Resource estimation for magic-state distillation on silicon spin qubits finds 42% overhead reduction via optimized pulses and ~3x physical footprint reduction with biased codes versus surface code.
Space-Efficient Quantum Algorithm for Elliptic Curve Discrete Logarithms with Resource Estimation
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abstract
Solving the Elliptic Curve Discrete Logarithm Problem (ECDLP) is critical for evaluating the quantum security of widely deployed elliptic-curve cryptosystems. Consequently, minimizing the number of logical qubits required to execute this algorithm is a key object. In implementations of Shor's algorithm, the space complexity is largely dictated by the modular inversion operation during point addition. Starting from the extended Euclidean algorithm (EEA), we refine the register-sharing method of Proos and Zalka and propose a space-efficient reversible modular inversion algorithm. We use length registers together with location-controlled arithmetic to store the intermediate variables in a compact form throughout the computation. We then optimize the stepwise update rules and give concrete circuit constructions for the resulting controlled arithmetic components. This leads to a modular inversion circuit that uses $3n + 4\lfloor \log_2 n \rfloor + O(1)$ logical qubits and $204n^2\log_2 n + O(n^2)$ Toffoli gates. By inserting this modular inversion component into the controlled affine point-addition circuit, we obtain a space-efficient algorithm for the ECDLP with $5n + 4\lfloor \log_2 n \rfloor + O(1)$ qubits and $O(n^3)$ Toffoli gates. In particular, for a 256-bit prime-field curve, our estimate reduces the logical-qubit count to 1333, compared with 2124 in the previous low-width implementation of H\"aner et al.
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quant-ph 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
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Hardware-Tailored Resource Estimation for Magic-State Distillation on Silicon Spin Qubits
Resource estimation for magic-state distillation on silicon spin qubits finds 42% overhead reduction via optimized pulses and ~3x physical footprint reduction with biased codes versus surface code.