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For a graph $G$, a subset $S$ of $V(G)$ is a {\it hop dominating set} of $G$ if every vertex not in $S$ has a $2$-step neighbor in $S$. The {\it hop domination number}, $\gamma_h(G)$, of $G$ is the minimum cardinality of a hop dominating set of $G$. In this paper, we show that for a connected triangle-free graph $G$ with $n\ge 15$ vertices, if $\delta(G)\ge 2$, then $\gamma_h(G)\le \frac{2n}{5}$, and the bound is tight. We also give some tight upper bounds on $\gamma_h(G)$ for {triangle-free} graphs $G$ that contain a Hamiltonian path or a Hamiltonian cycle.

The topological censorship theorem suggests that higher dimensional black holes can possess the domain of outer communication (DOC) of nontrivial topology. In this paper, we seek for a black hole coexisting with two bubbles adjacent to the horizon in five-dimensional minimal supergravity, under the assumptions of stationarity and bi-axisymmetry. For simplicity, we also assume that the spacetime is symmetric under the exchange of the two axisymmetric Killing vectors. To find the solution, we combine the inverse scattering method and the Harrison transformation, and we present the conditions for the absence of conical, orbifold and Dirac-Misner string singularities, respectively. As the result, we find that the black hole with topology of $S^3$ or $S^2\times S^1$ can be supported by two bubbles if we admit the conical singularities (deficits)., Comment: 15 pages, 7 figures

The space-air-ground integrated network (SAGIN) concept is vital for the development of seamless next-generation (NG) wireless coverage, integrating satellites, unmanned aerial vehicles, and manned aircraft along with the terrestrial infrastructure to provide resilient ubiquitous communications. By incorporating quantum communications using optical wireless signals, SAGIN is expected to support a synergistic global quantum Internet alongside classical networks. However, long-distance optical beam propagation requires line-of-sight (LoS) connections in the face of beam broadening and LoS blockages. To overcome blockages among SAGIN nodes, we propose deploying optical reconfigurable intelligent surfaces (ORISs) on building rooftops. They can also adaptively control optical beam diameters for reducing losses. This article first introduces the applications of ORISs in SAGINs, then examines their advances in quantum communications for typical SAGIN scenarios. Finally, the road ahead towards the practical realization of ORIS-aided NG quantum SAGINs is outlined., Comment: 8 pages, 5 figures, 1 table

Gaussian process regression (GPR) or kernel ridge regression is a widely used and powerful tool for nonlinear prediction. Therefore, active learning (AL) for GPR, which actively collects data labels to achieve an accurate prediction with fewer data labels, is an important problem. However, existing AL methods do not theoretically guarantee prediction accuracy for target distribution. Furthermore, as discussed in the distributionally robust learning literature, specifying the target distribution is often difficult. Thus, this paper proposes two AL methods that effectively reduce the worst-case expected error for GPR, which is the worst-case expectation in target distribution candidates. We show an upper bound of the worst-case expected squared error, which suggests that the error will be arbitrarily small by a finite number of data labels under mild conditions. Finally, we demonstrate the effectiveness of the proposed methods through synthetic and real-world datasets., Comment: 25 pages, 3 figures

The aim of the paper is to define the microlocal Sobolev singularities of functions using Pandey-Upadhyay's wavelet transform and provide a comparison with H\"ormander's microlocal singularities.

We propose Duality Gap KIP (DGKIP), an extension of the Kernel Inducing Points (KIP) method for dataset distillation. While existing dataset distillation methods often rely on bi-level optimization, DGKIP eliminates the need for such optimization by leveraging duality theory in convex programming. The KIP method has been introduced as a way to avoid bi-level optimization; however, it is limited to the squared loss and does not support other loss functions (e.g., cross-entropy or hinge loss) that are more suitable for classification tasks. DGKIP addresses this limitation by exploiting an upper bound on parameter changes after dataset distillation using the duality gap, enabling its application to a wider range of loss functions. We also characterize theoretical properties of DGKIP by providing upper bounds on the test error and prediction consistency after dataset distillation. Experimental results on standard benchmarks such as MNIST and CIFAR-10 demonstrate that DGKIP retains the efficiency of KIP while offering broader applicability and robust performance.

Cell-based design of a single-flux-quantum (SFQ) digital circuit requires input-output consistency; every output signal must be consumed only once by the input of the following component, which is a unique constraint, unlike the traditional CMOS digital circuit design. While there are some cell libraries and simulation tools for SFQ circuit development, they do not verify the input-output consistency, and designers have significant responsibilities to ensure it manually. Additionally, designers have to carefully manage net names without unintended duplication and correct connectivity among nets in a netlist for simulations. We propose RustSFQ, a domain-specific language (DSL) embedded in Rust that automatically ensures the input-output consistency in the SFQ circuit by leveraging the ownership system of Rust. Each SFQ circuit element is represented as a function while wires are represented as instances, and the Rust compiler verifies that multiple elements do not share a single wire through the ownership system. Circuit descriptions in the RustSFQ are successfully compiled into low-level netlists for both analog and digital circuit simulations, and the DSL provides higher productivity than the conventional design flow. Using the RustSFQ, we developed an SFQ-based Reed-Solomon encoder with a 4-bit width for the first time as a case study. We confirmed that the circuit operated correctly at 10 GHz through circuit simulations.

Dataflow-oriented spatial architectures are the emerging paradigm for higher computation performance and efficiency. AMD Versal AI Engine is a commercial spatial architecture consisting of tiles of VLIW processors supporting SIMD operations arranged in a two-dimensional mesh. The architecture requires the explicit design of task assignments and dataflow configurations for each tile to maximize performance, demanding advanced techniques and meticulous design. However, a few works revealed the performance characteristics of the Versal AI Engine through practical workloads. In this work, we provide the comprehensive performance evaluation of the Versal AI Engine using Gaussian feature computation in 3D Gaussian splatting as a practical workload, and we then propose a novel dedicated algorithm to fully exploit the hardware architecture. The computations of 3D Gaussian splatting include matrix multiplications and color computations utilizing high-dimensional spherical harmonic coefficients. These tasks are processed efficiently by leveraging the SIMD capabilities and their instruction-level parallelism. Additionally, pipelined processing is achieved by assigning different tasks to individual cores, thereby fully exploiting the spatial parallelism of AI Engines. The proposed method demonstrated a 226-fold throughput increase in simulation-based evaluation, outperforming a naive approach. These findings provide valuable insights for application development that effectively harnesses the spatial and architectural advantages of AI Engines.

