Spouses And Partners

Causality at the Intersection of Simulation, Inference, Science, and Learning

The sciences are replete with high-fidelity simulators: computational manifestations of causal, mechanistic models. Ironically, while these simulators provide our highest-fidelity physical models, they are not well suited for inferring properties of the model from data. Professor Kyle Cranmer of New York University will describe the emerging area of simulation-based inference and describe how machine learning is being brought to bear on these challenging problems.

NPA Seminar, Simon Foreman, Perimeter Institute, "Detection of Cosmological 21cm Emission with CHIME"

Abstract: Intensity mapping of redshifted 21cm emission from neutral hydrogen holds great promise for learning about cosmology, as it provides an efficient way to map large volumes of the universe without the need to characterize individual luminous sources. The Canadian Hydrogen Intensity Mapping Experiment (CHIME) is a cylinder telescope located in Western Canada that was custom-built for this purpose, and that has collected several hundred days’ worth of data since it reached full observational capacity in late 2018.

WIDG Seminar, London Cooper-Troendle, Yale, “Extraction of an Inclusive Muon Neutrino Charged Current Differential Cross Section at MicroBooNE”

The MicroBooNE detector is a Liquid Argon Time Projection Chamber (LArTPC) located along the Booster Neutrino Beam (BNB) at Fermilab. One of its key physics goals is the measurement of neutrino-Argon interaction cross sections. Due to the detector’s fully active volume as well as its capability to offer a high-efficiency neutrino event selection, MicroBooNE is well suited produce the first ever triple-differential neutrino-Argon cross section.

The Neuroscience of Human Decisions: Mapping as Knowing Lecture Series Virtual Talk

Mariano Sigman is one of the most outstanding neuroscientists in the world, with over 150 publications in the most prestigious scientific journals. He is also passionate about experimentation and has worked with magicians, chess masters, musicians, athletes and visual artists to bring his knowledge of neuroscience to different aspects of human culture and apply it in different contexts. He has participated twice (2016 and 2017) in the TED global events in Vancouver, the second with Dan Ariely.

Condensed Matter Theory Seminar: Yves Kwan, University of Oxford, “Kekulé spirals in twisted bilayer graphene"

Abstract: Intense experimental efforts over the past few years have uncovered a rich phenomenology in magic-angle twisted bilayer graphene (TBG). The search for a unifying theoretical framework is complicated by the variability of observations between different samples, which is often attributed to perturbations beyond the pristine limit. Among these is strain, which has been demonstrated via scanning tunnelling experiments to be ubiquitous in TBG devices.

Particle Theory Seminar: Hirosi Ooguri, California Institute of Technology, "Symmetry in QFT and Gravity"

Speaker: Hirosi Ooguri (Caltech)
Title: Symmetry in QFT and Gravity
Abstract: I will review aspects of symmetry in quantum field theory and combine them with the AdS/CFT correspondence to derive constraints on symmetry in quantum gravity. The quantum gravity constraints to be discussed include the no-go theorem on global symmetry, the completeness of gauge charges, and the decomposition of high energy states into gauge group representations.

Inference Project Talk and Discussion: The Inference of Nature: Cause and Effect in Molecular Biology

Theoretical approaches have always played an important role in biology, dating back to Mendel’s peas. In today’s era of genomics and big data in biology, statistical and computational tools are even more vital for biologists seeking to infer causation in living systems. To illustrate the range of methods, from modelling to machine learning, and how they contribute to understanding biological mechanisms, Dr. Teichmann will pick examples from some of the core problems her lab has been investigating as case studies.

Inference Project Talk: "No Cause for Concern: Indefinite Causal Ordering as a Tool for Understanding Entanglement"

Understanding the sorts of explanations and inferences that causal processes countenance is of course of great interest to philosophers and physicists (among others). But what can be said about physical processes that fail to exhibit classical causal structure? Indefinite causal ordering among events made possible by quantum correlations has become a fruitful arena of study recently, yielding new insights for quantum computing and communication, approaches to quantum gravity, and even for foundational issues in quantum mechanics.

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