Jonathan Weare
Warren Weaver Hall, Room 1103 251 Mercer Street New York, NY 10012-1185 weare [AT] cims [DOT] nyu [DOT] edu |
||

Our group is primarily focused on
the design, analysis, and application of stochastic algorithms
and models. Our work draws on tools from probability theory, the
theory of partial differential equations, and numerical
analysis. A significant portion of research in the group is
organized around long term collaborations with applications
experts in areas such as biophysics, computational chemistry,
and weather and climate science.
I am currently an associate
professor of mathematics in the Courant Institute of
Mathematical Sciences at New York University. Previously I was
an associate professor in the statistics department and in the
James Franck Institute at the University of Chicago and, before
that, an assistant professor in the mathematics department
there. Before moving to Chicago I was a Courant Instructor of
mathematics at NYU and a PhD student in mathematics at the
University of California at Berkeley.
Current
research areas Monte Carlo methods
multiscale modeling and simulation randomized numerical linear algebra rare event analysis and simulation statistical and machine learning for dynamical systems People
High school students
Anna Zhang,
Stuyvesant High School 2020-
Undergraduate
students
Charlie Marshall,
mathematics, University of Chicago 2019-2020
Douglas Dow, mathematics, University of Chicago 2019-2020 Bradley Stadie, mathematics, University of Chicago 2013-2014 Masters students Bixing Qiao,
mathematics, Courant Institute 2019-2020
Eileen Li, statistics, University of Chicago 2016-2017 Doctoral students Anya Katsevich,
mathematics, Courant Institute 2019-
Chatipat Lorpaiboon, chemistry, University of Chicago (co-mentored with A. Dinner) 2018- John Strahan, chemistry, University of Chicago (co-mentored with A. Dinner) 2018- Adam Antoszewski, chemistry, University of Chicago (co-mentored with A. Dinner) 2017- Justin Finkel, applied math, University of Chicago (co-mentored with D. Abbot) 2017- Sam Greene, chemistry, Columbia (co-mentored with T. Berkelbach) 2017- Robert Webber, mathematics, Courant Institute 2015- Bodhi Vani, chemistry, University of Chicago (co-mentored with A. Dinner) 2015- Erik Thiede, chemistry, University of Chicago (co-mentored with A. Dinner) 2013-2019 David Plotkin, geoscience, University of Chicago (co-mentored with D. Abbot) 2012-2018 Jeremy Tempkin, chemistry, University of Chicago (co-mentored with A. Dinner) 2012-2017 Postdoctoral scholars Brian Van Koten,
applied math, University of Chicago 2014-2018
Charles Matthews, applied math, University of Chicago 2014-2018 Seyit Kale, chemistry, University of Chicago 2012-2015 Editorial
work Stochastics and Partial Differential Equations: Analysis and Computations SIAM/ASA Journal on Uncertainty Quantification Publications
A (nearly) complete list of publications and preprints can be found on arXiv 2020 Integrated
VAC: A robust strategy for identifying eigenfunctions of
dynamical operatorswith C. Lorpaiboon, E.H. Thiede, R.J. Webber, and A.R. Dinner, Journal of Physical Chemistry B,
acceptedImproved Fast
Randomized Iteration approach to Full Configuration
Interaction with S.M. Greene, R.J. Webber, and T.C. Berkelbach, Journal of Chemical Theory and Computation,
16(9), 5572–5585 Insulin
dissociates by diverse mechanisms of coupled unfolding and
unbinding with A. Antoszewski, C.-J. Feng, B.P. Vani, E.H. Thiede, L. Hong, A. Tokmakoff, and A.R. Dinner, Journal of Physical Chemistry B, 124(27),
5571–5587 Path properties of atmospheric
transitions: illustration with a low-order sudden stratospheric
warming modelwith J. Finkel, and D.S. Abbot, Journal of
Atmospheric Science, 77(7), 2327–2347 Stratification as a general variance reduction method for Monte
Carlowith A.R. Dinner, E.H. Thiede, and B. Van Koten, SIAM/ASA Journal on Uncertainty Quantification (JUQ),
8(3), 1139-1188Beyond walkers
in stochastic quantum chemistry: reducing error using Fast
Randomized Iterationwith S.M. Greene, R.J. Webber, and T.C. Berkelbach, Journal of Chemical Theory and Computation,
15(9), 4834-4850 Galerkin
approximation of dynamical quantities using trajectory datawith E.H. Thiede, D. Giannakis, and A.R. Dinner, Journal of Chemical Physics, 150,
24111 Practical
rare event simulation for extreme mesoscale weatherwith R.J. Webber, D.A. Plotkin, M.E O'Neill, and D.S. Abbot, Chaos, 29, 053109 Maximizing simulated tropical cyclone intensity with action
minimizationwith D.A. Plotkin, R.J. Webber, M.E O'Neill, and D.S. Abbot, Journal of Advances in Modeling Earth
Systems (JAMES), 11(4), 863-891Trajectory
stratification of stochastic dynamicswith A.R. Dinner, J.C. Mattingly, J. Tempkin, and B. Van Koten, SIAM Reviews: Research
Spotlight, 60(4), 909–938 Umbrella sampling: a powerful method to sample tails of
distributionswith C. Matthews, A. Kravstov, and E. Jennings, Monthly Notices of the Royal Astronomical
Society, 480(3), 4069-4079Simulating
the stochastic dynamics and cascade failure of power networkswith C. Matthews, B. Stadie, M. Anitescu, and C. Demarco Ensemble preconditioning for Markov chain Monte Carlo
