Talk Saves Lives: An Introduction to Suicide Prevention.

Suicide is the 11th leading cause of death in Maryland. Tragically, we have recently lost members of our physics community to suicide. Raising awareness is an important first step toward prevention.

This community-based presentation will cover the general scope of suicide, the research on prevention, and what people can do to fight suicide. Attendees will learn the risk and warning signs of suicide, and how together, we can help prevent it.

 

Mapping the Milky Way's Dark Matter Halo with Gaia

The Gaia mission is in the process of mapping nearly 1% of the Milky Way’s stars. This data set is unprecedented and provides a unique view into the formation history of our Galaxy and its associated dark matter halo. I will review results based on the most recent Gaia data release, demonstrating how the evolution of the Galaxy can be deciphered from the stellar remnants of massive satellite galaxies that merged with the Milky Way early on. The recent advancements in our understanding of the Galaxy's evolution suggest that a component of the local dark matter is not in equilibrium, as typically assumed, and instead exhibits distinctive dynamics. The updated dark matter map built from the Gaia data has ramifications for direct detection experiments, which search for the interactions of these particles in terrestrial targets.

Symmetries in quantum field theory and quantum gravity

Symmetry is one of the essential aspects of physics, but there is an old set of conjecture restricting the kinds of symmetry that are possible in a theory of quantum gravity: there can be no global symmetries, gauge symmetries can exist but only if there are dynamical objects that carry all possible charges, and any gauge groups must be compact. I will show that all three of these conjectures hold within our best-understood theory of quantum gravity, the "AdS/CFT correspondence". This will require a general discussion of what is meant by global and gauge symmetries, and I will also comment on various possible phenomenological applications of these ideas. This talk is based on recent work with Hirosi Ooguri.

Quantum Tools for the Life Sciences

Extreme Plasma Astrophysics: a New Frontier

Bright, rapid high-energy flares and other spectacular phenomena are powered by collective plasma processes near neutron stars (NSs) and black holes (BHs), including in multi-messenger sources like gravitational-wave-emitting NS mergers and PeV-neutrino-producing blazars. While our understanding of these processes has been informed by traditional (e.g., space or fusion) plasma research, the physical conditions in plasmas around BHs and NSs are so extreme that traditional intuition often fails and a richer physical framework is required. Extreme astrophysical plasmas are relativistic, interact with radiation, and may be subject to QED pair-production effects. Studying collective plasma processes with these “exotic” effects constitutes the realm of Extreme Plasma Astrophysics. Rapid progress in exploring this new frontier is now being made thanks to concerted, vigorous theoretical efforts and computational breakthroughs due to the advent of novel first-principles relativistic kinetic plasma codes incorporating radiation and QED pair creation. Laser plasma experiments may soon also contribute to this revolution. I will describe these exciting developments, illustrating them with our recent kinetic studies of relativistic magnetic reconnection in NS magnetospheres and accreting BH coronae with radiation and pair-creation effects, and of radiative relativistic turbulence. I will end by outlining the future prospects of this vibrant Extreme Plasma Astrophysics research program.

No colloquium

No colloquium

Collision Course: Particle Physics Meets Machine Learning

Modern machine learning has had an outsized impact on many scientific fields, and particle physics is no exception. What is special about particle physics, though, is the vast amount of theoretical and experimental knowledge that we already have about many problems in the field. In this colloquium, I present two cases studies involving quantum chromodynamics (QCD) at the Large Hadron Collider (LHC), highlighting the fascinating interplay between theoretical principles and machine learning strategies. First, by cataloging the space of all possible QCD measurements, we (re)discovered technology relevant for self-driving cars. Second, by quantifying the similarity between two LHC collisions, we unlocked a class of nonparametric machine learning techniques based on optimal transport. In addition to providing new quantitative insights into QCD, these techniques enable new ways to visualize data from the LHC.

Proving Einstein Right: The Daring Expeditions that Changed How We Look at the Universe

TBA

TBA

TBA

Science meets Politics: The status of clean energy innovation in Maryland