Vicente has successfully defended his comprehensive examination titled 'Leveraging Machine Learning to Revolutionize Astrophysics Research Processes: From Peer Review to Research Management'. His work explores how computational techniques like machine learning can enhance various aspects of the research process in astrophysics.

We congratulate Dr. Jack O’Brien for successfully defending his thesis titled “Progenitor Identification of Type Ia Supernovae through Statistical Abundance Tomography from Optical Spectra with Machine Learning and Radiative Transfer” in astrophysics at Michigan State University. Jack started with us in 2020 and scientifically worked on (in addition to his thesis work) adding continuum opacities to TARDIS. He became and still is our education coordinator and made sure that students from different disciplines received training in physics, computing, and machine learning. He will join Gautham Narayan's group at University of Illinois, Urbana-Champaign in the Fall of 2024. Thank you for all of your contributions and help and for being a fantastic team member!

This upcoming August, Benjamin Mellon and fellow undergraduate at MSU, Aardarsh Swaminathan, will intern in Oslo, Norway under Dr. John Aiken.

The interns will apply modern AI tools to identify acoustic events occuring in a combined hydrophone and geophone data set acquired in the Oman Drilling Project's Multiborehole observatory.

The students will use a neural network to classify physical occurences for later classification based on limited validation data.

The interns are enthusiastic to use cutting edge computing resources to collaboratively devolope AI software solutions for a geophyscal problem.

Bea, an undergraduate in the group, is excited to join Blue Cross Blue Shield of Michigan's Analytics Center of Excellence as a Summer 2024 Intern! Bea has previously worked with big data and different projects in the Deepthought Initiative Collaboration (DTI). That includes conducting text classification of abstracts with machine learning, website development with GitHub and web template engines, and creating map visualizations of researcher migration paths. She is eager to explore a new industry and help create impact with her skills. Even more so, Bea is excited to learn and grow as a data scientist through this upcoming experience.

Tripp Dow and Iliomar Rodriguez Ramos have both begun working with the Kerzendorf Group, as summmer REU students.

Tripp is a computer science student at the University of Minnesota. He will work under Vicente Amado Olivo, on author name disambiguation. The two will implement and compare algorithms for computational metascience, including name-based and graph-based approaches. His research interests include natural language processing, mathematical modelling, and machine learning. After graduation, he plans to attend graduate school, with hopes of becoming a professor.

Iliomar is a Theoretical and Astrophysics student at the University of Puerto Rico, at the Mayagüez Campus. He is working under Joshua Shields, on The Complex Structure and Composition of Ancient Stars, studying the spectrum of ancient stars with the open-source code STARDIS. In the future, he expects to attend graduate school and dedicate to study the amazign mysteries of the stellar remnants.

The two students are excited for this amazing oppurtunity, and look forward to working with the members of the Kerzendorf Group.

The Deepthought Initiative (DTI) collaboration applies computational techniques and tools to analyze the vast literature in scientific research, with a specific focus on leveraging machine learning to understand astrophysics literature. Vicente Amado Olivo's research revolves around tracking astrophysics publications and identifying astronomers worldwide through publications on arXiv. Being part of a research group comprising astrophysicists, Vicente's work in computational meta-research ensures that the tools developed by DTI are directly applicable to the needs of astrophysicists. To further their research in astrophysics meta-research, Vicente is visiting ESAC, a world-leading space agency, in order to gain firsthand experience with their current research systems, understand their future needs, actively participate in a proposal cycle, and collaborate with the librarians at ESA.

An example outcome of the fitting process for one of the stars in the search region. The blue crosses show the photometric observations with the vertical spread showing observational uncertainty, and the horizontal spread shows the width of the filter used for the observation, corresponding to the rough portion of the spectrum probed by the observation. The transmission curve of each filters is shown in dashed purple. The black and grey regions show a distribution of spectra created by sampling the posterior distribution of constrained stellar parameters.