Multi-scalar multiplication (MSM) is crucial in cryptographic applications and computationally intensive in zero-knowledge proofs. MSM involves accumulating the products of scalars and points on an elliptic curve over a 377-bit modulus, and the Pippenger algorithm converts MSM into a series of elliptic curve point additions (PADDs) with high parallelism. This study investigates accelerating MSM on the Versal ACAP platform, an emerging hardware that employs a spatial architecture integrating 400 AI Engines (AIEs) with programmable logic and a processing system. AIEs are SIMD-based VLIW processors capable of performing vector multiply-accumulate operations, making them well-suited for multiplication-heavy workloads in PADD. Unlike simpler multiplication tasks in previous studies, cryptographic computations also require complex operations such as carry propagation. These operations necessitate architecture-aware optimizations, including intra-core dedicated coding style to fully exploit VLIW capabilities and inter-core strategy for spatial task mapping. We propose various optimizations to accelerate PADDs, including (1) algorithmic optimizations for carry propagation employing a carry-save-like technique to exploit VLIW and SIMD capabilities and (2) a comparison of four distinct spatial mappings to enhance intra- and inter-task parallelism. Our approach achieves a computational efficiency that utilizes 50.2% of the theoretical memory bandwidth and provides 568 speedup over the integrated CPU on the AIE evaluation board.

We performed low-frequency ac first- and second-harmonic resistance measurements and dc $I-V$ measurements on bulk FeSe crystals in a temperature range between 1.8 and 150 K and in magnetic field up to 14 T. We observed considerable second-harmonic resistance, indicative of nonreciprocal charge transport, in some samples. By examining correlation between contact resistances and second-harmonic signals, we concluded that the second-harmonic resistance was not due to the genuine nonreciprocal transport effect but was caused by joule heating at a current contact through the thermoelectric effect. Our conclusion is consistent with a recent preprint (Nagata \textit{et al.}, arXiv:2409.01715), in which the authors reported a zero-field superconducting diode effect in devices fabricated with FeSe flakes and attributed it to the thermoelectric effect., Comment: 9 pages, 12 figures, 1 Table

We discuss the thermal CP phase transition in QCD at $\theta=\pi$ under a weak magnetic field background, where the electromagnetic scale anomaly gets significant. To explicitize, we work on a two-flavor Polyakov-loop Nambu-Jona-Lasinio model at $\theta=\pi$ in the mean field approximation, including the electromagnetic-scale anomaly term. We find that the thermal CP phase transition becomes first order and the strength of the first order gets more prominent as the magnetic field increases. The associated potential barrier is thermally created by the electromagnetic scale anomaly and gives rise to criticality due to the induced potential of a non-perturbative form $\sim \frac{|eB|^3}{f_\pi} \frac{|P|}{P^2 + m_0^2}$, where $eB$ denotes the magnetic field strength; $P$ the CP order parameter, and $m_0$ the isospin-symmetric current-quark mass. The CP-broken deconfinement(-like) domain, $T^{\rm (CP)}_c > T^{\rm (dec)}_{\rm pc}$, gets wider as $eB$ increases., Comment: 13 pages, 4 figures; minor typos fixed

A resistive magnetohydrodynamics simulation with a dynamo term is performed for modeling the collapsar in full general relativity. As an initial condition, a spinning black hole and infalling stellar matter are modeled based on a stellar evolution result, superimposing a weak toroidal magnetic field. After the growth of a massive torus around the black hole, the magnetic field is amplified in it, developing poloidal fields via dynamo. In an early stage of the torus growth, magnetic fluxes that fall to the vicinity of the central black hole are swallowed by the black hole and global poloidal magnetic fields that can be the source of the Blandford-Znajek mechanism are not developed. However, in a later stage in which the ram pressure of the infalling matter becomes weak, the magnetic field amplified by the black hole spin via the winding becomes large enough to expel the infalling matter by the magnetic pressure, and subsequently, a global poloidal magnetic field that penetrates the black hole is established, launching a jet along the spin axis by the Blandford-Znajek mechanism with the luminosity suitable for explaining typical long gamma-ray bursts. Together with the jet launch, the effectively viscous effect in the inner region of the torus and the magnetocentrifugal effect drive the stellar explosion with the explosion energy comparable to typical or powerful supernovae. We also find large amounts of synthesized $^{56}$Ni and Zn associated with the stellar explosion. In the presence of jet launching, $r$-process elements are weakly synthesized. The numerical results of the explosion energy, ejecta mass, and $^{56}$Ni mass are in a good agreement with those for observed broad-lined type Ic supernovae. Our result illustrates a self-consistent scenario for the gamma-ray-burst-associated broad-lined type Ic supernovae., Comment: 22 pages, 13 figures. submitted to PRD

In this paper, we present a theoretical and computational investigations of the atomic scale structure of the heterointerface formed between the (001) surface of $L1_0$-ordered iron palladium (FePd) alloy and graphene (Gr), namely, $L1_0$-FePd(001)/Gr. Using density functional theory (DFT) calculations, we demonstrate that the topmost surface layer consisting of Pd (Pd-terminated surface) becomes more energetically stable than Fe, and Pd-terminated surfaces are not conducive to Gr adsorption. On the other hand, under oxygen atmosphere conditions, our calculation suggests the presence of Fe-terminated surfaces with Gr-covered structures reproducing recent experimental observations. Moreover, the finding of Fe--O bonds formed by oxidizated surface is also consistent with those of X-ray photoelectron spectroscopy. These findings are crucial for understanding the fabrication processes of interfaces in Fe-based $L1_0$ alloy materials., Comment: 21 pages, 8 figures

Coreset selection, which involves selecting a small subset from an existing training dataset, is an approach to reducing training data, and various approaches have been proposed for this method. In practical situations where these methods are employed, it is often the case that the data distributions differ between the development phase and the deployment phase, with the latter being unknown. Thus, it is challenging to select an effective subset of training data that performs well across all deployment scenarios. We therefore propose Distributionally Robust Coreset Selection (DRCS). DRCS theoretically derives an estimate of the upper bound for the worst-case test error, assuming that the future covariate distribution may deviate within a defined range from the training distribution. Furthermore, by selecting instances in a way that suppresses the estimate of the upper bound for the worst-case test error, DRCS achieves distributionally robust training instance selection. This study is primarily applicable to convex training computation, but we demonstrate that it can also be applied to deep learning under appropriate approximations. In this paper, we focus on covariate shift, a type of data distribution shift, and demonstrate the effectiveness of DRCS through experiments.

