arXiv subjects

Kohei Matsuura

Publications and source records attributed to Kohei Matsuura.

At least 19 recordsLinked to original sources

arXiv2026

Extended strange metal regime in a pure nematic quantum critical superconductor

High-temperature superconductivity often emerges from a strange metallic state, where the electrical resistivity exhibits a linear-in-temperature dependence over an anomalously extended temperature range. The prevailing belief is that magnetic critical fluctuations gives rise to strange metallicity, enhancing the superconducting transition temperature. Here, using high pulsed magnetic fields, we have uncovered the strange metallic ground state hidden below the superconducting dome of nonmagnetic FeSe$_{1-x}$Te$_{x}$, which harbors a quantum critical point (QCP) of pure electronic nematicity, characterized by spontaneous rotational symmetry breaking. Unlike the conventional quantum criticality, this strange metallic state does not appear in a fan-shaped region above the singular QCP but spans a wide compositional range, where pairing interactions are strengthened by nonmagnetic nematic critical fluctuations. This stands in sharp contrast to the much cleaner system FeSe$_{1-x}$S$_{x}$, which displays a quantum critical fan above nematic QCP, indicating that disorder-induced spatial randomness of the nematic fluctuations likely enlarges the QCP of FeSe$_{1-x}$Te$_{x}$ into an extended region of criticality, as suggested by relevant hybrid Quantum Monte Carlo simulations. These observations highlight superconductivity promoted by a unique interplay between pure nematic critical fluctuations, strange metallicity and disorder, providing new insight into the emergence of non-Fermi-liquid transport in various correlated materials.

cond-mat.supr-con↗

arXiv2026

Heralded Leakage Detection with Preserved Computational-State Coherence in a Fixed-Frequency Transmon

Leakage out of the computational subspace is a major error mechanism in superconducting quantum processors. Detecting leakage without disturbing the encoded quantum information can provide a heralded error signal that error-correction decoders exploit. However, standard dispersive readout collapses all qubit eigenstates indiscriminately. Here, we demonstrate heralded leakage detection on a fixed-frequency transmon by applying a Rabi drive on the computational transition during dispersive readout. The drive makes the computational states indistinguishable to the probe on the resonator while leaving the second and higher excited states distinguishable from the computational states. We achieve a leakage-detection fidelity of 97.1(3)% within the 80-ns detection window, with a false-flag rate of 2.3(3)% from the computational subspace. Conditioned on the no-leakage outcome, the post-detection state retains an average fidelity of 92.9(5)% across the six cardinal states for an equal mixture of computational and leakage population. The scheme requires no circuit elements beyond those used for standard dispersive readout, making it applicable to various types of superconducting qubits without hardware modification.

quant-ph↗

arXiv2026

Improving Large-Scale Weakly Supervised ASR by Filtering and Selection

Leveraging large-scale weakly supervised datasets is crucial to train robust end-to-end automatic speech recognition (ASR) models. However, such datasets often contain noisy labels and lack domain specificity, limiting their effectiveness. To address these issues and make better use of weakly supervised datasets, we propose a novel training approach incorporating data filtering and selection. Our approach consists of three steps: pretraining on the entire dataset, continued pretraining on a filtered subset based on character error rate (CER), and fine-tuning on a small number of acoustically similar samples to the target domain, selected from the filtered subset. In experiments with a 90,000-hour weakly supervised Japanese dataset, the proposed filtering and selection methods synergistically reduced CER by up to 6.4% and 4.0%, respectively, even though these steps reused training samples already used in the first pretraining step.

eess.AS↗

arXiv2026

Systematic frequency-collision analysis of the cross-resonance gate outside the straddling regime

