arXiv subjects

Lingyu Wang

Publications and source records attributed to Lingyu Wang.

At least 37 records · Page 2Linked to original sources

arXiv2023

Characterisation of Herschel-selected strong lens candidates through HST and sub-mm/mm observations

We have carried out HST snapshot observations at 1.1 $μ$m of 281 candidate strongly lensed galaxies identified in the wide-area extragalactic surveys conducted with the Herschel space observatory. Our candidates comprise systems with flux densities at $500\,μ$m$ S_{500}\geq 80$ mJy. We model and subtract the surface brightness distribution for 130 systems, where we identify a candidate for the foreground lens candidate. After combining visual inspection, archival high-resolution observations, and lens subtraction, we divide the systems into different classes according to their lensing likelihood. We confirm 65 systems to be lensed. Of these, 30 are new discoveries. We successfully perform lens modelling and source reconstruction on 23 systems, where the foreground lenses are isolated galaxies and the background sources are detected in the HST images. All the systems are successfully modelled as a singular isothermal ellipsoid. The Einstein radii of the lenses and the magnifications of the background sources are consistent with previous studies. However, the background source circularised radii (between 0.34 kpc and 1.30 kpc) are $\sim$3 times smaller than the ones measured in the sub-mm/mm for a similarly selected and partially overlapping sample. We compare our lenses with those in the SLACS survey, confirming that our lens-independent selection is more effective at picking up fainter and diffuse galaxies and group lenses. This sample represents the first step towards characterising the near-IR properties and stellar masses of the gravitationally lensed dusty star-forming galaxies.

astro-ph.GA↗

arXiv2023

Observational evidence for cosmological coupling of black holes and its implications for an astrophysical source of dark energy

Observations have found black holes spanning ten orders of magnitude in mass across most of cosmic history. The Kerr black hole solution is however provisional as its behavior at infinity is incompatible with an expanding universe. Black hole models with realistic behavior at infinity predict that the gravitating mass of a black hole can increase with the expansion of the universe independently of accretion or mergers, in a manner that depends on the black hole's interior solution. We test this prediction by considering the growth of supermassive black holes in elliptical galaxies over $0<z\lesssim2.5$. We find evidence for cosmologically coupled mass growth among these black holes, with zero cosmological coupling excluded at 99.98% confidence. The redshift dependence of the mass growth implies that, at $z\lesssim7$, black holes contribute an effectively constant cosmological energy density to Friedmann's equations. The continuity equation then requires that black holes contribute cosmologically as vacuum energy. We further show that black hole production from the cosmic star formation history gives the value of $Ω_Λ$ measured by Planck while being consistent with constraints from massive compact halo objects. We thus propose that stellar remnant black holes are the astrophysical origin of dark energy, explaining the onset of accelerating expansion at $z \sim 0.7$.

astro-ph.CO↗

arXiv2022

A Preferential Growth Channel for Supermassive Black Holes in Elliptical Galaxies at z<2

The assembly of stellar and supermassive black hole (SMBH) mass in elliptical galaxies since $z\sim1$ can help to diagnose the origins of locally-observed correlations between SMBH mass and stellar mass. We therefore construct three samples of elliptical galaxies, one at $z\sim0$ and two at $0.7\lesssim z \lesssim2.5$, and quantify their relative positions in the $M_{BH}-M_*$ plane. Using a Bayesian analysis framework, we find evidence for translational offsets in both stellar mass and SMBH mass between the local sample and both higher redshift samples. The offsets in stellar mass are small, and consistent with measurement bias, but the offsets in SMBH mass are much larger, reaching a factor of seven between $z\sim1$ and $z\sim0$. The magnitude of the SMBH offset may also depend on redshift, reaching a factor of $\sim20$ at $z\sim 2$. The result is robust against variation in the high and low redshift samples and changes in the analysis approach. The magnitude and redshift evolution of the offset are challenging to explain in terms of selection and measurement biases. We conclude that either there is a physical mechanism that preferentially grows SMBHs in elliptical galaxies at $z\lesssim 2$, or that selection and measurement biases are both underestimated, and depend on redshift.

