Assessing Finite Scalability in Early Fault-Tolerant Quantum Computing for Homogeneous Catalysts
Yanbing Zhou, Athena Caesura, Corneliu Buda, Xavier Jackson, Clena M. Abuan, Shangjie Guo

TL;DR
This paper analyzes how finite scalability impacts resource needs in early fault-tolerant quantum computing for simulating catalytic systems, emphasizing the importance of scalable architectures for future quantum applications.
Contribution
It introduces a framework comparing hardware archetypes and scalability models, highlighting the role of fidelity and fault-tolerance codes in quantum resource optimization.
Findings
Finite scalability increases qubit and runtime demands.
High-fidelity architectures require lower scalability thresholds.
LDPC codes reduce space-time overhead, expanding operational regimes.
Abstract
As quantum hardware advances toward fault-tolerant operation, an intermediate stage known as early fault-tolerant quantum computing (EFTQC) is emerging, where partial error correction enables meaningful computation. In this regime, the ability of quantum processors to scale in size and depth has become a crucial factor shaping their achievable performance. This study investigates how finite scalability influences resource requirements for simulating open-shell catalytic systems using Quantum Phase Estimation (QPE). The analysis compares hardware archetypes distinguished by fidelity or operation speed under two representative scalability models. Finite scalability increases qubit and runtime demands yet leaves overall scaling behavior intact, with high-fidelity architectures requiring lower minimum scalability to solve equally sized problems. These effects are largely independent of the…
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Taxonomy
TopicsQuantum Computing Algorithms and Architecture · Radiation Effects in Electronics · Distributed systems and fault tolerance
