2024/06/18 by Roberto Campos, Campos, Roberto · 1 citation
Computer Science · #FOS: Physical sciences #Quantum Computing Algorithms and Architecture #Quantum Information and Cryptography #Quantum Physics (quant-ph)
paper · pdf · doi:10.48550/arxiv.2406.12371
openalex publication_date 2024/06/18 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
This thesis explores hybrid algorithms that combine classical and quantum computing to enhance the performance of classical algorithms. Two approaches are studied: a hybrid search and sample optimization algorithm and a classical algorithm that assesses the cost and performance of quantum algorithms in chemistry. Hybrid algorithms are vital due to limitations in both classical and quantum computing, offering a solution by leveraging the strengths of both. The first algorithm, quantum Metropolis Solver (QMS), adapts a quantum walk to a Metropolis-Hastings algorithm for industrial applications, demonstrating advantages over classical counterparts in various sectors. The second algorithm, TFermion, is a classical tool for evaluating the cost of T-type gates in quantum chemistry algorithms, aiding in the comparison and execution of these algorithms on real quantum hardware, and applied to the design of more efficient electric batteries.