The delay of the first-order electroweak phase transitions (EWPT) may lead to the emergence of baby universes inside wormhole structures due to the large vacuum energy density in false vacuum domains. Observers outside the false vacuum domains observe them as primordial black holes (PBHs), categorized as super-critical PBHs. We specifically investigate the dynamics of PBH formation due to delayed first-order EWPTs by solving the equations of bubble wall dynamics. We numerically confirm that such super-critical PBHs can be formed by the delayed first-order EWPT assuming spherically symmetric false vacuum domains with the thin-wall approximation for its boundary. Our numerical results show that a PBH formation criterion utilizing characteristic timescales is more appropriate than the conventional criterion based on density fluctuations. Employing our numerical results, we update the parameter regions of new physics models which can be explored by current and future constraints on the PBH abundance., Comment: 27 pages, 4 figures

Foundation models pretrained on large-scale pathology datasets have shown promising results across various diagnostic tasks. Here, we present a systematic evaluation of transfer learning strategies for brain tumor classification using these models. We analyzed 252 cases comprising five major tumor types: glioblastoma, astrocytoma, oligodendroglioma, primary central nervous system lymphoma, and metastatic tumors. Comparing state-of-the-art foundation models with conventional approaches, we found that foundation models demonstrated robust classification performance with as few as 10 patches per case, challenging the traditional assumption that extensive per-case image sampling is necessary. Furthermore, our evaluation revealed that simple transfer learning strategies like linear probing were sufficient, while fine-tuning often degraded model performance. These findings suggest a paradigm shift from extensive data collection to efficient utilization of pretrained features, providing practical implications for implementing AI-assisted diagnosis in clinical pathology., Comment: 25 pages, 7 figures

The XRISM (X-Ray Imaging and Spectroscopy Mission) satellite was successfully launched and put into a low-Earth orbit on September 6, 2023 (UT). The Resolve instrument onboard XRISM hosts an x-ray microcalorimeter detector, which was designed to achieve a high-resolution ($\leq$7 eV FWHM at 6 keV), high-throughput, and non-dispersive spectroscopy over a wide energy range. It also excels in a low background with a requirement of $< 2 \times 10^{-3}$ s$^{-1}$ keV$^{-1}$ (0.3--12.0 keV), which is equivalent to only one background event per spectral bin per 100 ks exposure. Event screening to discriminate x-ray events from background is a key to meeting the requirement. We present the result of the Resolve event screening using data sets recorded on the ground and in orbit based on the heritage of the preceding x-ray microcalorimeter missions, in particular, the Soft X-ray Spectrometer (SXS) onboard ASTRO-H. We optimize and evaluate 19 screening items of three types based on (1) the event pulse shape, (2) relative arrival times among multiple events, and (3) good time intervals. We show that the initial screening, which is applied for science data products in the performance verification phase, reduces the background rate to $1.8 \times 10^{-3}$ s$^{-1}$ keV$^{-1}$ meeting the requirement. We further evaluate the additional screening utilizing the correlation among some pulse shape properties of x-ray events and show that it further reduces the background rate particularly in the $<$2 keV band. Over 0.3--12 keV, the background rate becomes $1.0 \times 10^{-3}$ s$^{-1}$ keV$^{-1}$.

The origin of neutrino masses can be simply attributed to a new scalar beyond the Standard Model. We demonstrate that leptogenesis can explain the baryon asymmetry of the universe already in such a minimal framework, where the electroweak scalar is favored to enhance the baryon asymmetry. Different from traditional leptogenesis, the realization here exploits the thermal behavior of leptons at finite temperatures, which is otherwise kinetically forbidden in vacuum. We present detailed calculations of the CP asymmetry in the Schwinger-Keldysh Closed-Time-Path formalism, and compute the asymmetry evolution via the Kadanoff-Baym equation. Such minimal forbidden neutrinogenesis establishes a direct link between the baryon asymmetry and the CP-violating phase from neutrino mixing, making the scenario a compelling target in neutrino oscillation experiments. Complementary probes from cosmology, flavor physics and colliders are also briefly discussed., Comment: 38 pages, 9 figures

The use of language models (LMs) has increased considerably in recent years, and the biases and stereotypes in training data that are reflected in the LM outputs are causing social problems. In this paper, inspired by the task arithmetic, we propose the ``Bias Vector'' method for the mitigation of these LM biases. The Bias Vector method does not require manually created debiasing data. The three main steps of our approach involve: (1) continual training the pre-trained LMs on biased data using masked language modeling; (2) constructing the Bias Vector as the difference between the weights of the biased LMs and those of pre-trained LMs; and (3) subtracting the Bias Vector from the weights of the pre-trained LMs for debiasing. We evaluated the Bias Vector method on the SEAT across three LMs and confirmed an average improvement of 0.177 points. We demonstrated that the Bias Vector method does not degrade the LM performance on downstream tasks in the GLUE benchmark. In addition, we examined the impact of scaling factors, which control the magnitudes of Bias Vectors, with effect sizes on the SEAT and conducted a comprehensive evaluation of our debiased LMs across both the SEAT and GLUE benchmarks., Comment: Accepted to COLING2025

