Format results
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Talk
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Lecture - Cosmology, PHYS 621
Neal Dalal Perimeter Institute for Theoretical Physics
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Lecture - Cosmology, PHYS 621
Neal Dalal Perimeter Institute for Theoretical Physics
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Lecture - Cosmology, PHYS 621
Neal Dalal Perimeter Institute for Theoretical Physics
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Lecture - Cosmology, PHYS 621
Neal Dalal Perimeter Institute for Theoretical Physics
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Lecture - Cosmology, PHYS 621
Neal Dalal Perimeter Institute for Theoretical Physics
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Lecture - Cosmology, PHYS 621
Neal Dalal Perimeter Institute for Theoretical Physics
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Lecture - Cosmology, PHYS 621
Neal Dalal Perimeter Institute for Theoretical Physics
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Lecture - Cosmology, PHYS 621
Neal Dalal Perimeter Institute for Theoretical Physics
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Talk
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Lecture - Causal Inference, PHYS 777
Robert Spekkens Perimeter Institute for Theoretical Physics
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Lecture - Causal Inference, PHYS 777
Robert Spekkens Perimeter Institute for Theoretical Physics
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Lecture - Causal Inference, PHYS 777
Robert Spekkens Perimeter Institute for Theoretical Physics
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Lecture - Causal Inference, PHYS 777
Robert Spekkens Perimeter Institute for Theoretical Physics
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Lecture - Causal Inference, PHYS 777
Robert Spekkens Perimeter Institute for Theoretical Physics
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Lecture - Causal Inference, PHYS 777
Robert Spekkens Perimeter Institute for Theoretical Physics
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Lecture - Causal Inference, PHYS 777
Robert Spekkens Perimeter Institute for Theoretical Physics
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Lecture - Causal Inference, PHYS 777
Robert Spekkens Perimeter Institute for Theoretical Physics
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Talk
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Lecture - AdS/CFT, PHYS 777
David Kubiznak Charles University
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Lecture - AdS/CFT, PHYS 777
David Kubiznak Charles University
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Lecture - AdS/CFT, PHYS 777
David Kubiznak Charles University
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Lecture - AdS/CFT, PHYS 777
David Kubiznak Charles University
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Lecture - AdS/CFT, PHYS 777
David Kubiznak Charles University
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Lecture - AdS/CFT, PHYS 777
David Kubiznak Charles University
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Lecture - AdS/CFT, PHYS 777
David Kubiznak Charles University
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Lecture - AdS/CFT, PHYS 777
David Kubiznak Charles University
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Talk
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Extra Lecture - Quantum Matter, PHYS 777 2/2
Chong Wang Perimeter Institute for Theoretical Physics
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Extra Lecture - Quantum Matter, PHYS 777 1/2
Chong Wang Perimeter Institute for Theoretical Physics
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Lecture - Quantum Matter, PHYS 777
Chong Wang Perimeter Institute for Theoretical Physics
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Lecture - Quantum Matter, PHYS 777
Chong Wang Perimeter Institute for Theoretical Physics
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Lecture - Quantum Matter, PHYS 777
Chong Wang Perimeter Institute for Theoretical Physics
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Lecture - Quantum Matter, PHYS 777
Chong Wang Perimeter Institute for Theoretical Physics
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Lecture - Quantum Matter, PHYS 777
Chong Wang Perimeter Institute for Theoretical Physics
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Lecture - Quantum Matter, PHYS 777
Chong Wang Perimeter Institute for Theoretical Physics
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Talk
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Lecture - Quantum Gravity, PHYS 644
Aldo Riello Perimeter Institute for Theoretical Physics
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Lecture - Quantum Gravity, PHYS 644
Aldo Riello Perimeter Institute for Theoretical Physics
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Lecture - Quantum Gravity, PHYS 644
Aldo Riello Perimeter Institute for Theoretical Physics
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Lecture - Quantum Gravity, PHYS 644
Aldo Riello Perimeter Institute for Theoretical Physics
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Lecture - Quantum Gravity, PHYS 644
Aldo Riello Perimeter Institute for Theoretical Physics
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Lecture - Quantum Gravity, PHYS 644
