Searcharxiv⌕ Search

arXiv subjects

Sergey V. Grebnev

Publications and source records attributed to Sergey V. Grebnev.

2 recordsLinked to original sources

Experimental factoring integers using fixed-point-QAOA with a trapped-ion quantum processor

Factoring integers is considered as a computationally-hard problem for classical methods, whereas there exists polynomial-time Shor's quantum algorithm for solving this task. However, requirements for running the Shor's algorithm for realistic tasks, which are beyond the capabilities of existing and upcoming generations of quantum computing devices, motivates to search for alternative approaches. In this work, we experimentally demonstrate factoring of the integer with a trapped ion quantum processor using the Schnorr approach and a modified version of quantum approximate optimization algorithm (QAOA). The key difference of our approach in comparison with the recently proposed QAOA-based factoring method is the use of the fixed-point feature, which relies on the use of universal parameters. We present experimental results on factoring $1591=37\times43$ using 6 qubits as well as simulation results for $74425657=9521\times7817$ with 10 qubits and $35183361263263=4194191\times8388593$ with 15 qubits. Alongside, we present all the necessary details for reproducing our results and analysis of the performance of the factoring method, the scalability of this approach both in classical and quantum domain still requires further studies.

quant-ph↗

Pitfalls of the sublinear QAOA-based factorization algorithm

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.

quant-ph↗