arXiv subjects

Gan Luo

Publications and source records attributed to Gan Luo.

At least 19 recordsLinked to original sources

arXiv2026

ALOHA IRDCs Molecular Line Follow-up: I. Gas properties and kinematics

Infrared Dark Clouds are ideal sites for investigating the initial conditions of massive star and cluster formation. The A Lei Of the Habitat and Assembly of Infrared Dark Clouds (ALOHA IRDCs), a James Clerk Maxwell Telescope (JCMT) Large Program, has mapped nearby IRDCs with SCUBA-2. Complementary molecular line observations are needed to characterise the physical, kinematic, and chemical properties of the dense gas. We aim to determine the thermal, kinematic, and chemical properties of clumps identified in the ALOHA IRDCs, and to assess their evolutionary status and level of star-forming activity. We performed single-pointing K-band and W-band observations towards 56 ALOHA IRDCs clumps using the Effelsberg 100-m and Yebes 40-m telescopes, respectively. We derived NH3 kinetic temperatures using the hyperfine group ratio (HFGR) method and identified infall and shock signatures from HCO+, H13CO+, SiO, and HNCO profiles. Water masers and NH2D emission were used as complementary tracers of chemical evolution and star formation. The clumps exhibit kinetic temperatures of 15-29 K. We detect NH2D emission towards 18 sources, with NH2D centroid velocities consistent with NH3, indicating both species trace the same dense gas component. More than half of the clumps display blue-asymmetric HCO+ profiles, identifying them as infall candidates. Water masers are detected in 22 sources, with prominent velocity ranges and variability. Broad SiO emission (>~20 km/s) indicates strong shocks, while narrower extents (<~6km/s) likely trace large-scale interactions or low-velocity shocks. The widespread infall signatures, shock tracers, masers, and NH2D emission suggest that relatively quiescent, chemically young material can coexist with dynamically active gas affected by early protostellar feedback, providing insight into the coupled physical and chemical evolution of massive IRDC clumps.

astro-ph.GA↗

arXiv2026

Anomalously high deuterium fractionation in a galactic translucent cloud: a challenge to chemical models

Deuterated (D-) species have long been proposed to diagnose the physical conditions and chemical evolution of cold dense molecular clouds. While deuterium fractionation has been extensively measured in dense cores, observations in diffuse and translucent clouds remain rare. We report here the detection of DCN and DNC toward a translucent cloud ($A_{\rm V} =1.2\pm0.2$ mag, $n_{\rm H_2}$ = $3.9\pm0.2\times10^2$ cm$^{-3}$) through sensitive absorption observations with the IRAM NOrthern Extended Millimeter Array (NOEMA). This detection reaches the lowest column-density and volume-density regime in which deuteration has been observed so far. Interestingly, the observed DCN/HCN and DNC/HNC abundance ratios ($3.3\pm0.6\times10^{-3}$ and $3.6\pm1.2\times10^{-3}$, respectively), which are more than two orders of magnitude higher than the element abundance [D]/[H] (1.5$\times$10$^{-5}$), suggest an unexpected enhancement of deuterium fractionation in the translucent cloud. These results represent a significant departure from established chemical models considering deuterium fractionation, which predict negligible formation of D-molecules in such environments. Although it remains unclear how D-molecules built up their abundances in translucent gas, a dispersed dense core scenario could potentially explain the observed high deuterium fraction. This interpretation is consistent with the idea proposed by Price et al. (2003) more than two decades ago: a translucent cloud may be a transient, dynamically evolving structure formed through the dissipation of a dense molecular cloud.