A magneto-optical trap of cesium atoms was generated by applying a circularly polarized cooling laser beam onto a reflective two-dimensional diffraction grating with an aperture and by retroreflecting the incident beam passing through the aperture while reversing the circular polarization. The cooling laser beams comprised the incident, retroreflected, and four diagonally diffracted beams at an angle of 50{\deg}. The intensity of the retroreflected beam was carefully adjusted to balance the radiation forces acting on the atoms. Despite the challenges posed by cesium atoms with high nuclear spin, a significant number of cold atoms ($7.0 {\times} 10^6$) were captured when the detuning and power of the incident beam were -10 MHz and 131 mW, respectively, with the intensity of the retroreflected beam set to 69 % of that of the incident beam. The importance of the retroreflected beam in the trapping process was highlighted when the intensity ratio was reduced to 24 %, resulting in the absence of trapped atoms. This underscores the significance of the retroreflected beam in the trapping process. Notably, the distribution of the cold atom cloud differed from other magneto-optical traps, as it was not centered in the region where the cooling beams overlapped. Instead, numerous cold atoms were observed when the cloud was positioned near the apex closer to the grating side and an edge line of the overlapping region. Therefore, trapping can be achieved with the assistance of attractive dipole forces exerted by the diffracted beams, which exhibits high intensities at these positions., Comment: 13 pages, 3 figures

Let $q$ be a Pisot or Salem number. Let $f_j(x)$ $(j=1,2,\dots)$ be integer-valued polynomials of degree $\ge2$ with positive leading coefficients, and let $\{a_j (n)\}_{n\ge1}$ $(j=1,2,\dots)$ be sequences of algebraic integers in the field $\mathbb{Q}(q)$ with suitable growth conditions. In this paper, we investigate linear independence over $\mathbb{Q}(q)$ of the numbers \begin{equation*} 1,\qquad \sum_{n=1}^{\infty} \frac{a_j (n)}{q^{f_j (n)}} \quad (j=1,2,\dots). \end{equation*} In particular, when $a_j(n)$ $(j=1,2,\dots)$ are polynomials of $n$, we give a linear independence criterion for the above numbers., Comment: 20 pages

We present a new viable benchmark scenario under the current experimental data for the model which can explain tiny mass of active neutrinos and dark matter, as a summary of our results. Majorana masses of right-handed neutrinos are given by the spontaneous breaking of the $\mathrm{U(1)}_{B-L}$ gauge symmetry above the electroweak scale, and tiny neutrino masses are radiatively induced by quantum effects of particles of the dark sector including dark matter candidates. We first show benchmark points which satisfy current experimental data, and then give comments on how this model can be tested at collider experiments., Comment: 5 pages, 2 figures, Presented in LCWS2024 and submitted in conference proceedings

We present a new non-BPS solution describing an asymptotically flat, stationary, bi-axisymmetric capped black hole in the bosonic sector of five-dimensional minimal supergravity. This solution describes a spherical black hole, while the exterior region of the horizon exhibits a non-trivial topology of $[{\mathbb R}^4 \# {\mathbb C}{\mathbb P}^2] \setminus {\mathbb B}^4$ on a timeslice. This solution extends our previously constructed three-parameter solution to a more general four-parameter solution. To derive this solution, we utilize a combination of the Ehlers and Harrison transformations and then impose appropriate boundary conditions on the solution's parameters. It can be shown that the resultant solution is free from curvature, conical, Dirac-Misner string and orbifold singularities, as well as closed timelike curves on and outside the horizon. Characterized by four independent conserved charges -- mass, two angular momenta, and electric charge -- this solution reveals two distinct branches: a small bubble branch and a large bubble branch, distinguished by non-conserved local quantities such as magnetic flux or magnetic potential. This shows the non-uniqueness for spherical black holes, even among capped black holes. For equivalent sets of conserved charges, we find that the large/small bubble branch can have larger/smaller entropy than the Cveti\v{c}-Youm black hole., Comment: 26 pages, 8 figures. arXiv admin note: text overlap with arXiv:2407.18142; v2: added the missing part of the phase diagram, 28 pages, 9 figures

We discuss a new renormalization scheme for mixing angles in extended Higgs sectors for the coming era of the Higgs precise measurements at future lepton colliders. We focus on the two Higgs doublet models (2HDMs) with a softly-broken $Z_2$ symmetry as a simple and important example, in which two mixing angles $\alpha$ and $\beta$ appear in the Higgs sector. In this new scheme, the counterterms for two mixing angles $\delta\alpha$ and $\delta\beta$ are determined by requiring that deviations in the decay rates of $h\to ZZ^* \to Z\ell^+\ell^-$ and $h \to \tau\tau$ from the corresponding predictions in the standard model at NLO are given by the square of the scaling factor at tree level. We show how this scheme works in the 2HDMs, and demonstrate how the other decay rates (e.g., $h \to WW^*$, $h \to b\bar{b}$, etc.) are predicted at NLO., Comment: 8 pages, 2 figures, Presented in LCWS2024 and submitted in conference proceedings

We investigate a gravitational model based on local Lorentz invariance and general coordinate invariance. The model incorporates classical scale invariance, which forbids dimensionful parameters, and the irreversible vierbein postulate, which enables continuous degenerate limits of the vierbein, both at a specific scale. Through the dynamics of the system, we demonstrate the simultaneous emergence of the Planck mass and a curved spacetime background., Comment: 18 pages, 2 figures, version published in Phys. Rev. D

Optical neural network (ONN) has been attracting intense attention owing to their low latency and low-power consumption. Among the ONNs, optical recurrent neural network (RNN) enables low-power and high-speed time-series data processing using a compact loop structure. The loop losses need to be efficiently compensated so that the time-series information is maintained in the RNN operation. For this purpose, we focus on the optoelectronic RNN (OE-RNN) with optical-electrical-optical (OEO) converters to compensate for the loop losses. However, the effect of resistive-capacitive (RC) delay of OEO converters on the RNN performance is unclear. Here, we study in simulation an OE-RNN equipped with OEO converters with RC delay. We confirm that our modeled OE-RNN achieves the high training accuracy of time-series data classification even when RC delay is comparably large to the time interval of time-series data. Our analyses reveal that the accumulation of time-series data by RC delay does not degrade the RNN performance but rather can compensate for the degraded RNN performance due to loop losses. From the theoretical analysis referring to the gradient explosion and vanishing problems, we find the region related to loss and RC delay where the high training accuracy can be achieved. In simulation, we confirm this compensation effect in the large OE-RNN circuit up to 32$\times$32 scale. Our proposed scheme opens a new way of time-series data processing by utilizing RC delay for the optical computing and optical communication.

