John F. Wu
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View article: Improving Posterior Inference of Galaxy Properties with Image-Based Conditional Flow Matching
Improving Posterior Inference of Galaxy Properties with Image-Based Conditional Flow Matching Open
Estimating physical properties of galaxies from wide-field surveys remains a central challenge in astrophysics. While spectroscopy provides precise measurements, it is observationally expensive, and photometry discards morphological inform…
View article: How Does Feedback Affect the Star Formation Histories of Galaxies?
How Does Feedback Affect the Star Formation Histories of Galaxies? Open
Star formation in galaxies is regulated by the interplay of a range of processes that shape the multiphase gas in the interstellar and circumgalactic media. Using the Cosmology and Astrophysics with MachinE Learning Simulations (CAMELS) su…
View article: How does feedback affect the star formation histories of galaxies?
How does feedback affect the star formation histories of galaxies? Open
Star formation in galaxies is regulated by the interplay of a range of processes that shape the multiphase gas in the interstellar and circumgalactic media. Using the CAMELS suite of cosmological simulations, we study the effects of varyin…
View article: ALMA Lensing Cluster Survey: Physical Characterization of Near-infrared-dark Intrinsically Faint ALMA Sources at <i>z</i> = 2–4
ALMA Lensing Cluster Survey: Physical Characterization of Near-infrared-dark Intrinsically Faint ALMA Sources at <i>z</i> = 2–4 Open
We present results from Atacama Large Millimeter/submillimeter Array (ALMA) spectral line-scan observations at 3 mm and 2 mm bands of three near-infrared-dark (NIR-dark) galaxies behind two massive lensing clusters MACS J0417.5-1154 and RX…
View article: Looking at the Distant Universe with the MeerKAT Array: The H <scp>i</scp> Mass Function in the Local Universe
Looking at the Distant Universe with the MeerKAT Array: The H <span>i</span> Mass Function in the Local Universe Open
We present measurements of the neutral atomic hydrogen (H i ) mass function (H i MF) and cosmic H i density (Ω H I ) at 0 ≤ z ≤ 0.088 from the Looking at the Distant Universe with MeerKAT Array (LADUMA) survey. Using LADUMA Data Release 1 …
View article: Insights into Galaxy Evolution from Interpretable Sparse Feature Networks
Insights into Galaxy Evolution from Interpretable Sparse Feature Networks Open
Galaxy appearances reveal the physics of how they formed and evolved. Machine learning (ML) models can now exploit galaxies’ information-rich morphologies to predict physical properties directly from image cutouts. Learning the relationshi…
View article: Research on the Overall Design and Water Entry Simulation of Cross-Media Unmanned Underwater Vehicles
Research on the Overall Design and Water Entry Simulation of Cross-Media Unmanned Underwater Vehicles Open
Novel cross-media vehicles can operate efficiently in different media where water entry is a critical process. In this paper, a water–air cross-media unmanned vehicle is designed and its hydrodynamic characteristics during water entry are …
View article: Insights on Galaxy Evolution from Interpretable Sparse Feature Networks
Insights on Galaxy Evolution from Interpretable Sparse Feature Networks Open
Galaxy appearances reveal the physics of how they formed and evolved. Machine learning models can now exploit galaxies' information-rich morphologies to predict physical properties directly from image cutouts. Learning the relationship bet…
View article: Looking At the Distant Universe with the MeerKAT Array: the HI Mass Function in the Local Universe
Looking At the Distant Universe with the MeerKAT Array: the HI Mass Function in the Local Universe Open
We present measurements of the neutral atomic hydrogen (HI) mass function (HIMF) and cosmic HI density ($Ω_{\rm HI}$) at $0 \leq z \leq 0.088$ from the Looking at the Distant Universe with MeerKAT Array (LADUMA) survey. Using LADUMA Data R…
View article: The Multimodal Universe: 100 TB of Machine Learning Ready Astronomical Data
The Multimodal Universe: 100 TB of Machine Learning Ready Astronomical Data Open
We present the Multimodal Universe , a new framework collating over 100 TB of multimodal astronomical data for its first release, spanning images, spectra, time series, tabular and hyper-spectral data. This unified collection enables a wid…
