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Takashi Kobayashi

Publications and source records attributed to Takashi Kobayashi.

At least 19 recordsLinked to original sources

Assessing fidelity-limiting factors and achieving single-qubit gate fidelity beyond 99.999% in driven silicon spin qubits

In semiconductor single-spin qubits, high-fidelity quantum gates have been demonstrated; however, achieving consistent performance remains challenging due to variations in driven qubit coherence, which is less explored than free-evolution coherence such as $T_2^*$. Here, we report single-qubit gate fidelities above 99.999%, achieved by dramatically extending the driven-spin coherence time and suppressing off-resonant driving effects that are detrimental to accurate fidelity benchmarking. We demonstrate that removing proximal reservoirs significantly enhances the spin-locking coherence time ($T_{1ρ}$), a critical metric for qubits under microwave driving. Furthermore, we reveal that in typical spin qubit setups using parity readout and rectangular pulses, off-resonant excitation of neighboring qubits causes substantial benchmarking artifacts. By optimizing device conditions to mitigate microwave-induced degradation and implementing spectrally tailored pulse shaping, we achieve a $π/2$ gate fidelity of 99.99920(2)%, with remaining errors primarily limited by incoherent noise. These results showcase the mechanisms that bound fidelity benchmarking in state-of-the-art silicon spin qubits and provide practical guidelines for achieving and verifying high fidelities in these systems.

cond-mat.mes-hall

Tangling Pull Requests: Curating a Commit Untangling Dataset from Merged PRs

Composite commits (CC), in which multiple unrelated changes are bundled into a single commit, are frequent in software development and significantly hinder code comprehension and maintenance. Although machine learning-based methods have been developed to ``untangle'' such commits into smaller, coherent change sets, these methods require large-scale training data with correct untangling labels. Preparing such datasets is costly and typically requires expert labelling. In this study, we propose a scalable and cost-effective method for dataset construction by leveraging commits extracted from open-source repositories' pull requests (PRs). We empirically validated our dataset and found that when applying our filtering rules, PRs that, when viewed as a single commit, are tangled, yet each individual commit on the feature branch is atomic (ideal PRs), increased from 9.5% to 55%. This composite commits dataset is more than 5.7 times larger than previous heuristic-based datasets. Using our new dataset, we find that the PR-based dataset differs statistically from previous datasets directly constructed using Herzig's proposed heuristics even after accounting for our proposed rules that may alter CC or STS sizes. When constructing datasets using the previous heuristics, they differ statistically along dimensions that impact the confidence voters and are likely to impact learning-based approaches. We validate the impact on the original Herzig \etal method, which used confidence voters across our dataset. To show that our approach extends to other languages, we also create a Python dataset which we empirically validate, finding comparable rates for ideal PRs (56.5%).

cs.SE

Simultaneous High-Fidelity Single-Qubit Gates in a Spin Qubit Array

Silicon spin qubits offer a promising path to scalable quantum computing due to their compatibility with industrial semiconductor manufacturing and recent advances in multi-qubit integration. A key requirement for scaling quantum processors is the ability to perform high-fidelity operations in parallel across many qubits. In silicon spin systems, however, simultaneous control remains a major challenge, as fidelities typically degrade under parallel operation. In a five-qubit silicon spin array, we identify microwave-drive-induced AC Stark shifts as the dominant source of this degradation. We address this by introducing a scalable mitigation protocol based solely on pairwise phase calibrations. Using tailored control pulses on a shared control line, we achieve primitive $π/2$ gate fidelities well above 99.99% for each qubit individually, with some approaching 99.999%, surpassing previously reported fidelities in silicon spin qubits. Crucially, these fidelities are preserved above 99.99% during simultaneous operation of up to three qubits. During parallel five-qubit operation, fidelities remain at the practical fault-tolerant threshold of 99.9%, with the loss attributed to drive-induced decoherence resulting from increased microwave power. This effect can be mitigated through device-level improvements. By demonstrating that high-fidelity control is maintained during simultaneous operation, we overcome a central challenge in silicon spin qubits and highlight the potential of shared qubit-control lines for scaling.

