arXiv subjects

Yoshiyuki Yajima

Publications and source records attributed to Yoshiyuki Yajima.

17 recordsLinked to original sources

arXiv2026

Optimal-Control Suggestion for Congestion on Freeways using Data Assimilation of Distributed Fiber-Optic Sensing

This paper presents the optimal-control suggestion for congestion on freeways using data assimilation (DA) of distributed fiber-optic sensing (DFOS). To simultaneously maximize throughput and avoid/mitigate congestion, it is necessary to execute optimal control for the current traffic state as active transportation and demand management (ATDM) according to multi-objective optimization with real-time monitoring data. However, optimal control cannot be estimated due to intermittent observed data obtained from conventional sensors. To solve the issue, this paper proposes the ATDM optimal control estimation with DA of DFOS, which can monitor traffic flow in real time without dead zones. Our real-time DA method enables us to estimate the effectiveness of control scenarios by simulation. This paper also provides a method to uniquely determine the optimal-control solution among the Pareto solutions for multi-objective optimization. Throughput and mean speed across the entire road are considered as the objective functions. Variable speed limit (VSL) and inflow control are taken as ATDM examples. Validation results on a Japanese freeway show that (i) the optimal control scenario varies depending on the traffic state, especially congestion level; (ii) optimal control considering VSL alone improves throughput by 5-14% while the improvement rate for mean speed is 0-8%; (iii) throughput and mean speed are improved by 10-15% and 20-30%, respectively when VSL and inflow control are considered. This paper also implies the importance of balance management for the lane occupancy and proactive optimal control before congestion occurs.

eess.SY↗

arXiv2026

Monitoring exposure-length variations in submarine power cables using distributed fiber-optic sensing

This study proposes an anomaly-detection framework for monitoring exposure-length variations in submarine free-span cables using Distributed Acoustic Sensing (DAS), which is one of the distributed fiber-optic sensing technologies. To address environmental variability and limited training data in offshore environments, a regression-based feature extraction method was introduced to derive low-dimensional latent representations that retain exposure length-dependent vibration characteristics while suppressing environmental influences. The extracted features were used for one-class Support Vector Machine (SVM)-based anomaly detection. The proposed framework was evaluated through wave-tank experiments with exposure lengths ranging from 2 to 10 m. Experimental results showed that anomaly scores decreased approximately monotonically with increasing exposure-length change, exhibiting a strong correlation ($r = -0.83$). The binary classification achieved an F1 score of 0.82 despite training with only small-sample datasets. These findings demonstrate that exposure-length variations can be reliably detected under severe data limitations, supporting the potential of DAS-based cable condition monitoring.

eess.SP↗

arXiv2026

Wave Tank Experiment for Sea State Monitoring with Distributed Acoustic Sensing

Monitoring sea states across the offshore wind farm areas is essential to keep their structures safe, efficiently operate the systems, and assess the environmental effects of wind turbines. Conventional sea state sensors like buoys limit their observable coverage; therefore, installing many sensors across the wide area is necessary to obtain sufficient sea state information. However, such a situation is not practical in terms of cost. Instead, the study proposes utilising optical fibres, which is embedded in existing power cables for telecommunications on the seabed, as sea state monitoring sensors with distributed acoustic sensing (DAS). DAS is a vibration-sensing technology along optical fibres based on the Rayleigh backscattering of the injected laser. It measures the dynamic strain of the optical fibre in real time at each spatial bin, which is called a "channel" along the fibre. In power cables on the seabed, time-varying water pressure due to waves is expected to exert dynamic strain. This hypothesis motivates us to validate whether the application of DAS for power cables can estimate sea state, such as wave period, height, and the direction of arrival. Hence, the authors carried out a wave tank experiment with a programmable wave generator. An actual power cable is installed under the same condition as the bottom-mounted offshore wind turbines. The experimental results show that (i) the wave period can be accurately estimated from the frequency-domain analysis. (ii) The strong linearity between DAS vibration power and the wave height is found. (iii) The direction of arrival of waves can be estimated with the error of 1.5$^\circ$ when there are at least two laying angles of the cable in parallel with the estimation of wavelength. These outcomes promote the feasibility of utilising the existing power cables across offshore wind farms as sea state monitoring sensors.

