Physics

The power of quantum information lies in its capacity to be non-local, encoded in correlations among entangled particles.  Yet our ability to produce, understand, and exploit such correlations is hampered by the fact that the interactions between particles are ordinarily local.  I will report on experiments in which we use light to engineer non-local interactions among cold atoms, with photons acting as messengers conveying information between them.  We program the spin-spin couplings in an array of atomic ensembles by tailoring the frequency spectrum of an optical control field.  We harness this programmability to access interaction graphs conducive to frustration and to explore quantum spin dynamics in exotic geometries and topologies.  More broadly, advances in optical control of interactions open new opportunities in areas ranging from quantum technologies to fundamental physics.  I will touch on implications for quantum-enhanced sensing, combinatorial optimization, and simulating quantum gravity.

In his May 5 Perimeter Public Lecture webcast, Harvard professor L. Mahadevan will take viewers on a journey into the mathematical, physical, and biological workings of morphogenesis to demonstrate how scientists are beginning to unlock many of the secrets that have vexed scientists since Darwin.

I will present a single idea about representation which allows several recent advances in neural networks  to be combined into an imaginary system called GLOM.  GLOM answers the question: How can a neural network with a fixed architecture parse an image into a part-whole hierarchy which has a different structure for each image? The idea is simply to use islands of identical vectors to represent the nodes in the parse tree. The talk will discuss the many ramifications of this idea.  If GLOM can be made to work, it should significantly improve the interpretability of the representations produced by neural nets when applied to vision or language.  

The remarkable properties of electrons moving through crystalline lattices continue to surprise us. Recently, electrons in artificial moiré lattices have emerged as an extraordinary new platform. The simplest such moiré material consists of a pair of graphene sheets twisted relative to one another. At a  "magic" angle of about 1 degree, a variety of phenomena, including strong-coupling superconductivity, is observed. In this talk, I will review this rapidly moving field and describe our theoretical ideas that invoke the geometry of quantum states and topological textures like skyrmions. Finally, I will explain how these insights indicate a promising new family of moiré materials, twisted trilayer graphene, which is currently under active experimental study.

Quantum computers need to manipulate quantum states, and the only ways we know of doing this are inherently noisy. Thus, if we are ever to be able to do long computations on quantum computers, we need to make them fault tolerant. The way we know how to do this currently is to use quantum error correcting codes. We will introduce error correcting codes and explain how they can be used to provide fault tolerance for quantum computers.
 

Indigenous wellness and higher education in Canada, through the creation of Indian Residential Schools, has a dark history and has left a legacy of intergenerational trauma for Indigenous peoples. Currently, the Truth and Reconciliation Commission’s Final Report (2015) provides  a timely context for systemic change that can improve the lives of Indigenous individuals and provide healing to Indigenous communities. This presentation addresses Indigenous academic strengths and challenges in Canada and provides practical implications of implementing decolonial change in higher education settings. Examples from Dr. Stewart’s community-based Indigenous ethics and educational research provide concrete illustrations of issues such as racism, oppression, cultural identity, tensions between Western and Indigenous worldviews, and the importance of traditional knowledges.

We will discuss the recent advances involving programmable, coherent manipulation of quantum many-body systems using atom arrays excited into Rydberg states. Specifically, we will describe our recent technical upgrades that now allow the control over 200 atoms in two-dimensional arrays. Recent results involving the realization  of exotic phases of matter, study of quantum phase transitions and  exploration of  their non-equilibrium dynamics will be presented. In particular, we will report on realization and probing of quantum spin liquid states - the exotic states of matter have thus far evaded direct experimental detection. Finally,  realization and testing  of quantum optimization algorithms using such systems will be discussed.

Statistical mechanics is the branch of physics that explains how macroscopic properties of matter emerge from the behavior of its microscopic constituents. Population ecology studies how and why populations change over time and space, primarily due to the interaction among individuals and between individuals and the environment where they thrive. Although seemingly very different, both disciplines aim to explain large-scale phenomena based on a description of their underlying drivers, and statistical mechanics tools have been largely used to formalize population ecology. For over 100 years, however, mathematical models in population ecology have relied on very strong and unrealistic assumptions about the way individuals move and get to interact with each other and with the environment. Specifically, they assume that individuals behave like the molecules of an ideal gas: following completely random trajectories through the entire area occupied by the population and only interacting with each other when their trajectories intersect. 

In this presentation, I will first discuss why mathematical models are powerful tools to understand ecological processes. Then, I will show how traditional models of population dynamics emerge from ideal gas assumptions for individual movement and briefly touch on our recent efforts to refine those models combining more elaborated tools from statistical physics, random walk theory, and GPS tracking data of natural populations.