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Ran Wang

Publications and source records attributed to Ran Wang.

At least 91 records · Page 5Linked to original sources
arXiv2023

Learning to Control under Uncertainty with Data-Based Iterative Linear Quadratic Regulator

This paper studies the learning-to-control problem under process and sensing uncertainties for dynamical systems. In our previous work, we developed a data-based generalization of the iterative linear quadratic regulator (iLQR) to design closed-loop feedback control for high-dimensional dynamical systems with partial state observation. This method required perfect simulation rollouts which are not realistic in real applications. In this work, we briefly introduce this method and explore its efficacy under process and sensing uncertainties. We prove that in the fully observed case where the system dynamics are corrupted with noise but the measurements are perfect, it still converges to the global minimum. However, in the partially observed case where both process and measurement noise exist in the system, this method converges to a biased "optimum". Thus multiple rollouts need to be averaged to retrieve the true optimum. The analysis is verified in two nonlinear robotic examples simulated in the above cases.

cs.RO↗
arXiv2023

Searching for [CII] Emission from the First Sample of $z\sim 6$ OI Absorption-Associated Galaxies with ALMA

We report the first statistical analyses of [CII] and dust continuum observations in six strong OI absorber fields at the end of the reionization epoch obtained by the Atacama Large Millimeter/Submillimeter Array (ALMA). Combined with one [CII] emitter reported in Wu et al. (2021), we detect one OI-associated [CII] emitter in six fields. At redshifts of OI-absorbers in non-detection fields, no emitters are brighter than our detection limit within impact parameters of 50 kpc and velocity offsets between $\pm200\ {\rm km\ s^{-1}}$. The averaged [CII]-detection upper limit is $< 0.06$ Jy ${\rm km\ s^{-1}}$ (3$σ$), corresponding to the [CII] luminosity of $L_{\rm [CII]} <5.8\times 10^7\ L_{\odot}$ and the [CII]-based star formation rate of ${\rm SFR_{\rm [CII]}} < 5.5$ $M_\odot$ yr$^{-1}$. Cosmological simulations suggest that only $\sim10^{-2.5}$ [CII] emitters around [OI] absorbers have comparable SFR to our detection limit. Although the detection in one out of six fields is reported, an order of magnitude number excess of emitters obtained from our ALMA observations supports that the contribution of massive galaxies that caused the metal enrichment cannot be ignored. Further, we also found 14 tentative galaxy candidates with S/N of $\approx4.3$ at large impact parameters ($>50$ kpc) and having larger outflow velocities within $\pm 600$ km s$^{-1}$. If these detections are confirmed in the future, then the mechanism of pushing metals at larger distances with higher velocities needs to be further explored from the theoretical side.

astro-ph.GA↗
arXiv2023

Multi-label Classification with High-rank and High-order Label Correlations

Exploiting label correlations is important to multi-label classification. Previous methods capture the high-order label correlations mainly by transforming the label matrix to a latent label space with low-rank matrix factorization. However, the label matrix is generally a full-rank or approximate full-rank matrix, making the low-rank factorization inappropriate. Besides, in the latent space, the label correlations will become implicit. To this end, we propose a simple yet effective method to depict the high-order label correlations explicitly, and at the same time maintain the high-rank of the label matrix. Moreover, we estimate the label correlations and infer model parameters simultaneously via the local geometric structure of the input to achieve mutual enhancement. Comparative studies over twelve benchmark data sets validate the effectiveness of the proposed algorithm in multi-label classification. The exploited high-order label correlations are consistent with common sense empirically. Our code is publicly available at https://github.com/Chongjie-Si/HOMI.

