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Paper 1

Assessing System Capabilities and Bottlenecks of an Early Fault-Tolerant Bicycle Architecture

Kun Liu, Ben Foxman, Gian-Luca R. Anselmetti, Yongshan Ding

Year
2026
Journal
arXiv preprint
DOI
arXiv:2604.20013
arXiv
2604.20013

Early modular fault tolerant quantum computers remain constrained by costly inter-module communication and limited magic state factory service. Understanding such bottlenecks and investigating compiler optimizations most close the gap between algorithm requirements and hardware capabilities is a concrete and practically urgent systems problem. We study the modular architectures based on Bivariate Bicycle codes and identify the dominant bottleneck: inter-module communication induced by non-Clifford operations. We build a compilation pipeline to fill the missing parts of prior works and propose compiler optimizations: synthesizing arbitrary-angle rotations at the factory (syn@fac), transvection based Clifford deferral, and Clifford insertion for critical path duration reduction. We extend the evaluation scope of the prior work to 40+ benchmark categories drawn from PennyLane and MQTBench, including quantum algorithms and Hamiltonian simulations with varying sizes. Under the present instruction cost, syn@fac reduces estimated circuit failure probability by a factor of 9.0 on average across non-Clifford benchmarks. The robustness persists across sweeps of instruction cost ratios, LPU count, and factory count. Besides, transvection reduces Clifford deferral compile time by 77.04\%, while Clifford insertion reduces end-to-end circuit duration by 11.54\% on average on MQTBench, with smaller gains on Hamiltonian simulations. We hope this work inspires the studies on compiler optimizations for early modular FTQC systems.

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Paper 2

Quantum optimization with arbitrary connectivity using Rydberg atom arrays

Minh-Thi Nguyen, Jin-Guo Liu, Jonathan Wurtz, Mikhail D. Lukin, Sheng-Tao Wang, Hannes Pichler

Year
2022
Journal
arXiv preprint
DOI
arXiv:2209.03965
arXiv
2209.03965

Programmable quantum systems based on Rydberg atom arrays have recently been used for hardware-efficient tests of quantum optimization algorithms [Ebadi et al., Science, 376, 1209 (2022)] with hundreds of qubits. In particular, the maximum independent set problem on so-called unit-disk graphs, was shown to be efficiently encodable in such a quantum system. Here, we extend the classes of problems that can be efficiently encoded in Rydberg arrays by constructing explicit mappings from a wide class of problems to maximum weighted independent set problems on unit-disk graphs, with at most a quadratic overhead in the number of qubits. We analyze several examples, including: maximum weighted independent set on graphs with arbitrary connectivity, quadratic unconstrained binary optimization problems with arbitrary or restricted connectivity, and integer factorization. Numerical simulations on small system sizes indicate that the adiabatic time scale for solving the mapped problems is strongly correlated with that of the original problems. Our work provides a blueprint for using Rydberg atom arrays to solve a wide range of combinatorial optimization problems with arbitrary connectivity, beyond the restrictions imposed by the hardware geometry.

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