simulationwith B. Leimkuhler and C. Matthews, Statistics
and Computing, 28(2) 277-290 Fast randomized iteration: diffusion Monte Carlo
through the lens of numerical linear algebrawith L.H. Lim, SIAM Reviews: Research
Spotlight, 59(3) 547-587Eigenvector
method for umbrella sampling enables error analysiswith E. Thiede, B. Van Koten, and A. Dinner, Journal of Chemical Physics, 145(8) 084115 Multiple time-step dual-Hamiltonian hybrid molecular
dynamics Monte Carlo canonical propagation algorithm with Y. Chen, S. Kale, A. Dinner, and B. Roux, Journal of Chemical Theory and Computation, 12(4)
1449-1458Sharp
entrywise perturbation bounds for Markov chainswith E. Thiede and B. Van Koten, SIAM
Journal on Matrix Analysis and Applications, 36(3),
917-941 The Brownian fan with M. Hairer, Communications in Pure
and Applied Mathematics, 68(1) 1-60Finding
chemical reaction paths with a multilevel preconditioning
protocol with S. Kale, S. Olaseni, and A. Dinner, Journal
of Chemical Theory and Simulation, 10(12),
5467-5475 Distinguishing meanders of the Kuroshio using
machine learning with D. Plotkin and D. Abbot, Journal of
Geophysical Research - Oceans, 119(10) 6593-6604
Using multiscale preconditioning to accelerate the
convergence of iterative molecular calculations with J. Tempkin, B. Qui, M. Saunders, B. Roux, and A. Dinner, Journal of Chemical Physics, 140(18)
184114 Improved diffusion Monte Carlo with M. Hairer, Communications in Pure
and Applied Mathematics, 67(12) 1995-2021 Nucleotide regulation of the structure and dynamics
of G-actinwith M. Saunders, J. Tempkin, A. Dinner, B. Roux, and G. Voth, Biophysical Journal, 106(8)
1710-1720The
relaxation of a family of broken bond crystal surface modelswith J. Marzuola, Physical Review E,
88 032403 The theory of ultra coarse graining I, general
principleswith J. Dama, A. Sinitskiy, M. McCullagh, B. Roux, A. Dinner, and G. Voth, Journal of Chemical Theory
and Computation, 9(5) 2466-2480 On the statistical equivalence of
restrained-ensemble simulations with the maximum entropy
methodwith B. Roux, Journal of Chemical
Physics, 138(8) 084107 Minimizing memory as an objective for
coarse-grainingwith N. Guttenberg, J. Dama, M. Saunders, A. Dinner, and G. Voth, Journal of Chemical Physics, 138(9)
094111 Extending molecular simulation time scales:
Parallel-in-time integrations for high-lelel quantum chemistry
and complex force representationswith E. Bylaska and J.H. Weare, Journal
of Chemical Physics, 139 074114 Data assimilation in the low noise regime with
applications to the Kuroshio with E.
Vanden-Eijnden, Monthly Weather Review, 141
1822-1841Steered
transition path samplingwith N. Guttenberg and A. Dinner, Journal
of Chemical Physics, 136 234103 Rare event simulation for small noise diffusionswith E. Vanden-Eijnden, Communications
in Pure and Applied Mathematics, 65(12)
1770-1803 An affine-invariant sampler for exoplanet fitting
and discovery in radial velocity datawith F. Hou, J. Goodman, D. Hogg, and C. Schwab, The Astrophysical Journal, 75 198The evolution
of a crystal surface: analysis of a 1D step train connecting
two facets in the ADL regimewith H. Al Hajj Shehadeh and R.V. Kohn, Physica
D, 240 1771-1784 Ensemble
samplers with affine invariancewith J. Goodman, Communications in
Applied Mathematics and Computational Science, 5
65-80Particle
filtering with path sampling and an application to a bimodal
ocean current modelJournal of Computational Physics, 228
4312-4331 Variance reduction for particle filters of systems with
time-scale separationwith D. Givon and P. Stinis, IEEE
Transactions on Signal Processing, 57(2) 424-435
Efficient
Monte Carlo sampling by parallel marginalizationProceedings of the National Academy of
Science, 104(31) 12657-12662 Software
pyEDGARhttps://github.com/ehthiede/pyEDGAR E. Thiede (I am not an author) Python implementation of Dynamic Galerkin Approximation (DGA) which builds predictions of long-timescale phenomena from short trajectory data. Eigenvector Method for Umbrella Sampling (EMUS)https://github.com/ehthiede/EMUS E. Thiede (I am not an author) Python implementation of a stratification approach to MCMC Ensemble QuasiNewton MCMC (EQN)https://bitbucket.org/c_matthews/ensembleqn C. Matthews (I am not an author) Python implementation of an emsemble preconditioning approach to MCMC Fast Randomized Iteration (FRI)https://github.com/jonathanweare/Fast-Randomized-Iteration-FRI- with J. Dama Demonstration C++ implementation of randomized power iteration. Enhanced Sampling Toolkithttps://github.com/jtempkin/enhanced_sampling_toolkit J. Tempkin (I am not an author) The Enhanced Sampling Toolkit provides a flexible and extensible toolkit for rapidly prototyping rare event simulation algorithms. The code is written entirely in Python and acts as a wrapper to various well-established molecular dynamics codes. Ticketed Diffusion Monte Carlo (TDMC)http://dx.doi.org/10.5281/zenodo.17001 J. Dama (I am not an author) Demonstration C++ implementation of an improved diffusion Monte Carlo method. emcee: The MCMC Hammerhttp://dan.iel.fm/emcee/current/ D. Foreman-Mackey, D. Hogg, D. Lang, and J. Goodman (I am not an author) Python implementation of an affine invariant ensemble MCMC scheme. |