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J. F. Wu

Publications and source records attributed to J. F. Wu.

15 recordsLinked to original sources
arXiv2026

The DECam MAGIC Survey $-$ Mapping the Ancient Galaxy in CaHK: Overview and Summary of Early Science

We present the DECam Mapping the Ancient Galaxy in CaHK (MAGIC) survey, a 54-night NOIRLab Survey Program to image $\gtrsim$5,000$\,$deg$^2$ of the southern hemisphere using a metallicity-sensitive narrow-band filter covering the Ca$\,$ii$\,$H&K lines centered at 3955$\,$A. This filter is installed on the Dark Energy Camera (DECam), mounted on the 4-m NSF Víctor M. Blanco Telescope. The survey reaches typical $10σ$ depths of $\text{mag}_{\text{CaHK}} \approx 22.5$, 3$-$4$\,$mag deeper than comparable surveys in the southern hemisphere. By combining photometry from this Ca$\,$ii$\,$H&K filter with existing DECam $g,r,i$ broadband photometry from the DECam Local Volume Exploration (DELVE) survey, MAGIC is deriving photometric metallicities for red giant branch stars down to the magnitude limit of usable proper motions from Gaia data release 3 (DR3). MAGIC has already imaged $\sim$3,000$\,$deg$^2$, supplemented by other affiliated observing programs that have used this filter to image star clusters, dwarf galaxies, and stellar streams. We overview MAGIC's survey strategy, describe data processing through the derivation of metallicities and photometric distances, and summarize early science results that have been published with this dataset. In addition, we present several new results, including the confirmation of a distant ($>5\,r_h$) member of the Reticulum II ultra-faint dwarf galaxy, on-sky density maps of low-metallicity stars into the distant Milky Way halo ($\sim150\,$kpc) recovering 13/14 ultra-faint dwarf galaxies in the current footprint, and a validation of our initial targeting of extremely metal-poor stars. Collectively, these results demonstrate that the MAGIC dataset enables cutting-edge studies of the faint, low-metallicity regime of the Milky Way and its substructures.

astro-ph.GA↗
arXiv2025

Towards Understanding the Origin of Swift Gamma-Ray Bursts Driven by Magnetars

We analyze a sample of\textit{ Swift} gamma-ray bursts (GRBs) with extended emissions in $γ$-rays and/or X-ray plateaus that may be driven by magnetars. Multi-wavelength data and multi-standards have been adopted to investigate the issue jointly. First, we find that GRBs with both extended emission and X-ray plateau satisfy a three-parameter relation between the luminosity and the end time of X-ray plateaus and the $γ$-ray isotropic energy as $L_X\varpropto T_a^{-1.13}E_{γ,iso}^{0.74}$, which is consistent with that of normal GRBs. Second, we distinguish these GRBs in the plane of magnetic field versus period of neutron star and find that almost all GRBs but GRB 211024B have reasonable periods and majority of them could be powered by magnetars. Third, we standardize the X-ray afterglows with distinct characteristics and find that the standard X-ray light curves with/without plateaus are significantly different. The standardized X-ray plateaus are similar to the mean temporal profile of magnetars. Fourth, it is verified with a K-S test that all types of GRBs except short ones have the similar distributions of redshift and isotropic energy in the observer/rest frame. GRBs with internal plateaus are significantly different from those of normal long GRBs and GRBs with external plateaus and/or extended emissions. Interestingly, the isotropic energy distributions of GRBs with internal and external plateaus are identical with those of short and long GRBs, respectively. Overall, our study can bring solid evidence that the fascinating magnetars could have multi-formation channels to account for not only short but also long GRBs with either internal or external X-ray plateaus as well.

astro-ph.HE↗
arXiv2025

A Unit Enhancement and Guidance Framework for Audio-Driven Avatar Video Generation