cs.LG↗
arXiv2023

Large-scale Foundation Models and Generative AI for BigData Neuroscience

Recent advances in machine learning have made revolutionary breakthroughs in computer games, image and natural language understanding, and scientific discovery. Foundation models and large-scale language models (LLMs) have recently achieved human-like intelligence thanks to BigData. With the help of self-supervised learning (SSL) and transfer learning, these models may potentially reshape the landscapes of neuroscience research and make a significant impact on the future. Here we present a mini-review on recent advances in foundation models and generative AI models as well as their applications in neuroscience, including natural language and speech, semantic memory, brain-machine interfaces (BMIs), and data augmentation. We argue that this paradigm-shift framework will open new avenues for many neuroscience research directions and discuss the accompanying challenges and opportunities.

q-bio.NC↗
arXiv2023

An Information-state based Approach to the Optimal Output Feedback Control of Nonlinear Systems

This paper develops a data-based approach to the closed-loop output feedback control of nonlinear dynamical systems with a partial nonlinear observation model. We propose an information state based approach to rigorously transform the partially observed problem into a fully observed problem where the information state consists of the past several observations and control inputs. We further show the equivalence of the transformed and the initial partially observed optimal control problems and provide the conditions to solve for the deterministic optimal solution. We develop a data based generalization of the iterative Linear Quadratic Regulator (iLQR) to partially observed systems using a local linear time varying model of the information state dynamics approximated by an Autoregressive moving average (ARMA) model, that is generated using only the input-output data. This open-loop trajectory optimization solution is then used to design a local feedback control law, and the composite law then provides an optimum solution to the partially observed feedback design problem. The efficacy of the developed method is shown by controlling complex high dimensional nonlinear dynamical systems in the presence of model and sensing uncertainty.

cs.RO↗
arXiv2023

ALMA/ACA CO Survey of the IC 1459 and NGC 4636 Groups: Environmental Effects on the Molecular Gas of Group Galaxies

We present new results of a 12CO(J=1-0) imaging survey using the Atacama Compact Array (ACA) for 31 HI detected galaxies in the IC 1459 and NGC 4636 groups. This is the first CO imaging survey for loose galaxy groups. We obtained well-resolved CO data (~0.7-1.5 kpc) for a total of 16 galaxies in two environments. By comparing our ACA CO data with the HI and UV data, we probe the impacts of the group environment on the cold gas components (CO and HI gas) and star formation activity. We find that CO and/or HI morphologies are disturbed in our group members, some of which show highly asymmetric CO distributions (e.g., IC 5264, NGC 7421, and NGC 7418). In comparison with isolated galaxies in the xCOLD GASS sample, our group galaxies tend to have low star formation rates and low H2 gas fractions. Our findings suggest that the group environment can change the distribution of cold gas components, including the molecular gas, and star formation properties of galaxies. This is supporting evidence that preprocessing in the group-like environment can play an important role in galaxy evolution.

astro-ph.GA↗
arXiv2023

CharacterChat: Learning towards Conversational AI with Personalized Social Support

In our modern, fast-paced, and interconnected world, the importance of mental well-being has grown into a matter of great urgency. However, traditional methods such as Emotional Support Conversations (ESC) face challenges in effectively addressing a diverse range of individual personalities. In response, we introduce the Social Support Conversation (S2Conv) framework. It comprises a series of support agents and the interpersonal matching mechanism, linking individuals with persona-compatible virtual supporters. Utilizing persona decomposition based on the MBTI (Myers-Briggs Type Indicator), we have created the MBTI-1024 Bank, a group that of virtual characters with distinct profiles. Through improved role-playing prompts with behavior preset and dynamic memory, we facilitate the development of the MBTI-S2Conv dataset, which contains conversations between the characters in the MBTI-1024 Bank. Building upon these foundations, we present CharacterChat, a comprehensive S2Conv system, which includes a conversational model driven by personas and memories, along with an interpersonal matching plugin model that dispatches the optimal supporters from the MBTI-1024 Bank for individuals with specific personas. Empirical results indicate the remarkable efficacy of CharacterChat in providing personalized social support and highlight the substantial advantages derived from interpersonal matching. The source code is available in \url{https://github.com/morecry/CharacterChat}.

cs.CL↗
arXiv2023

Multiobjective Hydropower Reservoir Operation Optimization with Transformer-Based Deep Reinforcement Learning