Aldo Riello Perimeter Institute for Theoretical Physics
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Lecture - Quantum Gravity, PHYS 644
Aldo Riello Perimeter Institute for Theoretical Physics
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Lecture - Quantum Gravity, PHYS 644
Aldo Riello Perimeter Institute for Theoretical Physics
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Talk
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Causal Inference Meets Quantum Physics
Robert Spekkens Perimeter Institute for Theoretical Physics
PIRSA:25040086 -
Creativity by Compositionality in Generative Diffusion Models
Alessandro Favero École Polytechnique Fédérale de Lausanne
PIRSA:25040088 -
Towards a “Theoretical Minimum” for Physicists in AI
Yonatan Kahn Princeton University
PIRSA:25040089 -
Solvable models of scaling and emergence in deep learning
Cengiz Pehlevan Harvard University
PIRSA:25040091 -
Architectural bias in a transport-based generative model : an asymptotic perspective
Hugo Cui Harvard University
PIRSA:25040092 -
Statistical physics of learning with two-layer neural networks
Bruno Loureiro École Normale Supérieure - PSL
PIRSA:25040093 -
Renormalization Group Flows: from Optimal Transport to Diffusion Models
Jordan Cotler Harvard University
PIRSA:25040095
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Talk
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Panel Discussion
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Shirley Ho Flatiron Institute
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Vicky Kalogera Northwestern University
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Roger Melko University of Waterloo
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Jesse Thaler Massachusetts Institute of Technology (MIT)
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Marcela Carena Perimeter Institute for Theoretical Physics
PIRSA:25040079 -
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Opening Remarks
PIRSA:25040109 -
EAIRA: Establishing a methodology to evaluate LLMs as research assistants.
Frank Cappello Argonne National Laboratory
PIRSA:25040059 -
State of AI Reasoning for Theoretical Physics - Insights from the TPBench Project
Moritz Munchmeyer University of Wisconsin–Madison
PIRSA:25040061 -
UniverseTBD: Democratising Science with AI & Why Stories Matter
Ioana Ciuca Stanford University
PIRSA:25040062 -
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Talk
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Lecture - Quantum Information, PHYS 635
Alex May Perimeter Institute for Theoretical Physics
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Lecture - Quantum Information, PHYS 635
Alex May Perimeter Institute for Theoretical Physics
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Talk
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Lecture - Strong Gravity, PHYS 777
William East Perimeter Institute for Theoretical Physics
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Lecture - Strong Gravity, PHYS 777
William East Perimeter Institute for Theoretical Physics
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Lecture - Strong Gravity, PHYS 777
William East Perimeter Institute for Theoretical Physics
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Lecture - Strong Gravity, PHYS 777
William East Perimeter Institute for Theoretical Physics
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Lecture - Strong Gravity, PHYS 777
William East Perimeter Institute for Theoretical Physics
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Lecture - Strong Gravity, PHYS 777
William East Perimeter Institute for Theoretical Physics
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Lecture - Strong Gravity, PHYS 777
William East Perimeter Institute for Theoretical Physics
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Lecture - Strong Gravity, PHYS 777
William East Perimeter Institute for Theoretical Physics
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Talk
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Lecture - Mathematical Physics, PHYS 777
Kevin Costello Perimeter Institute for Theoretical Physics
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Lecture - Mathematical Physics, PHYS 777
Kevin Costello Perimeter Institute for Theoretical Physics
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Lecture - Mathematical Physics, PHYS 777
Kevin Costello Perimeter Institute for Theoretical Physics
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Lecture - Mathematical Physics, PHYS 777
Kevin Costello Perimeter Institute for Theoretical Physics
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Lecture - Mathematical Physics, PHYS 777
Kevin Costello Perimeter Institute for Theoretical Physics
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Lecture - Mathematical Physics, PHYS 777
Kevin Costello Perimeter Institute for Theoretical Physics
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Lecture - Mathematical Physics, PHYS 777
Kevin Costello Perimeter Institute for Theoretical Physics
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Lecture - Mathematical Physics, PHYS 777
Kevin Costello Perimeter Institute for Theoretical Physics
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Talk
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Lecture - Quantum Field Theory III - PHYS 777
Mykola Semenyakin Perimeter Institute for Theoretical Physics
