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Yicheng Guo

Publications and source records attributed to Yicheng Guo.

At least 19 recordsLinked to original sources
arXiv2026

The Roman eXtreme Deep Field (RXDF)

The Roman eXtreme Deep Field (RXDF) program is one of the five General Astrophysics Survey (GAS) programs approved for observing time with the Nancy Grace Roman Space Telescope in Cycles 1 and 2. It has been allocated 386.41 hours to carry out an imaging survey to AB = 30 mag (5-sigma) over ~140x larger area than the Hubble eXtreme Deep Field (HXDF) full-depth area (ACS+WFC3/IR). The RXDF will cover the full Roman wavelength range with 7 bands, reaching AB = 30 mag in RZYJH, 29 mag in F, and 28 mag in K, over a full-depth area of 678.75 arcmin^2 embedded in a total area of 1,243 arcmin^2, and far exceeding the depths of the Roman Core Community Surveys (CCS). The RXDF is within the Euclid Ultra Deep Field (EUDF) near the North Ecliptic Pole (NEP), a strategic long-term field for generational space facilities, with a wealth of multi-wavelength data including extensive coverage from the James Webb Space Telescope (JWST) NEXUS Treasury program. The observations will cover 3 epochs at a 1-year cadence, each epoch divided into 3 sub-epochs ~10 days apart, enabling time-domain studies on time baselines from ~10 days to over ~2 years. The RXDF is uniquely positioned to address critical questions in reionization, large scale structure (LSS), growth of supermassive black holes (SMBHs), little red dots (LRDs), and high-z supernovae (SNe); the volumes probed by HST+JWST are too small at these extreme depths, and even the deepest CCS tiers are too shallow. In addition to our key objectives, a wealth of additional science will be enabled by engaging the community with our rapidly released datasets, revolutionizing a wide range of science for a lasting legacy. This short document, which is converted from the approved RXDF proposal, aims to provide the community with a summary of the program.

astro-ph.GA↗
arXiv2026

Spiral arms across cosmic time: JWST measurements of the pitch angles of spiral galaxies at $z<3.5$

The properties of spiral galaxies in the early universe remain poorly studied and, as such, little is known about their nature and evolution. We use JWST data to measure the pitch angles of spiral galaxies across cosmic time. Our sample consists of 593 spiral galaxies with stellar masses ($M_*$) greater than $10^{10} M_\odot$ up to $z \sim 3.5$, drawn from the CEERS and JADES surveys. Spiral galaxies are identified by fine-tuning a Zoobot deep-learning model. We use SpArcFiRe to identify spiral arms and measure their pitch angles. We find no significant redshift evolution in the average pitch angle across the full sample. However, in the most massive systems (log$(M_*/M_\odot)=11-12$), spiral arms slightly wind up with time. We show that at $z>1.25$, pitch angle does not correlate with some key internal galaxy properties (stellar mass, bulge mass, disk mass, specific star formation rate [sSFR]). In contrast, at $z<1.25$, pitch angle shows a weak but statistically significant negative correlation with stellar mass, bulge mass, and disk mass, and a positive correlation with sSFR at $z<0.75$. We also find no dependence of pitch angle on the tidal strength applied by nearby companions. These results indicate a transition epoch at $z\sim1$: above this redshift, spiral structures appear to be primarily locally driven and not correlated with global galaxy properties; and below this redshift, spiral arms are regulated by global gravitational potential, consistent with the predictions of the density wave theory.