astro-ph.GA↗

arXiv2026

From Search to Synthesis: Training LLMs as Zero-Shot Workflow Generators

Large language models (LLMs) excel across a wide range of tasks, yet their instance-specific solutions often lack the structural consistency needed for reliable deployment. Workflows that encode recurring algorithmic patterns at the task level provide a principled framework, offering robustness across instance variations, interpretable traces for debugging, and reusability across problem instances. However, manually designing such workflows requires significant expertise and effort, limiting their broader application. While automatic workflow generation could address this bottleneck, existing methods either produce instance-specific solutions without learning task-level patterns, or cannot generalize beyond their training configurations. We present MetaFlow, which casts workflow generation as a meta-learning problem: given a task and an operator set, the model learns to compose solution strategies. MetaFlow trains in two stages: supervised fine-tuning on synthetic workflow data, followed by reinforcement learning with verifiable rewards (RLVR) that uses execution feedback across problem instances in the task to improve end-to-end success. The resulting model produces effective workflows for trained tasks and exhibits strong generalization to untrained tasks and novel operator sets. Across benchmarks in question answering, code generation, and mathematical reasoning, MetaFlow achieves performance comparable to state-of-the-art baselines on in-domain tasks with single inference, while demonstrating remarkable zero-shot generalization capabilities on out-of-domain tasks and operator sets.

cs.LG↗

arXiv2026

A HINSA view of cosmic-ray ionization in IC 348 and NGC 1333: evidence for a strong low-energy cosmic-ray disparity

The cosmic-ray ionization rate (CRIR) is one of the fundamental parameters influencing the chemical and dynamical evolution of molecular clouds. Although observations in recent years have revealed high CRIR values in massive star-forming regions and in the vicinity of protostars, the sources and acceleration mechanisms of cosmic rays remain uncertain. In this work, we present our new estimates of CRIR using the HI narrow self-absorption (HINSA) technique towards two nearby low-mass star-forming clouds, IC 348 and NGC 1333. In both clouds, the CRIR decreases with increasing H$_2$ column density, but IC 348 exhibits values that are roughly an order of magnitude higher than those in NGC 1333. To interpret this contrast, we model the low-energy spectrum of CRs in a finite slab attenuation framework, using additional constraints from the high-energy CR spectrum inferred from Fermi $\gamma$-ray observations. The best-fit spectra reproduce the observed CRIR profiles and the contrast between IC 348 and NGC 1333 suggests an order of magnitude difference in low-energy CR populations, likely originating from local acceleration sources beyond protostars (e.g., stellar-wind termination shocks), and partly from the same sources responsible for the GeV $\gamma$-ray excess. Although uncertainties in cloud structure and gas density may affect the absolute CRIR values, they do not erase the pronounced disparity between the two regions.

astro-ph.GA↗

arXiv2026

Service-Induced Congestion in Memory-Constrained LLM Serving

In large language model (LLM) serving, each request accumulates persistent graphics processing unit (GPU) memory during service as its key-value cache grows with every generated token. Under high concurrency, aggregate memory usage therefore increases endogenously over time: the service process itself creates future capacity pressure. When memory capacity is exceeded, systems evict active requests, discarding cached state and restarting them later, which wastes computation and reduces throughput. We develop a discrete-time dynamical model of memory-constrained LLM inference that captures admission, memory growth, and eviction under continuous batching. In the saturated-input regime, the system admits both eviction-free fixed points and limit cycles with evictions. For homogeneous workloads, we show that the eviction-free equilibrium is unstable and that, except for a Lebesgue-measure-zero exact-capture set, the system converges to a unique worst-case limit cycle that is asymptotically stable outside this exceptional set, with throughput losses as large as 50%. For heterogeneous workloads, we prove a stability criterion in the two-class common-input setting and explain how the survival-polynomial mechanism generalizes to multiple classes and heterogeneous-input lengths. Under an input-dominated scaling regime, coprime decoding lengths stabilize the eviction-free equilibrium, while non-coprime lengths create synchronized modes that drive instability. These results characterize when workload heterogeneity desynchronizes completions and helps stabilize memory-constrained serving. More broadly, we identify service-induced congestion as a structural instability mechanism and derive scheduling design principles for sustaining high throughput.