eess.SP↗

arXiv2026

Event Classification by Physics-informed Inpainting for Distributed Multichannel Acoustic Sensor with Partially Degraded Channels

Distributed multichannel acoustic sensing (DMAS) enables large-scale sound event classification (SEC), but performance drops when many channels are degraded and when sensor layouts at test time differ from training layouts. We propose a learning-free, physics-informed inpainting frontend based on reverse time migration (RTM). In this approach, observed multichannel spectrograms are first back-propagated on a 3D grid using an analytic Green's function to form a scene-consistent image, and then forward-projected to reconstruct inpainted signals before log-mel feature extraction and Transformer-based classification. We evaluate the method on ESC-50 with 50 sensors and three layouts (circular, linear, right-angle), where per-channel SNRs are sampled from -30 to 0 dB. Compared with an AST baseline, scaling-sparsemax channel selection, and channel-swap augmentation, the proposed RTM frontend achieves the best or competitive accuracy across all layouts, improving accuracy by 13.1 points on the right-angle layout (from 9.7% to 22.8%). Correlation analyses show that spatial weights align more strongly with SNR than with channel--source distance, and that higher SNR--weight correlation corresponds to higher SEC accuracy. These results demonstrate that a reconstruct-then-project, physics-based preprocessing effectively complements learning-only methods for DMAS under layout-open configurations and severe channel degradation.

cs.SD↗

arXiv2025

CO Multi-line Imaging of Nearby Galaxies (COMING). XI. Azimuthally averaged star formation rate and stellar mass relation with molecular gas amount

This study investigated the relation between the surface density of star formation rate (SFR) ($Σ_{\mathrm{SFR}}$), stellar mass ($Σ_{M_{\ast}}$), and molecular gas mass ($Σ_{M_\mathrm{mol}}$) on nearly 1 kpc scales averaged over concentric tilted rings using the $^{12}$CO $J=1-0$ mapping data of 92 nearby galaxies obtained in the CO Multi-line Imaging of Nearby Galaxies (COMING) project. We categorized these galaxies into three groups based on the deviation of each global SFR from the star-forming main sequence (MS), $Δ$MS: upper MS (UMS), MS, and lower MS (LMS). UMS galaxies tend to be less massive or barred spiral galaxies, exhibiting molecular gas fraction ($f_{\mathrm{gas}}$) comparable to those of MS galaxies but higher star formation efficiency (SFE). In contrast, the LMS galaxies tend to be massive or active galaxies hosting an active galactic nucleus (AGN). Their $f_{\mathrm{gas}}$ values are lower than those of MS galaxies, and their SFEs are slightly lower or comparable to those of MS galaxies in the inner region. These trends indicate that enhanced SFE contributes to higher $Δ$MS values, whereas reduced $f_{\mathrm{gas}}$ results in lower $Δ$MS values. The less prominent bulge or the presence of a bar structure in UMS galaxies induces disk-wide star formation, consequently increasing the SFE. In LMS galaxies, the molecular gas is exhausted, and their star formation activity is low. Environmental effects, such as tidal gas stripping, may also reduce gas supply from the outer regions. Furthermore, our sample galaxies show that both the specific star formation rate (sSFR) and $f_{\mathrm{gas}}$ decrease in the central region in LMS galaxies but did not change in the same region in UMS galaxies. These results seem to support the inside-out quenching of star formation although the dominant cause of depletion remains uncertain.

astro-ph.GA↗

arXiv2025

Traffic State Estimation in Congestion to Extend Applicability of DFOS

This paper presents a traffic state estimation (TSE) method in congestion for distributed fiber-optic sensing (DFOS). DFOS detects vehicle driving vibrations along the optical fiber and obtains their trajectories in the spatiotemporal plane. From these trajectories, DFOS provides mean velocities for real-time spatially continuous traffic monitoring without dead zones. However, when vehicle vibration intensities are insufficiently low due to slow speed, trajectories cannot be obtained, leading to missing values in mean velocity data. It restricts DFOS applicability in severe congestion. Therefore, this paper proposes a missing value imputation method based on data assimilation. Our proposed method is validated on two expressways in Japan with the reference data. The results show that the mean absolute error (MAE) of the imputed mean velocities to the reference increases only by 1.5 km/h as compared with the MAE of non-missing values. This study enhances the wide-range applicability of DFOS in practical cases.