Radius vs. Effective Temperature and metallicity fits of stars within 4.2 arcsec of the hydrodynamic center of SNR 0509−67.5, the sample of potential surviving companion stars. The gray crosses show the surrounding control sample of nearby stars which we used to estimate the underlying temperature-radius distribution of the local stellar population, shown by the contours. The purple crosses show the three stars identified in A22. The red X markers show surviving companion models from we considered that were close enough in this space enough to be compared, with the other models too high in temperature or large in radius to be placed within the bounds of the figure.

Yuki and Wolfgang were awarded from the College of Natural Science at Michigan State University.The program incentivizes graduate students and their mentors to spend some time away from their research to focus on inclusion, diversity, equity, and accessibility, or IDEA, initiatives and projects.

We are delighted to announce that our NSF research proposal (led by Maryam Modjaz, Wolfgang Kerzendorf with large contributions by Marc Williamson) on the study of massive stars and their explosive deaths, known as Stripped Supernovae, has successfully secured funding. With access to the largest dataset of Stripped Supernovae in existence, our team aims to unravel the complexities surrounding these cataclysmic events. By analyzing the optical spectra and light curves of three dozen Stripped Supernovae, along with employing the open-source radiative transfer code TARDIS and machine learning technology, we will gain unprecedented insights into the progenitor make-up and explosion dynamics of these cosmic phenomena. This research has far-reaching implications, not only for understanding stellar evolution, but also for exploring the conditions required for jet production and clarifying the contentious SN-GRB progenitor models. By shedding light on these fundamental aspects, we will pave the way for utilizing Stripped Supernovae as indicators of star formation across vast cosmic distances and investigating their role in re-ionizing the Universe. Furthermore, our findings will help advance the field of time-domain astronomy, as our modeling framework can be adapted to analyze other types of supernovae and astrophysical events, such as Superluminous SNe Ic and kilonova spectra. This project will enable us to address critical questions, resolve long-standing controversies, and contribute to a deeper understanding of the cosmos.

Wolfgang Kerzendorf and collaborators organized a workshop on peer review at the European Southern Observatory (ESO) in Garching, Germany. The workshop aimed to address the persistent challenges faced by peer review in the scientific community, including the difficulty of identifying experts in specialized fields and the increasing number of researchers and publications. Experts from organizations such as ESO, ESA, ALMA, STScI, NASA, and NOIRLab came together to discuss the state of peer review and explored innovative approaches for a digital and interconnected science community. The workshop consisted of four main sessions and was held at the ESO Headquarters from February 6 to 10, 2023. Vicente Amado Olivo presented a contributed talk and you can find the slides see link in references.

2017 DECam imagery of the SN 1006 remnant. The contours are CHANDRA X-ray data (0.5-0.9 keV) showing the position of the remnant. The circles indicate the search region (red) and the the likely maximum displacement of a D6 star (blue), as well as the physical transverse velocity of a star corresponding to the angular distance assuming a distance of the remnant. The larger search region allows for ambiguity on the center of the remnant.

Results of proper motion survey showing apparent r-band magnitude against proper motion measurement and calculated transverse velocities assuming a distance of 2.17 kpc for DECam sources. The three Shen et al. 2018 stars have corrected apparent magnitudes as they would appear at the same distance with uncertainties and including foreground extinction. A surviving white dwarf companion in accordance with the predictions of the D6 scenario was expected to lie in the shaded region with the previously discovered D6 stars. The four Gaia stars in the analyzed region are shown in Table 1 and Figure 6, and are discussed in Section 4 along with the high proper motion objects fainter than 21

Color-Magnitude Diagram of 150 000 secure parallax (parallax over error > 30), Gaia stars around SN 1006. The blue dots show the three D6 candidates discovered in the field by (Shen et al. 2018) far off the main sequence. The red dots show the high proper motion (> 500 km s−1) Gaia objects inside SN 1006 in our search. They lie on or close to the main sequence with ordinary colors