math.OC↗

arXiv2026

Star Formation Drives Production of Low Energy Cosmic Rays

For over a century, the origin of low-energy cosmic rays (LECRs), the dominant heaters and ionizers of dense interstellar gas, remains elusive owing to solar modulation and uncertain transport processes. In this study, we introduce a new astrophysical approach based on HI Narrow Self-Absorption (HINSA) to obtain spatially resolved measurements of LECR ionization rates using high-fidelity HI observations toward the Orion region from the FAST telescope. The LECR ionization rate is found to scale with local star formation rate (SFR) as $log_{10}\zeta = (1.4\pm 0.70)log_{10}\mathrm{SFR} + (-10.5\pm 2.9)$. Moreover, it increases with visual extinction, and is found to exceed, toward active star-forming regions, the value predicted for diffuse regions based on \textit{Voyager} measurements and an external propagation model. These findings demonstrate that LECRs are generated in situ by star-forming activities rather than penetrating from the broader Galactic cosmic-ray population. This is further supported by \textit{Fermi}-LAT gamma-ray observations toward the Orion region. Together, these results resolve a key uncertainty in cosmic-ray origin and establish a new avenue for quantifying the energetic feedback that regulates the interstellar medium.

astro-ph.GA↗

arXiv2026

CO-dark molecular gas traced by HCO$^+$ in the diffuse interstellar medium

A classic problem in the study of the interstellar medium (ISM) is the near-invisibility of molecular hydrogen (H$_2$) in cold environments. Observations of CO emission are typically used to indirectly trace H$_2$, but a significant fraction of H$_2$ in the diffuse ISM is not associated with any detectable CO emission (``CO-dark'' molecular gas). Meanwhile, observations of H$_2$ absorption trace nearly all of the H$_2$ in diffuse directions. In particular, a kinematically broad HCO$^+$ absorption signature traces extremely diffuse, CO-dark H$_2$. We have used sensitive observations of HCO$^+$, CO, and atomic hydrogen (HI) in absorption to constrain the properties of such diffuse molecular gas in five directions. The diffuse molecular gas revealed by broad HCO$^+$ absorption has a lower fraction of cold HI ($f_{\mathrm{CNM}} = 0.38^{+0.28}_{-0.27}$) and a lower fraction of hydrogen in H$_2$ ($f_{\mathrm{mol}}=0.09^{+0.06}_{-0.03}$) than gas traced by CO in the same directions. We detect almost no CO absorption from the gas traced by broad HCO$^+$ absorption. We constrain the CO abundance relative to H$_2$ to be $\lesssim10^{-6}$-$10^{-5}$ for gas traced by both broad and narrow HCO$^+$ absorption, consistent with chemical model predictions for the diffuse ISM. We further show that neither CO emission nor absorption is likely to be detected where $N(\mathrm{H_2})\lesssim\mathrm{few}\times10^{19}$ $\mathrm{cm^{-2}}$ - a result of both the low CO abundance and the low H$_2$ column - while HCO$^+$ absorption is readily detected for $N(\mathrm{H_2})\gtrsim\text{few}\times10^{18}$ $\mathrm{cm^{-2}}$. These results demonstrate that even modest amounts of cold HI can bear H$_2$, providing critical constraints on the HI-to-H$_2$ transition in the ISM.

astro-ph.GA↗

arXiv2026

Large scale mapping of [CI] and the [CI]-to-CO transition in $\rho$ Ophiuchus molecular cloud

Atomic carbon ([CI]) is a key species in the carbon chemistry of the interstellar medium (ISM). Using the Submillimeter Wave Astronomy Satellite (SWAS), we conducted a [CI]($^3$P$_1$--$^3$P$_0$) 492 GHz survey covering approximately 4 deg$^2$ of the L1688 and L1689 regions in the $\rho$ Oph molecular cloud, achieving a spatial resolution of 4.25$\hbox{$^{\prime}$}$. The derived [CI] column densities, N([CI]), range from 4.85 $\times$ 10$^{14}$ cm$^{-2}$ to 6.29 $\times$ 10$^{17}$ cm$^{-2}$, corresponding to an abundance ratio N([CI])/N($H_2$) of 2.24$\times$ 10$^{-7}$ to 2.39$\times$ 10$^{-4}$, with a median value of 1.8$\times$ 10$^{-5}$. Combining observations with photodissociation region (PDR) modeling, we find that [CI] abundance varies less than CO in regions with UV intensity G$_0$ $> 16$ and N(H$_2$) $<$ 4.6 $\times$ 10$^{21}$ cm$^{-2}$, suggesting [CI] is a more reliable tracer of molecular hydrogen in low-density, high-radiation environments where the [CI]-to-CO transition occurs. Utilizing [CI] as direct H$_2$ tracer, the CO-dark gas fraction is estimated to be 0.43 , meaning that 43% of the total cloud mass will be missed by conventional calculation based on CO observations but can be calibrated by [CI] emission. The [CI] line widths are systematically broader than those of $^{13}$CO, possibly due to contributions from atomic carbon. These findings provide key insights into Galactic [CI] emission and the carbon cycle evolution in the interstellar medium. Future high-sensitivity [CI] ($^3$P$_1$--$^3$P$_0$) surveys with the Chinese Survey Space Telescope (CSST) will significantly advance our understanding of the carbon cycle evolution.