eess.SY↗

arXiv2025

Distributed Fiber-Optic Sensing based Single-Lane Abnormal Event Detection in Low-Density Traffic Flow

Distributed fiber-optic sensing (DFOS) based traffic flow monitoring systems are a cost-effective wide-area traffic monitoring solution that utilize existing fiber infrastructure along roads. These systems analyse vehicle vibrations and measure average traffic speeds to detect traffic events. However, these systems face difficulties in detecting early signs of non-recurring traffic congestions in low-density traffic flow caused by presence of single-lane abnormal events. This is because average traffic speeds do not decrease quickly in such events. During abnormal events, multiple vehicles perform spontaneous braking and abrupt lane-changes to avoid obstacles on travel lanes. These vehicle behaviours gradually lead to traffic congestion. Thus, frequent lane-change maneuver, performed by multiple vehicles at similar location, may suggest occurrence of congestion-inducing abnormal events. This paper discusses methods to identify and locate occurrence of these single-lane abnormal events by detecting frequent lane-change maneuver along road sections. We first propose a method to locate vehicle positions along a road section and estimate the vehicle path. We then propose a method to detect vehicle lane-change maneuver by monitoring variations in spectral centroid of vehicle vibrations. The evaluation of our proposed methods with real traffic data for two different expressways showed 81.5% accuracy for individual vehicle path tracking and 83.5% accuracy in lane-change event detection. These results suggest that the proposed method has potential for detecting occurrence of single-lane abnormal events in low-density traffic flow so that necessary mitigation measures can be initiated before onset of traffic congestions.

physics.optics↗

arXiv2025

A Novel Approach to Real-Time Short-Term Traffic Prediction based on Distributed Fiber-Optic Sensing and Data Assimilation with a Stochastic Cell-Automata Model

This paper demonstrates real-time short-term traffic flow prediction through distributed fiber-optic sensing (DFOS) and data assimilation with a stochastic cell-automata-based traffic model. Traffic congestion on expressways is a severe issue. To alleviate its negative impacts, it is necessary to optimize traffic flow prior to becoming serious congestion. For this purpose, real-time short-term traffic flow prediction is promising. However, conventional traffic monitoring apparatus used in prediction methods faces a technical issue due to the sparsity in traffic flow data. To overcome the issue for realizing real-time traffic prediction, this paper employs DFOS, which enables to obtain spatially continuous and real-time traffic flow data along the road without dead zones. Using mean velocities derived from DFOS data as a feature extraction, this paper proposes a real-time data assimilation method for the short-term prediction. As the theoretical model, the stochastic Nishinari-Fukui-Schadschneider model is adopted. Future traffic flow is simulated with the optimal values of model parameters estimated from observed mean velocities and the initial condition estimated as the latest microscopic traffic state. This concept is validated using two congestion scenarios obtained in Japanese expressways. The results show that the mean absolute error of the predicted mean velocities is 10-15 km/h in the prediction horizon of 30 minutes. Furthermore, the prediction error in congestion length and travel time decreases by 40-84% depending on congestion scenarios when compared with conventional methods with traffic counters. This paper concludes that real-time data assimilation using DFOS enables an accurate short-term traffic prediction.

cond-mat.stat-mech↗

arXiv2024

Trainingless Adaptation of Pretrained Models for Environmental Sound Classification