Frequency crowding remains a major obstacle to scaling fixed-frequency transmon processors. Among the widely used all-microwave two-qubit gates, the cross-resonance (CR) gate is particularly sensitive to qubit-frequency spread because the conventional straddling regime condition constrains assignable qubit frequencies tightly and makes the system susceptible to frequency collisions. Here, we propose and analyze the CR gate outside the straddling regime, which we refer to as the far-detuned regime, and evaluate frequency collisions using a numerical method that remains accurate under high-intensity, smoothly ramped microwave drives. Based on this analysis, we perform systematic parameter sweeps and provide collision-free conditions that define designable frequency regions in which qubit frequencies can be assigned consistently with surrounding qubit frequencies. Furthermore, we formulate frequency allocation as a linear programming optimization on a unit-cell lattice with periodic boundary conditions to obtain an optimal allocation. We demonstrate that far-detuned designs significantly reduce collisions compared with designs in the straddling regime. Monte Carlo yield analysis indicates that 10% collision-free yield for a 1024-qubit square lattice at a 0.1% two-qubit-gate error threshold requires $σ_{\mathrm{f}}/2π\le 6.8~\mathrm{MHz}$. Our findings suggest that this is feasible with an approximately twofold reduction in the state-of-the-art qubit-frequency spread.

quant-ph↗

arXiv2026

High-gain and large-bandwidth Josephson parametric amplifier influenced by Fabry-Pérot interference

Quantum-limited parametric amplifiers are essential components for many quantum technologies operating in the microwave domain. Achieving both high gain and broad bandwidth, however, remains challenging due to trade-offs between gain and bandwidth, pump efficiency, and dynamic range. Moreover, high-gain broadband amplifiers become increasingly sensitive to their external electromagnetic environment, which can distort their gain spectra and hinder reliable operation. Here, we present an accurate theoretical model and a systematic design methodology for a flux-driven, lumped-element Josephson parametric amplifier based on a SQUID array. Our device achieves near-quantum-limited, phase-preserving amplification with a net gain of 20 (maximally 44) dB and a 3-dB bandwidth of $\sim$50 ($\lesssim$0.2) MHz. We further show that the gain spectra exhibit pronounced sensitivity to weak reflections in the input-output waveguide caused by impedance mismatches in the microwave environment. By incorporating Fabry-Pérot-type interference into a quantum input-output model, we analytically reproduce these complex spectral features and identify how they depend on the physical parameters of the environment. More generally, our results provide a practical framework for separating the intrinsic dynamics of parametric amplifiers from environmental effects. This approach enables reliable characterization and optimization of amplifier performance while providing a systematic strategy for diagnosing microwave reflections and engineering environmental interference to shape amplifier gain spectra, thereby offering a pathway toward robust, reproducible, and truly quantum-limited microwave amplification.

quant-ph↗

arXiv2026

Deterministic Quantum Communication Between Fixed-Frequency Superconducting Qubits via Broadband Resonators

Quantum communication between remote chips is essential for realizing large-scale superconducting quantum computers. For such communication, itinerant microwave photons propagating through transmission lines offer a promising approach. However, demonstrations to date have relied on frequency-tunable circuit elements to compensate for fabrication-related parameter variations between sender and receiver devices, introducing control complexity and limiting scalability. In this work, we demonstrate deterministic quantum state transfer and remote entanglement generation between fixed-frequency superconducting qubits on separate chips. To compensate for the sender-receiver mismatch, we employ a frequency-tunable photon-generation technique which enables us to adjust the photon frequency without modifying circuit parameters. To enhance the frequency tunability, we implement broadband transfer resonators composed of two coupled coplanar-waveguide resonators, achieving a bandwidth of more than 100 MHz. This broadband design enables successful quantum communication across a 30-MHz range of photon frequencies between the remote qubits. Quantum process tomography reveals state transfer fidelities of around 79% and Bell-state fidelities of around 73% across the full frequency range. Our approach avoids the complexity of the control lines and noise channels, providing a flexible pathway toward scalable quantum networks.

quant-ph↗

arXiv2026

Temporal-Mode Engineering for Multiplexed Microwave Photons and Mode-Selective Quantum State Transfer

Quantum communication between distant superconducting qubits on separate chips using itinerant microwave photons has been studied to realize distributed quantum information processing. To enhance information capacity and fault tolerance in quantum networks, it is beneficial to encode a large quantity of quantum information using auxiliary degrees of freedom of these photons. In this work, we experimentally investigate the use of temporal modes of photon wave packets. Through the photon-shaping technique with a fixed-frequency transmon qubit, we generate single microwave photons in four orthogonal temporal modes propagating along a waveguide. We demonstrate mode-selective absorption across orthogonal modes via the time-reversed process of emission, achieving absorption efficiencies exceeding 0.89 for mode-matched cases, while remaining below 0.13 for orthogonal modes. Photons rejected by a given receiver mode can remain mutually orthogonal, enabling selective absorption at subsequent receivers in future multi-node architectures. These results highlight the feasibility of temporal-mode engineering for constructing a higher-dimensional orthogonal basis for multiplexed quantum networks.

