Award Abstract # 2302375
Representation Theory Meets Computational Algebra and Complexity Theory

NSF Org: DMS
Division Of Mathematical Sciences
Recipient: AUBURN UNIVERSITY
Initial Amendment Date: May 30, 2023
Latest Amendment Date: May 30, 2023
Award Number: 2302375
Award Instrument: Standard Grant
Program Manager: Tim Hodges
thodges@nsf.gov
 (703)292-5359
DMS
 Division Of Mathematical Sciences
MPS
 Direct For Mathematical & Physical Scien
Start Date: July 1, 2023
End Date: June 30, 2026 (Estimated)
Total Intended Award Amount: $107,961.00
Total Awarded Amount to Date: $107,961.00
Funds Obligated to Date: FY 2023 = $107,961.00
History of Investigator:
  • Hang Huang (Principal Investigator)
    hzh0105@auburn.edu
Recipient Sponsored Research Office: Auburn University
321-A INGRAM HALL
AUBURN
AL  US  36849-0001
(334)844-4438
Sponsor Congressional District: 03
Primary Place of Performance: Auburn University
107 SAMFORD HALL
AUBURN
AL  US  36849-0001
Primary Place of Performance
Congressional District:
03
Unique Entity Identifier (UEI): DMQNDJDHTDG4
Parent UEI:
NSF Program(s): ALGEBRA,NUMBER THEORY,AND COM,
EPSCoR Co-Funding
Primary Program Source: 01002324DB NSF RESEARCH & RELATED ACTIVIT
Program Reference Code(s): 9150
Program Element Code(s): 126400, 915000
Award Agency Code: 4900
Fund Agency Code: 4900
Assistance Listing Number(s): 47.049, 47.083

ABSTRACT

The goal of this project is to use mathematical tools to tackle computational and applied mathematical problems. The main themes are (1) Systems of Polynomial Equations, (2) Computer Science and Computational Complexity. Systems of polynomial equations can be thought of as describing the dependence relations between physical quantities in some models. The solution set of them describes the geometric shape of the model. Natural phenomena, and hence the model describing them, often come equipped with a rich symmetry. Hence it is natural to use symmetry-based methods to study them. The proposed research will lead to a better understanding of the geometry as well as the utility of the model. A second theme of the project is the complexity of matrix multiplication (a matrix is a rectangular array of numbers). Finding efficient ways to multiply matrices is the topic of a subfield of Computer Science known as complexity theory. In 1968, Strassen discovered that the widely used algorithm for matrix multiplication which was assumed to be the best possible, is in fact not optimal. Since then, there has been intense research in both determining just how efficiently matrices may be multiplied and determining the limits of how much Strassen's algorithm can be improved. The PI proposes to use modern mathematical techniques to tackle those problems. This project will have a substantial broader impact through the development of new software for the open-source computer algebra system Macaulay2, and through the PI?s interest in broadening participation in mathematical research.

The proposal involves several main themes: Weyman-Kempf geometric techniques, syzygies and minimal free resolutions, secant varieties and the study of tensor ranks. The first goal is to find new examples and analyze existing examples to extend Weyman-Kempf geometric techniques to study non-normal varieties. The second goal is the study of nilpotent orbit closures and determinantal thickenings. The PI will use technical tools such as spectral sequence and Lie superalgebra representations to compute numerical and homological invariants of related varieties. The third topic is the computation of different tensor ranks and their application to matrix multiplication complexity. Using tools from modern algebraic geometry such as deformation theory, the PI will tackle a number of longstanding open conjectures.

This project is jointly funded by the Algebra and Number Theory program in the Division of Mathematical sciences, and by the Established Program to Stimulate Competitive Research (EPSCoR).

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.

Please report errors in award information by writing to: awardsearch@nsf.gov.

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