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Lecture - Quantum Field Theory III - PHYS 777
Mykola Semenyakin Perimeter Institute for Theoretical Physics
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Lecture - Quantum Field Theory III - PHYS 777
Mykola Semenyakin Perimeter Institute for Theoretical Physics
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Lecture - Quantum Field Theory III - PHYS 777
Mykola Semenyakin Perimeter Institute for Theoretical Physics
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Lecture - Quantum Field Theory III - PHYS 777
Mykola Semenyakin Perimeter Institute for Theoretical Physics
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Lecture - Quantum Field Theory III - PHYS 777 (extra Lecture)
Mykola Semenyakin Perimeter Institute for Theoretical Physics
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Lecture - Quantum Field Theory III - PHYS 777
Mykola Semenyakin Perimeter Institute for Theoretical Physics
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Lecture - Quantum Field Theory III - PHYS 777
Mykola Semenyakin Perimeter Institute for Theoretical Physics
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Talk
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Lecture - Machine Learning, PHYS 777
Mohamed Hibat Allah University of Waterloo
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Lecture - Machine Learning, PHYS 777
Mohamed Hibat Allah University of Waterloo
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Lecture - Machine Learning, PHYS 777
Mohamed Hibat Allah University of Waterloo
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Lecture - Machine Learning, PHYS 777
Mohamed Hibat Allah University of Waterloo
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Lecture - Machine Learning, PHYS 777
Mohamed Hibat Allah University of Waterloo
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Lecture - Machine Learning, PHYS 777
Mohamed Hibat Allah University of Waterloo
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Lecture - Machine Learning, PHYS 777
Mohamed Hibat Allah University of Waterloo
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Lecture - Machine Learning, PHYS 777
Mohamed Hibat Allah University of Waterloo
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Quantum Matter (Elective), PHYS 777, March 31 - May 2, 2025
This course will cover quantum phases of matter, with a focus on long-range entangled states, topological states, and quantum criticality. Instructor: Chong Wang/Subhayan Sahu Students who are not part of the PSI MSc program should review enrollment and course format information here: https://perimeterinstitute.ca/graduate-courses -
Quantum Gravity (Elective), PHYS 644, February 24 - March 28, 2025
The main goal of this course is to show in which ways General Relativity (GR) is similar, and especially in which ways it is different, from other gauge theories. The largest component of the course is dedicated to studying the specific symmetry structure of GR and how it intimately relates to its dynamics. To do so, we will introduce a host of concepts and techniques, broadly (and loosely) known under the name of “Covariant Phase Space Method”. This provides a different perspective on GR’s physics, a perspective in which phase space, rather than spacetime, is front and center. Along the way we will take a few detours: we will explore (parts of) the historical debate on whether gravity should be quantized at all, discuss how to think of time evolution when there is no absolute time, and go through Wald’s proposal of black hole entropy as a Noether charge. The intended outcome of the course is to provide a new perspective on GR which, hopefully, will inform you on why it is much harder to quantize than other theories – especially from a non-perturbative perspective. In this sense the course always keeps an eye on Quantum Gravity, even though there will be very little “quantum” in it. It is also a course that does not hinge on any specific approach to the quantization of gravity. Also, it is worth noting that the covariant phase space techniques are broadly used in the current literature on the black hole information paradox, soft symmetries, and holography, and is therefore a useful tool to learn if you are interested in any of these topics. Instructor: Aldo Riello Students who are not part of the PSI MSc program should review enrollment and course format information here: https://perimeterinstitute.ca/graduate-courses -
Cosmology (Elective), PHYS 621, March 31 - May 2, 2025
This course in Cosmology provides a theoretical overview of the standard cosmological model. Key topics include the FRW metric and the homogeneous universe, the thermal history of the universe (with an emphasis on the hot Big Bang and equilibrium thermodynamics), inflation and scalar field dynamics, along with selected aspects of cosmological perturbation theory (time permitting). Instructor: Neal Dalal/Ghazal Geshnizjani Students who are not part of the PSI MSc program should review enrollment and course format information here: https://perimeterinstitute.ca/graduate-courses -
Causal Inference (Elective), PHYS 777, March 31 - May 2, 2025