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arXiv2026

The Importance of Galaxy-Wide Star Formation in Driving Winds at z~1

In this work, we study winds for a representative sample of 86 star-forming galaxies (SFGs) at z~1 with $M_\star = 10^{9.0}-10^{11.5} M_\odot$, by measuring the Mg II line profiles in deep Keck spectra. A total of 50 (58\%) are found to have winds. Unlike local starburst galaxies, the wind detection rate does not exhibit a threshold in star-formation rate (SFR) density $\Sigma_\mathrm{SFR}$ at 0.1 Msun/yr/kpc$^2$, but shows a gradual decline around this value. We find correlations between wind velocity $v_\mathrm{wind}$ and SFR, $\Sigma_\mathrm{SFR}$, and stellar mass, as per previous studies. Intriguingly, the z~1 SFGs appear to follow the same $v_\mathrm{wind}$-SFR relation as local starbursts. A combined fit gives: log $v_\mathrm{wind}$ = 0.16 log SFR + 2.4 (3-sigma significance). This unified relation spans over 4 dex in SFR and agrees with Illustris-TNG. No unified relation is found between $v_\mathrm{wind}$ and stellar mass, sSFR, or $\Sigma_\mathrm{SFR}$. This suggests winds might be most closely associated with SFR. We examine whether winds in z~1 SFGs are driven by their most compact star-forming regions. To do so, we consider whether the relation between $v_\mathrm{wind}$ and the $\Sigma_\mathrm{SFR}$ measured from only these regions is stronger than that for the galaxy-wide $\Sigma_\mathrm{SFR}$. We do not find a stronger correlation, suggesting that winds are most related to $\Sigma_\mathrm{SFR}$ of the entire galaxy. Collectively, these findings suggest a picture in which galaxy-wide star formation plays an important role in driving winds at z~1. Wind bubbles from all star-forming regions could combine momentum and help lift their entrained gas out of the galaxy.

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arXiv2026

Evaluation as Evolution: Transforming Adversarial Diffusion into Closed-Loop Curricula for Autonomous Vehicles

Autonomous vehicles in interactive traffic environments are often limited by the scarcity of safety-critical tail events in static datasets, which biases learned policies toward average-case behaviors and reduces robustness. Existing evaluation methods attempt to address this through adversarial stress testing, but are predominantly open-loop and post-hoc, making it difficult to incorporate discovered failures back into the training process. We introduce Evaluation as Evolution ($E^2$), a closed-loop framework that transforms adversarial generation from a static validation step into an adaptive evolutionary curriculum. Specifically, $E^2$ formulates adversarial scenario synthesis as transport-regularized sparse control over a learned reverse-time SDE prior. To make this high-dimensional generation tractable, we utilize topology-driven support selection to identify critical interacting agents, and introduce Topological Anchoring to stabilize the process. This approach enables the targeted discovery of failure cases while strictly constraining deviations from realistic data distributions. Empirically, $E^2$ improves collision failure discovery by 9.01% on the nuScenes dataset and up to 21.43% on the nuPlan dataset over the strongest baselines, while maintaining low invalidity and high realism. It further yields substantial robustness gains when the resulting boundary cases are recycled for closed-loop policy fine-tuning.

cs.RO↗
arXiv2026

Characterization of Residual Morphological Substructure Using Supervised and Unsupervised Deep Learning

Automated characterization of galactic substructure is an essential step in understanding the transformative physical processes driving galaxy evolution. In this study, we investigate the application of deep learning (DL) frameworks to characterize different galactic substructures hosted within parametric light-profile subtracted ``residual'' images of a large sample galaxies from the CANDELS survey. We develop a supervised Convolutional Neural Network (CNN) and unsupervised Convolutional Variational Autoencoder (CvAE) and train it on the single-S\'ersic profile fitting based residual images of $10,046$ bright and massive galaxies ($H<24.5\,{\rm mag}$ and $M_{\rm stellar} \geq 10^{9.5}\,M_{\odot}$) spanning $1<z<3$, in conjunction with their visual-based classification labels indicating the nature of residual substructures hosted within them. Using our unique data preprocessing approach, we prepare our residual images such that the inputs to our DL networks comprise only ``galaxy of interest'', and augment them such that our sample span uniformly across different residual characteristics. We assess the latent space of the CNN and CvAE using Principle Component Analysis (PCA) along with independently quantified metrics of residual strength (significant pixel flux $SPF$, Bumpiness, and Residual Flux Fraction). We also employ an unsupervised Gaussian Mixture Modeling (GMM) based clustering scheme with Support Vector Classification (SVC) to identify groupings in PCA space that correspond to similar residual substructure. We find that our supervised CNN latent features in PCA space correlate with the $SPF$ values and distinguish between qualitatively strong and weak residual substructures. While our unsupervised CvAE latent space also correlates with visual and quantitative residual characteristics, but lacks clear discriminatory power when characterizing different residual substructures.