Kilonova spectra provide us with the direct information of r-process nucleosynthesis in neutron star mergers. In this paper, we study the signatures of elements beyond the third r-process peak expected to be produced in neutron-rich ejecta in the photospheric spectra of kilonova. Ra II, Ac III, and Th III are our candidates because they have a small number of valence electrons and low-lying energy levels, which tend to result in strong absorption features. We systematically calculate the strength of bound-bound transitions of these candidates by constructing the line list based on the available atomic database. We find that Th III is the most promising species showing strong transitions at the NIR wavelengths. By performing radiative transfer simulations, we find that Th III produces broad absorption features at ~18000 A in the spectra when the mass ratio of actinides to lanthanides is larger than the solar r-process ratio and the mass fraction of lanthanides is $\lesssim 6\times10^{-4}$. Our models demonstrate that the Th feature may be detectable if the bulk of the ejecta in the line-forming region is dominated by relatively light r-process elements with the mixture of a small fraction of very neutron-rich material. Such conditions may be realized in the mergers of unequal-mass neutron stars or black hole-neutron star binaries. To detect the Th absorption features, the observations from the space (such as JWST) or high-altitude sites are important as the wavelength region of the Th features is overlapped with that affected by the strong telluric absorption., Comment: 18 pages, 12 figures, 2 tables, accepted for publication in ApJ (submission date: Aug 6, 2024)

We work on the functional renormalization group analysis on a four-fermion model with the CP and P violation in light of nonperturbative exploration of the infrared dynamics of quantum chromodynamics (QCD) arising from the spontaneous CP violation models in a view of the Wilsonian renormalization group. The fixed point structure reveals that in the large-$N_c$ limit, the CP $\bar{\theta}$ parameter is induced and approaches $\pi \cdot (N_f/2)$ (with the number of flavors $N_f$) toward the chiral broken phase due to the criticality and the large anomalous dimensions of the $U(1)$ axial violating four-fermion couplings. This trend seems to be intact even going beyond the large-$N_c$ leading, as long as the infrared dynamics of QCD is governed by the scalar condensate of the quark bilinear as desired. This gives an impact on modeling of the spontaneous CP violation scenarios: the perturbatively irrelevant four-fermion interactions nonperturbatively get relevant in the chiral broken phase, implying that the neutron electric dipole moment becomes too big, unless cancellations due to extra CP and P violating contributions outside of QCD are present at a certain intermediate infrared scale., Comment: 18 pages, 3 figures

Memristors, which are characterized by their unique input-voltage-history-dependent resistance, have garnered significant attention for the exploration of next-generation in-memory computing, reconfigurable logic circuits, and neural networks. Memristors are controlled by the applied input voltage; however, the latent potential of their magnetic field sensitivity for spintronics applications has rarely been explored. In particular, valuable functionalities are expected to be yielded by combining their history dependence and magnetic field response. Here, for the first time, we reveal a giant memory function based on the magnetic field history of memristive switching, with an extremely large magnetoresistance ratio of up to 32,900% under a constant bias voltage, using a two-terminal Ge-channel device with Fe/MgO electrodes. We attribute this behavior to colossal magnetoresistive switching induced by the d0 ferromagnetism of Mg vacancies in the MgO layers and impact ionization breakdown in the Ge substrate. Our findings may lead to the development of highly sensitive multi-field sensors, high-performance magnetic memory, and advanced neuromorphic devices., Comment: 30 pages, 5 figures in the main text, 8 figures in Supporting Information

We performed shot analyses of X-ray and optical sub-second flares observed during the low/hard state of the 2018 outburst in MAXI J1820$+$070. Optical shots were less spread than X-ray shots. The amplitude of X-ray shots was the highest at the onset of the outburst, and they faded at the transition to the intermediate state. The timescale of shots was $\sim$0.2 s, and we detected the abrupt spectral hardening synchronized with this steep flaring event. The time evolution of optical shots was not similar to that of X-ray shots. These results suggest that accreting gas blobs triggered a series of magnetic reconnections at the hot inner accretion flow in the vicinity of the black hole, which enhanced X-ray emission and generated flaring events. The rapid X-ray spectral hardening would be caused by this kind of magnetic activity. Also, the synchrotron emission not only at the hot flow but also at the jet plasma would contribute to the optical rapid variability. We also found that the low/hard state exhibited six different phases in the hardness-intensity diagram and the correlation plot between the optical flux and the X-ray hardness. The amplitude and duration of X-ray shots varied in synchrony with these phases. This time variation may provide key information about the evolution of the hot flow, the low-temperature outer disk, and the jet-emitting plasma., Comment: 16 pages, 7 figures, accepted for publication in PASJ

A precoded orthogonal time frequency space (OTFS) modulation scheme relying on faster-than-Nyquist (FTN) transmission over doubly selective fading channels is {proposed}, which enhances the spectral efficiency and improves the Doppler resilience. We derive the input-output relationship of the FTN signaling in the delay-Doppler domain. Eigenvalue decomposition (EVD) is used for eliminating both the effects of inter-symbol interference and correlated additive noise encountered in the delay-Doppler domain to enable efficient symbol-by-symbol demodulation. Furthermore, the power allocation coefficients of individual frames are optimized for maximizing the mutual information under the constraint of the derived total transmit power. Our performance results demonstrate that the proposed FTN-based OTFS scheme can enhance the information rate while achieving a comparable BER performance to that of its conventional Nyquist-based OTFS counterpart that employs the same root-raised-cosine shaping filter., Comment: 5 pages, 3 figures