Due to shortage of water resources and increasing water demands, the joint operation of multireservoir systems for balancing power generation, ecological protection, and the residential water supply has become a critical issue in hydropower management. However, the numerous constraints and nonlinearity of multiple reservoirs make solving this problem time-consuming. To address this challenge, a deep reinforcement learning approach that incorporates a transformer framework is proposed. The multihead attention mechanism of the encoder effectively extracts information from reservoirs and residential areas, and the multireservoir attention network of the decoder generates suitable operational decisions. The proposed method is applied to Lake Mead and Lake Powell in the Colorado River Basin. The experimental results demonstrate that the transformer-based deep reinforcement learning approach can produce appropriate operational outcomes. Compared to a state-of-the-art method, the operation strategies produced by the proposed approach generate 10.11% more electricity, reduce the amended annual proportional flow deviation by 39.69%, and increase water supply revenue by 4.10%. Consequently, the proposed approach offers an effective method for the multiobjective operation of multihydropower reservoir systems.

cs.LG↗
arXiv2023

Unveiling the small-scale jets in the rapidly growing supermassive black hole IZw1

Accretion of black holes at near-Eddington or super-Eddington rates is the most powerful episode that drives black hole growth, and it may work in several types of objects. However, the physics of accretion and jet-disc coupling in such a state remains unclear, mainly because the associated jets are not easily detectable due to the extremely weak emission or possibly episodic nature of the jets. Only a few near/super-Eddington systems have demonstrated radio activity, and it remains unclear whether there is a jet and what are their properties, in super-Eddington active galactic nuclei (AGNs) (and ultraluminous X-ray sources). The deficit is mainly due to the complex radio mixing between the origins of jets and others, such as star formation activity, photo-ionized gas, accretion disk wind, and coronal activity. In this work, we conducted high-resolution very long baseline interferometry (VLBI) observations to explore the jets in the highly accreting narrow-line Seyfert I system IZw1. Our observations successfully revealed small-scale jets (with a linear size of $\sim45$ parsec) at both 1.5 and 5 GHz, based on the high radio brightness temperature, radio morphology, and spectral index distribution. Interestingly, the lack of a flat-spectrum radio core and knotty jet structures imply episodic ejections in IZw1, which resemble the ejection process in Galactic X-ray binaries that are in the canonical very high state. The high accretion rates and jet properties in the AGN IZw1 may support the AGN/XRB analogy in the extreme state.

astro-ph.HE↗
arXiv2023

Inspiraling streams of enriched gas observed around a massive galaxy 11 billion years ago

Stars form in galaxies, from gas that has been accreted from the intergalactic medium. Simulations have shown that recycling of gas-the reaccretion of gas that was previously ejected from a galaxy-could sustain star formation in the early Universe. We observe the gas surrounding a massive galaxy at redshift 2.3 and detect emission lines from neutral hydrogen, helium, and ionized carbon that extend 100 kiloparsecs from the galaxy. The kinematics of this circumgalactic gas is consistent with an inspiraling stream. The carbon abundance indicates that the gas had already been enriched with elements heavier than helium, previously ejected from a galaxy. We interpret the results as evidence of gas recycling during high-redshift galaxy assembly.

astro-ph.GA↗
arXiv2023

Lack of Correlations between Cold Molecular Gas and AGN Properties in Type 1 AGNs at $z \lesssim 0.5$

We present new NOrthern Extended Millimeter Array (NOEMA) observations of the CO(2--1) emission in eight of the brightest Palomar-Green quasars at $z \lesssim 0.5$ to investigate the role of active galactic nuclei (AGN) feedback in luminous quasars detected at low redshifts. We detect CO(2--1) emission in three objects, from which we derive CO luminosities, molecular gas masses and fractions, and gas depletion times. In combination with data available in the literature, we build a total sample of 138 local type 1 AGNs with CO(2--1) measurements. We compare the AGN properties with the host galaxy molecular gas properties, considering the systems non-detected in CO emission. We find that the CO luminosity does not correlate with AGN luminosity and Eddington ratio, while the molecular gas fraction is weakly correlated with Eddington ratio. The type 1 AGNs can be roughly separated into two populations in terms of infrared-to-CO luminosity ratio, one population presenting values typically found in normal star-forming systems, while the other have lower ratio values, comparable to those measured for starbursts. We find no evidence that AGN feedback rapidly quenches star formation in type 1 AGNs. Our results may imply an underlying the role of host galaxy gravitational instabilities or the fast inflow of cold gas in triggering AGN activity.