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arXiv2025

Searching Within Galaxies for the Earliest Signs of Quenching With Spatially Resolved Star Formation Histories in UVCANDELS Galaxies at z< 0.3

Understanding the complicated processes that regulate star formation and cause a galaxy to become quiescent is key to our comprehension of galaxy evolution. We used eight well resolved star-forming z$<$ 0.3 galaxies from the UVCANDELS survey, where a total of 10 HST bands including UV follow up in UVIS/F275W allow us to reconstruct the star formation histories (SFHs) of regions across each galaxy. This approach provides a powerful tool to explore the spatio-temporal connection between star formation and galaxy evolution. The spatial and temporal profiles of stellar mass and star formation rate surface density were obtained from the SFHs of these regions. We measure scaling relations and projected radial profiles of regions within each galaxy at the time of observation and at 1 Gyr lookback time, noting possible trends in the evolution. By comparing the change in star formation over time we can infer the timing and location of star formation and see early signs of star formation shut off before quenching occurs. We compared the star formation rate density -- stellar mass density scaling relations for individual galaxies as they evolve from 1 Gyr lookback time. The correlation lines pivot around a log-stellar mass surface density of 7.25 [$M_\odot$ $kpc^{-2}$] may be evidence of a self-regulating process on these scales. Radial profiles of galaxy Log sSFR show an overall decrease over 1 Gyr, but five galaxies show a greater change in Log sSFR at the outskirts than the center indicating a possible early onset of quenching in these galaxies.

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arXiv2025

A Knowledge-Driven Diffusion Policy for End-to-End Autonomous Driving Based on Expert Routing

End-to-end autonomous driving remains constrained by the difficulty of producing adaptive, robust, and interpretable decision-making across diverse scenarios. Existing methods often collapse diverse driving behaviors, lack long-horizon consistency, or require task-specific engineering that limits generalization. This paper presents KDP, a knowledge-driven diffusion policy that integrates generative diffusion modeling with a sparse mixture-of-experts routing mechanism. The diffusion component generates temporally coherent action sequences, while the expert routing mechanism activates specialized and reusable experts according to context, enabling modular knowledge composition. Extensive experiments across representative driving scenarios demonstrate that KDP achieves consistently higher success rates, reduced collision risk, and smoother control compared to prevailing paradigms. Ablation studies highlight the effectiveness of sparse expert activation and the Transformer backbone, and activation analyses reveal structured specialization and cross-scenario reuse of experts. These results establish diffusion with expert routing as a scalable and interpretable paradigm for knowledge-driven end-to-end autonomous driving.

cs.RO↗
arXiv2025

Interactive Adversarial Testing of Autonomous Vehicles with Adjustable Confrontation Intensity

Scientific testing techniques are essential for ensuring the safe operation of autonomous vehicles (AVs), with high-risk, highly interactive scenarios being a primary focus. To address the limitations of existing testing methods, such as their heavy reliance on high-quality test data, weak interaction capabilities, and low adversarial robustness, this paper proposes ExamPPO, an interactive adversarial testing framework that enables scenario-adaptive and intensity-controllable evaluation of autonomous vehicles. The framework models the Surrounding Vehicle (SV) as an intelligent examiner, equipped with a multi-head attention-enhanced policy network, enabling context-sensitive and sustained behavioral interventions. A scalar confrontation factor is introduced to modulate the intensity of adversarial behaviors, allowing continuous, fine-grained adjustment of test difficulty. Coupled with structured evaluation metrics, ExamPPO systematically probes AV's robustness across diverse scenarios and strategies. Extensive experiments across multiple scenarios and AV strategies demonstrate that ExamPPO can effectively modulate adversarial behavior, expose decision-making weaknesses in tested AVs, and generalize across heterogeneous environments, thereby offering a unified and reproducible solution for evaluating the safety and intelligence of autonomous decision-making systems.

cs.RO↗
arXiv2025

Towards Human-Centric Autonomous Driving: A Fast-Slow Architecture Integrating Large Language Model Guidance with Reinforcement Learning

