.

For more updates, see our News page.

How to join

Fill out our interest form and mention the GROWL Task Force. It helps to tell us a bit about your background and what you are hoping to get out of it. I will then get in touch about the next steps. You can also email me directly at fbroekgaarden@ucsd.edu.

If you would like to join the lab at UC San Diego as a student, PhD student, or postdoc, see the Join the Lab page. For other ways to support the lab, including donations, see the Support the Lab page.

References

  • Bangera, G. & Brownell, S. E. 2014, Course-Based Undergraduate Research Experiences Can Make Scientific Research More Inclusive, CBE—Life Sciences Education, 13, 602. doi:10.1187/cbe.14-06-0099
  • Cummings, J. N. & Kiesler, S. 2005, Collaborative Research Across Disciplinary and Organizational Boundaries, Social Studies of Science, 35, 703. doi:10.1177/0306312705055535
  • Cummings, J. N. & Kiesler, S. 2008, Who Collaborates Successfully? Prior Experience Reduces Collaboration Barriers in Distributed Interdisciplinary Research, Proc. ACM CSCW 2008, 437. doi:10.1145/1460563.1460633
  • Estrada, M., Hernandez, P. R. & Schultz, P. W. 2018, A Longitudinal Study of How Quality Mentorship and Research Experience Integrate Underrepresented Minorities into STEM Careers, CBE—Life Sciences Education, 17, ar9. doi:10.1187/cbe.17-04-0066
  • Hanauer, D. I. et al. 2017, An inclusive Research Education Community (iREC): Impact of the SEA-PHAGES program on research outcomes and student learning, PNAS, 114, 13531. doi:10.1073/pnas.1718188115
  • Higgins, M. C. & Kram, K. E. 2001, Reconceptualizing Mentoring at Work: A Developmental Network Perspective, Academy of Management Review, 26, 264. doi:10.5465/amr.2001.4378023
  • Marks, M. A., Sabella, M. J., Burke, C. S. & Zaccaro, S. J. 2002, The Impact of Cross-Training on Team Effectiveness, Journal of Applied Psychology, 87, 3. doi:10.1037/0021-9010.87.1.3
  • National Academies of Sciences, Engineering, and Medicine 2019, The Science of Effective Mentorship in STEMM, Washington, DC: The National Academies Press. doi:10.17226/25568
  • Rodenbusch, S. E., Hernandez, P. R., Simmons, S. L. & Dolan, E. L. 2016, Early Engagement in Course-Based Research Increases Graduation Rates and Completion of Science, Engineering, and Mathematics Degrees, CBE—Life Sciences Education, 15, ar20. doi:10.1187/cbe.16-03-0117
  • Wuchty, S., Jones, B. F. & Uzzi, B. 2007, The Increasing Dominance of Teams in Production of Knowledge, Science, 316, 1036. doi:10.1126/science.1136099