Physics

Learn more about the benefits of creating an accessible environment and how you play a part. Dr. Mahadeo Sukhai and Ainsley Latour are scientists, researchers, educators and IDEA professionals, who are passionate about and committed to inclusion in the scientific research and training enterprise. 

• Learning Objective 1 – provide an understanding of the “leaky funnel” in STEM training for persons with disabilities
• Learning Objective 2 – provide an overview of the principles underpinning a culture of accessibility and inclusion in the sciences
• Learning Objective 3 – provide an appreciation for the importance of accessibility in scientific conferences and publications

Dr. Mahadeo A. Sukhai (He/Him), Ph.D. is the world’s first congenitally blind geneticist. Dr. Sukhai is Vice-President Research & International Affairs and Chief Accessibility Officer for the CNIB (Canadian National Institute for the Blind), having previously served as a researcher in cancer genomics at the University Health Network in Toronto. Dr. Sukhai also holds an adjunct faculty appointment in the Department of Ophthalmology, School of Medicine, Queens University (Kingston, ON, Canada), as well as additional Adjunct roles in the Faculty of Business and Information Technology at Ontario Tech University and in the Inclusive Design Program at OCAD University. In his role at CNIB, Dr. Sukhai is responsible for organizational employee culture-building strategy related to inclusion, accessibility and employee wellness. Dr. Sukhai is the Principal Investigator for "Creating a Culture of Accessibility in the Sciences," a book based on his ground-breaking work on access to science within higher education, and serves as the principal investigator for national projects to examine accessibility and inclusion within science education and healthcare. Dr. Sukhai co-founded IDEA-STEM, and INOVA, the international Network of researchers with Visual impairments and their Allies, a new professional society with the mission to improve accessibility and inclusion in the biomedical sciences for researchers with vision loss. Dr. Sukhai is the External Co-Chair for the Canadian Institutes of Health Research External Advisory Committee on Accessibility and Systemic Ableism and the Chair of the Employment Technical Committee for Accessibility Standards Canada.

Ms. Ainsley R. Latour (She/Her), B.Ed., MLT, M.Sc. is the president and co-founder of IDEA-STEM, an organization created to enhance the participation and inclusion for people with disabilities in STEM.  She identifies as hard of hearing and neurodiverse.  She also serves on the Government of Ontario’s AODA Post-Secondary Education Standards Development Committee. Ainsley's work on the experience of students with disabilities in Canada has been presented at national and international conferences on science and disability, including SciAccess 2019 and 2020, the ISLAND 2020 conference, and the American Association for the Advancement of Science (2018, 2019 and 2021).  She also maintains a practice as a licensed cytogenetic and molecular genetic technologist (MLT).  She holds two undergraduate degrees, two graduate diplomas and will graduate soon with a masters in marine environmental genetics from the Memorial University of Newfoundland.

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Zoom link:  https://pitp.zoom.us/j/99867497693?pwd=ZDRkdE44dVBWRDdtS3J3ZzFOMFlHZz09

This session will introduce the grad student seminar series, include an interactive session focusing on thoughts and ideas for effective preparation and presentation, and will gauge students' interest about upcoming science outreach activities.

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Zoom link https://pitp.zoom.us/j/95397824623?pwd=LzViSVBpTXJzcjZXbjlhdzZKMk9Ndz09

Numerical simulations of collision events within the ATLAS experiment have played a pivotal role in shaping the design of future experiments and analyzing ongoing ones. However, the quest for accuracy in describing Large Hadron Collider (LHC) collisions comes at an imposing computational cost, with projections estimating the need for millions of CPU-years annually during the High Luminosity LHC (HL-LHC) run. Simulating a single LHC event with Geant4 currently devours around 1000 CPU seconds, with calorimeter simulations imposing substantial computational demands. To address this challenge, we propose a Quantum-Assisted deep generative model. Our model marries a variational autoencoder (VAE) on the exterior with a Restricted Boltzmann Machine (RBM) in the latent space, delivering enhanced expressiveness compared to conventional VAEs. The RBM nodes and connections are meticulously engineered to enable the use of qubits and couplers on D-Wave's Pegasus Quantum Annealer. We also provide preliminary insights into the requisite infrastructure for large-scale deployment.

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Zoom link https://pitp.zoom.us/j/97724484247?pwd=Witua1lKcHlrc3JDNHNDWXpHYkVvQT09

How did the universe begin? How did it evolve to what we see now?

There was a time when few people believed such questions could even be posed in scientific terms. Now, as increasingly precise instruments deliver their treasure trove of data, the answers may be within reach.

On Wednesday, October 25, Perimeter Director Emeritus Neil Turok will tackle this intriguing topic in a Perimeter Institute Public Lecture, “Secrets of the Universe: Hiding in Plain Sight?”

