  Quantum computing devices are believed to be powerful in solving the prime
factorization problem, which is at the heart of widely deployed public-key
cryptographic tools. However, the implementation of Shor's quantum
factorization algorithm requires significant resources scaling linearly with
the number size; taking into account an overhead that is required for quantum
error correction the estimation is that 20 millions of (noisy) physical qubits
are required for factoring 2048-bit RSA key in 8 hours. Recent proposal by Yan
et al. claims a possibility of solving the factorization problem with sublinear
quantum resources. As we demonstrate in our work, this proposal lacks
systematic analysis of the computational complexity of the classical part of
the algorithm, which exploits the Schnorr's lattice-based approach. We provide
several examples illustrating the need in additional resource analysis for the
proposed quantum factorization algorithm.