astro-ph.GA↗

arXiv2022

Energy-Sensitive Trajectory Design and Restoration Areas Allocation for UAV-Enabled Grassland Restoration

Grassland restoration is a critical means to safeguard grassland ecological degradation. To alleviate the extensive human labors and boost the restoration efficiency, UAV is promising for its fully automatic capability yet still waits to be exploited. This paper progresses this emerging technology by explicitly considering the realistic constraints of the UAV and the grassland degradation while planning the grassland restoration. To this end, the UAV-enabled restoration process is first mathematically modeled as the maximization of restoration areas of the UAV under the limited battery energy of UAV, the grass seeds weight, the number of restored areas, and the corresponding sizes. Then we analyze that, by considering these constraints, this original problem emerges two conflict objectives, namely the shortest flight path and the optimal areas allocation. As a result, the maximization of restoration areas turns out to be a composite of a trajectory design problem and an areas allocation problem that are highly coupled. From the perspective of optimization, this requires solving two NP-hard problems of both the traveling salesman problem (TSP) and the multidimensional knapsack problem (MKP) at the same time. To tackle this complex problem, we propose a cooperative optimization algorithm, called CHAPBILM, to solve those two problems interlacedly by utilizing the interdependencies between them. Multiple simulations verify the conflicts between the trajectory design and areas allocation. The effectiveness of the cooperative optimization algorithm is also supported by the comparisons with traditional optimization methods which do not utilize the interdependencies between the two problems. As a result, the proposed algorithm successfully solves the multiple simulation instances in a near-optimal way.

cs.NE↗

arXiv2022

DPOAD: Differentially Private Outsourcing of Anomaly Detection through Iterative Sensitivity Learning

Outsourcing anomaly detection to third-parties can allow data owners to overcome resource constraints (e.g., in lightweight IoT devices), facilitate collaborative analysis (e.g., under distributed or multi-party scenarios), and benefit from lower costs and specialized expertise (e.g., of Managed Security Service Providers). Despite such benefits, a data owner may feel reluctant to outsource anomaly detection without sufficient privacy protection. To that end, most existing privacy solutions would face a novel challenge, i.e., preserving privacy usually requires the difference between data entries to be eliminated or reduced, whereas anomaly detection critically depends on that difference. Such a conflict is recently resolved under a local analysis setting with trusted analysts (where no outsourcing is involved) through moving the focus of differential privacy (DP) guarantee from "all" to only "benign" entries. In this paper, we observe that such an approach is not directly applicable to the outsourcing setting, because data owners do not know which entries are "benign" prior to outsourcing, and hence cannot selectively apply DP on data entries. Therefore, we propose a novel iterative solution for the data owner to gradually "disentangle" the anomalous entries from the benign ones such that the third-party analyst can produce accurate anomaly results with sufficient DP guarantee. We design and implement our Differentially Private Outsourcing of Anomaly Detection (DPOAD) framework, and demonstrate its benefits over baseline Laplace and PainFree mechanisms through experiments with real data from different application domains.

cs.CR↗

arXiv2022

Diagnosing the interstellar medium of galaxies with far-infrared emission lines II. [C II], [O I], [O III], [N II] and [N III] up to z=6

Gas cooling processes in the interstellar medium (ISM) are key to understanding how star-formation processes occur in galaxies. Far-infrared (FIR) fine-structure emission lines can be used as a tool to understand the gas conditions and trace the different phases of the ISM. We model the most important far-infrared (FIR) emission lines throughout cosmic time back to $z=6$ with cosmological hydrodynamical simulations. We study how different physical parameters, such as the interstellar radiation field (ISRF) and metallicity, impact the ISM phases traced by FIR line luminosities and connect those with the star-formation rate (SFR). We implement a physically motivated multi-phase model of the ISM by post-processing EAGLE cosmological simulation with Cloudy look-up tables. In this model, we assume four phases of the ISM: dense molecular gas, neutral atomic gas, diffuse ionised gas (DIG) and HII regions. Our model shows good agreement with the observed luminosity-SFR relation up to $z=6$ in the FIR emission lines analysed and we also provide linear fits. Our predictions also agree with observations in terms of diagnostic diagrams involving various line ratios. We find that [C II] is the best SFR tracer of the FIR lines even though it traces multiple ISM phases, while [O III] and [N II] can be used to understand the DIG-HII balance in the ionised phase. In addition, line ratios like [C II]/[O III] and [N II/[O I] are useful to trace parameters such as ISRF, metallicity and specific star-formation rate. These results help to interpret observations of FIR line emission from the local Universe to high-$z$ galaxies.

