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Some Applications of Statistics in Physics: quantized light, scattering, and tomography

February 12, 2020 - 2:40pm
Zachary Levine
  1.  Intro.  Physics and statistics  (a) where theory and experiment meet, (b) divergent world views, (c) underlying probabilistic nature of the world:  Bell's theorem and random number generation.
  2. The calibration of a few photon detector.  (a) What is a Transition Edge Sensor?  What needs to be calibrated?  (b) The K-means algorithm as maximum likelihood.  (c) Adaptation of the K-means algorithm to Poisson statistics:  a new maximum likelihood objective function: PIKA.  (d) Application of PIKA to calibration of an attenuator at near-ideal quantum efficiency.
  3. Monte Carlo and importance sampling:  a rapid algorithm to determine scattering parameters for an optical medical phantom.
  4. Tomography:   (a) early application of a Bayesian method to integrated circuit interconnect tomography, (b) scattering, Monte Carlo and tomography:  algorithmic developments - the moving expanding window and a hybrid standard and Forced-Fixed Detection Monte Carlo, (c) quantifying the uncertainty of the Response Evaluation Criteria in Solid Tumors (RECIST).


Organizers: Niranjan Ramachandran, Dio Margetis, and Leo Koralov

Math 3206