MATs (Monday Afternoon Talks)

3:00pm – 3:30pm, Gokul Srinivasaragavan

GRB 221009A/SN 2022xiw and GRB 230812B/SN 2023pel – Two Ordinary SNe Associated with Energetic GRBs
In this talk, I will present the characterization of two supernovae (SNe) associated with energetic long gamma-ray bursts (LGRBs): GRB 221009A/SN 2022xiw ( https://ui.adsabs.harvard.edu/abs/2023ApJ…949L..39S/abstract) and GRB 230812B/SN 2023pel (https://ui.adsabs.harvard.edu/abs/2023arXiv231014397S/abstract). Due to the extreme rarity of being both nearby and highly energetic, these GRBs offer unique opportunities to probe the connection between massive star core collapse and relativistic jet formation across a broad range of gamma-ray properties. We determine that there is moderate evidence for the existence of SN 2022xiw associated with GRB 221009A (the brightest GRB of all time), through Bayesian modeling techniques of the GRB’s optical counterpart’s light curve (LC), and broadly constrain SN 2022xiw’s parameters through a radioactive heating model. We confirm that the late-time flattening of GRB 230812B’s optical counterpart’s LC is due to SN 2023pel, and determine that it has an absolute r band peak magnitude of M_r = -19.46 \pm 0.18 mag. We confirm its classification as a broad-lined Type Ic SN by analyzing an optical spectrum taken 15.5 days after the SN peak, and also constrain SN 2023pel’s parameters through a radioactive heating model. We place both of these GRB-SNe in the context of the overall GRB-SN population, and find that they have SN properties that are mostly consistent with the overall GRB-SN population, despite their high energies. The lack of correlations found in the GRB-SN population between SN brightness and the isotropic equivalent gamma-ray energies for their associated GRBs, across a broad range of 7 orders of magnitude, provides further evidence that the central engine powering the relativistic ejecta is not coupled to the SN powering mechanism in GRB-SN systems.

3:30pm – 4:00pm, Ming-Feng Ho
Multi-fidelity emulators and the cosmological constraints from Lyman alpha forest
In this talk, I will introduce our newly built cosmological emulators for Lyman-alpha forest cosmology and explain how we use these emulators to obtain cosmology and HeII reionization constraints from the eBOSS 1D power spectrum. First, I will discuss our multi-fidelity machine learning technique, which uses low-fidelity simulations to explore the parameter space and employs a few high-fidelity simulations to upscale the resolution. This approach enables the construction of emulators that span a broad range of parameter dimensions at a lower cost. Next, I will describe how we apply this technique to develop emulators that encompasses 9 dimensions of cosmology and astrophysics, utilizing a suite of hydrodynamical simulations called Astrid-PRIYA. Finally, I will examine the posterior results from Bayesian inference, specifically focusing on how σ₈ correlates with other astrophysical parameters in the emulator. I will also discuss the effects of Lyman limit systems and damped Lyman-alpha absorbers on the cosmological inference results.