astro-ph.GA↗

arXiv2022

Stellar and black hole assembly in z<0.3 infrared-luminous mergers: intermittent starbursts vs. super-Eddington accretion

We study stellar and black hole mass assembly in a sample of 42 infrared-luminous galaxy mergers at z<0.3 by combining results from radiative transfer modelling with archival measures of molecular gas and black hole mass. The ratios of stellar mass, molecular gas mass, and black hole mass to each other are consistent with those of massive gas-rich galaxies at z<0.3. The advanced mergers may show increased black hole mass to stellar mass ratios, consistent with the transition from AGN to ellipticals and implying substantial black hole mass growth over the course of the merger. Star formation rates are enhanced relative to the local main sequence, by factors of ~100 in the starburst and ~1.8 in the host. The starburst star formation rates appear distinct to star formation in the main sequence at all redshifts up to at least z~5. Starbursts may prefer late-stage mergers, but are observed at any merger stage. We do not find evidence that the starbursts in these low-redshift systems substantially increase the total stellar mass, with a soft upper limit on the stellar mass increase from starburst activity of about a factor of two. In contrast, 12 objects show evidence for super-Eddington accretion, associated with late-stage mergers, suggesting that many AGN in infrared-luminous mergers go through a super-Eddington phase. The super-Eddington phase may increase black hole mass by up to an order of magnitude at an accretion efficiency of 42+/-33% over a period of 44+/-22Myr. Our results imply that super-Eddington accretion is an important black hole growth channel in infrared-luminous galaxies at all redshifts.

astro-ph.GA↗

arXiv2022

Galaxy And Mass Assembly (GAMA): Self-Organizing Map Application on Nearby Galaxies

Galaxy populations show bimodality in a variety of properties: stellar mass, colour, specific star-formation rate, size, and Sérsic index. These parameters are our feature space. We use an existing sample of 7556 galaxies from the Galaxy and Mass Assembly (GAMA) survey, represented using five features and the K-means clustering technique, showed that the bimodalities are the manifestation of a more complex population structure, represented by between 2 and 6 clusters. Here we use Self Organizing Maps (SOM), an unsupervised learning technique which can be used to visualize similarity in a higher dimensional space using a 2D representation, to map these five-dimensional clusters in the feature space onto two-dimensional projections. To further analyze these clusters, using the SOM information, we agree with previous results that the sub-populations found in the feature space can be reasonably mapped onto three or five clusters. We explore where the "green valley" galaxies are mapped onto the SOM, indicating multiple interstitial populations within the green valley population. Finally, we use the projection of the SOM to verify whether morphological information provided by GalaxyZoo users, for example, if features are visible, can be mapped onto the SOM-generated map. Voting on whether galaxies are smooth, likely ellipticals, or "featured" can reasonably be separated but smaller morphological features (bar, spiral arms) can not. SOMs promise to be a useful tool to map and identify instructive sub-populations in multidimensional galaxy survey feature space, provided they are large enough.

astro-ph.GA↗

arXiv2021

Galaxy and Mass Assembly (GAMA): The Weak Environmental Dependence of Quasar Activity at 0.1<z<0.35