This paper proposes a federated learning framework designed to achieve \textit{relative fairness} for clients. Traditional federated learning frameworks typically ensure absolute fairness by guaranteeing minimum performance across all client subgroups. However, this approach overlooks disparities in model performance between subgroups. The proposed framework uses a minimax problem approach to minimize relative unfairness, extending previous methods in distributionally robust optimization (DRO). A novel fairness index, based on the ratio between large and small losses among clients, is introduced, allowing the framework to assess and improve the relative fairness of trained models. Theoretical guarantees demonstrate that the framework consistently reduces unfairness. We also develop an algorithm, named \textsc{Scaff-PD-IA}, which balances communication and computational efficiency while maintaining minimax-optimal convergence rates. Empirical evaluations on real-world datasets confirm its effectiveness in maintaining model performance while reducing disparity., Comment: 43 pages

New sources of CP violation are necessary to solve the problem of the baryon asymmetry of the Universe. Extending Higgs sector is one way to introduce such new CP violating phases, and studying observables resulting from the CP violation is important to test the model in future experiments. In these proceedings, we discuss the loop induced $ H^\pm W^\mp Z$ vertices in the CP violating general two Higgs doublet model, summarizing our results. We evaluate impacts of the CP violation on the decays $H^\pm \to W^\pm Z$ through these vertices, and find that the difference between the decays $H^+ \to W^+ Z$ and $H^- \to W^- Z$ is sensitive to the CP violating phases in the model., Comment: 9 pages, 2 figures, Presented in LCWS2024 and submitted in conference proceedings

The radiative seesaw model with gauged $\mathrm{U(1)}_{B-L}\times\mathbb{Z}_2$ extension is a well-motivated scenario which gives consistent predictions of active neutrino masses and the abundance of dark matter. Majorana masses of right-handed neutrinos, the lightest of which can be identified as dark matter, are given by the spontaneous breaking of the $\mathrm{U(1)}_{B-L}$ gauge symmetry. We revisit this model with the latest constraints from dark matter searches, neutrino oscillations, flavor experiments and collider experiments. We explore the feasible parameter space of this model, and find that there are still allowed regions under the latest experimental constraints. We present new viable benchmark scenarios for this model, i.e., the right-handed neutrino dark matter scenario and the scalar dark matter scenario. We also mention the testability of these benchmark scenarios at future experiments., Comment: 21 pages, 6 figures, 2 tables

Decadal changes in a nearby supernova remnant (SNR) were analyzed using a multiepoch maximum likelihood estimation (MLE) approach. To achieve greater accuracy in capturing the dynamics of SNRs, kinematic features and point-spread function effects were integrated into the MLE framework. Using Cassiopeia A as a representative example, data obtained by the Chandra X-ray Observatory in 2000, 2009, and 2019 were utilized. The proposed multiepoch MLE was qualitatively and quantitatively demonstrated to provide accurate estimates of various motions, including shock waves and faint features, across all regions. To investigate asymmetric structures, such as singular components that deviate from the direction of expansion, the MLE method was extended to combine multiple computational domains and classify kinematic properties using the $k$-means algorithm. This approach allowed for the mapping of different physical states onto the image, and one classified component was suggested to interact with circumstellar material by comparison with infrared observations from the James Webb Space Telescope. Thus, this technique will help quantify the dynamics of SNRs and discover their unique evolution., Comment: Accepted for publication in ApJ. The paper is 20 pages long with 13 figures. Animations for Fig. 8 and Fig. 9, which provide a visual illustration of the results, are available in ApJ

The decrease of the chiral pseudocritical temperature $T_{\mathrm{pc}}$ with an applied strong magnetic field has been extensively investigated by various QCD low-energy effective models and lattice QCD at physical point. We find that this decreasing feature may not hold in the case with a weak magnetic field and still depends on quark masses: when the quark masses get smaller, $T_{\mathrm{pc}}$ turns to increase with the weak magnetic field. This happens due to the significant electromagnetic-scale anomaly contribution in the thermomagnetic medium. We demonstrate this salient feature by employing the Polyakov Nambu-Jona-Lasinio model with 2 + 1 quark flavors including the electromagnetic-scale anomaly contribution. We observe a critical point in a sort of the Columbia plot, $(m_{0c}, m_{sc}) \simeq (3, 30) \mathrm{MeV}$ for the isospin symmetric mass for up and down quarks, $m_0$, and the strange quark mass, $m_s$, where $T_{\mathrm{pc}}$ decreases with the magnetic field if the quark masses exceed the critical values, and increases as the quark masses become smaller. Related cosmological implications, arising when the supercooled electroweak phase transition or dark QCD cosmological phase transition is considered along with a primordial magnetic field, are also briefly addressed., Comment: 10 pages, 3 figures; references and some discussions added

We study the formation of stars with varying amounts of heavy elements synthesized by the rapid neutron-capture process ($r$-process) based on our detailed cosmological zoom-in simulation of a Milky Way-like galaxy with an $N$-body/smoothed particle hydrodynamics code, ASURA. Most stars with no overabundance in $r$-process elements, as well as the strongly $r$-process enhanced $r$-II stars ([Eu/Fe] $>+0.7$), are formed in dwarf galaxies accreted by the Milky Way within the 6 Gyr after the Big Bang. In contrast, over half of the moderately enhanced $r$-I stars ($+0.3 <$ [Eu/Fe] $\leq +0.7$) are formed in the main in-situ disk after 6 Gyr. Our results suggest that the fraction of $r$-I and $r$-II stars formed in disrupted dwarf galaxies is larger the higher their [Eu/Fe] is. Accordingly, the most strongly enhanced $r$-III stars ([Eu/Fe] $> +2.0$) are formed in accreted components. These results suggest that non-$r$-process-enhanced stars and $r$-II stars are mainly formed in low-mass dwarf galaxies that hosted either none or a single neutron star merger, while the $r$-I stars tend to form in the well-mixed in-situ disk. We compare our findings with high-resolution spectroscopic observations of $r$-process-enhanced metal-poor stars in the halo and dwarf galaxies, including those collected by the R-Process Alliance. We conclude that observed [Eu/Fe] and [Eu/Mg] ratios can be employed in chemical tagging of the Milky Way's accretion history., Comment: 16 pages, 11 figures, submitted to ApJ

