Project Grant 2533499
- This Project Grant award from the National Science Foundation (CFDA 47.049 - Mathematical and Physical Sciences) is focused on developing novel mathematical theories and computational methods to efficiently solve high-dimensional partial differential equations (PDEs) and learn PDE solution operators using deep neural network-based approaches. The $100,000 award to the Georgia State University Research Foundation Inc. will support research across three key objectives: (1) supervised learning...
- This Project Grant award from the National Science Foundation (NSF) under the Mathematical and Physical Sciences program (CFDA 47.049) provides $302,028 to the University of California, Berkeley (UC Berkeley) to conduct research on nonlinear partial differential equations (PDEs) and their applications in physics. The key objectives of the project are to deepen the understanding of nonlinear hyperbolic and dispersive PDEs, which are fundamental to describing natural phenomena across scales. The...
- This $300,000 Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences program (CFDA 47.049) supports fundamental research aimed at advancing the mathematical analysis of nonlinear partial differential equations. The research has three main focus areas: (1) studying fluid dynamics problems with free boundaries, such as water waves, tsunamis, and hurricanes; (2) investigating the dynamics of gases and plasmas under physical kinetic boundary conditions,...
- This Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences (CFDA 47.049) program is supporting research by The Trustees of Columbia University in the City of New York to advance the theoretical understanding of partial differential equations, free boundary problems, and related mathematical concepts. The $273,927 award, with a performance period from July 1, 2024 to June 30, 2027, focuses on developing new methods and regularity theories for specific...
- The National Science Foundation (NSF) Division of Mathematical Sciences awarded a $400,000 Project Grant to Duke University on August 1, 2023 under the Mathematical and Physical Sciences program (CFDA 47.049) to support innovative numerical methods for solving high-dimensional partial differential equations (PDEs). The key objectives of the 3-year project are to: (1) design and analyze neural-network parametrization for high-dimensional functions with symmetry constraints, and (2) develop and...
- This federal Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences program (CFDA 47.049) provides $300,000 to the University of Pittsburgh to analyze nonlinear partial differential equations (PDEs) that govern fluid flows and related phenomena. The research aims to advance the mathematical understanding of multi-dimensional conservation laws and their applications in fluid dynamics and geometry, with a focus on four core problems: (1) the transonic...
- This three-year National Science Foundation Project Grant of $429,761 will support research into developing theoretical tools for analyzing the dynamics of partial differential equations in higher spatial dimensions. Specifically, the grant to Boston University will fund work on investigating topological implications for stability in higher-order PDE systems and analyzing PDE solutions with more than one spatial variable. This includes developing a useful spatial dynamics approach to treat a...
- This Project Grant award from the National Science Foundation (NSF) Division of Mathematical Sciences (CFDA 47.049 - Mathematical and Physical Sciences) supports research focused on addressing fundamental questions in partial differential equations and optimization theory. The $291,367 award, spanning July 2024 to June 2027, will advance the Principal Investigator's work on characterizing extremal functions for Morrey's inequality, studying solutions to the pressureless Euler system, and...
- This $200,000 Project Grant was awarded by the National Science Foundation (NSF) under the Mathematical and Physical Sciences (CFDA 47.049) federal grant program. The award supports a collaborative research project to develop novel mathematical theories and computational methods for efficiently solving high-dimensional partial differential equations (PDEs) and learning solution operators using deep neural network-based approaches. The key objectives are to: 1) propose a supervised learning...
- This $399,583 federal Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences (CFDA 47.049) program supports research to develop numerical algorithms that can estimate solutions to partial differential equations (PDEs) without full boundary condition information. The research aims to enable improved modeling and forecasting capabilities across various applications, including meteorology, biology, and engineering design. The primary awardee, Texas...
