Applied Mathematics

ASCR Applied Mathematics supports basic research leading to fundamental mathematical advances and computational breakthroughs across the DOE and SC missions. Basic research in scalable algorithms and mathematical libraries, multiscale and multi-physics modeling, scientific artificial intelligence (AI) / machine learning (ML), and efficient analysis of massive data sets underpin all of DOE’s computational and data-intensive science efforts.

Key activities include support for foundational research in:

  • Problem formulation
  • Multiscale modeling and multiphysics coupling
  • Mesh discretization
  • Time integration
  • Advanced solvers for large-scale linear and nonlinear systems of equations
  • Methods that use asynchrony or randomness
  • Uncertainty quantification
  • Numerical optimization
  • Mathematical methods for scientific AI/ML

Advances in such methods have historically contributed as much, if not more, to gains in computational science than hardware improvements alone. Forward-looking efforts by applied-mathematics research anticipate DOE mission needs from the closer coupling and integration of scientific modeling, data, and scientific AI/ML with advanced computing. These efforts enable greater capabilities for scientific discovery, design, and decision-support in complex systems and new algorithms to support data analysis at the edge of experiments and instruments and protect the privacy of sensitive datasets.

ASCR Funding

Award abstracts and information about awards made prior to FY2018 can be found here.

ASCR Workshops and Reports

Workshop and reports completed prior to FY2018 can be found here.

ASCR Meetings

Other Notable Reports

Applied Mathematics Program Managers:

Steven Lee
Foundations: Algorithms, Models and Data

Bill Spotz
Multiscale Mathematics