arXiv subjects

Masayuki Hiromoto

Publications and source records attributed to Masayuki Hiromoto.

4 recordsLinked to original sources

arXiv2026

Development and Characterization of Low-Scattering Vanadium Nanoparticle Targets for Short-Range Interaction Searches

We developed high-purity vanadium-based nanoparticle targets for neutron scattering experiments aimed at exploring gravity-like short-range new interactions in the submicron regime. Vanadium and V-Ni nanoparticles were fabricated using top-down and bottom-up methods and quantitatively characterized by SEM-EDS, ICP-AES, NDIR and SAXS. Through the performance tests, an RF thermal plasma method was found to be the best from viewpoints of the reproducibility, dispersion of the radius, and contamination of metallic elements. The oxygen incorporation during fabrication was quantified, and its impact on the effective coherent scattering length was evaluated, leading to a minimum average coherent scattering length of $\mathrm{0.719(23)\,fm}$, comparable to that of natural vanadium. These results demonstrate that vanadium-based nanoparticle targets with controlled composition and nanostructure can be systematically designed and fabricated to suppress nuclear scattering backgrounds, thereby enabling experimentally viable coherent neutron scattering measurements for short-range interaction searches.

physics.ins-det↗

arXiv2021

ENSEI: Efficient Secure Inference via Frequency-Domain Homomorphic Convolution for Privacy-Preserving Visual Recognition

In this work, we propose ENSEI, a secure inference (SI) framework based on the frequency-domain secure convolution (FDSC) protocol for the efficient execution of privacy-preserving visual recognition. Our observation is that, under the combination of homomorphic encryption and secret sharing, homomorphic convolution can be obliviously carried out in the frequency domain, significantly simplifying the related computations. We provide protocol designs and parameter derivations for number-theoretic transform (NTT) based FDSC. In the experiment, we thoroughly study the accuracy-efficiency trade-offs between time- and frequency-domain homomorphic convolution. With ENSEI, compared to the best known works, we achieve 5--11x online time reduction, up to 33x setup time reduction, and up to 10x reduction in the overall inference time. A further 33% of bandwidth reductions can be obtained on binary neural networks with only 1% of accuracy degradation on the CIFAR-10 dataset.

cs.CR↗

arXiv2019

Measurement of the total neutron scattering cross section ratios of noble gases of natural isotopic composition using a pulsed neutron beam

Precision measurements of slow neutron cross sections with atoms have several scientific applications. In particular the n-$^{4}$He s-wave scattering length is important to know both for helping to constrain the nuclear three-body interaction and for the proper interpretation of several ongoing slow neutron experiments searching for other types of neutron-atom interactions. We present new measurements of the ratios of the neutron differential scattering cross sections for natural isotopic-abundance mixtures of the noble gases He, Ar, Kr, and Xe to natural isotopic abundance Ne. These measurements were performed using a recently developed neutron scattering apparatus for gas samples located on a pulsed slow neutron beamline which was designed to search for possible exotic neutron-atom interactions and employs both neutron time of flight information and a position-sensitive neutron detector for scattering event reconstruction. We found agreement with the literature values of scattering cross sections inferred from Ar/Ne, Kr/Ne and Xe/Ne differential cross section ratios over the $q$ range of $1 - 7$ nm$^{-1}$. However for the case of He/Ne we find that the cross section inferred differs by 11.3% (7.6 $σ$) from previously-reported values inferred from neutron phase shift measurements, but is in reasonable agreement with values from other measurements. The very large discrepancy in the He/Ne ratio calls for a new precision measurement of the n-$^{4}$He scattering length using neutron interferometry.

nucl-ex↗

arXiv2019

GPU Based Parallel Ising Computing for Combinatorial Optimization Problems in VLSI Physical Design

In VLSI physical design, many algorithms require the solution of difficult combinatorial optimization problems such as max/min-cut, max-flow problems etc. Due to the vast number of elements typically found in this problem domain, these problems are computationally intractable leading to the use of approximate solutions. In this work, we explore the Ising spin glass model as a solution methodology for hard combinatorial optimization problems using the general purpose GPU (GPGPU). The Ising model is a mathematical model of ferromagnetism in statistical mechanics. Ising computing finds a minimum energy state for the Ising model which essentially corresponds to the expected optimal solution of the original problem. Many combinatorial optimization problems can be mapped into the Ising model. In our work, we focus on the max-cut problem as it is relevant to many VLSI physical design problems. Our method is inspired by the observation that Ising annealing process is very amenable to fine-grain massive parallel GPU computing. We will illustrate how the natural randomness of GPU thread scheduling can be exploited during the annealing process to create random update patterns and allow better GPU resource utilization. Furthermore, the proposed GPU-based Ising computing can handle any general Ising graph with arbitrary connections, which was shown to be difficult for existing FPGA and other hardware based implementation methods. Numerical results show that the proposed GPU Ising max-cut solver can deliver more than 2000X speedup over the CPU version of the algorithm on some large examples, which shows huge performance improvement for addressing many hard optimization algorithms for practical VLSI physical design.

physics.comp-ph↗