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Events on Friday, March 5th, 2021

Graduate Program Event
PhD Prospective Student VIRTUAL Visit Day
Time: 12:00 am
Place: Virtual
Speaker: PhD Program Faculty & Graduate Students, UW-Madison, Department of Physics
Abstract: All admitted Ph.D. students for Fall 2021 will be invited for prospective student virtual visit days. Graduate students and faculty will receive more information as the dates approach.
Host: Michelle Holland, Graduate Program Coordinator
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Theory Seminar (High Energy/Cosmology)
Long Range Interactions in Cosmology: Implications for Neutrinos
Time: 2:00 pm
Place: For zoom link, sign up at:
Speaker: Jordi Salvadó, University of Barcelona
Abstract: Cosmology is well suited to study the effects of long range interactions due to the large densities in the early Universe. In this talk, we will explore how the energy density and equation of state of a fermion system diverge from the commonly assumed ideal gas form under the presence of scalar long range interactions with a range much smaller than cosmological scales. In this scenario, “small”-scale physics can impact our largest-scale observations. We will apply the formalism to self-interacting neutrinos, performing an analysis to present and future cosmological data. The results will show that the current cosmological neutrino mass bound is fully avoided in the presence of a long range interaction, opening the possibility for a laboratory neutrino mass detection in the near future. We will also see an interesting complementarity between neutrino laboratory experiments and the future EUCLID survey.
Host: Lars Aalsma
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Physics Department Colloquium
From galaxies to faces: recognizing the implications of Artificial Intelligence in astronomy and society
Time: 3:30 pm
Place: Zoom:
Speaker: Dr. Brian Nord, Fermilab
Abstract: Artificial Intelligence (AI) refers to a set of techniques that rely primarily on the data itself for the construction of a quantitative model. AI has arguably been in development for three quarters of a century, but there has been a recent resurgence in research and application. This current (third) wave of AI progress is marked by extraordinary results --- for example, in image analysis, language translation, and machine automation. Despite the aforementioned modest definition of AI, its potential to disrupt technologies, economies, and society is often presented as (nearly) unmatched in modern times, due in part to the versatility of the algorithms in modeling a wide variety of data. Similarly, there is great promise for applications across the sciences --- for example, simulations, image classification, and automated experimentation --- which are currently being investigated by researchers across the globe. Along with the significant promise of AI, comes great peril: in societal contexts, the consequences include enhanced surveillance, facial recognition, and automated weaponry. In science contexts, the issues are also significant and in many cases related --- for example, bias, lack of uncertainty quantification, and misuse. To take full advantage of the opportunities for AI to accelerate science and improve society, it's essential that we carefully guide its development. During this presentation, we will explore modern AI techniques, like neural networks, and review how they are being developed and deployed in astronomy. Then, we’ll discuss ideas for the future usage of AI in science, including technical barriers for long-term application. Finally, we’ll discuss the roles of scientists and academic communities in the development of AI algorithms.
Host: Keith Bechtol
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