Autonomous driving has made significant strides through data-driven techniques, achieving robust performance in standardized tasks. However, existing methods frequently overlook user-specific preferences, offering limited scope for interaction and adaptation with users. To address these challenges, we propose a "fast-slow" decision-making framework that integrates a Large Language Model (LLM) for high-level instruction parsing with a Reinforcement Learning (RL) agent for low-level real-time decision. In this dual system, the LLM operates as the "slow" module, translating user directives into structured guidance, while the RL agent functions as the "fast" module, making time-critical maneuvers under stringent latency constraints. By decoupling high-level decision making from rapid control, our framework enables personalized user-centric operation while maintaining robust safety margins. Experimental evaluations across various driving scenarios demonstrate the effectiveness of our method. Compared to baseline algorithms, the proposed architecture not only reduces collision rates but also aligns driving behaviors more closely with user preferences, thereby achieving a human-centric mode. By integrating user guidance at the decision level and refining it with real-time control, our framework bridges the gap between individual passenger needs and the rigor required for safe, reliable driving in complex traffic environments.

cs.RO↗
arXiv2025

Recent star formation in 0.5<z<1.5 quiescent galaxies

Observations of massive, quiescent galaxies reveal a relatively uniform evolution: following prolific star formation in the early universe, these galaxies quench and transition to their characteristic quiescent state in the local universe. The debate on the relative role and frequency of the process(es) driving this evolution is robust. In this letter, we identify 0.5<z<1.5 massive, quiescent galaxies in the HST/UVCANDELS extragalactic deep fields using traditional color selection methods and model their spectral energy distributions, which incorporates novel UV images. This analysis reveals ~15% of massive, quiescent galaxies have experienced minor, recent star formation(<10% of total stellar mass within the past ~1Gyr). We find only a marginal, positive correlation between the probability for recent star formation and a measure of the richness of the local environment from a statistical analysis. Assuming the recent star formation present in these quiescent galaxies is physically linked to the local environment, these results suggest only a minor role for dynamic external processes (galaxy mergers and interactions) in the formation and evolution of these galaxies at this redshift.

astro-ph.GA↗
arXiv2025

A Sample of Active Galactic Nuclei with Intermediate-mass Black Holes Extended to $z \approx$ 0.6

We present a sample of 930 intermediate-mass black hole (IMBH) active galactic nuclei (AGNs) with black hole masses of $M_\mathrm{BH} \leqslant 2 \times 10^{6}$ M$_{\odot}$, uniformly selected from the Seventeenth Data Release of the Sloan Digital Sky Survey, based on the detection of broad H$\alpha$ or H$\beta$ emission lines. Taking advantage of the wide wavelength coverage of BOSS/eBOSS spectroscopy, our sample extends the redshift coverage of low-$z$ IMBH AGNs to $z\leqslant0.57$, significantly improving upon previous studies that where generally limited to $z\leqslant0.35$. This sample encompasses black hole masses from $10^{4.0}$ to $10^{6.3}$ M$_{\odot}$, with Eddington ratios ranging from 0.01 to 1.9. Among the $z>0.3$ subset, 24 sources exhibit detectable broad Mg II $\lambda\lambda2796,2803$ emission lines, including eight confirmed by independent DESI spectra. A preliminary analysis reveals a marked decline in both the maximum accretion rate ($L/L_\mathrm{Edd}$) and broad H$\alpha$ luminosity with decreasing redshift, possibly reflecting a cosmic evolution of accretion activity at the low-mass end, akin to the ``downsizing'' evolutionary trend seen in high-mass AGNs.

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arXiv2024

The Lyman Continuum Escape Fraction of Star-forming Galaxies at $2.4\lesssim z\lesssim3.0$ from UVCANDELS

The UltraViolet Imaging of the Cosmic Assembly Near-infrared Deep Extragalactic Legacy Survey Fields (UVCANDELS) survey is a Hubble Space Telescope (HST) Cycle-26 Treasury Program, allocated in total 164 orbits of primary Wide-Field Camera 3 Ultraviolet and Visible light F275W imaging with coordinated parallel Advanced Camera for Surveys F435W imaging, on four of the five premier extragalactic survey fields: GOODS-N, GOODS-S, EGS, and COSMOS. We introduce this survey by presenting a comprehensive analysis of the absolute escape fraction ($f_{\rm esc}^{\rm abs}$) of Lyman continuum (LyC) radiation through stacking the UV images of a population of star-forming galaxies with secure redshifts at $2.4\leq z\leq3.0$. Our stacking benefits from the catalogs of high-quality spectroscopic redshifts compiled from archival ground-based data and HST slitless spectroscopy, carefully vetted by dedicated visual inspection efforts. We develop a robust stacking method to apply to 10 samples of in total 56 galaxies, and perform detailed Monte Carlo (MC) simulations of the intergalactic medium (IGM) attenuation, to take into account the sample variance of the mean IGM transmission when measuring $f_{\rm esc}^{\rm abs}$. The full stack at $z\approx2.44$ from 28 galaxies places a stringent 1-$σ$ upper limit of $f_{\rm esc}^{\rm abs}\lesssim5\%$, whereas the full stack at $z\approx2.72$ of equal number of galaxies gives an upper limit of $f_{\rm esc}^{\rm abs}\lesssim26\%$ at 1-$σ$ confidence level. These new F275W and F435W imaging mosaics from UVCANDELS have been made publicly available on the Barbara A. Mikulski Archive for Space Telescopes (MAST).