astro-ph.GA↗

arXiv2025

The evolution of CH in Planck Galactic Cold Clumps

Methylidyne (CH) has long been considered a reliable tracer of molecular gas in the low-to-intermediate extinction range. Although extended CH 3.3 GHz emission is commonly observed in diffuse and translucent clouds, observations in cold, dense clumps are rare. In this work, we conducted high-sensitivity CH observations toward 27 PGCCs with the Arecibo 305m telescope. Toward each source, the CH data were analyzed in conjunction with $^{13}$CO (1--0), HINSA, and H$_2$ column densities. Our results revealed ubiquitous subsonic velocity dispersions of CH, in contrast to $^{13}$CO, which is predominantly supersonic. The findings suggest that subsonic CH emissions may trace dense, low-turbulent gas structures in PGCCs. To investigate environmental effects, particularly the cosmic-ray ionization rate (CRIR), we estimated CRIR upper limits from HINSA, yielding values from $(8.1\pm4.7)\times10^{-18}$ to $(2.0\pm0.8)\times10^{-16}$ s$^{-1}$ ($N_{H_2}$ from $(1.7\pm0.2)\times10^{21}$ to $(3.6\pm0.4)\times10^{22}$~cm$^{-2}$). This result favors theoretical predictions of a cosmic-ray attenuation model, in which the interstellar spectra of low-energy CR protons and electrons match {\it Voyager} measurements, although alternative models cannot yet be ruled out. The abundance of CH decreases with increasing column density, while showing a positive dependence on the CRIR, which requires atomic oxygen not heavily depleted to dominate CH destruction in PGCCs. By fitting the abundance of CH with an analytic formula, we place constraints on atomic O abundance ($2.4\pm0.4\times10^{-4}$ with respect to total H) and C$^+$ abundance ($7.4\pm0.7\times10^{13}\zeta_2/n_{\rm H_2}$). These findings indicate that CH formation is closely linked to the C$^+$ abundance, regulated by cosmic-ray ionization, while other processes, such as turbulent diffusive transport, might also contribute a non-negligible effect.

astro-ph.GA↗

arXiv2025

Dense gas properties and star formation in M 82

High-density molecular gas plays a vital role in supporting star formation within galaxies. However, traditional tracers of dense gas, such as the low-$J$ transitions of HCN and HCO$^+$, are predominantly optically thick. This characteristic presents a significant challenge in accurately estimating the column density of dense gas and mapping its spatial distribution. Optically-thin tracers, including HC$_3$N (10-9) and isotopologues of HCN, HCO$^+$, HNC (1-0), among others, emerge as better tracers, by enabling more precise measurements and analyses of the dense gas in galaxies. Here, we present the first high-resolution ($\sim$3.8$''$, corresponding to $\sim$65 pc) molecular line observations of the nearby starburst galaxy M~82 with IRAM Northern Extended Millimeter Array (NOEMA). Notably, HC$_3$N (10-9) and H$^{13}$CN (1-0) emission lines are brighter at the northeast part (NE lobe) than those at the southwest part (SW lobe) of M~82, suggesting a higher accumulation of dense gas at the NE lobe. The spatial distributions of H41$\alpha$ and 3-mm continuum emission indicate that starburst activity varies across the central starburst disk, with more intense star formation occurring at the SW lobe compared to the NE lobe. The average optical depths of HCN and HCO$^+$ (1-0) across the triple-peaked regions exhibit significant variation, with the highest values observed at the NE lobe. Our results suggest a potential evolutionary sequence in M~82, where the distributions of star formation and dense gas appear to be partially decoupled -- a phenomenon that classical dense gas tracers cannot adequately probe.