quant-ph

Scaling of silicon spin qubits under correlated noise

The path to fault-tolerant quantum computing hinges on hardware that scales while remaining compatible with quantum error correction (QEC). Silicon spin qubits are a leading hardware candidate because they combine industrial fabrication compatibility with a nanoscale footprint that could accommodate millions of qubits on a chip. However, their suitability for QEC remains uncertain since spatially correlated noise naturally emerges from the resulting close proximity of qubits. These correlations increase the likelihood of simultaneous errors and erode the redundancy that QEC depends on. Here we quantify the spatial extent of noise correlations in a five-qubit silicon array and assess their impact on QEC. We identify two distinct sources of correlated noise: global magnetic field drifts that generate perfectly correlated fluctuations, and charge noise from two-level fluctuators that produces short-range correlations decaying within neighboring qubits. While magnetic drifts represent a critical correlated noise source that can compromise QEC, they can be mitigated. In contrast, the measured charge noise correlations are moderate, electrically tunable, and compatible with fault-tolerant operation with minimal qubit overhead. Our results establish quantitative benchmarks for correlated noise and clarify how such correlations impact the viability of quantum error correction in scalable qubit arrays.

cond-mat.mes-hall

Forecasting Developer Environments with GenAI: A Research Perspective

Generative Artificial Intelligence (GenAI) models are achieving remarkable performance in various tasks, including code generation, testing, code review, and program repair. The ability to increase the level of abstraction away from writing code has the potential to change the Human-AI interaction within the integrated development environment (IDE). To explore the impact of GenAI on IDEs, 33 experts from the Software Engineering, Artificial Intelligence, and Human-Computer Interaction domains gathered to discuss challenges and opportunities at Shonan Meeting 222, a four-day intensive research meeting. Four themes emerged as areas of interest for researchers and practitioners.

cs.SE

Inferring charge-noise source locations from correlations in spin qubits

We investigate low-frequency noise in a spin-qubit device made in isotopically purified Si/Si-Ge. Observing sizable cross-correlations among energy fluctuations of different qubits, we conclude that these fluctuations are dominated by charge noise. At low frequencies, the noise spectra are not well described by a power law; instead, they reveal the presence of a few individual two-level fluctuators (TLFs). We demonstrate that the noise cross-correlations allow one to get information on the spatial location of such individual TLFs.

cond-mat.mes-hall

Charge-induced energy shift of a single-spin qubit under a magnetic-field gradient

An electron confined by a semiconductor quantum dot (QD) can be displaced by changes in electron occupations of surrounding QDs owing to the Coulomb interaction. For a single-spin qubit in an inhomogeneous magnetic field, such a displacement of the host electron results in a qubit energy shift which must be handled carefully for high-fidelity operations. Here we spectroscopically investigate the qubit energy shift induced by changes in charge occupations of nearby QDs for a silicon single-spin qubit in a magnetic-field gradient. Between two different charge configurations of an adjacent double QD, a spin qubit shows an energy shift of about 4 MHz, which necessitates strict management of electron positions over a QD array. We confirm a correlation between the qubit frequency and the charge configuration by using a postselection analysis.

cond-mat.mes-hall

The origins of noise in the Zeeman splitting of spin qubits in natural-silicon devices

We measure and analyze noise-induced energy-fluctuations of spin qubits defined in quantum dots made of isotopically natural silicon. Combining Ramsey, time-correlation of single-shot measurements, and CPMG experiments, we cover the qubit noise power spectrum over a frequency range of nine orders of magnitude without any gaps. We find that the low-frequency noise spectrum is similar across three different devices suggesting that it is dominated by the hyperfine coupling to nuclei. The effects of charge noise are smaller, but not negligible, and are device dependent as confirmed from the noise cross-correlations. We also observe differences to spectra reported in GaAs {[Phys. Rev. Lett. 118, 177702 (2017), Phys. Rev. Lett. 101, 236803 (2008)]}, which we attribute to the presence of the valley degree of freedom in silicon. Finally, we observe $T_2^*$ to increase upon increasing the external magnetic field, which we speculate is due to the increasing field-gradient of the micromagnet suppressing nuclear spin diffusion.