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arXiv2024

UVCANDELS: Catalogs of photometric redshifts and galaxy physical properties

The UltraViolet imaging of the Cosmic Assembly Near-infrared Deep Extragalactic Legacy Survey Fields (UVCANDELS) program provides deep HST F275W and F435W imaging over four CANDELS fields (GOODS-N, GOODS-S, COSMOS, and EGS). We combine this newly acquired UV imaging with existing HST imaging from CANDELS as well as existing ancillary data to obtain robust photometric redshifts and reliable estimates for galaxy physical properties for over 150,000 galaxies in the $\sim$430 arcmin$^2$ UVCANDELS area. Here, we leverage the power of the new UV photometry to not only improve the photometric redshift measurements in these fields, but also constrain the full redshift probability distribution combining multiple redshift fitting tools. Furthermore, using the full UV-to-IR photometric dataset, we measure the galaxy physical properties by fitting templates from population synthesis models with two different parameterizations (flexible and fixed-form) of the star-formation histories (SFHs). Compared to the flexible SFH parametrization, we find that the fixed-form SFHs systematically underestimate the galaxy stellar masses, both at the low- ($\lesssim10^9 M_\odot$) and high- ($\gtrsim10^{10} M_\odot$) mass end, by as much as $\sim0.5$ dex. This underestimation is primarily due the limited ability of fixed-form SFH parameterization to simultaneously capture the chaotic nature of star-formation in these galaxies.

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arXiv2024

MAPPO-PIS: A Multi-Agent Proximal Policy Optimization Method with Prior Intent Sharing for CAVs' Cooperative Decision-Making

Vehicle-to-Vehicle (V2V) technologies have great potential for enhancing traffic flow efficiency and safety. However, cooperative decision-making in multi-agent systems, particularly in complex human-machine mixed merging areas, remains challenging for connected and autonomous vehicles (CAVs). Intent sharing, a key aspect of human coordination, may offer an effective solution to these decision-making problems, but its application in CAVs is under-explored. This paper presents an intent-sharing-based cooperative method, the Multi-Agent Proximal Policy Optimization with Prior Intent Sharing (MAPPO-PIS), which models the CAV cooperative decision-making problem as a Multi-Agent Reinforcement Learning (MARL) problem. It involves training and updating the agents' policies through the integration of two key modules: the Intention Generator Module (IGM) and the Safety Enhanced Module (SEM). The IGM is specifically crafted to generate and disseminate CAVs' intended trajectories spanning multiple future time-steps. On the other hand, the SEM serves a crucial role in assessing the safety of the decisions made and rectifying them if necessary. Merging area with human-machine mixed traffic flow is selected to validate our method. Results show that MAPPO-PIS significantly improves decision-making performance in multi-agent systems, surpassing state-of-the-art baselines in safety, efficiency, and overall traffic system performance. The code and video demo can be found at: \url{https://github.com/CCCC1dhcgd/A-MAPPO-PIS}.

cs.RO↗
arXiv2024

UVCANDELS: The role of dust on the stellar mass-size relation of disk galaxies at 0.5 $\leq z \leq$ 3.0