Audio-driven human animation technology is widely used in human-computer interaction, and the emergence of diffusion models has further advanced its development. Currently, most methods rely on multi-stage generation and intermediate representations, resulting in long inference time and issues with generation quality in specific foreground regions and audio-motion consistency. These shortcomings are primarily due to the lack of localized fine-grained supervised guidance. To address above challenges, we propose Parts-aware Audio-driven Human Animation, PAHA, a unit enhancement and guidance framework for audio-driven upper-body animation. We introduce two key methods: Parts-Aware Re-weighting (PAR) and Parts Consistency Enhancement (PCE). PAR dynamically adjusts regional training loss weights based on pose confidence scores, effectively improving visual quality. PCE constructs and trains diffusion-based regional audio-visual classifiers to improve the consistency of motion and co-speech audio. Afterwards, we design two novel inference guidance methods for the foregoing classifiers, Sequential Guidance (SG) and Differential Guidance (DG), to balance efficiency and quality respectively. Additionally, we build CNAS, the first public Chinese News Anchor Speech dataset, to advance research and validation in this field. Extensive experimental results and user studies demonstrate that PAHA significantly outperforms existing methods in audio-motion alignment and video-related evaluations. The codes and CNAS dataset will be released upon acceptance.

cs.CV↗
arXiv2024

Photometric Redshifts Probability Density Estimation from Recurrent Neural Networks in the DECam Local Volume Exploration Survey Data Release 2

Photometric wide-field surveys are imaging the sky in unprecedented detail. These surveys face a significant challenge in efficiently estimating galactic photometric redshifts while accurately quantifying associated uncertainties. In this work, we address this challenge by exploring the estimation of Probability Density Functions (PDFs) for the photometric redshifts of galaxies across a vast area of 17,000 square degrees, encompassing objects with a median 5$σ$ point-source depth of $g$ = 24.3, $r$ = 23.9, $i$ = 23.5, and $z$ = 22.8 mag. Our approach uses deep learning, specifically integrating a Recurrent Neural Network architecture with a Mixture Density Network, to leverage magnitudes and colors as input features for constructing photometric redshift PDFs across the whole DECam Local Volume Exploration (DELVE) survey sky footprint. Subsequently, we rigorously evaluate the reliability and robustness of our estimation methodology, gauging its performance against other well-established machine learning methods to ensure the quality of our redshift estimations. Our best results constrain photometric redshifts with the bias of $-0.0013$, a scatter of $0.0293$, and an outlier fraction of $5.1\%$. These point estimates are accompanied by well-calibrated PDFs evaluated using diagnostic tools such as Probability Integral Transform and Odds distribution. We also address the problem of the accessibility of PDFs in terms of disk space storage and the time demand required to generate their corresponding parameters. We present a novel Autoencoder model that reduces the size of PDF parameter arrays to one-sixth of their original length, significantly decreasing the time required for PDF generation to one-eighth of the time needed when generating PDFs directly from the magnitudes.

astro-ph.IM↗
arXiv2024

The cold interstellar medium of a normal sub-$L^\star$ galaxy at the end of reionization

We present the results of a ~60-hr observational campaign with ALMA targeting a spectroscopically confirmed and lensed sub-$L^\star$ galaxy at z=6.07, identified during the ALMA Lensing Cluster Survey (ALCS). We sample the dust continuum emission from rest frame 90 to 370 $μ$m at six different frequencies and set constraining upper limits on the molecular gas line emission and content via CO(7-6) and [CI](2-1) for two lensed images with $μ\gtrsim20$. Complementing these sub-mm observations with deep optical and near-IR photometry and spectroscopy with JWST, we find this galaxy to form stars at a rate of SFR~7 Msun/yr, ~50-70% of which is obscured by dust. This is consistent with what is expected for a $M_\star$~7.5$\times10^{8}$ Msun object by extrapolating the $M_\star$-obscured SFR fraction relation at z<2.5 and with observations at 5<z<7. The dust temperature of ~50K is similar to that of more massive galaxies at similar redshifts, although with large uncertainties and with possible negative gradients. We measure a dust mass of $M_{\rm dust}$~1.5$\times10^6$ Msun and, by combining [CI], [CII], and a dynamical estimate, a gas mass of ~2$\times10^9$ Msun. Their ratio is in good agreement with the predictions from models in the literature. The $M_{\rm dust}$/$M_\star$ fraction of ~0.002 and the young stellar age are consistent with dust production via supernovae. Also, models predict a number density of galaxies with $M_{\rm dust}\sim10^{6}$ Msun at z=6 in agreement with our estimate from the parent ALCS survey. The combination of lensing and multiwavelength observations allow us to probe luminosity regimes up to two orders of magnitude lower than what has been explored so far for field galaxies at similar redshifts. Our results serve as a benchmark for future observations of faint sub-$L^\star$ galaxy population that might have driven the reionization of the Universe. [Abridged]

