Summary
Computational complexity lies at the heart of information and computer science. Its aim is to formally understand the boundary between problems that can be solved efficiently and those that cannot. This has many applications: new algorithms are important to make progress in domains such as machine learning and optimization, and new complexity lower bounds (namely, computational impossibility results) are essential to provably secure cryptography. Beyond practical applications, these questions reveal deep mathematical and natural phenomena. One of the prominent directions to attack the fundamental lower bound questions in complexity comes from the study of resource bounded provability, namely proof complexity. Its aim is to understand which problems possess solutions with short correctness proofs and which do not. Traditionally, proof complexity is concerned with propositional (Boolean) logic, and thus techniques from Boolean function complexity have had a huge impact on the field, driving many of its results and agendas.
In this proposal we suggest to employ recent breakthroughs in the field of proof complexity exploiting algebraic approaches to broaden in a systematic way both the scope and techniques of proof complexity, going from weak settings to the very strong ones, up to the major open problems in the field and beyond. In particular, we propose to use algebraic notions and techniques such as structural algebraic circuit complexity, rank lower bounds, noncommutative and PI algebras, among others to significantly broaden the arsenal of lower bound tools as well as develop new models and insights into proofs, computation and their inter-relations.
This project has potential for a transformative impact in theoretical computer science and beyond, with applications to unconditional computational lower bounds, which underlie secure cryptography and derandomization of probabilistic algorithms, as well as improved SAT- and constraint-solving heuristics.
In this proposal we suggest to employ recent breakthroughs in the field of proof complexity exploiting algebraic approaches to broaden in a systematic way both the scope and techniques of proof complexity, going from weak settings to the very strong ones, up to the major open problems in the field and beyond. In particular, we propose to use algebraic notions and techniques such as structural algebraic circuit complexity, rank lower bounds, noncommutative and PI algebras, among others to significantly broaden the arsenal of lower bound tools as well as develop new models and insights into proofs, computation and their inter-relations.
This project has potential for a transformative impact in theoretical computer science and beyond, with applications to unconditional computational lower bounds, which underlie secure cryptography and derandomization of probabilistic algorithms, as well as improved SAT- and constraint-solving heuristics.
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| Web resources: | https://cordis.europa.eu/project/id/101002742 |
| Start date: | 01-07-2021 |
| End date: | 30-06-2026 |
| Total budget - Public funding: | 1 899 675,00 Euro - 1 899 675,00 Euro |
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Original description
Computational complexity lies at the heart of information and computer science. Its aim is to formally understand the boundary between problems that can be solved efficiently and those that cannot. This has many applications: new algorithms are important to make progress in domains such as machine learning and optimization, and new complexity lower bounds (namely, computational impossibility results) are essential to provably secure cryptography. Beyond practical applications, these questions reveal deep mathematical and natural phenomena. One of the prominent directions to attack the fundamental lower bound questions in complexity comes from the study of resource bounded provability, namely proof complexity. Its aim is to understand which problems possess solutions with short correctness proofs and which do not. Traditionally, proof complexity is concerned with propositional (Boolean) logic, and thus techniques from Boolean function complexity have had a huge impact on the field, driving many of its results and agendas.In this proposal we suggest to employ recent breakthroughs in the field of proof complexity exploiting algebraic approaches to broaden in a systematic way both the scope and techniques of proof complexity, going from weak settings to the very strong ones, up to the major open problems in the field and beyond. In particular, we propose to use algebraic notions and techniques such as structural algebraic circuit complexity, rank lower bounds, noncommutative and PI algebras, among others to significantly broaden the arsenal of lower bound tools as well as develop new models and insights into proofs, computation and their inter-relations.
This project has potential for a transformative impact in theoretical computer science and beyond, with applications to unconditional computational lower bounds, which underlie secure cryptography and derandomization of probabilistic algorithms, as well as improved SAT- and constraint-solving heuristics.
Status
SIGNEDCall topic
ERC-2020-COGUpdate Date
27-04-2024
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