arXiv subjects

Hyungseok Kim

Publications and source records attributed to Hyungseok Kim.

6 recordsLinked to original sources

arXiv2026

SpiderLS: Leveraging Full ZX Reduction for Lattice Surgery Compilation

Lattice surgery compilation plays a central role in translating fault-tolerant quantum programs into efficient surface code realizations, where both spatial and temporal resources directly determine the cost of execution. Recent work has demonstrated the benefits of using ZX-diagrams as an intermediate representation for lattice surgery compilation, enabling semantics-preserving transformations that reduce spacetime cost. However, existing compilation restricts ZX reduction to preserve diagram structures that can be directly embedded as lattice surgery junctions. We present SpiderLS, which extends prior approach by leveraging full ZX reduction. To translate the resulting diagram into executable lattice surgery operations, SpiderLS applies a sequence of compiler passes that derives an execution order, generates target code by grouping compatible interactions into multi-target operations, and lowers the target code to Pauli-product measurements. The resulting explicit patch and Pauli-boundary requirements guide logical scheduling and structure-aware spacetime routing. Across representative algorithmic and random workloads, SpiderLS achieves average reductions of 49.2% in spacetime volume and 99.8% in compilation time compared with the prior ZX-based compiler.

quant-ph↗

arXiv2026

Plutarch: Toward Scalable Operational Parallelism on Racetrack-Shaped Trapped-Ion Processors

A recent advancement in quantum computing shows a quantum advantage of certified randomness on the racetrack processor. This work investigates the execution efficiency of this architecture for general-purpose programs. We first explore the impact of increasing zones on runtime efficiency. Counterintuitively, our evaluations using variational programs reveal that expanding zones may degrade runtime performance under the existing scheduling policy. This degradation may be attributed to the increase in track length, which increases ion circulation overhead, offsetting the benefits of enhanced parallelism. To mitigate this, the proposed \textit{Plutarch} exploits 3 strategies: (i) unitary decomposition and translation to maximize zone utilization, (ii) prioritizing the execution of nearby gates over ion circulation, and (iii) implementing shortcuts to provide the alternative path.

quant-ph↗

arXiv2025

A perspective on inelastic light scattering spectroscopy for probing transport of collective acoustic excitations

Understanding and manipulating nanoscale energy transport and conversion processes are essential for diverse applications, ranging from thermoelectrics and energy harvesting to thermal management of microelectronics. While it has long been recognized that acoustic and thermal properties in condensed matters are primarily due to microscopic transport of phonons as quasiparticles, probing thermal acoustic excitations particularly at sub-THz remains a challenge primarily due to limitations in experimental techniques with spatiotemporal resolutions pertinent to probing them. Brillouin light scattering (BLS) and its variant, impulsive stimulated Brillouin scattering (ISS), provide access to these thermal acoustic excitations, enabling measurement of quantities such as acoustic dispersions along with relaxation dynamics occurring in ultrasonic as well as hypersonic frequencies. In this perspective, we provide a brief overview of the operational principles of BLS and ISS, and highlight their applications in probing acoustic, thermal, and magnetic excitations in emerging and low-dimensional materials. We conclude by discussing current challenges and future opportunities for advanced material characterization using Brillouin light scattering spectroscopy techniques.

cond-mat.mtrl-sci↗

arXiv2025

Multidimensional scaling informed by $F$-statistic: Visualizing grouped microbiome data with inference

Multidimensional scaling (MDS) is a dimensionality reduction technique for microbial ecology data analysis that represents the multivariate structure while preserving pairwise distances between samples. While its improvement has enhanced the ability to reveal data patterns by sample groups, these MDS-based methods require prior assumptions for inference, limiting their application in general microbiome analysis. In this study, we introduce a new MDS-based ordination, $F$-informed MDS, which configures the data distribution based on the $F$-statistic, the ratio of dispersion between groups sharing common and different characteristics. Using simulated compositional datasets, we demonstrate that the proposed method is robust to hyperparameter selection while maintaining statistical significance throughout the ordination process. Various quality metrics for evaluating dimensionality reduction confirm that $F$-informed MDS is comparable to state-of-the-art methods in preserving both local and global data structures. Its application to a diatom-associated bacterial community suggests the role of this new method in interpreting the community response to the host. Our approach offers a well-founded refinement of MDS that aligns with statistical test results, which can be beneficial for broader compositional data analyses in microbiology and ecology. This new visualization tool can be incorporated into standard microbiome data analyses.

stat.AP↗

arXiv2025

Mantra: Rewriting Quantum Programs to Minimize Trap-Movements for Zoned Rydberg Atom Arrays

A zoned neutral atom architecture achieves exceptional fidelity by segregating the execution spaces of 1- and 2-qubit gates, being a promising candidate for high-accuracy quantum systems. Unfortunately, naively applying programs designed for static qubit topologies to zoned architectures may result in most execution time being consumed by inter-zone travels of atoms. To address this, we introduce Mantra (Minimizing trAp movemeNts for aTom aRray Architectures), which rewrites quantum programs to reduce the interleaving of single- and two-qubit gates. Mantra incorporates three strategies: (i) a fountain-shaped controlled-Z (CZ) chain, (ii) ZZ-interaction protocol without a 1-qubit gate, and (iii) preemptive gate scheduling. Mantra reduces inter-zone movements by 68%, physical gate counts by 35%, and improves circuit fidelities by 17% compared to the standard executions.

quant-ph↗

arXiv2024

Distribution-Adaptive Dynamic Shot Optimization for Variational Quantum Algorithms

Variational quantum algorithms (VQAs) have attracted remarkable interest over the past few years because of their potential computational advantages on near-term quantum devices. They leverage a hybrid approach that integrates classical and quantum computing resources to solve high-dimensional problems that are challenging for classical approaches alone. In the training process of variational circuits, constructing an accurate probability distribution for each epoch is not always necessary, creating opportunities to reduce computational costs through shot reduction. However, existing shot-allocation methods that capitalize on this potential often lack adaptive feedback or are tied to specific classical optimizers, which limits their applicability to common VQAs and broader optimization techniques. Our observations indicate that the information entropy of a quantum circuit's output distribution exhibits an approximately exponential relationship with the number of shots needed to achieve a target Hellinger distance. In this work, we propose a distribution-adaptive dynamic shot (DDS) framework that efficiently adjusts the number of shots per iteration in VQAs using the entropy distribution from the prior training epoch. Our results demonstrate that the DDS framework sustains inference accuracy while achieving a ~50% reduction in average shot count compared to fixed-shot training, and ~60% higher accuracy than recently proposed tiered shot allocation methods. Furthermore, in noisy simulations that reflect the error rates of actual IBM quantum systems, DDS achieves approximately a ~30% reduction in the total number of shots compared to the fixed-shot method with minimal degradation in accuracy, and offers about ~70% higher computational accuracy than tiered shot allocation methods.

quant-ph↗