Deep neural network (DNN)-based models for environmental sound classification are not robust against a domain to which training data do not belong, that is, out-of-distribution or unseen data. To utilize pretrained models for the unseen domain, adaptation methods, such as finetuning and transfer learning, are used with rich computing resources, e.g., the graphical processing unit (GPU). However, it is becoming more difficult to keep up with research trends for those who have poor computing resources because state-of-the-art models are becoming computationally resource-intensive. In this paper, we propose a trainingless adaptation method for pretrained models for environmental sound classification. To introduce the trainingless adaptation method, we first propose an operation of recovering time--frequency-ish (TF-ish) structures in intermediate layers of DNN models. We then propose the trainingless frequency filtering method for domain adaptation, which is not a gradient-based optimization widely used. The experiments conducted using the ESC-50 dataset show that the proposed adaptation method improves the classification accuracy by 20.40 percentage points compared with the conventional method.

cs.SD↗

arXiv2024

Traffic Modeling and Forecast based on Stochastic Cell-Automata and Distributed Fiber-Optic Sensing -- A Numerical Experiment

This paper demonstrates accurate traffic modeling and forecast using stochastic cell-automata (CA) and distributed fiber-optic sensing (DFOS). Traffic congestion is a dominant issue in highways. To reduce congestion, real-time traffic control by short-term forecast is necessary. For achieving this, data assimilation using a stochastic CA model and DFOS is promising. Data assimilation with a CA enables us to model real-time traffic flow with simple processes even when rare or sudden events occur, which is challenging for usual machine learning-based methods. DFOS overcomes issues of conventional point sensors that have dead zones of observation. By estimating optimal model parameters that reproduce observed traffic flow in the simulation, future traffic flow is forecasted from the simulation. We propose an optimal model parameter estimation method using mean velocity as an extracted feature and the particle filter. In addition, an estimation methodology for the microscopic traffic situation is developed to set the initial condition of simulation for forecast in accordance with observation. The proposed methods are verified by simulation-based traffic flow. The simulation adopts the stochastic Nishinari-Fukui-Schadschneider model. The optimal model parameters are successfully derived from posterior probability distributions (PPDs) estimated from DFOS data. In contrast, those estimated from point sensors fail. The PPDs of model parameters also indicate that each parameter has different sensitivities to traffic flow. A traffic forecast up to 60 minutes later is carried out. Using optimal model parameters estimated from DFOS, the forecast error of mean velocity is approximately $\pm$10 km/h (percentage error is 18%). The error attains half of it when conventional point sensors are used. We conclude that DFOS is a powerful technique for traffic modeling and short-term forecast.

nlin.CG↗

arXiv2023

CO Multi-line Imaging of Nearby Galaxies (COMING). XII. CO-to-H$_{2}$ Conversion Factor and Dust-to-Gas Ratio

We simultaneously measured the spatially-resolved CO-to-H$_{2}$ conversion factor ($α_\mathrm{CO}$) and dust-to-gas ratio (DGR) in nearby galaxies on a kiloparsec scale. In this study, we used $^{12}$CO($J=1-0$) data obtained by the Nobeyama 45-m radio telescope with HI and dust mass surface densities. We obtained the values of global $α_\mathrm{CO}$ and DGR in 22 nearby spiral galaxies, with averages of $2.66 \pm 1.36\ M_\odot\ \mathrm{pc}^{-2}\ (\mathrm{K\ km\ s^{-1}})^{-1}$ and $0.0052 \pm 0.0026$, respectively. Furthermore, the radial variations of $α_\mathrm{CO}$ and DGR in four barred spiral galaxies (IC 342, NGC 3627, NGC 5236, and NGC 6946) were obtained by dividing them into the inner and outer regions with a boundary of $0.2R_{25}$, where $R_{25}$ is the isophotal radius at 25 mag arcsec$^{-2}$ in the $B$ band. The averages of $α_\mathrm{CO}$ and DGR in the inner region ($\leq 0.2R_{25}$) are $0.36 \pm 0.08\ M_\odot\ \mathrm{pc}^{-2}\ (\mathrm{K\ km\ s^{-1}})^{-1}$ and $0.0199 \pm 0.0058$, while those in the outer region ($> 0.2R_{25}$) are $1.49 \pm 0.76\ M_\odot\ \mathrm{pc}^{-2}\ (\mathrm{K\ km\ s^{-1}})^{-1}$ and $0.0084 \pm 0.0037$, respectively. The value of $α_\mathrm{CO}$ in the outer region is 2.3 to 5.3 times larger than that of the inner region. When separated into the inner and outer regions, we find that $α_\mathrm{CO}$ and DGR correlate with the metallicity and the star formation rate surface density. The value of $α_\mathrm{CO}$ derived in this study tends to be smaller than those obtained in previous studies for the Milky Way and nearby star-forming galaxies. This fact can be attributed to our measurements being biased toward the inner region; we measured $α_\mathrm{CO}$ at 0.85 and 0.76 times smaller in radius than the previous works for nearby star-forming galaxies and the Milky Way, respectively.

