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Condensed matter experimentalists are often confronted with multivariable data sets in which dependent variables such as resistance, susceptibility, or magnetization are measured as a function of independent variables such as temperature, magnetic field or frequency. When the data can be plotted in such a way that all of the data fall onto either a small subset of curves or even a single curve, an “ah ha†moment is close at hand. This talk will trace the speaker’s experience with such “ah ha†moments when confronted with data collapse in collaborative investigations on: (1) the disorder driven two-dimensional superconductor-insulator transition in thin films of indium oxide, (2) the disorder driven three-dimensional metal-insulator transition in ferromagnetic thin films of gadolinium, (3) a multivariable power-law scaling collapse of the dielectric constant in complex oxide manganites near the percolation transition and (4) a self-similar scaling behavior of the hysteretic magnetization of a wide variety of magnetic thin-film systems. Among these examples, the first two rely on insightful theoretical guidance to extract fundamental understanding whereas the second two have no apparent theoretical interpretation but do provide rather spectacular and surprising scaling collapses of multivariable data sets.
Dr. Hebard is a distinguished professor of physics at the University of Florida, Gaineville. He won the APS Oliver Buckley award in 2015 for superconductor-insulator quantum phase transitions, and the James McGroddy Prize for new Materials in 2008 for the discovery of superconductivity in Buckminister fullerenes. His interests are in thin films, interfaces physics, superconductivity, magnetism, graphene, fullerenes, among others. |