Can the effectiveness of a medical treatment be determined without the expense of a randomized controlled trial? Can the impact of a new policy be disentangled from other factors that happen to vary at the same time? Questions such as these are the purview of the field of causal inference, a general-purpose science of cause and effect, applicable in domains ranging from epidemiology to economics. Researchers in this field seek in particular to find techniques for extracting causal conclusions from statistical data. Meanwhile, one of the most significant results in the foundations of quantum theory—Bell’s theorem—can also be understood as an attempt to disentangle correlation and causation. Recently, it has been recognized that Bell’s result is an early foray into the field of causal inference and that the insights derived from almost 60 years of research on his theorem can supplement and improve upon state-of-the-art causal inference techniques. In the other direction, the conceptual framework developed by causal inference researchers provides a fruitful new perspective on what could possibly count as a satisfactory causal explanation of the quantum correlations observed in Bell experiments. Efforts to elaborate upon these connections have led to an exciting flow of techniques and insights across the disciplinary divide. This course will explore what is happening at the intersection of these two fields. Instructor: Robert Spekkens/Bindiya Arora Students who are not part of the PSI MSc program should review enrollment and course format information here: https://perimeterinstitute.ca/graduate-courses -
AdS/CFT (Elective), PHYS 777, March 31 - May 2, 2025
We will cover the basics of the gauge/gravity duality, including some of the following aspects: holographic fluids, applications to condensed matter systems, entanglement entropy, and recent advances in understanding the black hole information paradox. Instructor: David Kubiznak/Gang Xu Students who are not part of the PSI MSc program should review enrollment and course format information here: https://perimeterinstitute.ca/graduate-courses -
Theory + AI Workshop: Theoretical Physics for AI
This 5-day program will explore the intersection of AI and fundamental theoretical physics. The event will feature two components, a symposium and a workshop, centered around two complementary themes: AI for theoretical physics and theoretical physics for AI.
The program will begin on April 7 and 8 with a large symposium with speakers and panel discussions focusing on the promise of AI to accelerate progress in theoretical physics. These talks will address the possibilities and challenges associated with AI ‘doing science.’ The event will bring together physicists, engineers, AI researchers, and entrepreneurs to collect different perspectives on what the future of theoretical physics will look like, the engineering challenges we should expect along the way, what tools and collaborations will be needed to help get us there, and what exciting steps are already underway.
Registration for the symposium is available on the symposium website.
The symposium will be followed by a workshop on April 9, 10, 11 focusing on developing a theoretical framework for AI enabling the development of reliable, robust, and interpretable AI models for physics. Recent advances in theoretical foundations of AI, inspired by techniques from string theory, quantum field theory (QFT), and statistical physics, have uncovered parallels between AI systems and physical theories, utilizing methods like renormalization group (RG) flows, Feynman path integrals etc. to deepen understanding of deep neural networks (DNNs), generative AI (e.g., LLMs and diffusion models), and scaling laws. Key topics include physics-informed optimization and learning, the role of RG and QFT for DNNs and generative AI, and the application of physics to AI interpretability. Through interdisciplinary dialogue, the event aims to foster collaborations, advance the theoretical foundations of AI, and explore its potential in areas like theoretical physics and mathematics. Speakers:- David Berman (Queen Mary University of London)
- Blake Bordelon (Harvard University)
- Jordan Cotler (Harvard University)
- Hugo Cui (Harvard University)
- Alessandro Favero (EPFL)
- Ro Jefferson (Utrecht University)
- Yonatan Kahn (University of Toronto)
- Dmitry Krotov (IBM)
- Bruno Loureiro (École Normale Supérieure in Paris)
- Luisa Lucie-Smith (The University of Hamburg)
- Cengiz Pehlevan (Harvard University)
- Rob Spekkens (Perimeter Institute)
Scientific Organizers:
- Anindita Maiti (Perimeter Institute)
- Matt Johnson (Perimeter Institute)
- Sabrina Pasterski (Perimeter Institute)
Advisory Committee:
- Achim Kempf (University of Waterloo)
- Cengiz Pehlevan (Harvard University)
- Hiranya Peiris (University of Cambridge)
- Roger Melko (University of Waterloo)
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Theory + AI Symposium
As Perimeter enters its 25th year, we invite you to imagine what theoretical physics research will look like 25 years from now. On April 7 and 8, Perimeter will be hosting a symposium with speakers and panel discussions focusing on the promise of AI to accelerate progress in theoretical physics. These talks will address the possibilities and challenges associated with AI ‘doing science.’ The event will bring together physicists, engineers, AI researchers, and entrepreneurs to collect different perspectives on what the future of theoretical physics will look like, the engineering challenges we should expect along the way, what tools and collaborations will be needed to help get us there, and what exciting steps are already underway.