cond-mat.mes-hall

A Disruptive Research Playbook for Studying Disruptive Innovations

As researchers, we are now witnessing a fundamental change in our technologically-enabled world due to the advent and diffusion of highly disruptive technologies such as generative AI, Augmented Reality (AR) and Virtual Reality (VR). In particular, software engineering has been profoundly affected by the transformative power of disruptive innovations for decades, with a significant impact of technical advancements on social dynamics due to its the socio-technical nature. In this paper, we reflect on the importance of formulating and addressing research in software engineering through a socio-technical lens, thus ensuring a holistic understanding of the complex phenomena in this field. We propose a research playbook with the goal of providing a guide to formulate compelling and socially relevant research questions and to identify the appropriate research strategies for empirical investigations, with an eye on the long-term implications of technologies or their use. We showcase how to apply the research playbook. Firstly, we show how it can be used retrospectively to reflect on a prior disruptive technology, Stack Overflow, and its impact on software development. Secondly, we show it can be used to question the impact of two current disruptive technologies: AI and AR/VR. Finally, we introduce a specialized GPT model to support the researcher in framing future investigations. We conclude by discussing the broader implications of adopting the playbook for both researchers and practitioners in software engineering and beyond.

cs.SE

Evaluation of Cross-Lingual Bug Localization: Two Industrial Cases

This study reports the results of applying the cross-lingual bug localization approach proposed by Xia et al. to industrial software projects. To realize cross-lingual bug localization, we applied machine translation to non-English descriptions in the source code and bug reports, unifying them into English-based texts, to which an existing English-based bug localization technique was applied. In addition, a prototype tool based on BugLocator was implemented and applied to two Japanese industrial projects, which resulted in a slightly different performance from that of Xia et al.

cs.SE

Rapid single-shot parity spin readout in a silicon double quantum dot with fidelity exceeding 99 %

Silicon-based spin qubits offer a potential pathway toward realizing a scalable quantum computer owing to their compatibility with semiconductor manufacturing technologies. Recent experiments in this system have demonstrated crucial technologies, including high-fidelity quantum gates and multiqubit operation. However, the realization of a fault-tolerant quantum computer requires a high-fidelity spin measurement faster than decoherence. To address this challenge, we characterize and optimize the initialization and measurement procedures using the parity-mode Pauli spin blockade technique. Here, we demonstrate a rapid (with a duration of a few us) and accurate (with >99% fidelity) parity spin measurement in a silicon double quantum dot. These results represent a significant step forward toward implementing measurement-based quantum error correction in silicon.

cond-mat.mes-hall

Hamiltonian Phase Error in Resonantly Driven CNOT Gate Above the Fault-Tolerant Threshold

Because of their long coherence time and compatibility with industrial foundry processes, electron spin qubits are a promising platform for scalable quantum processors. A full-fledged quantum computer will need quantum error correction, which requires high-fidelity quantum gates. Analyzing and mitigating the gate errors are useful to improve the gate fidelity. Here, we demonstrate a simple yet reliable calibration procedure for a high-fidelity controlled-rotation gate in an exchange-always-on Silicon quantum processor allowing operation above the fault-tolerance threshold of quantum error correction. We find that the fidelity of our uncalibrated controlled-rotation gate is limited by coherent errors in the form of controlled-phases and present a method to measure and correct these phase errors. We then verify the improvement in our gate fidelities by randomized benchmark and gate-set tomography protocols. Finally, we use our phase correction protocol to implement a virtual, high-fidelity controlled-phase gate.

cond-mat.mes-hall

Spatial noise correlations beyond nearest-neighbor in ${}^{28}$Si/SiGe spin qubits

We detect correlations in qubit-energy fluctuations of non-neighboring qubits defined in isotopically purified Si/SiGe quantum dots. At low frequencies (where the noise is strongest), the correlation coefficient reaches 10% for a next-nearest-neighbor qubit-pair separated by 200 nm. Assigning the observed noise to be of electrical origin, a simple theoretical model quantitatively reproduces the measurements and predicts a polynomial decay of correlations with interqubit distance. Our results quantify long-range correlations of noise dephasing quantum-dot spin qubits arranged in arrays, essential for scalability and fault-tolerance of such systems.

cond-mat.mes-hall

A shuttling-based two-qubit logic gate for linking distant silicon quantum processors