astro-ph.GA↗

arXiv2025

On the Linear Speedup of the Push-Pull Method for Decentralized Optimization over Digraphs

The linear speedup property is essential for demonstrating the advantage of distributed algorithms over their single-node counterparts. In this paper, we study the stochastic Push-Pull method, a widely adopted decentralized optimization algorithm over directed graphs (digraphs). Unlike methods that rely solely on row-stochastic or column-stochastic mixing matrices, Push-Pull avoids nonlinear correction and has shown superior empirical performance across a variety of settings. However, its theoretical analysis remains challenging, and the linear speedup property has not been generally establishe--revealing a significant gap between empirical success and limited theoretical understanding. To bridge this gap, we propose a novel analysis framework and prove that Push-Pull achieves linear speedup over arbitrary strongly connected digraphs. Our results provide the comprehensive theoretical understanding for stochastic Push-Pull, aligning its theory with empirical performance. Code: https://github.com/pkumelon/PushPull.

math.OC↗

arXiv2025

Targeted False Positive Synthesis via Detector-guided Adversarial Diffusion Attacker for Robust Polyp Detection

Polyp detection is crucial for colorectal cancer screening, yet existing models are limited by the scale and diversity of available data. While generative models show promise for data augmentation, current methods mainly focus on enhancing polyp diversity, often overlooking the critical issue of false positives. In this paper, we address this gap by proposing an adversarial diffusion framework to synthesize high-value false positives. The extensive variability of negative backgrounds presents a significant challenge in false positive synthesis. To overcome this, we introduce two key innovations: First, we design a regional noise matching strategy to construct a negative synthesis space using polyp detection datasets. This strategy trains a negative-centric diffusion model by masking polyp regions, ensuring the model focuses exclusively on learning diverse background patterns. Second, we introduce the Detector-guided Adversarial Diffusion Attacker (DADA) module, which perturbs the negative synthesis process to disrupt a pre-trained detector's decision, guiding the negative-centric diffusion model to generate high-value, detector-confusing false positives instead of low-value, ordinary backgrounds. Our approach is the first to apply adversarial diffusion to lesion detection, establishing a new paradigm for targeted false positive synthesis and paving the way for more reliable clinical applications in colorectal cancer screening. Extensive results on public and in-house datasets verify the superiority of our method over the current state-of-the-arts, with our synthesized data improving the detectors by at least 2.6% and 2.7% in F1-score, respectively, over the baselines. Codes are at https://github.com/Huster-Hq/DADA.

cs.CV↗

arXiv2025

Achieving Linear Speedup and Near-Optimal Complexity for Decentralized Optimization over Row-stochastic Networks

A key challenge in decentralized optimization is determining the optimal convergence rate and designing algorithms to achieve it. While this problem has been extensively addressed for doubly-stochastic and column-stochastic mixing matrices, the row-stochastic scenario remains unexplored. This paper bridges this gap by introducing effective metrics to capture the influence of row-stochastic mixing matrices and establishing the first convergence lower bound for decentralized learning over row-stochastic networks. However, existing algorithms fail to attain this lower bound due to two key issues: deviation in the descent direction caused by the adapted gradient tracking (GT) and instability introduced by the Pull-Diag protocol. To address descent deviation, we propose a novel analysis framework demonstrating that Pull-Diag-GT achieves linear speedup, the first such result for row-stochastic decentralized optimization. Moreover, by incorporating a multi-step gossip (MG) protocol, we resolve the instability issue and attain the lower bound, achieving near-optimal complexity for decentralized optimization over row-stochastic networks.

