**Andrew Strominger** is the Gwill E. York Professor of Physics at Harvard University and a founding member of the Black Hole Initiative. He is a renowned theoretical physicist who has made pathbreaking contributions to classical and quantum gravity, quantum field theory and string theory. In recognition of his accomplishments, Strominger has been awarded the prestigious 2017 Breakthrough Prize in Fundamental Physics, the 2016 Dannie Heineman Prize from the American Physical Society, and numerous other honors.

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In this informal memoir, the author describes his passage through a golden age of elementary particle physics. It includes not only his career trajectory as a theoretical physicist but also his excursions into experimental physics and particle accelerator theory. While his successes are highlighted, some unsuccessful efforts are included in the narrative as well. Those “losers” were arguably as pleasurable as the less-frequent “winners.” Since retirement, the author has become interested in gravitation theory and cosmology—a new golden age. This activity is also briefly described ….. Read more at: https://www.annualreviews.org/doi/full/10.1146/annurev-nucl-101918-023359

]]>I defend the extremist position that the fundamental ontology of the world consists of a vector in Hilbert space evolving according to the Schrödinger equation. The laws of physics are determined solely by the energy eigenspectrum of the Hamiltonian. The structure of our observed world, including space and fields living within it, should arise as a higher-level emergent description. I sketch how this might come about, although much work remains to be done.

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**Tomasz Danek, Michael A. Slawinski, Theodore Stanoev**

We combine power-meter measurements with GPS measurements to study the model that accounts for the use of power by a cyclist. The model takes into account the change in elevation and speed along with adverse effects of air, rolling and drivetrain resistance. The focus is on estimating the resistance coefficients using numerical optimization techniques to maintain an agreement between modelled and measured power-meter values, which accounts for the associated uncertainties. The estimation of coefficients is performed for two typical scenarios of road cycling under windless conditions, along a course that is mainly flat as well as a course of near constant inclination. Also, we discuss relations between different combinations of two model parameters, where other quantities are constant, by the implicit function theorem. Using the obtained estimates of resistance coefficients for the two courses, we use the mathematical relations to make inferences on the model and physical conditions. Along with a discussion of results, we provide two appendices. In the first appendix, we illustrate the importance of instantaneous cadence measurements. In the second, we consider the model in constrained optimization using Lagrange multipliers.

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