Understanding the connection between nuclear activity and galaxy environment remains critical in constraining models of galaxy evolution. By exploiting extensive catalogued data from the Galaxy and Mass Assembly (GAMA) survey, we identify a representative sample of 205 quasars at 0.1 < z < 0.35 and establish a comparison sample of galaxies, closely matched to the quasar sample in terms of both stellar mass and redshift. On scales <1 Mpc, the galaxy number counts and group membership of quasars appear entirely consistent with those of the matched galaxy sample. Despite this, we find that quasars are ~1.5 times more likely to be classified as the group center, indicating a potential link between quasar activity and cold gas flows or galaxy interactions associated with rich group environments. On scales of ~a few Mpc, the clustering strength of both samples are statistically consistent and beyond 10 Mpc we find no evidence that quasars trace large scale structures any more than the galaxy control sample. Both populations are found to prefer intermediate-density sheets and filaments to either very high- or very low- density environments. This weak dependence of quasar activity on galaxy environment supports a paradigm in which quasars represent a phase in the lifetime of all massive galaxies and in which secular processes and a group-centric location are the dominant trigger of quasars at low redshift.

astro-ph.GA↗

arXiv2021

The viewing angle in AGN SED models, a data-driven analysis

The validity of the unified active galactic nuclei (AGN) model has been challenged in the last decade, especially when different types of AGNs are considered to only differ in the viewing angle to the torus. We aim to assess the importance of the viewing angle in classifying different types of Seyfert galaxies in spectral energy distribution (SED) modelling. We retrieve photometric data from publicly available astronomical databases: CDS and NED, to model SEDs with X-CIGALE in a sample of 13 173 Seyfert galaxies located at redshift range from $z=0$ to $z=3.5$, with a median redshift of $z\approx0.2$. We assess whether the estimated viewing angle from the SED models reflects different Seyfert classifications. Two AGN models with either a smooth or clumpy torus structure are adopted in this paper. We find that the viewing angle in Type-1 AGNs is better constrained than in Type-2 AGNs. Limiting the viewing angles representing these two types of AGNs do not affect the physical parameter estimates such as star-formation rate (SFR) or AGN fractional contribution ($f_{\rm{AGN}}$). In addition, the viewing angle is not the most discriminating physical parameter to differentiate Seyfert types. We suggest that the observed and intrinsic AGN disc luminosity can: i) be used in $z<0.5$ studies to distinguish between Type-1 and Type-2 AGNs, and ii) explain the probable evolutionary path between these AGN types. Finally, we propose the use of X-CIGALE for AGN galaxy classification tasks. All data from the 13 173 SED fits are available at https://doi.org/10.5281/zenodo.5221764

astro-ph.GA↗

arXiv2021

Multi-wavelength scaling relations in galaxy groups: a detailed comparison of GAMA and KiDS observations to BAHAMAS simulations

We study the scaling relations between the baryonic content and total mass of groups of galaxies, as these systems provide a unique way to examine the role of non-gravitational processes in structure formation. Using Planck and ROSAT data, we conduct detailed comparisons of the stacked thermal Sunyaev-Zel'dovich (tSZ) and X-ray scaling relations of galaxy groups found in the Galaxy And Mass Assembly (GAMA) survey and the BAHAMAS hydrodynamical simulation. We use weak gravitational lensing data from the Kilo Degree Survey (KiDS) to determine the average halo mass of the studied systems. We analyse the simulation in the same way, using realistic weak lensing, X-ray, and tSZ synthetic observations. Furthermore, to keep selection biases under control, we employ exactly the same galaxy selection and group identification procedures to the observations and simulation. Applying this comparison, we find that the simulations reproduce the richness, size, and stellar mass functions of GAMA groups, as well as the stacked weak lensing and tSZ signals in bins of group stellar mass. However, the simulations predict X-ray luminosities that are higher than observed for this optically-selected group sample. As the same simulations were previously shown to match the luminosities of X-ray-selected groups, this suggests that X-ray-selected systems may form a biased subset. Finally, we demonstrate that our observational processing of the X-ray and tSZ signals is free of significant biases. We find that our optical group selection procedure has, however, some room for improvement.

astro-ph.CO↗

arXiv2021

Mid-IR cosmological spectrophotometric surveys from space: Measuring AGN and star formation at the Cosmic Noon with a SPICA-like mission

