There is no scheduled Physics Colloquium for Friday, October 18 2019.

Professor Hari Srikanth, Dept. of Physics - Univ. of South Florida & 2019 IEEE Magnetic Society Distinguished Lecturer

Tuning Magnetic Anisotropy in Nanostructures for Biomedical Applications

Magnetic nanoparticles have been building blocks in applications ranging from high density recording to spintronics and nanomedicine. Magnetic anisotropies in nanoparticles arising from surfaces, shapes and interfaces in hybrid structures are important in determining the functional response in various applications. In this talk, I will first introduce the basic aspects of anisotropy, how to tune it in nanostructures and ways to measure it. I will discuss resonant RF transverse susceptibility, that we have used extensively, as a powerful method to probe the effective anisotropy in magnetic materials.

Dr. Neil Turok, Director Emeritus; Perimeter Institute

Quantum Universe

Observations show the cosmos to be astonishingly simple, and yet deeply puzzling, on the largest accessible scales. How did everything we see emerge from a singular “point” in the past? Why is there a cosmological constant (or dark energy) and what fixes its value? What caused the density variations which seeded the formation of galaxies? All these questions involve the interplay between quantum mechanics and spacetime.

Dr. Chris Williams, Brigham & Women's Hospital

MRI-Guided Adaptive Radiation Therapy: Improving Precision in Cancer Therapy

Radiation therapy treatments have traditionally used x-ray imaging to ensure that a patient is accurately positioned before treating them with a beam of ionizing radiation. In the past several years, new treatment machines have been developed that combine magnetic resonance imaging (MRI) systems with linear accelerators, enabling MRI-guidance before and during treatment delivery. These devices have the potential to improve our ability to visualize and treat soft-tissue tumors as well as to compensate for motion and changes in a patient’s anatomy.

Kristy McQuinn, Rutgers University

The Baryon Cycle in the Smallest of Star-Forming Galaxies

Our view of galaxy evolution has expanded to include not just the evolution of individual galaxy components (gas, stars, chemical elements), but the cyclical interplay of a galaxy with its surroundings. Frequently termed the 'baryon cycle', the galaxy evolution framework now includes: how gas is accreted onto galaxies, turned in stars, ejected out of galaxies via energetic feedback processes, and potentially re-accreted.

Peter M. Hoffmann Wayne State University

The Physics of Life: Molecular Machines

Living beings are based on nanoscale machinery. This is no accident: the nanoscale is the only length scale at which autonomous, self-constructing machinery is possible. Only at this scale do thermal, electrical, chemical and mechanical energy scales converge. Moreover, this scale is dominated by thermal chaos. These unique circumstances give nanoscale systems the ability to easily transform different types of energy into each other and to self-assemble into ordered structures. Although living cells have taken advantage of the physics of the nanoscale for billions of years, technology is just beginning to exploit the very different rules governing this scale.

No Physics Colloquium this week due to the Thanksgiving holiday.

Chuck Steidel, Caltech

Imaging the "Baryon Cycle" of Forming Galaxies

The rapid increase in the universal star formation density between z~6 and z~2 (12.5-10.5 Gyr ago) was driven by high rates of accretion onto galaxy-scale dark matter halos, but was simultaneously modulated by energetic feedback from massive stars, supernovae, and AGN activity whose large-scale effects remain uncertain. The competition between rapid accretion from the intergalactic medium and outflows driven by sources of energy and momentum originating near a galaxy's center is arguably the least well-understood aspect of the current galaxy formation paradigm.

Andrew Ferguson, University of Chicago

Reconstructing All-Atom Protein Folding from Low-Dimensional Experimental Time Series

Data-driven modeling and machine learning present powerful tools that are opening up new paradigms and opportunities in the understanding, discovery, and design of soft and biological materials. In the first part of this talk, I will describe an approach integrating ideas from dynamical systems theory and nonlinear manifold learning to reconstruct multidimensional protein folding funnels from the time evolution of single experimentally measurable observables.

Dr. Tomáš Bzdušek, Paul Scherrer Institute and University of Zurich

Mathematics of Topological Insulators and Semimetals

Many properties of crystalline materials, such as conductivity or the tendency to become magnetically ordered at low temperatures, derive from their so-called “electronic band structure.” Although this is an established notion in solid state physics, dating back to the early days of quantum mechanics, our understanding of electronic band structure has been greatly challenged and revolutionized over the past 15 years by the discovery of so-called topological materials.