math.OC↗

arXiv2025

Optimizing LLM Inference: Fluid-Guided Online Scheduling with Memory Constraints

Large language models now serve millions of users daily, with providers incurring costs exceeding $700,000 per day. Each request requires token-by-token inference, making GPU scheduling central to latency, capacity, and cost. The difficulty is endogenous memory growth: generated tokens expand the Key-Value (KV) cache, and overflow can evict in-progress requests and waste prior computation. We formulate inference as a multi-stage online scheduling problem with endogenous memory growth, linear iteration times, and GPU-resident KV-cache constraints. We introduce a fluid model that characterizes equilibrium batch composition, memory requirement, and stability region. Guided by the fluid model, we design WAIT (Waiting for Accumulated Inference Threshold), a threshold-based admission rule for known output lengths, and Nested WAIT, which extends the rule to unknown output lengths by regulating how requests advance across decode-stage segments. Both algorithms approximate the fluid benchmark asymptotically under the stated memory conditions. Nested WAIT uses an additional safety buffer of moderate scale to hedge against memory-overflow-induced evictions under unknown output lengths. In Vidur simulations configured for Llama-2-7B on an A100 GPU, with supplemental real-GPU validation reported in the appendix, the policies enlarge the empirically observed stable operating range relative to widely used baseline algorithms and reduce latency especially in near-overloaded and overloaded regimes.

cs.LG↗

arXiv2025

Physical Properties and HI-to-H2 Transition Across Taurus Linear Edge

Studying the atomic-to-molecular transition is essential for understanding the evolution of interstellar medium. The linear edge of Taurus molecular cloud, clearly identified in the $^{13}$CO(1-0) intensity map, serves as an ideal site for investigating this transition. Utilizing the Arizona Radio Observatory Sub-Millimeter Telescope, we obtained mapping observations of CO(2-1), $^{13}$CO(2-1), and CO(3-2) across this linear edge. The intensity ratio between CO(2-1) and $^{13}$CO(2-1) indicates a lower limit of the $^{12}C/^{13}C$ ratio of $54\pm 17$. Based on multi-transition observations of CO and $^{13}$CO, we performed Markov Chain Monte Carlo (MCMC) fit of the physical properties across this edge using non-Local Thermodynamic Equilibrium analysis with the RADEX code, based on the Large velocity Gradient (LVG) assumption. The number density profile exhibits a pronounced jump coinciding with the H$_2$ infrared emission peak. The cold HI gas within the molecular cloud, manifested as HI-Narrow Self-Absorption (HINSA) features, is detected along the cloud edge. Our quantitative comparison with numerical simulations provides tentative evidence that shocks induced by colliding gas flows may contribute to the atomic-to-molecular phase transition observed along the linear edge.

astro-ph.GA↗

arXiv2025

Metallicity dependence of the CO-to-H$_2$ and the [CI]-to-H$_2$ conversion factors in galaxies

Understanding the molecular gas content in the interstellar medium (ISM) is crucial for studying star formation and galaxy evolution. The CO-to-H$_2$ ($X_{\rm CO}$) and the [CI]-to-H$_2$ ($X_{\rm CI}$) conversion factors are widely used to estimate the molecular mass content in galaxies. However, these factors depend on many ISM environmental parameters. This work investigates the dependence of $X_{\rm CO}$ and $X_{\rm CI}$ on these parameters, with a focus on the low-metallicity $\alpha$-enhanced ISM ($\rm [C/O]<0$), to provide improved tracers of molecular gas in diverse conditions. We used the PDFchem algorithm, coupled with a database of 3D-PDR models. These account for a wide range of metallicities, dust-to-gas mass ratios, FUV intensities, and cosmic-ray ionization rates. The conversion factors were computed by integrating the PDR properties over log-normal column density distributions ($A_{\rm V}$-PDFs) representing various cloud types. The $X_{\rm CO}$ factor increases significantly with decreasing metallicity, exceeding $\sim\!\!1000$ times the Galactic value at ${\rm [O/H] = -1.0}$ under $\alpha$-enhanced conditions, as opposed to $\sim\!\!300$ times under non-$\alpha$-enhanced conditions (${\rm [C/O]=0}$). In contrast, $X_{\rm CI}$ shows a more gradual variation with metallicity, making it a more reliable tracer of molecular gas in metal-poor environments under most conditions. The fraction of `CO-dark' molecular gas increases dramatically in low-metallicity regions, exceeding 90\% at ${\rm [O/H] = -1.0}$, particularly in diffuse clouds and environments with strong FUV radiation fields. We recommend the use of the $\log_{10}X_{\rm CO}\simeq-2.41Z+41.3$ relation for the CO-to-H$_2$ conversion factor, and the $\log_{10}X_{\rm CI}\simeq-0.99Z+29.7$ relation for the [CI]-to-H$_2$, where $Z=12+\log_{10}({\rm O/H})$.