astro-ph.GA↗
arXiv2023

Ensemble Clustering via Co-association Matrix Self-enhancement

Ensemble clustering integrates a set of base clustering results to generate a stronger one. Existing methods usually rely on a co-association (CA) matrix that measures how many times two samples are grouped into the same cluster according to the base clusterings to achieve ensemble clustering. However, when the constructed CA matrix is of low quality, the performance will degrade. In this paper, we propose a simple yet effective CA matrix self-enhancement framework that can improve the CA matrix to achieve better clustering performance. Specifically, we first extract the high-confidence (HC) information from the base clusterings to form a sparse HC matrix. By propagating the highly-reliable information of the HC matrix to the CA matrix and complementing the HC matrix according to the CA matrix simultaneously, the proposed method generates an enhanced CA matrix for better clustering. Technically, the proposed model is formulated as a symmetric constrained convex optimization problem, which is efficiently solved by an alternating iterative algorithm with convergence and global optimum theoretically guaranteed. Extensive experimental comparisons with twelve state-of-the-art methods on eight benchmark datasets substantiate the effectiveness, flexibility and efficiency of the proposed model in ensemble clustering. The codes and datasets can be downloaded at https://github.com/Siritao/EC-CMS.

cs.LG↗
arXiv2023

Dynamic Offloading Loading Optimization in distributed Fault Diagnosis system with Deep Reinforcement Learning Approach

Artificial intelligence and distributed algorithms have been widely used in mechanical fault diagnosis with the explosive growth of diagnostic data. A novel intelligent fault diagnosis system framework that allows intelligent terminals to offload computational tasks to Mobile edge computing (MEC) servers is provided in this paper, which can effectively address the problems of task processing delays and enhanced computational complexity. As the resources at the MEC and intelligent terminals are limited, performing reasonable resource allocation optimization can improve the performance, especially for a multi-terminals offloading system. In this study, to minimize the task computation delay, we jointly optimize the local content splitting ratio, the transmission/computation power allocation, and the MEC server selection under a dynamic environment with stochastic task arrivals. The challenging dynamic joint optimization problem is formulated as a reinforcement learning (RL) problem, which is designed as the computational offloading policies to minimize the long-term average delay cost. Two deep RL strategies, deep Q-learning network (DQN) and deep deterministic policy gradient (DDPG), are adopted to learn the computational offloading policies adaptively and efficiently. The proposed DQN strategy takes the MEC selection as a unique action while using the convex optimization approach to obtain the local content splitting ratio and the transmission/computation power allocation. Simultaneously, the actions of the DDPG strategy are selected as all dynamic variables, including the local content splitting ratio, the transmission/computation power allocation, and the MEC server selection. Numerical results demonstrate that both proposed strategies perform better than the traditional non-learning schemes.

