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Symmetry and Optimization at the Frontiers of Computation

Project description

Navigating curved mathematical spaces

Most optimisation tasks occur in flat spaces. However, challenging problems in quantum computing and machine learning arise in curved spaces. Symmetry defines the structure of these worlds. Standard methods are not adapted to these structures. The ERC-funded SYMOPTIC project aims to develop a system called noncommutative group optimisation. This method extends standard optimisation techniques to spaces with complex symmetries. The project will apply group-theoretic mathematics, in which the order of operations affects the outcome. It will develop fast algorithms for statistical and quantum data. By establishing the foundations for this new method, it helps scientists to apply these tools to classical and quantum problems and advance how researchers explore the limits of modern computing.

Objective

Noncommutative group optimization is a powerful emerging paradigm, which has already led to the solution of outstanding problems in computational complexity, algebra, and statistics. Pioneered by the PI and collaborators, it generalizes convex optimization from Euclidean space to the far more general setting of curved spaces with symmetries. Its unfamiliar kind of convexity has recently received much attention in statistics and machine learning. The symmetries are realized by noncommutative groups and imply a high degree of algebraic structure. This combination of symmetry and optimization promises to be key to fast algorithms and deep structural insight. Noncommutative group optimization connects important problems across a wide range of disciplines that appear unrelated at first glance: program testing and derandomization in computer science, estimation problems in statistics, isomorphism problems in algebra, the P vs NP problem and circuit lower bounds in complexity theory, optimal transport in machine learning, marginal and entanglement problems in quantum information, and optimization on quantum computers. This list contains both discrete and continuous problems, theoretical and applied ones, for classical as well as for quantum computers. They have been studied separately over many years by many authors. Here they are brought together in a new innovative way.

This project aims to develop the theoretical and algorithmic foundations of noncommutative group optimization and apply it to longstanding theoretical problems and practical applications. This has high potential for long-lasting impact at several frontiers of computation: in addition to contributing a new paradigm and widely-applicable methods to optimization, we aim to give efficient algorithmic solutions to difficult problems in algebra, make progress on the limits of efficient computation, and unlock the potential of quantum computers for optimization.

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Programme(s)

Topic(s)

Funding Scheme

HORIZON-ERC - HORIZON ERC Grants

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Call for proposal

(opens in new window) ERC-2021-STG

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Host institution

LUDWIG-MAXIMILIANS-UNIVERSITAET MUENCHEN
Net EU contribution
€ 667 031,25
Address
GESCHWISTER SCHOLL PLATZ 1
80539 Planegg
Germany
Region
Bayern Oberbayern München, Kreisfreie Stadt
Activity type
Higher or Secondary Education Establishments
Links
Total cost
€ 667 031,25

Beneficiaries (3)