On the practicality of quantum sieving algorithms for the shortest vector problem
Joao F. Doriguello, George Giapitzakis, Alessandro Luongo, Aditya Morolia

TL;DR
This paper analyzes the resource requirements for quantum sieving algorithms solving the shortest vector problem, concluding current quantum approaches offer minimal speedup for cryptographic dimensions.
Contribution
It provides a detailed resource estimation for quantum sieving algorithms on SVP, considering realistic quantum hardware constraints and error correction.
Findings
Quantum sieving algorithms require ~10^{13} qubits for dimension 400 SVP.
Estimated quantum runtime is comparable to classical for current cryptographic dimensions.
Significant hardware and protocol breakthroughs are needed for practical quantum speedup.
Abstract
One of the main candidates of post-quantum cryptography is lattice-based cryptography. Its cryptographic security against quantum attackers is based on the worst-case hardness of lattice problems like the shortest vector problem (SVP), which asks to find the shortest non-zero vector in an integer lattice. Asymptotic quantum speedups for solving SVP are known and rely on Grover's search. However, to assess the security of lattice-based cryptography against these Grover-like quantum speedups, it is necessary to carry out a precise resource estimation beyond asymptotic scalings. In this work, we perform a careful analysis on the resources required to implement several sieving algorithms aided by Grover's search for dimensions of cryptographic interests. For such, we take into account fixed-point quantum arithmetic operations, non-asymptotic Grover's search, the cost of using quantum random…
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