astro-ph.GA↗

arXiv2020

CO Multi-line Imaging of Nearby Galaxies (COMING). IX. $^{12}$CO($J$=2-1)/$^{12}$CO($J$=1-0) line ratio on kiloparsec scales

While molecular gas mass is usually derived from $^{12}$CO($J$=1-0) - the most fundamental line to explore molecular gas - it is often derived from $^{12}$CO($J$=2-1) assuming a constant $^{12}$CO($J$=2-1)/$^{12}$CO($J$=1-0) line ratio ($R_{2/1}$). We present variations of $R_{2/1}$ and effects of the assumption that $R_{2/1}$ is a constant in 24 nearby galaxies using $^{12}$CO data obtained with the Nobeyama 45-m radio telescope and IRAM 30-m telescope. The median of $R_{2/1}$ for all galaxies is 0.61, and the weighted mean of $R_{2/1}$ by $^{12}$CO($J$=1-0) integrated-intensity is 0.66 with a standard deviation of 0.19. The radial variation of $R_{2/1}$ shows that it is high (~0.8) in the inner ~1 kpc while its median in disks is nearly constant at 0.60 when all galaxies are compiled. In the case that the constant $R_{2/1}$ of 0.7 is adopted, we found that the total molecular gas mass derived from $^{12}$CO($J$=2-1) is underestimated/overestimated by ~20%, and at most by 35%. The scatter of a molecular gas surface density within each galaxy becomes larger by ~30%, and at most by 120%. Indices of the spatially resolved Kennicutt-Schmidt relation by $^{12}$CO($J$=2-1) are underestimated by 10-20%, at most 39% in 17 out of 24 galaxies. $R_{2/1}$ has good positive correlations with star-formation rate and infrared color, and a negative correlation with molecular gas depletion time. There is a clear tendency of increasing $R_{2/1}$ with increasing kinetic temperature ($T_{\rm kin}$). Further, we found that not only $T_{\rm kin}$ but also pressure of molecular gas is important to understand variations of $R_{2/1}$. Special considerations should be made when discussing molecular gas mass and molecular gas properties inferred from $^{12}$CO($J$=2-1) instead of $^{12}$CO($J$=1-0).

astro-ph.GA↗

arXiv2020

CO Multi-line Imaging of Nearby Galaxies (COMING). X. Physical conditions of molecular gas and the local SFR-Mass relation

We investigate the molecular gas properties of galaxies across the main sequence of star-forming (SF) galaxies in the local Universe using $^{12}$CO($J=1-0$) (hereafter $^{12}$CO) and $^{13}$CO($J=1-0$) ($^{13}$CO) mapping data of 147 nearby galaxies obtained in the COMING project, a legacy project of the Nobeyama Radio Observatory. In order to improve signal-to-noise ratios of both lines, we stack all the pixels where $^{12}$CO emission is detected after aligning the line center expected from the first-moment map of $^{12}$CO. As a result, $^{13}$CO emission is successfully detected in 80 galaxies with a signal-to-noise ratio larger than three. The error-weighted mean of integrated-intensity ratio of $^{12}$CO to $^{13}$CO lines ($R_{1213}$) of the 80 galaxies is $10.9$ with a standard deviation of $7.0$. We find that (1) $R_{1213}$ positively correlates to specific star-formation rate (sSFR) with a correlation coefficient of $0.46$, and (2) both flux ratio of IRAS 60~$μ$m to 100~$μ$m ($f_{60}/f_{100}$) and inclination-corrected linewidth of $^{12}$CO stacked spectra ($σ_{{\rm ^{12}CO},i}$) also correlate with sSFR for galaxies with the $R_{1213}$ measurement. Our results support the scenario where $R_{1213}$ variation is mainly caused by the changes in molecular-gas properties such as temperature and turbulence. The consequent variation of CO-to-H$_2$ conversion factor across the SF main sequence is not large enough to completely extinguish the known correlations between sSFR and $M_{\rm mol}/M_{\rm star}$ ($μ_{\rm mol}$) or star-formation efficiency (SFE) reported in previous studies, while this variation would strengthen (weaken) the sSFR-SFE (sSFR-$μ_{\rm mol}$) correlation.