Control of entanglement between qubits at distant quantum processors using a two-qubit gate is an essential function of a scalable, modular implementation of quantum computation. Among the many qubit platforms, spin qubits in silicon quantum dots are promising for large-scale integration along with their nanofabrication capability. However, linking distant silicon quantum processors is challenging as two-qubit gates in spin qubits typically utilize short-range exchange coupling, which is only effective between nearest-neighbor quantum dots. Here we demonstrate a two-qubit gate between spin qubits via coherent spin shuttling, a key technology for linking distant silicon quantum processors. Coherent shuttling of a spin qubit enables efficient switching of the exchange coupling with an on/off ratio exceeding 1,000 , while preserving the spin coherence by 99.6% for the single shuttling between neighboring dots. With this shuttling-mode exchange control, we demonstrate a two-qubit controlled-phase gate with a fidelity of 93%, assessed via randomized benchmarking. Combination of our technique and a phase coherent shuttling of a qubit across a large quantum dot array will provide feasible path toward a quantum link between distant silicon quantum processors, a key requirement for large-scale quantum computation.

quant-ph

Feedback-based active reset of a spin qubit in silicon

Feedback control of qubits is a highly demanded technique for advanced quantum information protocols such as quantum error correction. Here we demonstrate active reset of a silicon spin qubit using feedback control. The active reset is based on quantum non-demolition readout of the qubit and feedback according to the readout results, which is enabled by hardware data processing and sequencing. We incorporate a cumulative readout technique to the active reset protocol, enhancing initialization fidelity above a limitation imposed by accuracy of the single QND measurement fidelity. Based on an analysis of the reset protocol, we suggest a way to achieve the initialization fidelity sufficient for the fault-tolerant quantum computation.

cond-mat.mes-hall

Revisiting the Effect of Branch Handling Strategies on Change Recommendation

Although literature has noted the effects of branch handling strategies on change recommendation based on evolutionary coupling, they have been tested in a limited experimental setting. Additionally, the branches characteristics that lead to these effects have not been investigated. In this study, we revisited the investigation conducted by Kovalenko et al. on the effect to change recommendation using two different branch handling strategies: including changesets from commits on a branch and excluding them. In addition to the setting by Kovalenko et al., we introduced another setting to compare: extracting a changeset for a branch from a merge commit at once. We compared the change recommendation results and the similarity of the extracted co-changes to those in the future obtained using two strategies through 30 open-source software systems. The results show that handling commits on a branch separately is often more appropriate in change recommendation, although the comparison in an additional setting resulted in a balanced performance among the branch handling strategies. Additionally, we found that the merge commit size and the branch length positively influence the change recommendation results.

cs.SE

Quantum error correction with silicon spin qubits

Large-scale quantum computers rely on quantum error correction to protect the fragile quantum information. Among the possible candidates of quantum computing devices, silicon-based spin qubits hold a great promise due to their compatibility to mature nanofabrication technologies for scaling up. Recent advances in silicon-based qubits have enabled the implementations of high quality one and two qubit systems. However, the demonstration of quantum error correction, which requires three or more coupled qubits and often involves a three-qubit gate, remains an open challenge. Here, we demonstrate a three-qubit phase correcting code in silicon, where an encoded three-qubit state is protected against any phase-flip error on one of the three qubits. The correction to this encoded state is performed by a three-qubit conditional rotation, which we implement by an efficient single-step resonantly driven iToffoli gate. As expected, the error correction mitigates the errors due to one qubit phase-flip as well as the intrinsic dephasing due to quasi-static phase noise. These results show a successful implementation of quantum error correction and the potential of silicon-based platform for large-scale quantum computing.

quant-ph

Fast universal quantum control above the fault-tolerance threshold in silicon

Fault-tolerant quantum computers which can solve hard problems rely on quantum error correction. One of the most promising error correction codes is the surface code, which requires universal gate fidelities exceeding the error correction threshold of 99 per cent. Among many qubit platforms, only superconducting circuits, trapped ions, and nitrogen-vacancy centers in diamond have delivered those requirements. Electron spin qubits in silicon are particularly promising for a large-scale quantum computer due to their nanofabrication capability, but the two-qubit gate fidelity has been limited to 98 per cent due to the slow operation.Here we demonstrate a two-qubit gate fidelity of 99.5 per cent, along with single-qubit gate fidelities of 99.8 per cent, in silicon spin qubits by fast electrical control using a micromagnet-induced gradient field and a tunable two-qubit coupling. We identify the condition of qubit rotation speed and coupling strength where we robustly achieve high-fidelity gates. We realize Deutsch-Jozsa and Grover search algorithms with high success rates using our universal gate set. Our results demonstrate the universal gate fidelity beyond the fault-tolerance threshold and pave the way for scalable silicon quantum computers.

quant-ph