In order to understand the early history of the universe, and to test baryogenesis models, determining the nature of the electroweak phase transition is imperative. The order and strength of this transition is strongly correlated to relatively large deviations in the $hhh$ coupling. In models where a considerable part of the $hhh$ coupling deviation is caused by charged particle loops, the $h\gamma\gamma$ coupling is also expected to deviate considerably. In this talk, by using a model-independent approach, I explain how to obtain conditions that are sufficient for a strongly first order phase transition. After the $h\gamma\gamma$ coupling is determined with precision at the HL-LHC, these conditions can be tested at Future Linear Colliders by measurements of the $hhh$ coupling, to conclusively determine the nature of the electroweak phase transition and the viability of electroweak baryogenesis on models with new charged scalars., Comment: 12 pages, 4 figures, Presented in LCWS2024 and submitted in conference proceedings

Interaction nets are a form of restricted graph rewrite system that can serve as a graphical or textual programming language. As such, benefits include one-step confluence, ease of parallelism and explicit garbage collection. However, some of these restrictions burden the programmer, so they have been extended in several ways, notably to include data types and conditional rules. This paper introduces a further extension to allow nested pattern matching and to do so in a way that preserves these benefits and fundamental properties of interaction nets. We also show that by introducing a translation to non-nested matching, this extension is conservative in rewriting. In addition, we propose a new notation to express this pattern matching., Comment: In Proceedings DCM 2023, arXiv:2409.19298

We discuss the production and the decay of top quark through flavor-changing neutral current (FCNC) interaction at future linear colliders. We first discuss the theoretical predictions of top quark FCNC decays into $qH$ and $qZ$ within a class of $t$-channel simplified dark matter models. For the existing bounds on the top quark FCNC interactions at the Large Hadron Collider, we estimate the production rates of top quark through FCNC interactions at future linear colliders for energies from $250$ GeV to $3$ TeV., Comment: 10 pages, 5 figures. Contribution to the International Workshop on Future Linear Colliders (LCWS2024)

Interconversion between charge and spin currents is a key phenomenon in realizing next-generation spintronic devices. Highly efficient spin-charge interconversion is expected to occur at band crossing points in materials with large spin-orbit interactions due to enhanced spin Berry curvature. On the other hand, if defects and/or impurities are present, they affect the electronic band structure, which in turn reduces the spin Berry curvature. Although defects and impurities are generally numerous in materials, their influence on the spin Berry curvature and, consequently, spin-charge interconversion has often been overlooked. In this paper, we perform spin-pumping experiments for stoichiometric SrRuO3 and non-stoichiometric SrRu0.7O3 films at 300 K, where the films are in paramagnetic states, to examine how Ru composition deviation from the stoichiometric condition influences the spin-to-charge conversion, showing that SrRuO3 has a larger spin Hall angle than SrRu0.7O3. We derive the band structures of paramagnetic SrRuO3 and SrRu0.75O3 using first-principles calculations, indicating that the spin Hall conductivity originating from the spin Berry curvature decreases when the Ru deficiency is incorporated, which agrees with the experimental results. Our results suggest that point-defect- and impurity control is essential to fully exploit the intrinsic spin Berry curvature and large spin-charge interconversion function of materials. These insights help us with material designs for efficient spin-charge interconversions.

We study an outflow problem for the $3$-dimensional isentropic compressible Navier-Stokes equations. The fluid under consideration occupies the exterior domain of unit ball, $\Omega=\{x\in\mathbb{R}^3\,\vert\, |x|\ge 1\}$, and it is flowing out from $\Omega$ at a constant speed $|u_b|$, in the normal direction to the boundary surface $\partial\Omega$. It is shown in Hashimoto-Matsumura(2021) that if the fluid velocity at the far-field is assumed to be zero, and $|u_b|$ is sufficiently small, then there exists a unique spherically symmetric stationary solution $(\tilde{\rho},\tilde{u})(x)$. In this paper, we prove that $(\tilde{\rho},\tilde{u})(x)$ is asymptotically stable in time, under small, possibly non-spherically symmetric initial perturbations., Comment: 26 pages. arXiv admin note: text overlap with arXiv:2404.07469

We discuss a QCD-scale composite axion model arising from dark QCD coupled to QCD. The presently proposed scenario not only solves the strong CP problem, but also is compatible with the preheating setup for the QCD baryogenesis. The composite axion is phenomenologically required to mimic the QCD pion, but can generically be flavorful, which could be testable via the induced flavor changing processes at experiments. Another axionlike particle (ALP) is predicted to achieve the axion relaxation mechanism, which can phenomenologically act as the conventional QCD axion. This ALP can be ultralight, having the mass less than 1 eV, to be a dark matter candidate. The QCD $\times$ dark QCD symmetry structure constrains dark QCD meson spectra, so that the dark $\eta'$-like meson would only be accessible at the collider experiments. Still, the Belle II and Electron ion collider experiments can have a high enough sensitivity to probe the dark $\eta'$-like meson in the diphoton channel, which dominantly arises from the mixing with the QCD $\eta'$ and the pionic composite axion. We also briefly address nontrivial cosmological aspects, such as those related to the dark-chiral phase transition, the dark matter production, and an ultraviolet completion related to the ultralight ALP., Comment: 15 pages, 1 figure; discussions on experimental and astrophysical limits revised"

We show new well-posedness results in anisotropic Sobolev spaces for dispersion-generalized KP-I equations with increased dispersion compared to the KP-I equation. We obtain the sharp dispersion rate, below which generalized KP-I equations on $\mathbb{R}^2$ and on $\mathbb{R} \times \mathbb{T}$ exhibit quasilinear behavior. In the quasilinear regime, we show improved well-posedness results relying on short-time Fourier restriction. In the semilinear regime, we show sharp well-posedness with analytic data-to-solution mapping. On $\mathbb{R}^2$ we cover the full subcritical range, whereas on $\mathbb{R} \times \mathbb{T}$ the sharp well-posedness is strictly subcritical. Nonlinear Loomis-Whitney inequalities are one ingredient. These are presently proved for Borel measures with growth condition reflecting the different geometries of the plane $\mathbb{R}^2$, the cylinder $\mathbb{R} \times \mathbb{T}$, and the torus $\mathbb{T}^2$. Finally, we point out that on tori $\mathbb{T}^2_\gamma$, KP-I equations are never semilinear., Comment: 72 pages