astro-ph.GA↗
arXiv2023

A dark siren measurement of the Hubble constant using gravitational wave events from the first three LIGO/Virgo observing runs and DELVE

The current and next observation seasons will detect hundreds of gravitational waves (GWs) from compact binary systems coalescence at cosmological distances. When combined with independent electromagnetic measurements, the source redshift will be known, and we will be able to obtain precise measurements of the Hubble constant $H_0$ via the distance-redshift relation. However, most observed mergers are not expected to have electromagnetic counterparts, which prevents a direct redshift measurement. In this scenario, one of the possibilities is to use the dark sirens method that statistically marginalizes over all the potential host galaxies within the GW location volume to provide a probabilistic redshift to the source. Here we presented $H_{0}$ measurements using two new dark sirens compared to previous analyses using DECam data, GW190924$\_$021846 and GW200202$\_$154313. The photometric redshifts of the possible host galaxies of these two events are acquired from the DECam Local Volume Exploration Survey (DELVE) carried out on the Blanco telescope at Cerro Tololo in Chile. The combination of the $H_0$ posterior from GW190924$\_$021846 and GW200202$\_$154313 together with the bright siren GW170817 leads to $H_{0} = 68.84^{+15.51}_{-7.74}\, \rm{km/s/Mpc}$. Including these two dark sirens improves the 68% confidence interval (CI) by 7% over GW170817 alone. This demonstrates that the inclusion of well-localized dark sirens in such analysis improves the precision with which cosmological measurements can be made. Using a sample containing 10 well-localized dark sirens observed during the third LIGO/Virgo observation run, we determine a measurement of $H_{0} = 76.00^{+17.64}_{-13.45}\, \rm{km /s/Mpc}$.

astro-ph.CO↗
arXiv2023

Constructing Impactful Machine Learning Research for Astronomy: Best Practices for Researchers and Reviewers

Machine learning has rapidly become a tool of choice for the astronomical community. It is being applied across a wide range of wavelengths and problems, from the classification of transients to neural network emulators of cosmological simulations, and is shifting paradigms about how we generate and report scientific results. At the same time, this class of method comes with its own set of best practices, challenges, and drawbacks, which, at present, are often reported on incompletely in the astrophysical literature. With this paper, we aim to provide a primer to the astronomical community, including authors, reviewers, and editors, on how to implement machine learning models and report their results in a way that ensures the accuracy of the results, reproducibility of the findings, and usefulness of the method.

astro-ph.IM↗
arXiv2023

Identification of Galaxy-Galaxy Strong Lens Candidates in the DECam Local Volume Exploration Survey Using Machine Learning

We perform a search for galaxy-galaxy strong lens systems using a convolutional neural network (CNN) applied to imaging data from the first public data release of the DECam Local Volume Exploration Survey (DELVE), which contains $\sim 520$ million astronomical sources covering $\sim 4,000$ $\mathrm{deg}^2$ of the southern sky to a $5σ$ point-source depth of $g=24.3$, $r=23.9$, $i=23.3$, and $z=22.8$ mag. Following the methodology of similar searches using DECam data, we apply color and magnitude cuts to select a catalog of $\sim 11$ million extended astronomical sources. After scoring with our CNN, the highest scoring 50,000 images were visually inspected and assigned a score on a scale from 0 (definitely not a lens) to 3 (very probable lens). We present a list of 581 strong lens candidates, 562 of which are previously unreported. We categorize our candidates using their human-assigned scores, resulting in 55 Grade A candidates, 149 Grade B candidates, and 377 Grade C candidates. We additionally highlight eight potential quadruply lensed quasars from this sample. Due to the location of our search footprint in the northern Galactic cap ($b > 10$ deg) and southern celestial hemisphere (${\rm Dec.}<0$ deg), our candidate list has little overlap with other existing ground-based searches. Where our search footprint does overlap with other searches, we find a significant number of high-quality candidates which were previously unidentified, indicating a degree of orthogonality in our methodology. We report properties of our candidates including apparent magnitude and Einstein radius estimated from the image separation.

