Objective
The classical definition of efficient algorithms as those running in poly-time is long recognized as insufficient. In the era of big data, for example, a linear-time algorithm can be deemed feasible in situations where a quadratic one is not. On the other end of the spectrum, even modest improvements to the base of the exponent in an exp-time algorithm can dramatically expand the range of problem instances for which a solution remains viable.
This research aims to refine complexity theory by developing precise characterizations of worst-case running times for fundamental problems, identifying input instances that require that worst-case complexity, and establishing bidirectional relationships between the exact hardness of poly-time problems and NP-complete ones.
More specifically, our major objectives are (1) Refine upper bounds on the running times of algorithms for core NP-complete problems (such as SAT, Graph Coloring, Subset Sum) to better ground, sharpen, or test fine-grained complexity conjectures; (2) Characterize the structure of worst-case instances for central NP-complete problems, agnostically to the running time itself; (3) Establish a bidirectional equivalence between the exact hardness of certain poly-time problems and NP-complete ones, building on insights from fine-grained complexity that provide one-directional reductions.
Our prior work includes significant advances in the relevant areas. We achieved the first improvements in decades for the running times of key NP-complete problems such as k-SAT and Graph Coloring. Additionally, we provided foundational conditional lower bounds for important approximation and graph algorithmic problems through fine-grained complexity theory. The fusion of expertise from exact algorithms and fine-grained complexity positions us uniquely to tackle the ambitious goals above. Achieving those may establish a theory of completely tying up exact running times of efficient problems to classical conjectures such as NP!=P.
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Keywords
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Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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HORIZON.1.1 - European Research Council (ERC)
MAIN PROGRAMME
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Topic(s)
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Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
HORIZON-ERC - HORIZON ERC Grants
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Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) ERC-2026-STG
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Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.
69978 Tel Aviv
Israel
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.