Michael R. Douglas

About

Michael R. Douglas received his bachelor’s degree in Physics from Harvard University in 1983 and his PhD from Caltech in 1988 under the supervision of John Schwarz. He is a string theorist, best known for his part in the development of matrix models, and for his work on noncommutative geometry in string theory, on Dirichlet branes and their relation to derived categories, and on the statistical approach to string phenomenology. Before coming to help start the Simons Center in 2008, Douglas was at Rutgers University where he was Professor of Physics and Director of the New High Energy Theory Center. He has been awarded the Sackler Prize in Physical Sciences, and has held positions as a Louis Michel Visiting Professor at the IHES and a Clay Mathematical Institute Mathematical Emissary. He is a fellow of the American Mathematical Society and a member of the American Physical Society, and has served as the editor of the Journal of High Energy Physics and of Communications in Mathematical Physics. His research focuses on theoretical physics, string theory, machine learning, and symbolic computation.

Research topics

• Physics
• Theoretical physics
• Mathematics
• Mathematical physics
• Pure mathematics

Selected publications

• The String Theory Landscape

  Universe · 2019-07-20 · 30 citations

  articleOpen access1st authorCorresponding

  String/M theory is formulated in 10 and 11 space-time dimensions; in order to describe our universe, we must postulate that six or seven of the spatial dimensions form a small compact manifold. In 1985, Candelas et al. showed that by taking the extra dimensions to be a Calabi–Yau manifold, one could obtain the grand unified theories which had previously been postulated as extensions of the Standard Model of particle physics. Over the years since, many more such compactifications were found. In t…

  PublisherOA PDFDOI

• Numerical Calabi-Yau metrics from holomorphic networks

  arXiv (Cornell University) · 2020-12-09 · 22 citations

  preprintOpen access1st authorCorresponding

  We propose machine learning inspired methods for computing numerical Calabi-Yau (Ricci flat Kähler) metrics, and implement them using Tensorflow/Keras. We compare them with previous work, and find that they are far more accurate for manifolds with little or no symmetry. We also discuss issues such as overparameterization and choice of optimization methods.

  PublisherOA PDFDOI

• Machine learning as a tool in theoretical science

  Nature Reviews Physics · 2022-02-14 · 10 citations

  review1st authorCorresponding
  PublisherDOI

• Large Language Models

  arXiv (Cornell University) · 2023-07-11 · 8 citations

  preprintOpen access1st authorCorresponding

  Artificial intelligence is making spectacular progress, and one of the best examples is the development of large language models (LLMs) such as OpenAI's GPT series. In these lectures, written for readers with a background in mathematics or physics, we give a brief history and survey of the state of the art, and describe the underlying transformer architecture in detail. We then explore some current ideas on how LLMs work and how models trained to predict the next word in a text are able to perfo…

  PublisherOA PDFDOI

• The Tameness of Quantum Field Theory, Part II -- Structures and CFTs

  arXiv (Cornell University) · 2023-02-08 · 1 citations

  preprintOpen access1st authorCorresponding

  Tame geometry originated in mathematical logic and implements strong finiteness properties by defining the notion of tame sets and functions. In part I we argued that observables in a wide class of quantum field theories are tame functions and that the tameness of a theory relies on its UV definition. The aims of this work are (1) to formalize the connection between quantum field theories and logical structures, and (2) to investigate the tameness of conformal field theories. To address the firs…

  PublisherOA PDFDOI

Frequent coauthors

• Frederik Denef

  Columbia University

  20 shared

• Albert Schwarz

  18 shared

• Constantin P. Bachas

  16 shared

• Inga Hofmann

  15 shared

• Willem H. Ouwehand

  University of Cambridge

  15 shared

• Corinne Pondarré

  Hôpital Intercommunal de Créteil

  15 shared

• Henrik Johansson

  Uppsala University

  13 shared

• Nathan Seiberg

  Institute for Advanced Study

  13 shared

Education

• Ph.D., Physics

  Caltech

  1988

Awards & honors

• Sackler Prize in Physical Sciences
• Louis Michel Visiting Professor at the IHES
• Clay Mathematical Institute Mathematical Emissary
• Fellow of the American Mathematical Society
• Member of the American Physical Society

Similar researchers at Stony Brook University

• Miriam Rafailovichh-84
• Ramana V Davulurih-75
• Joseph S.B. Mitchellh-65