astro-ph.GA↗
arXiv2021

The DECam Local Volume Exploration Survey: Overview and First Data Release

The DECam Local Volume Exploration survey (DELVE) is a 126-night survey program on the 4-m Blanco Telescope at the Cerro Tololo Inter-American Observatory in Chile. DELVE seeks to understand the characteristics of faint satellite galaxies and other resolved stellar substructures over a range of environments in the Local Volume. DELVE will combine new DECam observations with archival DECam data to cover ~15000 deg$^2$ of high-Galactic-latitude (|b| > 10 deg) southern sky to a 5$σ$ depth of g,r,i,z ~ 23.5 mag. In addition, DELVE will cover a region of ~2200 deg$^2$ around the Magellanic Clouds to a depth of g,r,i ~ 24.5 mag and an area of ~135 deg$^2$ around four Magellanic analogs to a depth of g,i ~ 25.5 mag. Here, we present an overview of the DELVE program and progress to date. We also summarize the first DELVE public data release (DELVE DR1), which provides point-source and automatic aperture photometry for ~520 million astronomical sources covering ~5000 deg$^2$ of the southern sky to a 5$σ$ point-source depth of g=24.3, r=23.9, i=23.3, and z=22.8 mag. DELVE DR1 is publicly available via the NOIRLab Astro Data Lab science platform.

astro-ph.GA↗
arXiv2021

ALMA Lensing Cluster Survey: an ALMA galaxy signposting a MUSE galaxy group at z=4.3 behind 'El Gordo'

We report the discovery of a Multi Unit Spectroscopic Explorer (MUSE) galaxy group at z=4.32 lensed by the massive galaxy cluster ACT-CL J0102-4915 (aka El Gordo) at z=0.87, associated with a 1.2 mm source which is at a 2.07+/-0.88 kpc projected distance from one of the group galaxies. Three images of the whole system appear in the image plane. The 1.2 mm source has been detected within the Atacama Large Millimetre/submillimetre Array (ALMA) Lensing Cluster Survey (ALCS). As this ALMA source is undetected at wavelengths lambda < 2 microns, its redshift cannot be independently determined, however, the three lensing components indicate that it belongs to the same galaxy group at z=4.32. The four members of the MUSE galaxy group have low to intermediate stellar masses (~ 10^7-10^{10} Msun) and star formation rates (SFRs) of 0.4-24 Msun/yr, resulting in high specific SFRs (sSFRs) for two of them, which suggest that these galaxies are growing fast (with stellar-mass doubling times of only ~ 2x10^7 years). This high incidence of starburst galaxies is likely a consequence of interactions within the galaxy group, which is compact and has high velocity dispersion. Based on the magnification-corrected sub-/millimetre continuum flux density and estimated stellar mass, we infer that the ALMA source is classified as an ordinary ultra-luminous infrared galaxy (with associated dust-obscured SFR~200-300 Msun/yr) and lies on the star-formation main sequence. This reported case of an ALMA/MUSE group association suggests that some presumably isolated ALMA sources are in fact signposts of richer star-forming environments at high redshifts.

astro-ph.GA↗
arXiv2016

Galaxy candidates at z ~ 10 in archival data from the Brightest of Reionizing Galaxies (BoRG[z8]) survey