We use the Ultraviolet Imaging of the Cosmic Assembly Near-infrared Deep Extragalactic Legacy Survey fields (UVCANDELS) to measure half-light radii in the rest-frame far-UV for $\sim$16,000 disk-like galaxies over $0.5\leq z \leq 3$. We compare these results to rest-frame optical sizes that we measure in a self-consistent way and find that the stellar mass-size relation of disk galaxies is steeper in the rest-frame UV than in the optical across our entire redshift range. We show that this is mainly driven by massive galaxies ($\gtrsim10^{10}$M$_\odot$), which we find to also be among the most dusty. Our results are consistent with the literature and have commonly been interpreted as evidence of inside-out growth wherein galaxies form their central structures first. However, they could also suggest that the centers of massive galaxies are more heavily attenuated than their outskirts. We distinguish between these scenarios by modeling and selecting galaxies at $z=2$ from the VELA simulation suite in a way that is consistent with UVCANDELS. We show that the effects of dust alone can account for the size differences we measure at $z=2$. This indicates that, at different wavelengths, size differences and the different slopes of the stellar mass-size relation do not constitute evidence for inside-out growth.

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arXiv2024

The UV luminosity function at 0.6 < z < 1 from UVCANDELS

UVCANDELS is a HST Cycle-26 Treasury Program awarded 164 orbits of primary ultraviolet (UV) F275W imaging and coordinated parallel optical F435W imaging in four CANDELS fields: GOODS-N, GOODS-S, EGS, and COSMOS, covering a total area of $\sim426$ arcmin$^2$. This is $\sim2.7$ times larger than the area covered by previous deep-field space UV data combined, reaching a depth of about 27 and 28 ABmag ($5σ$ in $0.2"$ apertures) for F275W and F435W, respectively. Along with the new photometric catalogs, we present an analysis of the rest-frame UV luminosity function (LF), relying on our UV-optimized aperture photometry method yielding a factor of $1.5\times$ increase than the H-isophot aperture photometry in the signal-to-noise ratios of galaxies in our F275W imaging. Using well tested photometric redshift measurements we identify 5810 galaxies at redshifts $0.6<z<1$, down to an absolute magnitude of $M_\text{UV} = -14.2$. In order to minimize the effect of uncertainties in estimating the completeness function, especially at the faint-end, we restrict our analysis to sources above $30\%$ completeness, which provides a final sample of 4726 galaxies at $-21.5<M_\text{UV}<-15.5$. We performed a maximum likelihood estimate to derive the best-fit parameters of the UV LF. We report a best-fit faint-end slope of $α= -1.359^{+0.041}_{-0.041}$ at $z \sim 0.8$. Creating sub-samples at $z\sim0.7$ and $z\sim0.9$, we observe a possible evolution of $α$ with redshift. The unobscured UV luminosity density at $M_\text{UV}<-10$ is derived as $ρ_\text{UV}=1.339^{+0.027}_{-0.030}\ (\times10^{26} \text{ergs/s/Hz/Mpc}^3)$ using our best-fit LF parameters. The new F275W and F435 photometric catalogs from UVCANDELS have been made publicly available on the Barbara A. Mikulski Archive for Space Telescopes (MAST).

astro-ph.GA↗
arXiv2024

JWST Reveals a Surprisingly High Fraction of Galaxies Being Spiral-like at $0.5\leq z\leq4$

Spiral arms are one of the most important features used to classify the morphology of local galaxies. The cosmic epoch when spiral arms first appeared contains essential clues to the evolution of disk galaxies. In this letter, we used James Webb Space Telescope (JWST) images from the Cosmic Evolution Early Release Science Survey to visually identify spiral galaxies with redshift $0.5\leq z\leq4$ and stellar mass $\geq10^{10}\; M_\odot$. Out of 873 galaxies, 216 were found to have a spiral structure. The spiral galaxies in our sample have higher star formation rates (SFRs) and larger sizes than non-spiral galaxies. We found the observed spiral fraction decreases from 48% at $z\sim0.75$ to 8% at $z\sim2.75$. These fractions are higher than the fractions observed with the Hubble Space Telescope (HST). We even detect possible spiral-like features at redshifts $z>3$. We artificially redshifted low redshift galaxies to high redshifts and re-inspected them to evaluate observational effects. By varying the input spiral fraction of the redshifted sample, we found that the input fraction of $\sim35$% matches the observed fraction at $z=2-3$ the best. We are able to rule out spiral fractions being $<20$% (2$σ$) and $<10$% (3$σ$) for real galaxies at $z\sim3$. This fraction is surprisingly high and implies that the formation of spiral arms, as well as disks, was earlier in the universe.

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