Condensed Matter

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

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

This course introduces the functional integral formalism, the renormalization group, and non-abelian gauge theory. Additional topics may be covered as time allows. Instructor: Francois David / 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

The aim of this course is to explore the main ideas of the statistical physics approach to critical phenomena. We will discuss phase transitions, using the ferromagnetic phase transition and the Ising model as our primary example, with particular emphasis on the renormalisation group approach. Instructor: Emilie Huffman / Maite Dupuis Students who are not part of the PSI MSc program should review enrollment and course format information here: https://perimeterinstitute.ca/graduate-courses

The first half of the course explains why fields are desirable when quantum mechanics meets special relativity. The second half introduces different kinds of spinor fields and their interactions. Instructor: 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

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.

Quantum phases have become a staple of modern physics, thanks to their appearance in fields as diverse as condensed matter physics, quantum field theory, quantum information processing, and topology. The description of quantum phases of matter requires novel mathematical tools that lie beyond the old symmetry breaking perspective on phases. Techniques from topological field theory, homotopy theory, and (higher) category theory show great potential for advancing our understanding of the characterization and classification of quantum phases. The goal of this workshop is to bring together experts from across mathematics and physics to discuss recent breakthroughs in these mathematical tools and their application to physical problems. 

 

Scientific Organizers

Lukas Mueller
Alex Turzillo
Davide Gaiotto
 

Sponsored in part by the Simons Collaboration on Global Categorical Symmetries 

 

 

Machine learning techniques are rapidly being adopted into the field of quantum many-body physics, including condensed matter theory, experiment, and quantum information science. The steady increase in data being produced by highly-controlled quantum experiments brings the potential of machine learning algorithms to the forefront of scientific advancement. Particularly exciting is the prospect of using machine learning for the discovery and design of molecules, quantum materials, synthetic matter, and computers. In order to make progress, the field must address a number of fundamental questions related to the challenges of studying many-body quantum mechanics using classical computing algorithms and hardware.

The goal of this conference is to bring together experts in computational physics, machine learning, and quantum information, to make headway on a number of related topics, including:
- Data-drive quantum state reconstruction
- Machine learning strategies for quantum error correction and quantum control
- Neural-network inspired wavefunctions
- Near-term prospects for data from quantum devices
- Machine learning for quantum algorithm discovery

pirsa.org/C23002

Territorial Land Acknowledgement

Perimeter Institute acknowledges that it is situated on the traditional territory of the Anishinaabe, Haudenosaunee, and Neutral peoples.

Perimeter Institute is located on the Haldimand Tract. After the American Revolution, the tract was granted by the British to the Six Nations of the Grand River and the Mississaugas of the Credit First Nation as compensation for their role in the war and for the loss of their traditional lands in upstate New York. Of the 950,000 acres granted to the Haudenosaunee, less than 5 percent remains Six Nations land. Only 6,100 acres remain Mississaugas of the Credit land. 

We thank the Anishinaabe, Haudenosaunee, and Neutral peoples for hosting us on their land.

This meeting will bring together researchers from the quantum technology, atomic physics, and fundamental physics communities to discuss how quantum simulation can be used to gain new insight into the physics of black holes and the early Universe. The core program of the workshop is intended to deepen collaboration between the UK-based Quantum Simulators for Fundamental Physics (QSimFP; https://www.qsimfp.org) consortium and researchers at Perimeter Institute and neighbouring institutions. The week-long conference will consist of broadly-accessible talks on work within the consortium and work within the broader community of researchers interested in quantum simulation, as well as a poster session and ample time for discussion and collaboration

pirsa.org/C23019

Territorial Land Acknowledgement

Perimeter Institute acknowledges that it is situated on the traditional territory of the Anishinaabe, Haudenosaunee, and Neutral peoples.

Perimeter Institute is located on the Haldimand Tract. After the American Revolution, the tract was granted by the British to the Six Nations of the Grand River and the Mississaugas of the Credit First Nation as compensation for their role in the war and for the loss of their traditional lands in upstate New York. Of the 950,000 acres granted to the Haudenosaunee, less than 5 percent remains Six Nations land. Only 6,100 acres remain Mississaugas of the Credit land. 

We thank the Anishinaabe, Haudenosaunee, and Neutral peoples for hosting us on their land.

In this mini course, I shall introduce the basic concepts in 2D topological orders by studying simple models of topological orders and then introduce topological quantum computing based on Fibonacci anyons. Here is the (not perfectly ordered) syllabus.                   

• Overview of topological phases of matter
• Z2 toric code model: the simplest model of 2D topological orders
• Quick generalization to the quantum double model
• Anyons, topological entanglement entropy, S and T matrices
• Fusion and braiding of anyons: quantum dimensions, pentagon and hexagon identities
• Fibonacci anyons
• Topological quantum computing

The goal of this conference is for quantum matter researchers at Perimeter, University of British Columbia, and University of Toronto to share their recent work with each other, to facilitate discussion and collaboration.

https://pirsa.org/C22033

Territorial Land Acknowledgement

Perimeter Institute acknowledges that it is situated on the traditional territory of the Anishinaabe, Haudenosaunee, and Neutral peoples.

Perimeter Institute is located on the Haldimand Tract. After the American Revolution, the tract was granted by the British to the Six Nations of the Grand River and the Mississaugas of the Credit First Nation as compensation for their role in the war and for the loss of their traditional lands in upstate New York. Of the 950,000 acres granted to the Haudenosaunee, less than 5 percent remains Six Nations land. Only 6,100 acres remain Mississaugas of the Credit land. 

We thank the Anishinaabe, Haudenosaunee, and Neutral peoples for hosting us on their land.