Events at Physics |
Events During the Week of February 23rd through March 2nd, 2025
Monday, February 24th, 2025
- Plasma Physics (Physics/ECE/NE 922) Seminar
- "Radiatively-cooled Magnetic Reconnection Experiments on the Z Machine"
- Time: 12:00 pm - 1:15 pm
- Place: 1227 Engineering Hall
- Speaker: Jack Hare, Cornell University
- Abstract: Magnetic reconnection is a fundamental plasma process which explosively dissipates magnetic energy and changes magnetic topology. In many astrophysical plasmas, such as the solar chromosphere, the interstellar medium, and pulsar magnetospheres, the heated plasma rapidly radiates away thermal energy in the form of high energy X-rays, leading to cooling instabilities including the complete radiative collapse of the reconnection layer. Analytical theory by Uzdensky and McKinney suggests this collapse process dramatically accelerates the reconnection rate, and simulations suggest that the plasmoids formed through the tearing instability are the regions of strongest emission within the reconnection layer. In this talk, I will present results from experiments designed to study radiatively cooled magnetic reconnection in the laboratory. Using a suite of diagnostics including X-ray and optical imaging, spectroscopy, magnetic probes, and laser shadowgraphy and interferometry, we demonstrate the formation of these bright plasmoids and their subsequent rapid cooling and radiative collapse.
- Host: Prof.Adelle Wright
- NPAC (Nuclear/Particle/Astro/Cosmo) Forum
- Finding Neutrinos: Advancing Neutrino Detection, Reconstruction, and Analysis
- Time: 4:00 pm - 5:00 pm
- Place: 5280 CH &
- Speaker: Dr. Jessica Micallef, Institute for Artificial Intelligence and Fundamental Interactions
- Abstract: Neutrino oscillation, or flavor changing between the neutral leptons, has indicated that neutrinos do not fit as perfectly into the Standard Model puzzle as they were first predicted. Improving measurements of neutrino oscillation and properties are important to help us better understand the Standard Model, and thus how these fundamental particles influence our universe. To successfully complete their goals, future experiments aiming to make decisive measurements need results from the new technology and methods used by current experiments and prototypes. Machine Learning (ML) is one such tool that particle physics has begun to employ that can tackle new challenges facing neutrino experiments. I will discuss how my work with ML will help the success of one of the largest, future neutrino physics experiments--the Deep Underground Neutrino Experiment.
- Host: Sridhara Dasu
Tuesday, February 25th, 2025
- Thesis Defense
- Multimodal vision-language modeling for advanced quantitative analysis of positron emission tomography imaging
- Time: 11:00 am - 1:00 pm
- Place: 5310 Chamberlin
- Speaker: Zachary Huemann, Physics PhD Graduate Student
- Host: Sridhara Dasu and Tyler Bradshaw
- Wisconsin Quantum Institute
- Quantum Coffee Hour
- Time: 3:00 pm - 4:00 pm
- Place: Rm.5294, Chamberlin Hall
- Abstract: Please join us for the WQI Quantum Coffee today at 3PM in the Physics Faculty Lounge (Rm.5294 in Chamberlin Hall). This series, which takes place approximately every other Tuesday, aims to foster a casual and collaborative atmosphere where faculty, post-docs, students, and anyone with an interest in quantum information sciences can come together. There will be coffee and treats.
Wednesday, February 26th, 2025
- NPAC (Nuclear/Particle/Astro/Cosmo) Forum
- Beyond the Observable: A Machine Learning perspective on modern Cosmology
- Time: 4:00 pm - 5:00 pm
- Place: 5280 CH &
- Speaker: Dr. Carolina Cuesta Lazaro, Institute for Artificial Intelligence and Fundamental Interactions, MIT
- Abstract: Our observations have painted a simple portrait of cosmic evolution, yet fundamental questions remain unanswered: What is the nature of dark matter, the invisible substance that makes up most of the matter in the Universe? What is driving the accelerated expansion of the cosmos? How did it begin? In this talk, I will present machine learning frameworks that bridge the gap between numerical simulations and increasingly precise astronomical observations to decode these invisible components. I will demonstrate how generative models can serve as both efficient emulators and tools for parameter estimation, enabling direct inference from high-dimensional astronomical data without relying on simplified summary statistics. I will then show how we can probabilistically reconstruct the dark matter distribution from observed galaxy clustering, while being robust to uncertainties in galaxy formation physics. Finally, I will discuss how machine learning enables us to reconstruct the primordial Universe by inferring the initial conditions that evolve into our observed cosmos. Through these methods, we can also identify potential anomalies in the cosmic web that might signal departures from our standard cosmological model. These advances come at a pivotal moment, as we enter an era of extremely precise cosmological surveys that may transform current statistical tensions into discoveries of new fundamental physics.
- Host: Sridhara Dasu
Thursday, February 27th, 2025
- No events scheduled
Friday, February 28th, 2025
- Black and Brown in Physics
- BBiP Black History Heritage Month Event
- Time: 1:00 pm - 3:00 pm
- Place: TBD
- Abstract: TBD
- Host: Black and Brown in Physics
- Physics Department Colloquium
- title to be announced
- Time: 3:30 pm - 5:00 pm
- Place: Chamberlin 2241
- Speaker: Jesse Thaler, MIT
- Host: Gary Shiu