quant-ph↗

arXiv2026

Generation of frequency-bin-encoded dual-rail cluster states via time-frequency multiplexing of microwave photonic qubits

Cluster states are a class of multi-qubit entangled states with broad applications such as quantum metrology and one-way quantum computing. Here, we present a protocol to generate frequency-bin-encoded dual-rail cluster states using a superconducting circuit consisting of a fixed-frequency transmon qubit, a resonator and a Purcell filter. We implement time-frequency multiplexing by sequentially emitting co-propagating microwave photons of distinct frequencies. The frequency-bin dual-rail encoding enables erasure detection based on photon occupancy. We characterize the state fidelity using quantum tomography and quantify the multipartite entanglement using the metric of localizable entanglement. Our implementation achieves a state fidelity exceeding 50$\%$ for a cluster state consisting of up to four logical qubits. The localizable entanglement remains across chains of up to seven logical qubits. After discarding the erasure errors, the fidelity exceeds 50% for states with up to eight logical qubits, and the entanglement persists across chains of up to eleven qubits. These results highlight the improved robustness of frequency-bin dual-rail encoding against photon loss compared to conventional single-rail schemes. This work provides a scalable pathway toward high-dimensional entangled state generation and photonic quantum information processing in the microwave domain.

quant-ph↗

arXiv2026

Frontend Token Enhancement for Token-Based Speech Recognition

Discretized representations of speech signals are efficient alternatives to continuous features for various speech applications, including automatic speech recognition (ASR) and speech language models. However, these representations, such as semantic or phonetic tokens derived from clustering outputs of self-supervised learning (SSL) speech models, are susceptible to environmental noise, which can degrade backend task performance. In this work, we introduce a frontend system that estimates clean speech tokens from noisy speech and evaluate it on an ASR backend using semantic tokens. We consider four types of enhancement models based on their input/output domains: wave-to-wave, token-to-token, continuous SSL features-to-token, and wave-to-token. These models are trained independently of ASR backends. Experiments on the CHiME-4 dataset demonstrate that wave-to-token enhancement achieves the best performance among the frontends. Moreover, it mostly outperforms the ASR system based on continuous SSL features.

cs.SD↗

arXiv2025

Quasiparticle interaction originating from Bogoliubov Fermi Surfaces under pressure in 18%-S substituted FeSe studied via NMR

S-substituted FeSe superconductors in the tetragonal phase display several unique features among iron-based superconductors, particularly the presence of zero-energy excitations in the superconducting (SC) state. The recent concept of Bogoliubov Fermi Surfaces (BFSs), a theoretical model describing ultranodal states, has attracted considerable interest. Nuclear magnetic resonance (NMR) studies on FeSe$_{1-x}$S$_x$ (x=0.18) have revealed an anomalous low-energy spin fluctuations deep in the SC state. The low-energy spin fluctuations are enhanced with decreasing temperature, supporting strong Bogoliubov quasiparticle interactions associated with BFSs. Here, we further investigate these correlation effects through $^{77}$Se-NMR measurements of FeSe$_{1-x}$S$_x$ (x=0.18) under pressures up to 2.0 GPa and temperatures down to ~100 mK. The results demonstrate that the anomalous enhancement is suppressed but persists under pressure, implying that quasiparticle interactions become weak by applying pressure. Furthermore, spin fluctuations in the normal state exhibit different temperature dependence from those deep in the SC state, suggesting that the nesting properties of normal electrons differ from those of Bogoliubov quasiparticles. These findings are consistent with the theoretical model of BFSs with C$_2$ symmetry and strengthen evidence for Bogoliubov quasiparticle interactions, providing insights into the unconventional pairing state of this system.

cond-mat.supr-con↗

arXiv2025

Microphone Array Geometry Independent Multi-Talker Distant ASR: NTT System for the DASR Task of the CHiME-8 Challenge