Approximate computing emerges as a promising approach to enhance the efficiency of compute-in-memory (CiM) systems in deep neural network processing. However, traditional approximate techniques often significantly trade off accuracy for power efficiency, and fail to reduce data transfer between main memory and CiM banks, which dominates power consumption. This paper introduces a novel probabilistic approximate computation (PAC) method that leverages statistical techniques to approximate multiply-and-accumulation (MAC) operations, reducing approximation error by 4X compared to existing approaches. PAC enables efficient sparsity-based computation in CiM systems by simplifying complex MAC vector computations into scalar calculations. Moreover, PAC enables sparsity encoding and eliminates the LSB activations transmission, significantly reducing data reads and writes. This sets PAC apart from traditional approximate computing techniques, minimizing not only computation power but also memory accesses by 50%, thereby boosting system-level efficiency. We developed PACiM, a sparsity-centric architecture that fully exploits sparsity to reduce bit-serial cycles by 81% and achieves a peak 8b/8b efficiency of 14.63 TOPS/W in 65 nm CMOS while maintaining high accuracy of 93.85/72.36/66.02% on CIFAR-10/CIFAR-100/ImageNet benchmarks using a ResNet-18 model, demonstrating the effectiveness of our PAC methodology.

A compact energy-recovery linac (cERL) has been un-der construction at KEK since 2009 to develop key technologies for the energy-recovery linac. The cERL began operating in 2013 to create a high-current beam with a low-emittance beam with stable continuous wave (CW) superconducting cavities. Owing to the development of critical components, such as the DC gun, superconducting cavities, and the design of ideal beam transport optics, we have successfully established approximately 1 mA stable CW operation with a small beam emittance and extremely small beam loss. This study presents the details of our key technologies and experimental results for achieving 100% energy recovery operation with extremely small beam loss during a stable, approximately 1 mA CW beam operation., Comment: 11 pages, 16 figures

A neurochip is a device that reproduces the signal processing mechanisms of brain neurons and calculates Spiking Neural Networks (SNNs) with low power consumption and at high speed. Thus, neurochips are attracting attention from edge robot applications, which suffer from limited battery capacity. This paper aims to achieve deep reinforcement learning (DRL) that acquires SNN policies suitable for neurochip implementation. Since DRL requires a complex function approximation, we focus on conversion techniques from Floating Point NN (FPNN) because it is one of the most feasible SNN techniques. However, DRL requires conversions to SNNs for every policy update to collect the learning samples for a DRL-learning cycle, which updates the FPNN policy and collects the SNN policy samples. Accumulative conversion errors can significantly degrade the performance of the SNN policies. We propose Robust Iterative Value Conversion (RIVC) as a DRL that incorporates conversion error reduction and robustness to conversion errors. To reduce them, FPNN is optimized with the same number of quantization bits as an SNN. The FPNN output is not significantly changed by quantization. To robustify the conversion error, an FPNN policy that is applied with quantization is updated to increase the gap between the probability of selecting the optimal action and other actions. This step prevents unexpected replacements of the policy's optimal actions. We verified RIVC's effectiveness on a neurochip-driven robot. The results showed that RIVC consumed 1/15 times less power and increased the calculation speed by five times more than an edge CPU (quad-core ARM Cortex-A72). The previous framework with no countermeasures against conversion errors failed to train the policies. Videos from our experiments are available: https://youtu.be/Q5Z0-BvK1Tc., Comment: Accepted by Robotics and Autonomous Systems

We propose a new renormalization scheme in the two Higgs doublet models with a softly-broken $Z_2$ symmetry and CP-conservation in the Higgs sector. In this scheme, counterterms for mixing angles of the Higgs bosons are determined by using the decay rates of the discovered Higgs boson $h$, $i.e.$, $h \to \tau^+\tau^-$ and $h \to ZZ^* \to Z\ell^+\ell^-$ at next leading order (NLO) instead of using the renormalized two-point functions which are adopted in the previous scheme. We require that the decay rates at NLO are determined to be the corresponding predictions at NLO in the Standard Model (SM) times square of the scaling factor which describes the deviation of $h$ couplings at tree level from the SM value. The mixing angles then maintain the meaning of the ``alignmentness", $i.e.$, how the properties of $h$ are close to the SM predictions, while they lose such meaning in the previous scheme. We compare the predictions of the decay rates at NLO given in the new scheme and those in the previous scheme., Comment: 22 pages, 4 figures

Understanding symmetry of extended Higgs models helps to construct the theory beyond the standard model and gives important insights for testing these models by experiments. The custodial symmetry plays an important role as a leading principle to construct non-minimal Higgs sectors. On the other hand, new sources of CP violation in the Higgs sector are essentially important to explain the baryon asymmetry of the Universe. In the two Higgs doublet model, it has been known that the CP violation and the custodial symmetry are not compatible, and thus the CP violating Higgs potential in general violates the custodial symmetry in the Higgs sector. In this paper, we discuss the loop-induced $H^\pm W^\mp Z$ vertices in the two Higgs doublet model, which are induced due to the custodial symmetry violation of the sector of the particles in the loop, and study how the vertices are affected by the CP violation. We calculate the $H^\pm W^\mp Z$ vertices in the most general two Higgs doublet model with the CP violation at the one-loop level and evaluate the decay modes $H^\pm \to W^\pm Z$ caused by these vertices. We obtain new contributions to the $H^\pm W^\mp Z$ vertices from the CP violating part of the model, in addition to the known contributions from the CP conserving part. Moreover, we find that an asymmetry between the decays $H^+ \to W^+ Z$ and $H^- \to W^- Z$ is caused by the CP violating phases in the model, some of which are important for the electroweak baryogenesis. We also briefly mention testability of these vertices at future collider experiments., Comment: 40 pages, 12 figures