Confirmed Speakers:
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Frank Cappello (Argonne National Laboratory)
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Yuri Chervonyi (Deep Mind)
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Ioana Ciuca (Stanford University)
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Deyan Ginev (LaTeXML)
- Geoffrey Hinton (University of Toronto)
- Shirley Ho (Polymathic & Simons Foundation)
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Vicky Kalogera (Northwestern University)
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Jared Kaplan* (Anthropic)
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Peter Koepke (University of Bonn)
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Roger Melko (University of Waterloo)
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Moritz Munchmeyer (University of Wisconsin–Madison)
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Axton Pitt (Litmaps)
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Xiaoliang Qi (Stanford University)
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Oleg Ruchayskiy (Niels Bohr Institute)
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Gaurav Sahu (MILA)
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Steinn Sigurdsson (arXiv)
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Jesse Thaler (Massachusetts Institute of Technology)
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Stephen Wolfram* (Wolfram Research)
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Richard Zanibbi (Rochester Institute of Technology)
*virtual presentation
Scientific Organizers:-
Matthew Johnson (Perimeter Institute)
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Anindita Maiti (Perimeter Institute)
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Sabrina Pasterski (Perimeter Institute)
Advisory Committee:- Mykola Semenyakin (Perimeter Institute)
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Quantum Field Theory III, PHYS 777-, February 24 - March 28, 2025
The course will cover the basics of conformal field theories and also some applications, including exact computations of the critical exponents in 2d statistical models. Instructor: Jaume Gomis/Mykola Semenyakin Students who are not part of the PSI MSc program should review enrollment and course format information here: https://perimeterinstitute.ca/graduate-courses -
Machine Learning (Elective), PHYS 777, February 24 - March 28, 2025
Machine learning has become a very valuable toolbox for scientists including physicists. In this course, we will learn the basics of machine learning with an emphasis on applications for many-body physics. At the end of this course, you will be equipped with the necessary and preliminary tools for starting your own machine learning projects. Instructor: Mohamed Hibat Allah Students who are not part of the PSI MSc program should review enrollment and course format information here: https://perimeterinstitute.ca/graduate-courses -
Quantum Information (Elective), PHYS 635, February 24 - March 28, 2025
We look to understand the possibilities and limits of quantum information processing, and how an information theory perspective can inform theoretical physics. Topics covered include: entanglement, tools for measuring nearness of quantum states, characterizing the most general possible quantum operations, entropy and measuring information, the stabilizer formalism, quantum error-correcting codes, the theory of computation, quantum algorithms, classical and quantum complexity. Instructor: Alex May/Bindiya Arora Students who are not part of the PSI MSc program should review enrollment and course format information here: https://perimeterinstitute.ca/graduate-courses -
Strong Gravity (Elective), PHYS 777, February 24 - March 28, 2025
This course will introduce some advanced topics in general relativity related to describing gravity in the strong field and dynamical regime. Topics covered include properties of spinning black holes, black hole thermodynamics and energy extraction, how to define horizons in a dynamical setting, formulations of the Einstein equations as constraint and evolution equations, and gravitational waves and how they are sourced. Instructor: William East/Ghazal Geshnizjani Students who are not part of the PSI MSc program should review enrollment and course format information here: https://perimeterinstitute.ca/graduate-courses -
Mathematical Physics (Elective), PHYS 777, March 31 - May 2, 2025
We will discuss mathematical aspects of classical and quantum field theory, including topics such as: symplectic manifolds and the phase space, symplectic reduction, geometric quantization, Chern-Simons theory, and others. Instructor: Kevin Costello/Mykola Semenyakin Students who are not part of the PSI MSc program should review enrollment and course format information here: https://perimeterinstitute.ca/graduate-courses