astro-ph.GA↗

arXiv2025

Tiny-Scale Properties within the Interstellar Medium towards PSR J1644$-$4559: I. Observational Evidence of Turbulence-induced Tiny Scale Atomic Structures

We investigated HI absorption toward a single pulsar, PSR J1644$-$4559, and its variability over timescales from days to years, using Murriyang, CSIRO's Parkes Radio Telescope. Our 19 epochs of spectral observations, spanning 1.2 years with intervals as short as 1 day, provide the most comprehensive cadence coverage for monitoring HI absorption to date. We identified two significant detections of tiny-scale atomic structure (TSAS) with spatial scales ranging from a lower limit of $\sim$11 au to an upper limit of 165 au, both exhibiting integrated signal-to-noise ratios exceeding 5.0. We find a relationship between linear size and optical depth variation in the cold neutral medium (CNM) component hosting the TSAS, described by a power-law relationship, $\Delta\tau_{\rm int} = \Delta\tau_0 (\Delta L)^{(\alpha-2)/2}$, with $\alpha = 4.1 \pm 0.4$. This is the first observational evidence explicitly connecting TSAS to turbulence in CNM. This power-law index is significantly steeper than previously reported values for the CNM, where $\alpha$ ranges from 2.3 to 2.9, but similar to those observed in the warm ionized gas. Additionally, we observe no significant variation in $\alpha$ across the entire range of spatial scales traced in our study, indicating that turbulence may be cascading down and dissipating at smaller scales. While there is no precise proper motion measurement for this pulsar, our estimates for the turbulence dissipation in the CNM place the lower and upper limits at less than 0.03 au and 0.4 au, respectively.

astro-ph.GA↗

arXiv2025

The Host Galaxy of FRB 20190520B and Its Unique Ionized Gas Distribution

The properties of host galaxies associated with Fast Radio Bursts (FRBs) provide critical information for inferring the progenitors and radiation mechanisms of these bursts. We report on the host galaxy of the repeating FRB 20190520B, a dwarf galaxy at the spectroscopic redshift $z=0.241$ with a stellar mass of $(6.2 \pm 0.8) \times 10^8 \ M_{\odot}$. The emission line ratios suggest that the ionized gas is powered by star formation. The total H$\alpha$-traced star formation rate (SFR) is $0.70 \pm 0.01 \ {M_{\odot} ~ \rm yr^{-1}}$, and the metallicity is $\rm 12+log_{10} ([O/H]) \geq 7.4 \pm 0.1$. The specific star formation rate (sSFR) is $\rm log \ sSFR/yr^{-1} = -9.0 \pm 0.1$, higher than the upper limit of $-9.4$ observed in nearby dwarf galaxies. The dispersion measure contribution from the host galaxy is estimated to be $\rm DM_{host} \approx 950 \pm 220 \ pc \ cm^{-3}$, based on the H$\alpha$ emission. The FRB and the associated persistent radio source are located at the H$\alpha$ emission peak, offset by $\sim 1.4^{\prime\prime}$ (5.5 kpc) in projection from the stellar continuum. At this position, the lower limit of $\rm \log \ sSFR/yr^{-1}$ is $-8.5 \pm 0.1$, more than three times the galaxy's total sSFR. The H$\alpha$ velocity difference between the stellar continuum and the offset gas is $39.6 \pm 0.4$ km s$^{-1}$, which is sufficient to draw conclusions about the nature of the offset.

astro-ph.GA↗