COLLABORATIVE RESEARCH: NUMERICAL METHODS AND DIFFERENTIAL GEOMETRY -PARTIAL DIFFERENTIAL EQUATIONS (PDES) MODEL A WIDE VARIETY OF PHENOMENA, RANGING FROM HOW AN AIRPLANE WING DEFORMS IN RESPONSE TO TURBULENCE, TO HOW RADIO WAVES TRAVEL THROUGH AND AROUND OBJECTS, TO HOW BLACK HOLES GENERATE GRAVITATIONAL WAVES WHEN THEY MERGE. NUMERICAL ANALYSTS DEVELOP ALGORITHMS FOR SIMULATING THESE SYSTEMS BY SOLVING PDES ON A COMPUTER; THESE SIMULATIONS ENABLE ENGINEERS AND SCIENTISTS TO DEVELOP PROTOTYPES AND TO INTERPRET DATA FROM SENSORS. FOR EXAMPLE, THE NSF-FUNDED NOBEL-WINNING DETECTION OF GRAVITATIONAL WAVES WOULD NOT HAVE BEEN POSSIBLE WITHOUT ADVANCES IN NUMERICAL ANALYSIS. IN RECENT DECADES, NUMERICAL ANALYSTS DISCOVERED THAT IDEAS FROM DIFFERENTIAL GEOMETRY, AN AREA OF PURE MATHEMATICS, CAN BE USED TO DEVELOP GOOD ALGORITHMS FOR SOLVING PDES. IN FACT, THESE IDEAS HELP NOT ONLY FOR GEOMETRIC PROBLEMS IN FIELDS OF STUDY LIKE COMPUTER VISION AND GENERAL RELATIVITY, BUT ALSO FOR FIELDS LIKE ELECTROMAGNETISM THAT HAVE LITTLE TO DO WITH GEOMETRY. ALTHOUGH APPLYING DIFFERENTIAL GEOMETRY TO NUMERICAL ANALYSIS HAS BEEN VERY SUCCESSFUL, THUS FAR THIS LINK HAS BEEN EXPLORED ONLY FOR A SMALL NUMBER OF DIFFERENTIAL GEOMETRY IDEAS. IN THIS PROJECT, THE INVESTIGATORS WILL CONTINUE EXPLORING THIS LINK, TAKING MORE IDEAS FROM DIFFERENTIAL GEOMETRY AND APPLYING THEM TO DEVELOP NEW NUMERICAL ALGORITHMS. THESE ALGORITHMS COULD THEN BE USED BOTH IN APPLIED AREAS, BY SOLVING PDES IN SCIENCE AND ENGINEERING, AND IN PURE AREAS, BY SOLVING PDES IN DIFFERENTIAL GEOMETRY ITSELF. THE PROJECT WILL ALSO SUPPORT THE TRAINING OF GRADUATE STUDENT RESEARCHERS. THIS PROJECT FOCUSES ON PROBLEMS AT THE CUSP OF NUMERICAL ANALYSIS AND DIFFERENTIAL GEOMETRY. IT DEALS SPECIFICALLY WITH THE DESIGN OF FINITE ELEMENT METHODS FOR PDES THAT INVOLVE VECTOR FIELDS AND TENSOR FIELDS ON RIEMANNIAN MANIFOLDS. IN THE LONG TERM, THESE EFFORTS HAVE THE POTENTIAL TO LEAD TO ROBUST NUMERICAL METHODS FOR SOLVING GEOMETRIC PDES LIKE THE EINSTEIN FIELD EQUATIONS, WHICH ARE USEFUL FOR STUDYING GRAVITATIONAL WAVE SIGNALS, AS WELL AS PDES LIKE THE ELASTICITY EQUATIONS, WHICH MODEL HOW OBJECTS DEFORM UNDER STRESS. THIS PROJECT HAS THREE MAIN GOALS. THE FIRST IS TO DEVELOP A NEW FAMILY OF FINITE ELEMENTS FOR DISCRETIZING ALGEBRAIC CURVATURE TENSORS AND OTHER BI-FORMS---TENSOR PRODUCTS OF DIFFERENTIAL FORMS---ON SIMPLICIAL TRIANGULATIONS. THE SECOND GOAL IS TO DEVELOP AN INTRINSIC FINITE ELEMENT DISCRETIZATION OF THE BOCHNER LAPLACIAN, WHICH IS A BASIC DIFFERENTIAL OPERATOR IN RIEMANNIAN GEOMETRY THAT DIFFERS FROM THE FAMILIAR HODGE LAPLACIAN FROM FINITE ELEMENT EXTERIOR CALCULUS. THE THIRD GOAL IS TO LEVERAGE WHAT WE LEARN TO DESIGN NUMERICAL METHODS FOR A WIDE RANGE OF GEOMETRIC PROBLEMS, SUCH AS COMPUTING SPECTRA OF ELLIPTIC OPERATORS ON MANIFOLDS, SIMULATING INTRINSIC GEOMETRIC FLOWS, AND SOLVING PRESCRIBED CURVATURE PROBLEMS. THIS AWARD REFLECTS NSF'S STATUTORY MISSION AND HAS BEEN DEEMED WORTHY OF SUPPORT THROUGH EVALUATION USING THE FOUNDATION'S INTELLECTUAL MERIT AND BROADER IMPACTS REVIEW CRITERIA.- SUBAWARDS ARE NOT PLANNED FOR THIS AWARD.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $0 | 6/23/25 | ||
| Not listed | $151.9k | 5/22/25 |