In this paper, we introduce a multi-talker distant automatic speech recognition (DASR) system we designed for the DASR task 1 of the CHiME-8 challenge. Our system performs speaker counting, diarization, and ASR. It handles various recording conditions, from diner parties to professional meetings and from two to eight speakers. We perform diarization first, followed by speech enhancement, and then ASR as the challenge baseline. However, we introduced several key refinements. First, we derived a powerful speaker diarization relying on end-to-end speaker diarization with vector clustering (EEND-VC), multi-channel speaker counting using enhanced embeddings from EEND-VC, and target-speaker voice activity detection (TS-VAD). For speech enhancement, we introduced a novel microphone selection rule to better select the most relevant microphones among the distributed microphones and investigated improvements to beamforming. Finally, for ASR, we developed several models exploiting Whisper and WavLM speech foundation models. We present the results we submitted to the challenge and updated results we obtained afterward. Our strongest system achieves a 63% relative macro tcpWER improvement over the baseline and outperforms the challenge best results on the NOTSOFAR-1 meeting evaluation data among geometry-independent systems.

eess.AS↗

arXiv2025

Generation of Frequency-Tunable Shaped Single Microwave Photons Using a Fixed-Frequency Superconducting Qubit

Scaling up a superconducting quantum computer will likely require quantum communication between remote chips, which can be implemented using an itinerant microwave photon in a transmission line. To realize high-fidelity communication, it is essential to control the frequency and temporal shape of the microwave photon. In this work, we demonstrate the generation of frequency-tunable shaped microwave photons without resorting to any frequency-tunable circuit element. We develop a framework which treats a microwave resonator as a band-pass filter mediating the interaction between a superconducting qubit and the modes in the transmission line. This interpretation allows us to stimulate the photon emission by an off-resonant drive signal. We characterize how the frequency and temporal shape of the generated photon depends on the frequency and amplitude of the drive signal. By modulating the drive amplitude and frequency, we achieve a frequency tunability of 40 MHz while maintaining the photon mode shape time-symmetric. Through measurements of the quadrature amplitudes of the emitted photons, we demonstrate consistently high state and process fidelities around 95\% across the tunable frequency range. Our hardware-efficient approach eliminates the need for additional biasing lines typically required for frequency tuning, offering a simplified architecture for scalable quantum communication.

quant-ph↗

arXiv2025

Flux-Trapping Fluxonium Qubit

In pursuit of superconducting quantum computing, fluxonium qubits have recently garnered attention for their large anharmonicity and high coherence at the sweet spot. Towards the large-scale integration of fluxonium qubits, a major obstacle is the need for precise external magnetic flux bias: To achieve high performance at its sweet spot, each qubit requires a DC bias line. However, such lines inductively coupled to the qubits bring in additional wiring overhead, crosstalk, heating, and decoherence, necessitating measures for mitigating the problems. In this work, we propose a flux-trapping fluxonium qubit, which, by leveraging fluxoid quantization, enables the optimal phase biasing without using external magnetic flux control at the operating temperature. We introduce the design and working principle, and demonstrate the phase biasing achieved through fluxoid quantization.

quant-ph↗

arXiv2025

Non-demolition fluorescence readout and high-fidelity unconditional reset of a fluxonium qubit via dissipation engineering

Non-demolition readout and high-fidelity unconditional reset of qubits are key requirements for practical quantum computation. For superconducting qubits, readout and reset are typically realized using resonators based on dispersive approximation. However, violations of the approximation often lead to detrimental effects on the qubit. In this work, we demonstrate non-demolition fluorescence readout and high-fidelity unconditional reset of a fluxonium qubit via dissipation engineering without employing a resonator. We design and implement a planar filter to protect the qubit from energy relaxation while enhancing the relaxation of the readout transition. By appropriately selecting the readout transition, we achieve fluorescence readout with enhanced quantum non-demolitionness. We also realize fast, high-fidelity and all-microwave unconditional reset of the fluxonium qubit. These results highlight the potential of superconducting-quantum computing architectures without relying on dispersive interaction between qubits and resonators.

quant-ph↗

arXiv2025

Development of microwave surface elastoresistivity measurement technique under tunable strain

