Laser cleaning is an emerging technique that has advantages of high energy performance and low chemical-waste emissions, thus minimizing environmental impact. We investigated pulse laser derusting of steel substrates severely corroded by iron rust (beta-FeOOH) containing high concentrations of Cl- ions as well as corrosion resistance of the resulting surface. Analyzing residual rust at different laser spot overlap rates and the same laser fluence revealed that laser energy density is a key parameter controlling removal of rust and Cl- ions. Under the same energy density but different laser fluences, the ablation rate strongly depended on laser fluence. The threshold fluence for rust removal was about 5 J/cm(2), above which ablation of beta-FeOOH proceeded continuously and left behind Fe3O4 and/or FeO grains. Below the threshold fluence, beta-FeOOH became dehydrated and transformed into gamma-Fe2O3, which built up on the rust layer underneath. In contrast, the Cl content in the residual rust monotonically decreased without saturation, which indicated that Cl- desorption proceeded independently of ablation of the rust layer. A few months after the cleaning, atmospheric recorrosion of the samples were examined. If the cleaning had left behind residual Fe3O4 and FeO, there was significant recorrosion recovering beta-FeOOH, where Cl- ions segregated at the surface of these iron oxides facilitated absorption of moisture. The threshold surface chloride density where recorrosion did not proceed coincided with the generally accepted value of 50 mg/m(2) to warrant painting on it. In contrast, a surface covered by a Cl--depleted gamma-Fe2O3 passivation layer showed no recorrosion.
This work presents a framework for compressing self-supervised models for speaker diarization through structured pruning guided by knowledge distillation. We investigate pruning objectives that target reducing both model parameters and computational complexity, where knowledge distillation enables compact models and pruning removes unnecessary parameters to improve hardware efficiency. We further analyze alternative pruning strategies, showing that a simple overall pruning approach provides the best balance between efficiency and accuracy. Compared to the original unpruned model, our method achieves up to 80% model size reduction and 4x faster inference without performance degradation. Comprehensive experiments across eight public diarization datasets demonstrate that the pruned models consistently match or surpass the performance of their uncompressed counterparts. Furthermore, we show strong out-of-domain generalization on the CHiME-6 dataset, achieving accuracy comparable to the top systems in the CHiME-7 challenge without any domain adaptation. These results highlight that structured pruning, when guided by distillation, can yield efficient and generalizable diarization systems suitable for real-world applications.
Many methods have been proposed for presenting digital information in mirror space, but existing methods were limited to displaying information confined within the mirror space. Therefore, we propose mirror-transcending aerial imaging (MiTAI), which allows digital information to move continuously between mirrored and physical spaces. By seamlessly fusing mirror space, physical space, and digital information, MiTAI offers an unprecedented interactive experience. This paper presents a detailed description of the MiTAI system, designed to allow users to experience the concept and facilitate initial studies toward its evaluation. Specifically, we detail the system implementation, including the refinement of the optical system based on previous studies, the control system design, content presentation designs, and interaction methods with the aerial image. Moreover, we report on an experiment evaluating the pointing accuracy in the depth direction of the interaction method and a user evaluation conducted using a refined system setup for a hands-on demonstration to evaluate the user experience. Finally, we present user feedback from the exhibition and discuss future points for improvement.
Encoding logical qubits with surface codes and performing multi-qubit logical operations with lattice surgery is one of the most promising approaches to demonstrate fault-tolerant quantum computing. Thus, a method to efficiently schedule a sequence of lattice-surgery operations is vital for high-performance fault-tolerant quantum computing. A possible strategy to improve the throughput of lattice-surgery operations is splitting a large instruction into several small instructions, such as Bell state preparation and measurements, and executing a part of them in advance. However, scheduling methods to fully utilize this idea have yet to be explored. In this paper, we propose a fast and high-performance scheduling algorithm for lattice-surgery instructions leveraging this strategy. We achieved this by converting the scheduling problem of lattice-surgery instructions to a graph problem of embedding 3D paths into a 3D lattice, which enables us to explore efficient scheduling by solving path search problems in the 3D lattice. Based on this reduction, we propose a method to solve the path-finding problems, the look-ahead Dijkstra projection. We numerically show that this method reduced the execution time of benchmark programs generated from quantum phase estimation algorithms by 3.8 times compared with a naive method based on greedy algorithms. Our study establishes the relation between the lattice-surgery scheduling and graph search problems, which leads to further theoretical analysis on compiler optimization of fault-tolerant quantum computing.
We report detection of 10.1 ± 0.2-dB squeezed light from a broadband periodically poled lithium niobate (PPLN) waveguide optical parametric amplifier (OPA). Based on our previous report, where a similar PPLN waveguide shows 8.3-dB squeezing [T. Kashiwazaki et al., Appl. Phys. Lett.122, 234003 (2023)10.1063/5.0144385], we reduce phase fluctuations and overall optical losses in the measurement system. In particular, we introduce a phase detection technique that does not require tapping a part of the squeezed light to get a phase locking signal. We use a phase-detection OPA seeded by a tapped probe and pump light before a squeezer OPA. This configuration breaks the conventional trade-off between generating a phase-locking signal with a high signal-to-noise ratio and suppressing the degradation of the squeezing level caused by optical tapping. With all these improvements, the phase fluctuation angle is reduced from 14 mrad to 9 mrad, and the total optical loss from 12% to 8%. Achieving more than 10 dB of squeezing by the broadband waveguide OPA is a significant step towards the realization of fault-tolerant ultra-fast universal optical quantum computation.
