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Exact and Approximate Computation of Tensors and Polynomials

Project description

Tackling complexity in computing polynomials

The complexity of computing and manipulating polynomials lies at the heart of some of the most profound challenges in theoretical computer science. Questions such as determining the total weight of perfect matchings in a graph, developing efficient deterministic algorithms, or understanding the complexity of approximations highlight fundamental issues spanning algebraic complexity, geometric complexity theory and quantum information. In this context, the ERC-funded EACTP project seeks to address these challenges by advancing methods to tackle questions like polynomial identity testing, the symbolic rank of matrices and tensor subrank in quantum states. Building on recent breakthroughs in algebraic computation, the project aims to deliver transformative solutions to these challenges, paving the way for significant progress in computer science and mathematics.

Objective

This research proposal will address fundamental problems concerning the complexity of computing
and manipulating polynomials. For example, consider the following questions:

1. What is the complexity of computing the total weight of perfect matchings of a weighted graph?
2. Is there an efficient deterministic parallel algorithm that determines whether a graph has a perfect matching?
3. Is approximation much easier than exact computation?
4. How many EPR pairs can we distill from a given quantum state?

These seemingly unrelated questions represent some of the most important and challenging open problems in theoretical computer science: the first is the algebraic analog of the famous P vs. NP problem. The second question amounts to asking whether a symbolic matrix associated with the graph has full rank. Parallel randomized algorithms for computing this rank are known, but not deterministic ones. This is an instance of the polynomial identity testing (PIT) problem, the most fundamental algebraic derandomization problem. The third question asks about the relation between a complexity class and its closure, which lies at the heart of the Geometric Complexity Theory (GCT) program. The last question concerns the subrank of a tensor representing the given quantum state. Problems related to rank of tensors are at the heart of both algebraic complexity and quantum information theory.

Recent years have seen tremendous advance in our understanding of algebraic computations with new lower bounds, new PIT algorithms and with increasing connections to other branches of computer science and mathematics discovered. Results proved by the PI play an important role in all of these advances.

This project aims to study these and related problems and to develop new methods for solving them. Making progress on any of these problems will constitute a significant breakthrough.

Fields of science (EuroSciVoc)

Keywords

Programme(s)

Topic(s)

Funding Scheme

HORIZON-ERC - HORIZON ERC Grants

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Call for proposal

(opens in new window) ERC-2023-ADG

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Host institution

TEL AVIV UNIVERSITY
Net EU contribution
€ 2 335 000,00
Total cost
€ 2 335 000,00

Beneficiaries (1)