astro-ph.GA↗

arXiv2019

CO Multi-line Imaging of Nearby Galaxies (COMING) IV. Overview of the Project

Observations of the molecular gas in galaxies are vital to understanding the evolution and star-forming histories of galaxies. However, galaxies with molecular gas maps of their whole discs having sufficient resolution to distinguish galactic structures are severely lacking. Millimeter wavelength studies at a high angular resolution across multiple lines and transitions are particularly needed, severely limiting our ability to infer the universal properties of molecular gas in galaxies. Hence, we conducted a legacy project with the 45 m telescope of the Nobeyama Radio Observatory, called the CO Multi-line Imaging of Nearby Galaxies (COMING), which simultaneously observed 147 galaxies with high far-infrared flux in $^{12}$CO, $^{13}$CO, and C$^{18}$O $J=1-0$ lines. The total molecular gas mass was derived using the standard CO-to-H$_2$ conversion factor and found to be positively correlated with the total stellar mass derived from the WISE $3.4 μ$m band data. The fraction of the total molecular gas mass to the total stellar mass in galaxies does not depend on their Hubble types nor the existence of a galactic bar, although when galaxies in individual morphological types are investigated separately, the fraction seems to decrease with the total stellar mass in early-type galaxies and vice versa in late-type galaxies. No differences in the distribution of the total molecular gas mass, stellar mass, and the total molecular gas to stellar mass ratio was observed between barred and non-barred galaxies, which is likely the result of our sample selection criteria, in that we prioritized observing FIR bright (and thus molecular gas-rich) galaxies.

astro-ph.GA↗

arXiv2019

CO Multi-line Imaging of Nearby Galaxies (COMING). III. Dynamical effect on molecular gas density and star formation in the barred spiral galaxy NGC 4303

We present the results of $^{12}$CO($J$=1-0) and $^{13}$CO($J$=1-0) simultaneous mappings toward the nearby barred spiral galaxy NGC 4303 as a part of the CO Multi-line Imaging of Nearby Galaxies (COMING) project. Barred spiral galaxies often show lower star-formation efficiency (SFE) in their bar region compared to the spiral arms. In this paper, we examine the relation between the SFEs and the volume densities of molecular gas $n(\rm{H}_2)$ in the eight different regions within the galactic disk with CO data combined with archival far-ultraviolet and 24 $μ$m data. We confirmed that SFE in the bar region is lower by 39% than that in the spiral arms. Moreover, velocity-alignment stacking analysis was performed for the spectra in the individual regions. The integrated intensity ratios of $^{12}$CO to $^{13}$CO ($R_{12/13}$) range from 10 to 17 as the results of stacking. Fixing a kinetic temperature of molecular gas, $n(\rm{H}_2)$ was derived from $R_{12/13}$ via non-local thermodynamic equilibrium (non-LTE) analysis. The density $n(\rm{H}_2)$ in the bar is lower by 31-37% than that in the arms and there is a rather tight positive correlation between SFEs and $n(\rm{H}_2)$, with a correlation coefficient of $\sim 0.8$. Furthermore, we found a dependence of $n(\rm{H}_2)$ on the velocity dispersion of inter-molecular clouds ($ΔV/ \sin i$). Specifically, $n(\rm{H}_2)$ increases as $ΔV/ \sin i$ increases when $ΔV/ \sin i < 100$ km s$^{-1}$. On the other hand, $n(\rm{H}_2)$ decreases as $ΔV/ \sin i$ increases when $ΔV/ \sin i > 100$ km s$^{-1}$. These relations indicate that the variations of SFE could be caused by the volume densities of molecular gas, and the volume densities could be governed by the dynamical influence such as cloud-cloud collisions, shear and enhanced inner-cloud turbulence.

