Format results
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Geometry and Information in Precision Collider Physics
Benoit Assi - University of Cincinnati
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CP Violation and Fundamental Questions in Particle Physics
Claudio Manzari - University of California, Berkeley
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Artificial General Intelligence and the Future of Physics
Adam Brown - Stanford University
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Hunting New Physics in the Dark Universe
Elena Pinetti - Fermi National Accelerator Laboratory (Fermilab)
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Physics-Informed AI, AI for Physics: From Precision Cosmology to Accelerated Discovery
Biwei Dai - University of California, Berkeley
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Towards a Science of AI: Scaling laws and synthetic data
Maissam Barkeshli - University of California, Santa Barbara
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The Quantum Computing and AI Frontier
Shayan Majidy - Harvard University
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The search for axion dark matter
Benjamin Safdi - Massachusetts Institute of Technology (MIT)
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Geometry and Information in Precision Collider Physics
Benoit Assi - University of Cincinnati
The next era of collider physics will be limited less by what we can measure than by what we can reliably predict. The cascades of QCD radiation that fill every collision are typically simulated at the lowest orders in perturbation theory, with correspondingly large uncertainties. Hadronization is… -
CP Violation and Fundamental Questions in Particle Physics
Claudio Manzari - University of California, Berkeley
Despite its extraordinary success, the Standard Model leaves unanswered some of the deepest questions in fundamental physics. In this talk I will discuss how advances in astrophysical observations and precision flavor experiments are creating new opportunities to test proposed solutions to two of… -
Artificial General Intelligence and the Future of Physics
Adam Brown - Stanford University
Over the last half decade, the capabilities of large language models (LLMs) have leapt from preschooler to graduate student and beyond. This talk reviews recent progress in teaching LLMs to do science and reasoning, and speculates as to what it will mean for the future of theoretical physics if… -
Hunting New Physics in the Dark Universe
Elena Pinetti - Fermi National Accelerator Laboratory (Fermilab)
For decades, we have known that most of the matter in the Universe is invisible. This unseen component—dark matter—accounts for roughly 85% of all matter and plays a central role in shaping cosmic structure. Yet, despite decades of experimental effort and remarkable ingenuity, its fundamental nature… -
Error-correcting codes test the postulates of quantum statistical mechanics
Andrew Lucas
This colloquium is presented in collaboration with the Physics of Quantum Information II conference. -
Physics-Informed AI, AI for Physics: From Precision Cosmology to Accelerated Discovery
Biwei Dai - University of California, Berkeley
Deep generative models are emerging as powerful tools for solving physics problems, enabling new approaches to inference, sampling, anomaly detection, and signal reconstruction. In the first part of the talk, I will discuss how generative models, designed with physical principles such as symmetry… -
Towards a Science of AI: Scaling laws and synthetic data
Maissam Barkeshli - University of California, Santa Barbara
The stunning capabilities of modern AI systems give rise to many questions regarding how they work and how much more capable they can possibly get. One way to gain additional insight is via synthetic models of data with tunable complexity, which can capture the basic relevant structures of real data… -
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The Quantum Computing and AI Frontier
Shayan Majidy - Harvard University
Quantum computers promise to simulate quantum systems and answer open questions across science from condensed matter and quantum chemistry to particle physics and quantum gravity. Two problems stand in the way: how to build them, and how to use them. Each brings hard optimisation, inference, and… -
The Wide and Wonderful World of Optimal Transport Theory in Physics
Jessica Howard
Optimal transport (OT) theory, first conceived to solve problems of moving dirt, has since evolved into a powerful mathematical framework with far-reaching applications across machine learning, probability and statistics, and theoretical physics. In particle physics, OT underpins many modern machine… -
The search for axion dark matter
Benjamin Safdi - Massachusetts Institute of Technology (MIT)
Axions are some of the best-motivated beyond the Standard Model particle candidates at present. These ultralight particles may account for the cosmological dark matter and explain other outstanding problems in nature, such as the strong-CP problem; they also are now known to emerge generically in… -
AI for Formal Math, and Physics, and why they're different
As little as five years ago, the image of 'AI for Math' focused on specialty models that could discover interesting examples or constructions, for example, graphs with interesting parameters, where our intuition might be lacking but computer checking is simple. With large language models this has…