By integrating a dielectric microwave resonator with a piezoelectric-based strain device, we develop an in situ strain-tunable microwave spectroscopy technique that enables contactless measurements of superconducting properties under strain. In the slightly overdoped iron-based superconductor BaFe$_2$(As$_{1-x}$P$_x$)$_2$, we successfully observe a systematic strain dependence of the superconducting transition, manifested as changes in the quality factor and resonance frequency shifts. Both compressive and tensile anisotropic lattice distortions along the [110]${_{\rm T}}$ direction suppress superconductivity, consistent with standard transport measurements, highlighting the pivotal role of nematic fluctuations in the superconducting mechanism. Our strain-tunable cavity therefore serves as a powerful, contactless probe of fundamental superconducting material properties under strain and may also potentially facilitate the design of hybrid quantum systems with strain-controlled quantum degrees of freedom.

cond-mat.supr-con↗

arXiv2024

Investigation of Speaker Representation for Target-Speaker Speech Processing

Target-speaker speech processing (TS) tasks, such as target-speaker automatic speech recognition (TS-ASR), target speech extraction (TSE), and personal voice activity detection (p-VAD), are important for extracting information about a desired speaker's speech even when it is corrupted by interfering speakers. While most studies have focused on training schemes or system architectures for each specific task, the auxiliary network for embedding target-speaker cues has not been investigated comprehensively in a unified cross-task evaluation. Therefore, this paper aims to address a fundamental question: what is the preferred speaker embedding for TS tasks? To this end, for the TS-ASR, TSE, and p-VAD tasks, we compare pre-trained speaker encoders (i.e., self-supervised or speaker recognition models) that compute speaker embeddings from pre-recorded enrollment speech of the target speaker with ideal speaker embeddings derived directly from the target speaker's identity in the form of a one-hot vector. To further understand the properties of ideal speaker embedding, we optimize it using a gradient-based approach to improve performance on the TS task. Our analysis reveals that speaker verification performance is somewhat unrelated to TS task performances, the one-hot vector outperforms enrollment-based ones, and the optimal embedding depends on the input mixture.

cs.SD↗

arXiv2024

Alignment-Free Training for Transducer-based Multi-Talker ASR

Extending the RNN Transducer (RNNT) to recognize multi-talker speech is essential for wider automatic speech recognition (ASR) applications. Multi-talker RNNT (MT-RNNT) aims to achieve recognition without relying on costly front-end source separation. MT-RNNT is conventionally implemented using architectures with multiple encoders or decoders, or by serializing all speakers' transcriptions into a single output stream. The first approach is computationally expensive, particularly due to the need for multiple encoder processing. In contrast, the second approach involves a complex label generation process, requiring accurate timestamps of all words spoken by all speakers in the mixture, obtained from an external ASR system. In this paper, we propose a novel alignment-free training scheme for the MT-RNNT (MT-RNNT-AFT) that adopts the standard RNNT architecture. The target labels are created by appending a prompt token corresponding to each speaker at the beginning of the transcription, reflecting the order of each speaker's appearance in the mixtures. Thus, MT-RNNT-AFT can be trained without relying on accurate alignments, and it can recognize all speakers' speech with just one round of encoder processing. Experiments show that MT-RNNT-AFT achieves performance comparable to that of the state-of-the-art alternatives, while greatly simplifying the training process.

eess.AS↗

arXiv2024

Boosting Hybrid Autoregressive Transducer-based ASR with Internal Acoustic Model Training and Dual Blank Thresholding

A hybrid autoregressive transducer (HAT) is a variant of neural transducer that models blank and non-blank posterior distributions separately. In this paper, we propose a novel internal acoustic model (IAM) training strategy to enhance HAT-based speech recognition. IAM consists of encoder and joint networks, which are fully shared and jointly trained with HAT. This joint training not only enhances the HAT training efficiency but also encourages IAM and HAT to emit blanks synchronously which skips the more expensive non-blank computation, resulting in more effective blank thresholding for faster decoding. Experiments demonstrate that the relative error reductions of the HAT with IAM compared to the vanilla HAT are statistically significant. Moreover, we introduce dual blank thresholding, which combines both HAT- and IAM-blank thresholding and a compatible decoding algorithm. This results in a 42-75% decoding speed-up with no major performance degradation.

eess.AS↗