The Wide Field Camera 3 (WFC3) on the Hubble Space Telescope (HST) enabled the search for the first galaxies observed at z ~ 8 - 11 (500 - 700 Myr after the Big Bang). To continue quantifying the number density of the most luminous galaxies (M_AB ~ -22.0) at the earliest epoch observable with HST, we search for z ~ 10 galaxies (F125W-dropouts) in archival data from the Brightest of Reionizing Galaxies (BoRG[z8]) survey, originally designed for detection of z ~ 8 galaxies (F098M-dropouts). By focusing on the deepest 293 arcmin^2 of the data along 62 independent lines of sight, we identify six z ~ 10 candidates satisfying the color selection criteria, detected at S/N > 8 in F160W with M_AB = -22.8 to -21.1 if at z = 10. Three of the six sources, including the two brightest, are in a single WFC3 pointing (~ 4 arcmin^2), suggestive of significant clustering, which is expected from bright galaxies at z ~ 10. However, the two brightest galaxies are too extended to be likely at z ~ 10, and one additional source is unresolved and possibly a brown dwarf. The remaining three candidates have m_AB ~ 26, and given the area and completeness of our search, our best estimate is a number density of sources that is marginally higher but consistent at 2σ with searches in legacy fields. Our study highlights that z ~ 10 searches can yield a small number of candidates, making tailored follow-ups of HST pure-parallel observations viable and effective.

astro-ph.GA↗
arXiv2015

Indirect-direct hybrid-drive work-dominated hotspot ignition for inertial confinement fusion

An indirect-direct hybrid-drive work-dominated hotspot ignition scheme for inertial confinement fusion is proposed: a layered fuel capsule inside a spherical hohlraum with an octahedral symmetry is compressed first by indirect-drive soft-x rays (radiation) and then by direct-drive lasers in last pulse duration. In this scheme, an enhanced shock and a follow-up compression wave for ignition with pressure far greater than the radiation ablation pressure are driven by the direct-drive lasers, and provide large pdV work to the hotspot to perform the work-dominated ignition. The numerical simulations show that the enhanced shock stops the reflections of indirect-drive shock at the main fuel-hotspot interface, and therefore significantly suppresses the hydrodynamic instabilities and asymmetry. Based on the indirect-drive implosion dynamics the hotspot is further compressed and heated by the enhanced shock and follow-up compression wave, resulting in the work-dominated hotspot ignition and burn with a maximal implosion velocity of ~400 km/s and a lower convergence ratio of ~25. The fusion yield of 15 MJ using total laser energy of 1.32 MJ is achieved.

physics.plasm-ph↗
arXiv2006

Hardness Ratio Estimation in Low Counting X-ray Photometry

Hardness ratios are commonly used in X-ray photometry to indicate spectral properties roughly. It is usually defined as the ratio of counts in two different wavebands. This definition, however, is problematic when the counts are very limited. Here we instead define hardness ratio using the $λ$ parameter of Poisson processes, and develop an estimation method via Bayesian statistics. Our Monte Carlo simulations show the validity of our method. Based on this new definition, we can estimate the hydrogen column density for the photoelectric absorption of X-ray spectra in the case of low counting statistics.

astro-ph↗
arXiv2006

Statistical Analysis of Point-like Sources in Chandra Galactic Center Survey

{\it Chandra} Galactic Center Survey detected $\sim 800$ X-ray point-like sources in the $2^{\circ} \times 0.8^{\circ}$ sky region around the Galactic Center. In this paper, we study the spatial and luminosity distributions of these sources according to their spectral properties. Fourteen bright sources detected are used to fit jointly an absorbed power-law model, from which the power-law photon index is determined to be $\sim$2.5. Assuming that all other sources have the same power-law form, the relation between hardness ratio and HI column density $N_H$ is used to estimate the $N_H$ values for all sources. Monte Carlo simulations show that these sources are more likely concentrated in the Galactic center region, rather than distributed throughout the Galactic disk. We also find that the luminosities of the sources are positively correlated with their HI column densities, i.e. a more luminous source has a higher HI column density. From this relation, we suggest that the X-ray luminosity comes from the interaction between an isolated old neutron star and interstellar medium (mainly dense molecular clouds). Using the standard Bondi accretion theory and the statistical information of molecular clouds in the Galactic center, we confirm this positive correlation and calculate the luminosity range in this scenario, which is consistent with the observation ($10^{32}\sim 10^{35}$ ergs s$^{-1}$).

astro-ph↗