cs.IT↗
arXiv2023

Dynamics of Molecular Gas in the Central Region of the Quasar I$\,$Zwicky$\,$1

We present a study of the molecular gas distribution and kinematics in the cicumnuclear region (radii $\lesssim 2\,$kpc) of the $z\approx0.061$ quasar I$\,$Zwicky$\,$1 using a collection of available Atacama Large Millimeter/submillimeter Array (ALMA) observations of the carbon monoxide (CO) emission. With an angular resolution of $\sim0.36''$ (corresponding to $\sim\,400\,\rm pc$), the host galaxy sub-structures including the nuclear molecular gas disk, spiral arms, and a compact bar-like component are resolved. We analyzed the gas kinematics based on the CO image cube and obtained the rotation curve and radial distribution of velocity dispersion. The velocity dispersion is about $30\,\rm km\,s^{-1}$ in the outer CO disk region and rises up to $\gtrsim 100\,\rm km\,s^{-1}$ at radius $\lesssim 1\,$kpc, suggesting that the central region of disk is dynamically hot. We constrain the CO-to-$\rm H_2$ conversion factor, $α_{\rm CO}$, by modeling the cold gas disk dynamics. We find that, with prior knowledge about the stellar and dark matter components, the $α_{\rm CO}$ value in the circumnuclear region of this quasar host galaxy is $1.55_{-0.49}^{+0.47}\,M_\odot\,\left(\rm K\,km\,s^{-1}\,pc^2\right)^{-1}$, which is between the value reported in ultra-luminous infrared galaxies and in the Milky-Way. The central 1$\,$kpc region of this quasar host galaxy has significant star formation activity, which can be identified as a nuclear starburst. We further investigate the high velocity dispersion in the central region. We find that the ISM turbulent pressure derived from the gas velocity dispersion is in equilibrium with the weight of the ISM. This argues against extra power from AGN feedback that significantly affects the kinematics of the cold molecular gas.

astro-ph.GA↗
arXiv2023

A comprehensive view of the interstellar medium in a quasar host galaxy at z~6.4

Characterizing the physical conditions (density, temperature, ionization state, metallicity, etc) of the interstellar medium is critical to our understanding of the formation and evolution of galaxies. Here we present a multi-line study of the interstellar medium in the host galaxy of a quasar at z~6.4, i.e., when the universe was 840 Myr old. This galaxy is one of the most active and massive objects emerging from the dark ages, and therefore represents a benchmark for models of the early formation of massive galaxies. We used the Atacama Large Millimeter Array to target an ensemble of tracers of ionized, neutral, and molecular gas, namely the fine-structure lines: [OIII] 88$μ$m, [NII] 122$μ$m, [CII] 158$μ$m, and [CI] 370$μ$m and the rotational transitions of CO(7-6), CO(15-14), CO(16-15), and CO(19-18); OH 163.1$μ$m and 163.4$μ$m; and H$_2$O 3(0,3)-2(1,2), 3(3,1)-4(0,4), 3(3,1)-3(2,2), 4(0,4)-3(1,3), 4(3,2)-4(2,3). All the targeted fine-structure lines are detected, as are half of the targeted molecular transitions. By combining the associated line luminosities, the constraints on the dust temperature from the underlying continuum emission, and predictions from photoionization models of the interstellar medium, we find that the ionized phase accounts for about one third of the total gaseous mass budget, and is responsible for half of the total [CII] emission. It is characterized by high density (n~180 cm$^{-3}$), typical of HII regions. The spectral energy distribution of the photoionizing radiation is comparable to that emitted by B-type stars. Star formation also appears to drive the excitation of the molecular medium. We find marginal evidence for outflow-related shocks in the dense molecular phase, but not in other gas phases. This study showcases the power of multi-line investigations in unveiling the properties of the star-forming medium in galaxies at cosmic dawn.

astro-ph.GA↗
arXiv2022

NOEMA Detection of Circumnuclear Molecular Gas in X-ray Weak Dual Active Galactic Nuclei: No Evidence for Heavy Obscuration