The performance of neural networks like large language models (LLMs) is governed by "scaling laws": the error of the network, averaged across the whole dataset, drops as a power law in the number of network parameters and the amount of data the network was trained on. While the mean error drops smoothly and predictably, scaled up LLMs seem to have qualitatively different (emergent) capabilities than smaller versions when one evaluates them at specific tasks. So how does scaling change what neural networks learn? We propose the "quantization model" of neural scaling, where smooth power laws in mean loss are understood as averaging over many small discrete jumps in network performance. Inspired by Max Planck's assumption in 1900 that energy is quantized, we make the assumption that the knowledge or skills that networks must learn are quantized, coming in discrete chunks which we call "quanta". In our model, neural networks can be understand as being implicitly a large number of modules, and scaling simply adds modules to the network. In this talk, I will discuss evidence for and against this hypothesis, its implications for interpretability and for further scaling, and how it fits in with a broader vision for a "science of deep learning".

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Zoom link https://pitp.zoom.us/j/93886741739?pwd=NzJrcTBNS2xEUUhXajgyak94LzVvdz09

I argue that the answer is yes, by reviewing the history and current status of such a theory.  Since 1982, I have been developing a series of such theories, beginning in 1982 with an N --> infinity limit of 2+1 dimensional matrix model (the IAS model), through another N --> infinity, T --> 0 limit of a BFSS model.  During this time our work was complemented by Adler's Trace model and others.   

Beginning in 2012, Cortes and I developed a different approach to an relational quantum cosmology by adding intrinsic energy momentum to Sorkin et al's causal set models.  The addition of energy- momentum as intrinsic variables opens up a new mechanism for the emergence of space, and spacetime, plus interacting relativistic particles.  Note that the warm phase is purely algebraic, you need no prior existence of any space to get other dimensions to emerge.   In 2021 I discovered how to derive quantum non-relativistic many body theory from what has since been called the Causal Theory of Views.  Finally in papers since we report progress on the construction of special and general relativistic  Causal Theory of Views.

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Zoom link: https://pitp.zoom.us/j/95891848248?pwd=TUpWK2RWbU9GTGxZS1lMeS81QWp1dz09

In this colloquium, the communicative boundary between science and society in Africa will be explored, using physics as an illustration. Different types of contact zones and scenes will be discussed, as well as the societal impact of staging and narrative formats. Based on our ongoing engagement project Making Science the Star, an overview of the relationship between sender and receiver will be presented, and recipes for tuning this interaction to unlock untapped potential in predominantly non-scientific communities will be analyzed.

DISCLAIMER: This talk contains Season1 Episode2 from the show series Science In The City. This is used with permission from Dr. Stéphane Kenmoe, Producer of the series and Presenter of this talk.

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Bio: Stéphane Kenmoe got a Ph.D. in Physics from the Max Planck Institute for Iron Research in Germany in 2015. He is presently a habilitation candidate at the Faculty of Chemistry at the University of Duisburg-Essen, Germany. He is also a science popularizer on TV and on social media, a science writer and a novelist. In 2020, he produced the movie ‘’Science in the City’’ (Science dans la Cité) in Cameroon. He is very active in networking for the promotion of early career African scientists and for connecting science and society. He has won many awards for his engagement, among which the 2020 Diversity Prize for Academic Leadership at the University of Duisburg-Essen, the Falling Walls Award for Science Engagement in 2021 and the Award for Prototypes of Humanity of the Dubai Authority for arts and culture in 2022. Since 2022, he is the chief editor of the African Physics Newsletter, an electronic quarterly about physics in Africa published by the American Physical Society. 

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Zoom link: https://pitp.zoom.us/j/92725978684?pwd=Yys0ci9JdE0zS054SGxyaWoxZkdUUT09

During this colloquium, I will discuss my journey in looking for astronomical information hiding in the ancestral knowledge of my community. I will show concrete examples of my findings and encourage communities to engage in similar practice to provide content that could be used to teach indigenous Astronomy in classrooms. 

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Bio:

Laurie Rousseau-Nepton is a new faculty at the University of Toronto and the Dunlap Institute for Astronomy and Astrophysics. She comes with six years of experience working as a resident astronomer at the Canada-France-Hawaii Observatory supporting various instruments including wide-field cameras, high-resolution spectrographs, Fourier Transform Spectro-imager. She received her diploma from Université Laval by studying regions of star formation in spiral galaxies and helping with the development of two Fourier Transform Spectro-imagers, SpIOMM and SITELLE. She is now leading an international project called SIGNALS, the Star formation,Ionized Gas, and Nebular Abundances Legacy Survey, which sampled with the SITELLE instrument more than 50,000 of star-forming regions in 40 nearby galaxies to understand how the local environment affect the young star clusters characteristics.

This seminar will be divided in two segments: 1) New Instrumentation for Astronomy and 2) the SIGNAL-Survey of Star-forming regions in Nearby Galaxy.