We use the SPace Infrared telescope for Cosmology and Astrophysics (SPICA) project as a template to demonstrate how deep spectrophotometric surveys covering large cosmological volumes over extended fields (1-15 square degrees) with a mid-IR imaging spectrometer (17-36 micron) in conjunction with deep 70 micron photometry with a far-IR camera, at wavelengths which are not affected by dust extinction can answer the most crucial questions in current galaxy evolution studies. A SPICA-like mission will be able for the first time to provide an unobscured three dimensional (3-D, i.e. x, y and redshift z) view of galaxy evolution back to an age of the Universe of less than ~2 Gyrs, in the mid-IR rest-frame. This survey strategy will produce a full census of the Star formation Rate (SFR) in the Universe, using Polycyclic Aromatic Hydrocarbons (PAH) bands and fine-structure ionic lines, reaching the characteristic knee of the galaxy luminosity function, where the bulk of the population is distributed, at any redshift up to z ~3.5. Deep follow-up pointed spectroscopic observations with grating spectrometers { onboard the satellite}, across the full IR spectral range (17-210 micron), would simultaneously measure Black Hole Accretion Rate (BHAR), from high-ionization fine-structure lines, and SFR, from PAH and low- to mid-ionization lines in thousands of galaxies from solar to low metallicities, down to the knee of their luminosity functions. The analysis of the resulting atlas of IR spectra will reveal the physical processes at play in evolving galaxies across cosmic time, especially its heavily dust-embedded phase during the activity peak at the cosmic noon (z ~1-3), through IR emission lines and features that are insensitive to the dust obscuration.

astro-ph.GA↗

arXiv2020

Diagnosing the interstellar medium of galaxies with far-infrared emission lines I. The [C II] 158 microns line at z~0

Atomic fine structure lines have been detected in the local Universe and at high redshifts over the past decades. The [C II] emission line at 158 $μ$m is an important observable as it provides constraints on the interstellar medium (ISM) cooling processes. We develop a physically motivated framework to simulate the production of far-infrared line emission from galaxies in a cosmological context. This first paper sets out our methodology and describes its first application, simulating the [C II] 158 $μ$m line emission in the local Universe. We combine the output from EAGLE cosmological hydrodynamical simulations with a multi-phase model of the ISM. Gas particles are divided into three phases: dense molecular gas, neutral atomic gas and diffuse ionised gas (DIG). We estimate the [C II] line emission from the three phases using a set of Cloudy cooling tables. Our results agree with previous findings regarding the contribution of these three ISM phases to the [C II] emission. Our model shows good agreement with the observed ${\rm L_{[C II]}}$-star formation rate (SFR) relation in the local Universe within 0.4 dex scatter. The fractional contribution to the [C II] line from different ISM phases depends on the total SFR and metallicity. The neutral gas phase dominates the [C II] emission in galaxies with $\rm{SFR}\sim0.01$-$1\,\rm{M_{\odot}}\,\rm{yr^{-1}}$, but the ionised phase dominates at lower SFRs. Galaxies above solar metallicity exhibit lower ${\rm L_{[C II]}}$/SFR ratios for the neutral phase. In comparison, the ${\rm L_{[C II]}}$/SFR ratio in the DIG is stable when metallicity varies. We suggest that the reduced size of the neutral clouds, caused by increased SFRs, is the likely cause for the ${\rm L_{[C II]}}$ deficit at high infrared luminosities, although EAGLE simulations do not reach these luminosities at $z=0$.

astro-ph.GA↗

arXiv2020

R$^2$DP: A Universal and Automated Approach to Optimizing the Randomization Mechanisms of Differential Privacy for Utility Metrics with No Known Optimal Distributions