View article: pathfinder: A Semantic Framework for Literature Review and Knowledge Discovery in Astronomy
pathfinder: A Semantic Framework for Literature Review and Knowledge Discovery in Astronomy Open
The exponential growth of astronomical literature poses significant challenges for researchers navigating and synthesizing general insights or even domain-specific knowledge. We present pathfinder , a machine learning framework designed to…
View article: Estimating Dark Matter Halo Masses in Simulated Galaxy Clusters with Graph Neural Networks
Estimating Dark Matter Halo Masses in Simulated Galaxy Clusters with Graph Neural Networks Open
Galaxies grow and evolve in dark matter halos. Because dark matter is not visible, galaxies' halo masses ($\rm{M}_{\rm{halo}}$) must be inferred indirectly. We present a graph neural network (GNN) model for predicting $\rm{M}_{\rm{halo}}$ …
View article: ALMA Lensing Cluster Survey: Dust mass measurements as a function of redshift, stellar-mass and star formation rate, from z=1 to z=5
ALMA Lensing Cluster Survey: Dust mass measurements as a function of redshift, stellar-mass and star formation rate, from z=1 to z=5 Open
Understanding the dust content of galaxies, its evolution with redshift and its relationship to stars and star formation is fundamental for our understanding of galaxy evolution. Using the ALMA Lensing Cluster Survey (ALCS) wide-area band-…
View article: How the Galaxy–Halo Connection Depends on Large-scale Environment
How the Galaxy–Halo Connection Depends on Large-scale Environment Open
We investigate the connection between galaxies, dark matter halos, and their large-scale environments at z = 0 with Illustris TNG300 hydrodynamic simulation data. We predict stellar masses from subhalo properties to test two types of machi…
View article: The SAGA Survey. V. Modeling Satellite Systems around Milky Way–Mass Galaxies with Updated UniverseMachine
The SAGA Survey. V. Modeling Satellite Systems around Milky Way–Mass Galaxies with Updated UniverseMachine Open
Environment plays a critical role in shaping the assembly of low-mass galaxies. Here, we use the U niverse M achine (UM) galaxy–halo connection framework and Data Release 3 of the Satellites Around Galactic Analogs (SAGA) Survey to place d…
View article: The SAGA Survey. III. A Census of 101 Satellite Systems around Milky Way–mass Galaxies
The SAGA Survey. III. A Census of 101 Satellite Systems around Milky Way–mass Galaxies Open
We present Data Release 3 (DR3) of the Satellites Around Galactic Analogs (SAGA) Survey, a spectroscopic survey characterizing satellite galaxies around Milky Way (MW)-mass galaxies. The SAGA Survey DR3 includes 378 satellites identified a…
View article: The SAGA Survey. IV. The Star Formation Properties of 101 Satellite Systems around Milky Way–mass Galaxies
The SAGA Survey. IV. The Star Formation Properties of 101 Satellite Systems around Milky Way–mass Galaxies Open
We present the star-forming properties of 378 satellite galaxies around 101 Milky Way analogs in the Satellites Around Galactic Analogs (SAGA) Survey, focusing on the environmental processes that suppress or quench star formation. In the S…
View article: Basic Data Processing of Gravitational Waves
Basic Data Processing of Gravitational Waves Open
This paper provides a comprehensive guide to gravitational wave data processing, with a particular focus on signal generation, noise modeling, and optimization techniques. Beginning with an introduction to gravitational waves and the detec…
View article: Photometric Redshifts Probability Density Estimation from Recurrent Neural Networks in the DECam Local Volume Exploration Survey Data Release 2
Photometric Redshifts Probability Density Estimation from Recurrent Neural Networks in the DECam Local Volume Exploration Survey Data Release 2 Open
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 …
View article: pathfinder: A Semantic Framework for Literature Review and Knowledge Discovery in Astronomy
pathfinder: A Semantic Framework for Literature Review and Knowledge Discovery in Astronomy Open
The exponential growth of astronomical literature poses significant challenges for researchers navigating and synthesizing general insights or even domain-specific knowledge. We present Pathfinder, a machine learning framework designed to …
View article: Disentangling Dense Embeddings with Sparse Autoencoders