1) Evolution of technologies and optics manufacturing technics are providing new interesting options for the design of astronomical instruments to increase precision and add new capabilities. In this presentation, I will discuss my new laboratory plan at the University of Toronto to include Micro-kinetic inductance detector arrays and meta-surface optics to a Fourier Transform Imaging spectrograph design. The goal is to reach high-spectral resolution (R:15,000 to 80,000) over a large field-of-view, while keeping high sensitivity.

2) SIGNALS stands for the Star formation, Ionized Gas, and Nebular Abundances Legacy Survey. Using a Fourier Transform Imaging Spectrograph SITELLE, at the Canada-France-Hawaii Telescope, we observed 40 nearby galaxies and covered over 50,000 star-forming regions in different environment at a spatial resolution from 0.5 to 40 pc. Covering several emission line spectral features including Halpha (at R: 5,000), the survey aims at characterizing the star-forming sites and their environments to produce the most complete and well resolved database on star formation.

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Zoom link https://pitp.zoom.us/j/94273599584?pwd=TUY3UFpVa20wbkJUcEdoTmlYUzlQUT09

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Bio:

Laurie Rousseau-Nepton is a new faculty at the University of Toronto and the Dunlap Institute for Astronomy and Astrophysics. She comes with six years of experience working as a resident astronomer at the Canada-France-Hawaii Observatory supporting various instruments including wide-field cameras, high-resolution spectrographs, Fourier Transform Spectro-imager. She received her diploma from Université Laval by studying regions of star formation in spiral galaxies and helping with the development of two Fourier Transform Spectro-imagers, SpIOMM and SITELLE. She is now leading an international project called SIGNALS, the Star formation, Ionized Gas, and Nebular Abundances Legacy Survey, which sampled with the SITELLE instrument more than 50,000 of star-forming regions in 40 nearby galaxies to understand how the local environment affect the young star clusters characteristics. 

With rapid progress in simulation of strongly interacting quantum Hamiltonians, the challenge in characterizing unknown phases becomes a bottleneck for scientific progress. We demonstrate that a Quantum-Classical hybrid approach (QuCl) of mining the projective snapshots with interpretable classical machine learning, can unveil new signatures of seemingly featureless quantum states. The Kitaev-Heisenberg model on a honeycomb lattice with bond-dependent frustrated interactions presents an ideal system to test QuCl. The model hosts a wealth of quantum spin liquid states: gapped and gapless Z2 spin liquids, and a chiral spin liquid (CSL) phase in a small external magnetic field. Recently, various simulations have found a new intermediate gapless phase (IGP), sandwiched between the CSL and a partially polarized phase, launching a debate over its elusive nature. We reveal signatures of phases in the model by contrasting two phases pairwise using an interpretable neural network, the correlator convolutional neural network (CCNN). We train the CCNN with a labeled collection of sampled projective measurements and reveal signatures of each phase through regularization path analysis. We show that QuCl reproduces known features of established spin liquid phases and ordered phases. Most significantly, we identify a signature motif of the field-induced IGP in the spin channel perpendicular to the field direction, which we interpret as a signature of Friedel oscillations of gapless spinons forming a Fermi surface. Our predictions can guide future experimental searches for U(1) spin liquids.

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Zoom link: https://pitp.zoom.us/j/94233944575?pwd=OVljLzMrZzlKeUErNHZQRkEzMFRKUT09

The aim of the Hammers & Nails climate workshop was to give researchers at Perimeter a unique opportunity to interact with invited experts from diverse fields related to climate, energy and biodiversity. The first half of the workshop was dedicated to short research pitches, where both PI researchers as well as invited guests from the Math4Climate network (including e.g. Waterloo Center for Innovation and Complexity, UW's Climate Institute, Energy Institute, Water Institute) could present their hammers & nails. Nails refers to open challenges within climate, energy & biodiversity research. Hammers refers to methods used by PI researchers in their daily work (e.g. causal inference, techniques in algebraic topology, strong gravity simulations etc.). The second half of the workshop built on these pitches through informal group discussions. Conversations from the workshop may be continued in the future through informal lunches and reading groups.

The aim of the Hammers & Nails climate workshop was to give researchers at Perimeter a unique opportunity to interact with invited experts from diverse fields related to climate, energy and biodiversity. The first half of the workshop was dedicated to short research pitches, where both PI researchers as well as invited guests from the Math4Climate network (including e.g. Waterloo Center for Innovation and Complexity, UW's Climate Institute, Energy Institute, Water Institute) could present their hammers & nails. Nails refers to open challenges within climate, energy & biodiversity research. Hammers refers to methods used by PI researchers in their daily work (e.g. causal inference, techniques in algebraic topology, strong gravity simulations etc.). The second half of the workshop built on these pitches through informal group discussions. Conversations from the workshop may be continued in the future through informal lunches and reading groups.