ECDSA.Fail

Circuit research for Shor’s algorithm

ECDSA is a widely used digital-signature scheme whose security rests on the elliptic-curve discrete logarithm problem. ECDSA.Fail is an open study of AI-assisted optimization of the elliptic-curve point-addition circuits that Shor’s algorithm needs in order to attack it. Members of the Potomac team contributed under their MultiVM Labs affiliation, and the research team has continued to contribute to the public benchmark since.


The publication

The paper and the benchmark

Publication

arXiv preprintSeptember 2026

arXiv:2609.09582

ECDSA.Fail: Open Autoresearch for Optimizing Elliptic-Curve Point Addition in Shor's Algorithm

Jieyi Long, Theodore Pender, Zhao Huang, Manuel B. Santos, et al.

AI-assisted optimization of reversible elliptic-curve point-addition circuits for Shor's algorithm, evaluated on a public benchmark with automated verification. Data cutoff 26 July 2026.

Manuel B. Santos and Ruben M. L. Paschoarelli are coauthors listed with the MultiVM Labs affiliation. The paper predates Ross Nkama’s September 2026 submission, which is documented separately.


What the work studies

Making the dominant arithmetic smaller

Shor’s algorithm for the elliptic-curve discrete logarithm problem repeatedly adds points on the curve inside a quantum circuit. Point addition is the dominant arithmetic, so the size of its reversible circuit, measured in the logical qubits it occupies and the non-Clifford gates it executes, largely sets the cost of the whole computation.

ECDSA.Fail asks how small that circuit can be made. It uses an open benchmark with automated evaluation, so that every submitted circuit is checked for correctness on sampled inputs and scored under one declared convention before it counts.

Open Autoresearch describes the format: humans and AI agents propose candidate circuits to a public leaderboard, an evaluator verifies them, and the record of what improved and how is public.


Later contributions

Contributions after the paper

The paper’s data cutoff is 26 July 2026. On 8 September 2026 the challenge organizers accepted a submission by Ross Nkama that reduced the average executed Toffoli count from 904,049 to 902,838 at an unchanged qubit width of 1,260. That contribution is recorded in the organizers’ repository and on the community leaderboard, and is documented here as a case study in research with frontier AI. It is separate from the paper, and Ross is not a coauthor of it.

The case study


What it does not show

What a logical-circuit result shows

The result is a logical-circuit result. It does not compile the circuit to a fault-tolerant architecture, does not account for error-correction overhead or scheduling on a specific machine, and does not demonstrate the recovery of any key on quantum hardware.

Comparisons with other published circuits depend on accounting conventions and interfaces that differ between papers, so a headline percentage is only meaningful alongside the exact submission, baseline, metric, and validation status. Potomac therefore cites the paper, the benchmark, and specific dated submissions rather than summarizing rankings.

Logical circuit
What the paper optimizes: qubit width and gate counts under a declared convention.
Fault-tolerant execution
Compilation, error correction, and scheduling on a real architecture. Not part of this result.
Key recovery
An end-to-end computation on hardware at deployed key sizes. Potomac’s long-term objective, not a demonstrated capability.

Authorship and attribution

Who did the work

The paper has many authors across several institutions; the arXiv submission was made by Jieyi Long. Manuel B. Santos and Ruben M. L. Paschoarelli are coauthors listed with the affiliation MultiVM Labs, the team whose work Potomac builds on.

Manuel leads cryptography research at Potomac. Ruben’s coauthorship is part of the historical record and does not indicate current Potomac team membership. Potomac did not author or submit the paper as an institution; the contribution belongs to the individuals and to the collaboration that produced it.

Source: Author affiliations (arXiv HTML)


What comes next

From the logical level to fault-tolerant execution

The next question is what a smaller point-addition circuit costs once it is compiled to a real architecture with error correction, and how reliably arithmetic kernels of increasing operand size can be run. That is the question the measurement framework is designed to answer, and where the model-assisted workflow is being extended beyond circuit design.