Dual active galactic nuclei (AGN), which are the manifestation of two actively accreting supermassive black holes (SMBHs) hosted by a pair of merging galaxies, are a unique laboratory for studying the physics of SMBH feeding and feedback during an indispensable stage of galaxy evolution. In this work, we present NOEMA CO(2-1) observations of seven kpc-scale dual-AGN candidates drawn from a recent Chandra survey of low-redshift, optically classified AGN pairs. These systems are selected because they show unexpectedly low 2-10 keV X-ray luminosities for their small physical separations signifying an intermediate-to-late stage of merger. Circumnuclear molecular gas traced by the CO(2-1) emission is significantly detected in 6 of the 7 pairs and 10 of the 14 nuclei, with an estimated mass ranging between $(0.2 - 21) \times10^9\rm~M_{\odot}$. The primary nuclei, i.e., the ones with the higher stellar velocity dispersion, tend to have a higher molecular gas mass than the secondary. Most CO-detected nuclei show a compact morphology, with a velocity field consistent with a kpc-scale rotating structure. The inferred hydrogen column densities range between $5\times10^{21} - 2\times10^{23}\rm~cm^{-2}$, but mostly at a few times $10^{22}\rm~cm^{-2}$, in broad agreement with those derived from X-ray spectral analysis. Together with the relatively weak mid-infrared emission, the moderate column density argues against the prevalence of heavily obscured, intrinsically luminous AGNs in these seven systems, but favors a feedback scenario in which AGN activity triggered by a recent pericentric passage of the galaxy pair can expel circumnuclear gas and suppress further SMBH accretion.

astro-ph.GA↗
arXiv2022

Enhanced Star Formation Efficiency in the Central Regions of Nearby Quasars Hosts

We combine Atacama Large Millimeter/submillimeter Array and Multi Unit Spectroscopic Explorer observations tracing the molecular gas, millimeter continuum, and ionized gas emission in six low-redshift ($z \lesssim 0.06$) Palomar-Green quasar host galaxies to investigate their ongoing star formation at $\sim$kpc-scale resolution. The AGN contribution to the cold dust emission and the optical emission-line flux is carefully removed to derive spatial distributions of the star formation rate (SFR), which, complemented with the molecular gas data, enables the mapping of the depletion time ($t_{\rm dep}$). We report ubiquitous star formation activity within the quasar host galaxies, with the majority of the ongoing star formation occurring in the galaxy center. The rise of the star formation rate surface density ($Σ_{\rm SFR}$) toward the nucleus is steeper than that observed for the cold molecular gas surface density, reaching values up to $Σ_{\rm SFR} \approx 0.15-0.80\,M_\odot\,$yr$^{-1}\,$kpc$^{-2}$. The gas in the nuclear regions is converted into stars at a shortened depletion time ($t_{\rm dep} \approx 0.2-2.0\,$Gyr), suggesting that those zones can be deemed as starbursts. At large galactocentric radius, we find that the ongoing star formation takes place within spiral arms or H$\,$II region complexes, with an efficiency comparable to that reported for nearby inactive spirals ($t_{\rm dep} \approx 1.8\,$Gyr). We find no evidence of star formation activity shutoff in the PG quasar host galaxies. On the contrary, these observations shed light on how the central environments of galaxies hosting actively accreting supermassive black holes builds up stellar mass.

astro-ph.GA↗
arXiv2022

The X-shaped radio galaxy J0725+5835 is associated with an AGN pair

X-shaped radio galaxies (XRGs) are those that exhibit two pairs of unaligned radio lobes (main radio lobes and "wings"), one of the promising models for the peculiar morphology is jet re-orientation. To clarify it, we conducted the European VLBI Network (EVN) 5 GHz observation of an XRG J0725+5835, which resembles the archetypal binary AGNs 0402+379 in radio morphology but it is larger in angular size. In our observation, two milliarcsec (mas) scale radio components with non-thermal radio emission are detected, each of them coincides with an optical counterpart with similar photometric redshift and (optical and infrared) magnitude, corresponding to dual active nuclei. Furthermore, with the improved VLA images, we find a bridge between the two radio cores and a jet bending in the region surrounding the companion galaxy, which further supports the interplay between the main and companion galaxies. In addition, we also report the discovery of an arcsec-scale jet in the companion. Given the projected separation of $\sim100$ kpc between the main and companion galaxies, XRG J0725+5835 is likely associated with a dual jetted-AGN system. In both EVN and VLA observations, we find signatures that the jet is changing its direction, which is likely responsible for the X-shaped morphology. On the origin of jet re-orientation, several scenarios are discussed.

astro-ph.GA↗