astro-ph.GA↗

arXiv2019

CO Multi-line Imaging of Nearby Galaxies (COMING): VI. Radial variations in star formation efficiency

We examined radial variations in molecular-gas based star formation efficiency (SFE), which is defined as star formation rate per unit molecular gas mass, for 80 galaxies selected from the CO Multi-line Imaging of Nearby Galaxies project (Sorai et al. 2019). The radial variations in SFE for individual galaxies are typically a factor of 2 -- 3, which suggests that SFE is nearly constant along galactocentric radius. We found the averaged SFE in 80 galaxies of $(1.69 \pm 1.1) \times 10^{-9}$ yr$^{-1}$, which is consistent with Leroy et al. 2008 if we consider the contribution of helium to the molecular gas mass evaluation and the difference in the assumed initial mass function between two studies. We compared SFE among different morphological (i.e., SA, SAB, and SB) types, and found that SFE within the inner radii ($r/r_{25} < 0.3$, where $r_{25}$ is $B$-band isophotal radius at 25 mag arcsec$^{-2}$) of SB galaxies is slightly higher than that of SA and SAB galaxies. This trend can be partly explained by the dependence of SFE on global stellar mass, which probably relates to the CO-to-H$_2$ conversion factor through the metallicity. For two representative SB galaxies in our sample, NGC 3367 and NGC 7479, the ellipse of $r/r_{25}$ = 0.3 seems to cover not only the central region but also the inner part of the disk, mainly the bar. These two galaxies show higher SFE in the bar than in spiral arms. However, we found an opposite trend in NGC 4303; SFE is lower in the bar than in spiral arms, which is consistent with earlier studies (e.g., Momose et al. 2010). These results suggest diversity of star formation activities in the bar.

astro-ph.GA↗

arXiv2019

CO Multi-line Imaging of Nearby Galaxies (COMING). VII. Fourier decomposition of molecular gas velocity fields and bar pattern speed

The $^{12}$CO $(J=1\rightarrow0)$ velocity fields of a sample of 20 nearby spiral galaxies, selected from the CO Multi-line Imaging of Nearby Galaxies (COMING) legacy project of Nobeyama Radio Observatory, have been analyzed by Fourier decomposition to determine their basic kinematic properties, such as circular and noncircular velocities. On average, the investigated barred (SAB and SB) galaxies exhibit a ratio of noncircular to circular velocities of molecular gas larger by a factor of 1.5-2 than non-barred (SA) spiral galaxies at radii within the bar semimajor axis $a_\mathrm{b}$ at 1 kpc resolution, with a maximum at a radius of $R/a_\mathrm{b}\sim0.3$. Residual velocity field images, created by subtracting model velocity fields from the data, reveal that this trend is caused by kpc-scale streaming motions of molecular gas in the bar region. Applying a new method based on radial velocity reversal, we estimated the corotation radius $R_\mathrm{CR}$ and bar pattern speed $Ω_\mathrm{b}$ in seven SAB and SB systems. The ratio of the corotation to bar radius is found to be in a range of $\mathcal{R}\equiv R_\mathrm{CR}/a_\mathrm{b}\sim0.8\mathrm{-}1.6$, suggesting that intermediate (SBb-SBc), luminous barred spiral galaxies host fast and slow rotator bars. Tentative negative correlations are found for $Ω_\mathrm{b}$ vs. $a_\mathrm{b}$ and $Ω_\mathrm{b}$ vs. total stellar mass $M_\ast$, indicating that bars in massive disks are larger and rotate slower, possibly a consequence of angular momentum transfer. The kinematic properties of SAB and SB galaxies, derived from Fourier decomposition, are compared with recent numerical simulations that incorporate various rotation curve models and galaxy interactions.

astro-ph.GA↗