This is a past event.

Please join physics graduate students, Mahsa Najafi, Tanner Sether , and Krishna Teja Vedula for their presentations on Thursday, March 13th at 4 PM - Fisher Hall 139.

Mahsa Najafi​​​​​​​ (Advisor: Petra Huentemeyer)

Modeling Potential TeV Halos with High-Energy Gamma Rays from the HAWC Observatory

TeV halos are extended gamma-ray emissions powered by high-energy electrons and positrons that escape from pulsar wind nebulae (PWNe) but remain trapped in a larger region. Their unexpected slow diffusion challenges cosmic-ray transport models. Using data from the High-Altitude Water Cherenkov (HAWC) Observatory, I investigate the gamma-ray emission near 3HWC J1928+178, a candidate TeV halo in a complex astrophysical environment. By analyzing its spatial and spectral properties, I distinguish potential TeV halo emission from background sources. These findings provide new insights into pulsar-driven cosmic-ray acceleration and diffusion in the interstellar medium.

Tanner Sether (Advisor: Elena Giusarma)

Probabilistic Galaxy Field Generation with Diffusion Models

In the era of precision cosmology, the ability to generate accurate and large-scale galaxy catalogs is crucial for advancing our understanding of the universe. With the flood of cosmological data from current and upcoming missions, generating theoretical predictions to compare with these observations is essential for constraining key cosmological parameters. While traditional methods, such as the Halo-Occupation Distribution (HOD), have provided foundational insights, they struggle to balance the need for both accuracy and computational efficiency. High-fidelity hydrodynamic simulations offer improved precision but are computationally expensive and resource-intensive. In this work, we introduce a novel machine learning approach that harnesses Convolutional Neural Networks (CNNs) and Diffusion Models, trained on the CAMELS simulation suite, to bridge the gap between computationally inexpensive dark matter simulations and the galaxy distributions of more costly hydrodynamic simulations. Our method not only outperforms traditional HOD techniques in accuracy but also significantly accelerates the simulation process, offering a scalable solution for next-generation cosmological surveys. This advancement has the potential to revolutionize galaxy catalog generation, enabling more precise, data-driven cosmological analyses.

Krishna Teja Vedula (Advisor: Tiffany Lewis)

Modeling Synchrotron Polarization in Blazars

Blazars are the most energetic sustained objects in the universe. They have a relativistic jet pointed toward Earth, allowing for an in-depth study of the physics at the base of the jet due to Doppler beaming. Magnetic fields play a fundamental role in particle acceleration and radiation processes within the jet, but cannot be observed directly. However, the degree of order in the magnetic field can be determined through a model-dependent fit of the polarization degree. This provides an additional constraint on theoretical models of blazar jets and thus improves our insight into the physical environment that produces most of the radiation. Blazars emit electron synchrotron radiation, which makes up the lower-energy bump in the characteristic multiwavelength blazar spectrum. We develop a new computational model for the synchrotron polarization. The model is applied to multiwavelength data for 3C 454.3, with simultaneous optical polarization measurements.