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Ilkwon Byun

Publications and source records attributed to Ilkwon Byun.

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Revisiting Thermal Scalability for Large-Scale Superconducting Quantum Systems

The readout amplification chain imposes a critical thermal scalability bottleneck in large-scale superconducting quantum systems. This happens through three mechanisms: amplifier dissipation, passive conduction through bias wiring and Joule heating within that same wiring. These terms are absent or only partially represented in several prior system-level thermal-scalability models, leading to bottleneck misidentification and scalability overestimation. In this work, we improve upon previous system-level heat estimation models by fully accounting for the major heat sources in modern cryogenic quantum systems including the active dissipation, passive conduction, and Joule heating in the readout amplifier module. Our analysis demonstrates that amplifier-associated heat emerges as the dominant thermal bottleneck that fundamentally alters the thermal landscape of modern large-scale cryogenic systems. We explore various technology options and their tradeoffs to identify configurations that reduce this critical heat load and improve scalability. Finally, we evaluate forward-looking system configurations, including larger refrigeration platforms and optical approaches, and analyze forward-looking pathways toward single-fridge 10k-qubit cryogenic systems.

quant-ph

Accelerating BP-based decoders for QLDPC Codes with Local Syndrome-Based Preprocessing

Due to the high error rate of qubits, detecting and correcting errors is essential for achieving fault-tolerant quantum computing (FTQC). Quantum low-density parity-check (QLDPC) codes are one of the most promising quantum error correction (QEC) methods due to their high encoding rates. BP (Belief Propagation)-based decoders are widely used and highly competitive for QLDPC codes because BP offers inherent parallelism and strong scalability. However, BP-based decoders still suffer from high decoding latency, a large portion of which is spent in the iterative BP stage. In this paper, we propose a lightweight preprocessing step that utilizes local patterns in the syndrome to detect likely trivial error events and provide them as hints to BP-based decoders. These hints accelerate BP convergence and thereby reduce the overall decoding time. The proposed preprocessing step offers a broadly compatible approach to reducing the latency of BP-based QLDPC decodes. On the bivariate bicycle code $[[144,12,12]]$ at low physical error rates, our method achieves a $10\times$ speedup in decoding time for BP-OSD, and more than $2\times$ speedup for both BP-LSD and Relay-BP. Our method maintains the logical error rate when combined with BP-OSD and Relay-BP, while further achieving a significant reduction in logical error rate when combined with BP-LSD.

quant-ph