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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

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

Interactive Theorem Provers (or Proof Assistants) are tools that verify and partially automate mathematical proofs. The process of encoding mathematics into these systems, known as formalisation, has gained significant interest due to its role in proof verification, generating verified code for computer algebra systems, and expanding digital mathematical libraries. It seems likely with the growth in sophistication of proof assistants, and progress of Generative AI technologies, interactive theorem provers will become a useful aide for research and teaching of mathematics.  Lean, a leading proof assistant, has grown in popularity thanks to its extensive mathlib library, which now covers most undergraduate mathematics and beyond. Notable milestones include the Liquid Tensor Experiment, which formalised a key result by Fields medalist Peter Scholze, and the rapid formalisation of the Polynomial Freiman-Ruzsa Conjecture led by Terry Tao.The goal of the workshop is to introduce mathematicia...

This is an annual discussion meeting of the Indian statistical physics community attended by scientists, postdoctoral fellows and graduate students, from across the country, working in the broad area of statistical physics.This meeting will be the 10th in the series. The following list of topics, that are covered in STATPHYS meetings of the International Union of Pure and Applied Physics, will be covered in this discussion meeting.General and mathematical aspectsRigorous results, exact solutions, probability theory, stochastic field theory, phase transitions and critical phenomena at equilibrium, information theory, optimization, etc.Out-of-equilibrium aspectsDriven systems, transport theory, relaxation and response dynamics, random processes, anomalous diffusion, fluctuation theorems, large deviations, out-of-equilibrium phase transitions, etc.Quantum fluids and condensed matterStrongly correlated electrons, cold atoms, graphene, mesoscopic quantum phenomena, fractional quantum Hall e...

The Turing lectures will be delivered by Prof. Gabriel Mindlin, University of Buenos Aires, Argentina, on the topic of The Physics of Birdsong. His recent work on the recovery of the songs of extinct species has received much attention and acclaim. He is an acknowledged expert in the field and is also the winner ofthe ICTP prize for his work on the subject and numerous other honours. The Turing lectures are expected to provide an overview of the neurophysical mechanisms that lead to the production of birdsong, the acoustic effects that the avian vocal organ generates, and the neural instructions needed to drive it. This topic draws on analysis and techniques from neuroscience, dynamics, and data science. Hence the discussion meeting  draws on speakers from all three topics. In addition to the tentative list of invited speakers below, we hope to invite about 15 researchers, consisting of young faculty, students and postdoctoral fellows with background in the above to participate in the ...

The Square Kilometre Array (SKA), set to begin operations in 2027, will be the world’s largest radio telescope marking one of the great scientific and engineering feats of the 21st century. The SKA will advance a wide range of research areas within astronomy, with a major focus on cosmology and radio continuum science at low and mid frequencies. Despite their different objectives, these two fields share a substantial overlap and thus stand to benefit from collaborative efforts in joint observation strategies, data calibration, and innovative analysis techniques.This two week long program aims to bring together national and international experts in radio cosmology and continuum science, fostering collaboration and training the next generation of researchers in these areas. The program will have two main components: a program and a school.The program (7-11 April 2025) will focus on the current state of observation, modelling, and inference tools for radio cosmology and continuum science....

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)

 

 

*virtual presentation

Scientific Organizers:

• Matthew Johnson (Perimeter Institute) 

• Anindita Maiti (Perimeter Institute) 

• Sabrina Pasterski (Perimeter Institute)

Advisory Committee:

• Mykola Semenyakin (Perimeter Institute)

 

We are living in an exciting era of great discoveries in the field of gravitational physics. The detection of gravitational waves by the LIGO-VIRGO-KAGRA (LVK) collaboration starting from  2016 has already led to an enormous interest in various aspects of the physics of compact objects. The recent observations of the shadows of the galactic centers for M87 and Milky Way, by the Event Horizon Telescope (EHT), have further resulted into diverse research programs on the nature of compact objects. The primary emphasis of these observations is to test the theory of general relativity at the strong-field regime and to understand the nature of the astrophysical compact objects. Several recent developments led to the extensive use of various new mathematical and computational techniques to probe the physics associated with these compact objects. The primary motivation of the school would be to learn from leading researchers about several crucial aspects of the physics of compact objects. The p...

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 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

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