Asher Berlin (Fermilab)
https://lbnl.zoom.us/j/94928022788?pwd=emVQWG1mTnhSbHVqekVuenk0VEVQZz09
Particle Seminar – Speaker: Vincent Lee (N3AS), Title: Quantum Gravity Signals in 4D Einstein gravity from 2D JT gravity
Title: Quantum Gravity Signals in 4D Einstein gravity from 2D JT gravity Abstract: It is generally believed that quantum gravity fluctuations in a vacuum are immeasurably small from an effective field theory (EFT) perspective, as their size is suppressed by powers of the Planck mass. In this talk, we study quantum fluctuations in the lightcone metric of the 4-d Einstein-Hilbert … Read More
Particle Seminar: Jessica Howard (UCSB) – Note location: 50B-4205 – Understanding Neural Network Behavior with the Renormalization Group
Note: We will be in 50B-4205 this week. Title:Understanding Neural Network Behavior with the Renormalization Group Abstract:The growing presence and influence of machine learning in both science and society necessitates a better understanding of these algorithms. Interestingly, many neural network behaviors are reminiscent of physical phenomena, such as the empirically-observed approximate power law dependence of a network’s generalization performance on … Read More
Particle Seminar: TBD
https://lbnl.zoom.us/j/94928022788?pwd=emVQWG1mTnhSbHVqekVuenk0VEVQZz09
Particle Seminar: Huangyu Xiao (Fermilab), “Monopole Baryogenesis with a theta angle”
Title: Monopole Baryogenesis with a theta angle Abstract: Monopoles are generally expected in Grand Unified Theories (GUTs) where they can catalyze baryon decay at an unsuppressed rate by the Callan-Rubakov effect. For the first time, we show that this catalysis effect can generate the observed baryon asymmetry at GeV-scale temperatures. We study the minimal SU(5) GUT model and demonstrate that monopole-fermion … Read More
Particle Seminar: Kevin Langhoff (LBNL), “A Flavor of SO(10) Unification with a Spinor Higgs”
Title: A Flavor of SO(10) Unification with a Spinor Higgs Abstract: My talk will be focused towards a relatively large audience. I will briefly review grand unified theories (GUTs) and flavor model building within GUTs. Then I investigate the Higgs Parity Unification model. I’ll describe how 1) gauge coupling unification successfully predicts the QCD coupling to better than 1% accuracy, … Read More
Particle Seminar: Geraldine Servant (U of Hamburg), “Standard Model Baryon Number Violation at zero temperature from macroscopic out-of-equilibrium Higgs dynamics?”
Title: Standard Model Baryon Number Violation at zero temperature from macroscopic out-of-equilibrium Higgs dynamics? Abstract: Baryon number is very efficiently violated in the Standard Model by the chiral anomaly at high temperature through SU(2) vacuum transitions producing integer Chern-Simons number, the so-called sphaleron processes, which play a key role in essentially all models of baryogenesis, whether at the electroweak scale or … Read More
Particle Seminar: Yifan Chen (Niels Bohr), “Black Holes as Discovery Channels for New Particles”
Title: Black Holes as Discovery Channels for New Particles Abstract: The extreme environments near black holes (BHs) offer unique opportunities to probe fundamental physics. These regions can host extraordinarily high particle densities, effectively turning BHs into natural concentrators of new physics. Notable examples include the superradiant amplification of ultralight bosons, which can reach near–Planck-scale field strengths, and the adiabatic growth of dark … Read More
Particle Seminar: David Simmons-Duffin (Caltech), “Seeing through the confinement screen: DGLAP/BFKL mixing and light-ray matching in QCD”
Title: Seeing through the confinement screen: DGLAP/BFKL mixing and light-ray matching in QCDAbstract: We argue that collider observables such as hadron number flux can be matched onto a linear combination of detectors/light-ray operators in perturbative QCD. The spectrum of detectors in QCD is subtle, due to recombination between the DGLAP and BFKL trajectories. We explain how to define and renormalize these trajectories … Read More
Particle Seminar: Zhengkang Zhang (Utah), Title: Neural Networks, Scaling Laws and Effective Field Theories
Title: Neural Networks, Scaling Laws and Effective Field Theories Abstract: Starting from simple curve fitting problems, I will explain how modern AI works by learning a large number of features from data: wide neural networks fit data to linear combinations of many random features, and stacking layers to form deep neural networks allows the features to evolve according to data. It has been empirically observed … Read More