arXiv subjects

Jiwon Yun

Publications and source records attributed to Jiwon Yun.

7 recordsLinked to original sources

arXiv2026

High-fidelity two-qubit gates in a 7-qubit register for quantum networks

Quantum networks based on optically active solid-state spins may enable quantum technologies including long-range quantum communication and distributed quantum computing. Network nodes containing multiple high-fidelity qubits can facilitate large-scale fault-tolerant operation. However, the stringent error thresholds remain out of reach for multi-qubit registers. In this work, we demonstrate high-fidelity two-qubit gates in a 7-qubit register, based on nuclear spins coupled to a nitrogen-vacancy (NV) center in diamond. We analyze crosstalk in highly connected spin systems, develop an efficient optimization procedure, and characterize the gates using gate set tomography. The two-qubit gate fidelities (best: 99.61(5)%, average: 99.18(2)%) demonstrate a multi-qubit register at the threshold for distributed quantum computation. Finally, as an example application, we perform a variational quantum eigensolver (VQE) simulation of the ground-state energy of H2 and LiH molecules. These results demonstrate one of the key prerequisites for scalable quantum networks based on solid-state spins.

quant-ph↗

arXiv2026

Trans-dimensional Hamiltonian model selection and parameter estimation from sparse, noisy data

High-throughput characterization often requires estimating parameters and model dimension from experimental data of limited quantity and quality. Such data may result in an ill-posed inverse problem, where multiple sets of parameters and model dimensions are consistent with available data. This ill-posed regime may render traditional machine learning and deterministic methods unreliable or intractable, particularly in high-dimensional, nonlinear, and mixed continuous and discrete parameter spaces. To address these challenges, we present a Bayesian framework that hybridizes several Markov chain Monte Carlo (MCMC) sampling techniques to estimate both parameters and model dimension from sparse, noisy data. By integrating sampling for mixed continuous and discrete parameter spaces, reversible-jump MCMC to estimate model dimension, and parallel tempering to accelerate exploration of complex posteriors, our approach enables principled parameter estimation and model selection in data-limited regimes. We apply our framework to a specific ill-posed problem in quantum information science: recovering the locations and hyperfine couplings of nuclear spins surrounding a spin-defect in a semiconductor from sparse, noisy coherence data. We show that a hybridized MCMC method can recover meaningful posterior distributions over physical parameters using an order of magnitude less data than existing approaches, and we validate our results on experimental measurements. More generally, our work provides a flexible, extensible strategy for solving a broad class of ill-posed inverse problems under realistic experimental constraints.

quant-ph↗

arXiv2021

Temperature selective thermometry with sub-microsecond time resolution using dressed-spin states in diamond

Versatile nanoscale sensors that are susceptible to changes in a variety of physical quantities often exhibit limited selectivity. This paper reports a novel scheme based on microwave-dressed spin states for optically probed nanoscale temperature detection using diamond quantum sensors, which provides selective sensitivity to temperature changes. By combining this scheme with a continuous pump-probe scheme using ensemble nitrogen-vacancy centers in nanodiamonds, a sub-microsecond temporal resolution with thermal sensitivity of 3.7 K$\cdot$Hz$^{-1/2}$ that is insensitive to variations in external magnetic fields on the order of 2 G is demonstrated. The presented results are favorable for the practical application of time-resolved nanoscale quantum sensing, where temperature imaging is required under fluctuating magnetic fields.

quant-ph↗

arXiv2020

Algorithmic decomposition for efficient multiple nuclear spin detection in diamond

Efficiently detecting and characterizing individual spins in solid-state hosts is an essential step to expand the fields of quantum sensing and quantum information processing. While selective detection and control of a few 13C nuclear spins in diamond have been demonstrated using the electron spin of nitrogen-vacancy (NV) centers, a reliable, efficient, and automatic characterization method is desired. Here, we develop an automated algorithmic method for decomposing spectral data to identify and characterize multiple nuclear spins in diamond. We demonstrate efficient nuclear spin identification and accurate reproduction of hyperfine interaction components for both virtual and experimental nuclear spectroscopy data. We conduct a systematic analysis of this methodology and discuss the range of hyperfine interaction components of each nuclear spin that the method can efficiently detect. The result demonstrates a systematic approach that automatically detects nuclear spins with the aid of computational methods, facilitating the future scalability of devices.

quant-ph↗

arXiv2020

Deep learning enhanced individual nuclear-spin detection

The detection of nuclear spins using individual electron spins has enabled new opportunities in quantum sensing and quantum information processing. Proof-of-principle experiments have demonstrated atomic-scale imaging of nuclear-spin samples and controlled multi-qubit registers. However, to image more complex samples and to realize larger-scale quantum processors, computerized methods that efficiently and automatically characterize spin systems are required. Here, we realize a deep learning model for automatic identification of nuclear spins using the electron spin of single nitrogen-vacancy (NV) centers in diamond as a sensor. Based on neural network algorithms, we develop noise recovery procedures and training sequences for highly non-linear spectra. We apply these methods to experimentally demonstrate fast identification of 31 nuclear spins around a single NV center and accurately determine the hyperfine parameters. Our methods can be extended to larger spin systems and are applicable to a wide range of electron-nuclear interaction strengths. These results enable efficient imaging of complex spin samples and automatic characterization of large spin-qubit registers.

quant-ph↗

arXiv2019

Strong polarization of individual nuclear spins weakly coupled to nitrogen-vacancy color centers in diamond

We experimentally demonstrate high degree of polarization of 13C nuclear spins weakly interacting with nitrogen-vacancy (NV) centers in diamond. We combine coherent microwave excitation pulses with optical illumination to provide controlled relaxation and achieve a polarity-tunable, fast nuclear polarization of degree higher than 85% at room temperature for remote 13C nuclear spins exhibiting hyperfine interaction strength with NV centers of the order of 600 kHz. We show with the aid of numerical simulation that the anisotropic hyperfine tensor components naturally provide a route to control spin mixing parameter so that highly efficient nuclear polarization is enabled through careful tuning of nuclear quantization axis by external magnetic field. We further discuss spin dynamics and wide applicability of this method to various target 13C nuclear spins around the NV center electron spin. The proposed control method demonstrates an efficient and versatile route to realize, for example, high-fidelity spin register initialization and quantum metrology using nuclear spin resources in solids.

quant-ph↗

arXiv2018

An efficient fluorescent single-particle position tracking system for long-term pulsed measurements of nitrogen-vacancy centers in diamond

A simple and convenient design enables real-time three-dimensional position tracking of nitrogen-vacancy (NV) centers in diamond. The system consists entirely of commercially available components (a single photon counter, a high-speed digital-to-analog converter, a phase-sensitive detector-based feedback device, and a piezo stage), eliminating the need for custom programming or rigorous optimization processes. With a large input range of counters and trackers combined with the high sensitivity of single-photon counting, high-speed position tracking (upper bound recovery time of 0.9 s upon 250 nm of step-like positional shift) not only of bright ensembles but also of low-photon-collection-efficiency single to few NV centers is possible. The tracking requires position modulation of only 10 nm, which allows simultaneous position tracking and pulsed measurements in the long term. Therefore, this tracking system enables measuring a single spin magnetic resonance and Rabi oscillations at a very high resolution even without photon collection optimization. The system is widely applicable to various fields related to NV centers quantum manipulation research such as NV optical trapping, NV tracking in fluid dynamics, and biological sensing using NV centers inside a biological cell.

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