Differential privacy (DP) has emerged as a de facto standard privacy notion for a wide range of applications. Since the meaning of data utility in different applications may vastly differ, a key challenge is to find the optimal randomization mechanism, i.e., the distribution and its parameters, for a given utility metric. Existing works have identified the optimal distributions in some special cases, while leaving all other utility metrics (e.g., usefulness and graph distance) as open problems. Since existing works mostly rely on manual analysis to examine the search space of all distributions, it would be an expensive process to repeat such efforts for each utility metric. To address such deficiency, we propose a novel approach that can automatically optimize different utility metrics found in diverse applications under a common framework. Our key idea that, by regarding the variance of the injected noise itself as a random variable, a two-fold distribution may approximately cover the search space of all distributions. Therefore, we can automatically find distributions in this search space to optimize different utility metrics in a similar manner, simply by optimizing the parameters of the two-fold distribution. Specifically, we define a universal framework, namely, randomizing the randomization mechanism of differential privacy (R$^2$DP), and we formally analyze its privacy and utility. Our experiments show that R$^2$DP can provide better results than the baseline distribution (Laplace) for several utility metrics with no known optimal distributions, whereas our results asymptotically approach to the optimality for utility metrics having known optimal distributions. As a side benefit, the added degree of freedom introduced by the two-fold distribution allows R$^2$DP to accommodate the preferences of both data owners and recipients.

cs.CR↗

arXiv2019

Galaxy And Mass Assembly (GAMA): Properties and evolution of red spiral galaxies

We use multi-wavelength data from the Galaxy and Mass Assembly (GAMA) survey to explore the cause of red optical colours in nearby (0.002 = 47% of all spirals in our sample. Furthermore, for a small subsample of our spiral galaxies which are detected in HI, we find that the SFR of gas-rich red spiral galaxies is lower by ~1 dex than their blue counterparts.

astro-ph.GA↗

arXiv2019

Galaxy classification: A machine learning analysis of GAMA catalogue data

We present a machine learning analysis of five labelled galaxy catalogues from the Galaxy And Mass Assembly (GAMA): The SersicCatVIKING and SersicCatUKIDSS catalogues containing morphological features, the GaussFitSimple catalogue containing spectroscopic features, the MagPhys catalogue including physical parameters for galaxies, and the Lambdar catalogue, which contains photometric measurements. Extending work previously presented at the ESANN 2018 conference - in an analysis based on Generalized Relevance Matrix Learning Vector Quantization and Random Forests - we find that neither the data from the individual catalogues nor a combined dataset based on all 5 catalogues fully supports the visual-inspection-based galaxy classification scheme employed to categorise the galaxies. In particular, only one class, the Little Blue Spheroids, is consistently separable from the other classes. To aid further insight into the nature of the employed visual-based classification scheme with respect to physical and morphological features, we present the galaxy parameters that are discriminative for the achieved class distinctions.

astro-ph.GA↗

arXiv2019

The case for a 'sub-millimeter SDSS': a 3D map of galaxy evolution to z~10

The Sloan Digital Sky Survey (SDSS) was revolutionary because of the extraordinary breadth and ambition of its optical imaging and spectroscopy. We argue that a 'sub-millimeter SDSS' - a sensitive large-area imaging+spectroscopic survey in the sub-mm window - will revolutionize our understanding of galaxy evolution in the early Universe. By detecting the thermal dust continuum emission and atomic and molecular line emission of galaxies out to z~10 it will be possible to measure the redshifts, star formation rates, dust and gas content of hundreds of thousands of high-z galaxies down to ~L*. Many of these galaxies will have counterparts visible in the deep optical imaging of the Large Synoptic Survey Telescope. This 3D map of galaxy evolution will span the peak epoch of galaxy formation all the way back to cosmic dawn, measuring the co-evolution of the star formation rate density and molecular gas content of galaxies, tracking the production of metals and charting the growth of large-scale structure.

astro-ph.GA↗

arXiv2019

Deep Learning for Galaxy Mergers in the Galaxy Main Sequence

Starburst galaxies are often found to be the result of galaxy mergers. As a result, galaxy mergers are often believed to lie above the galaxy main sequence: the tight correlation between stellar mass and star formation rate. Here, we aim to test this claim. Deep learning techniques are applied to images from the Sloan Digital Sky Survey to provide visual-like classifications for over 340 000 objects between redshifts of 0.005 and 0.1. The aim of this classification is to split the galaxy population into merger and non-merger systems and we are currently achieving an accuracy of 91.5%. Stellar masses and star formation rates are also estimated using panchromatic data for the entire galaxy population. With these preliminary data, the mergers are placed onto the full galaxy main sequence, where we find that merging systems lie across the entire star formation rate - stellar mass plane.

astro-ph.GA↗