Disentangling Dense Embeddings with Sparse Autoencoders Open
Sparse autoencoders (SAEs) have shown promise in extracting interpretable features from complex neural networks. We present one of the first applications of SAEs to dense text embeddings from large language models, demonstrating their effe…
View article: Predicting dark matter halo masses from simulated galaxy images and environments
Predicting dark matter halo masses from simulated galaxy images and environments Open
Galaxies are theorized to form and co-evolve with their dark matter halos, such that their stellar masses and halo masses should be well-correlated. However, it is not known whether other observable galaxy features, such as their morpholog…
View article: ALMA Lensing Cluster Survey: Physical characterization of near-infrared-dark intrinsically faint ALMA sources at z=2-4
ALMA Lensing Cluster Survey: Physical characterization of near-infrared-dark intrinsically faint ALMA sources at z=2-4 Open
We present results from Atacama Large Millimeter/submillimeter Array (ALMA) spectral line-scan observations at 3-mm and 2-mm bands of three near-infrared-dark (NIR-dark) galaxies behind two massive lensing clusters MACS J0417.5-1154 and RX…
View article: PHANGS-ML: Dissecting Multiphase Gas and Dust in Nearby Galaxies Using Machine Learning
PHANGS-ML: Dissecting Multiphase Gas and Dust in Nearby Galaxies Using Machine Learning Open
The PHANGS survey uses Atacama Large Millimeter/submillimeter Array, Hubble Space Telescope, Very Large Telescope, and JWST to obtain an unprecedented high-resolution view of nearby galaxies, covering millions of spatially independent regi…
View article: Designing an Evaluation Framework for Large Language Models in Astronomy Research
Designing an Evaluation Framework for Large Language Models in Astronomy Research Open
Large Language Models (LLMs) are shifting how scientific research is done. It is imperative to understand how researchers interact with these models and how scientific sub-communities like astronomy might benefit from them. However, there …
View article: Katachi (形): Decoding the Imprints of Past Star Formation on Present-day Morphology in Galaxies with Interpretable CNNs*
Katachi (形): Decoding the Imprints of Past Star Formation on Present-day Morphology in Galaxies with Interpretable CNNs* Open
The physical processes responsible for shaping how galaxies form and quench over time leave imprints on both the spatial (galaxy morphology) and temporal (star formation history; SFH) tracers that we use to study galaxies. While the morpho…
View article: The SAGA Survey. V. Modeling Satellite Systems around Milky Way-mass Galaxies with Updated UniverseMachine
The SAGA Survey. V. Modeling Satellite Systems around Milky Way-mass Galaxies with Updated UniverseMachine Open
Environment plays a critical role in shaping the assembly of low-mass galaxies. Here, we use the UniverseMachine (UM) galaxy-halo connection framework and the Data Release 3 of the Satellites Around Galactic Analogs (SAGA) Survey to place …
View article: The SAGA Survey. IV. The Star Formation Properties of 101 Satellite Systems around Milky Way-mass Galaxies
The SAGA Survey. IV. The Star Formation Properties of 101 Satellite Systems around Milky Way-mass Galaxies Open
We present the star-forming properties of 378 satellite galaxies around 101 Milky Way analogs in the Satellites Around Galactic Analogs (SAGA) Survey, focusing on the environmental processes that suppress or quench star formation. In the S…
View article: The SAGA Survey. III. A Census of 101 Satellite Systems around Milky Way-mass Galaxies
The SAGA Survey. III. A Census of 101 Satellite Systems around Milky Way-mass Galaxies Open
We present Data Release 3 (DR3) of the Satellites Around Galactic Analogs (SAGA) Survey, a spectroscopic survey characterizing satellite galaxies around Milky Way (MW)-mass galaxies. The SAGA Survey DR3 includes 378 satellites identified a…
View article: Katachi: Decoding the Imprints of Past Star Formation on Present Day Morphology in Galaxies with Interpretable CNNs
Katachi: Decoding the Imprints of Past Star Formation on Present Day Morphology in Galaxies with Interpretable CNNs Open
The physical processes responsible for shaping how galaxies form and quench over time leave imprints on both the spatial (galaxy morphology) and temporal (star formation history; SFH) tracers that we use to study galaxies. While the morpho…