arXiv subjects

Xiaoyuan Zhang

Publications and source records attributed to Xiaoyuan Zhang.

At least 55 records · Page 3Linked to original sources

arXiv2025

The warm-hot intergalactic medium in inter-cluster filaments -- A forecast for HUBS observations based on eRASS1 superclusters

Cosmological simulations indicate that nearly half of the baryons in the nearby Universe are in the warm-hot intergalactic medium (WHIM) phase, and about a half them reside in cosmic filaments connecting galaxy clusters. Recent observational studies using stacked survey data and deep exposures of galaxy cluster outskirts have detected soft X-ray excesses associated with optically identified filaments. However, the physical characteristics of WHIM in filaments remain largely undetermined due to a lack of direct spectral diagnostics of individual targets, which are limited by the spectral resolution of current instruments in the soft X-ray band. We aim to select appropriate targets for WHIM characterization through pointing observations with the future Hot Universe Baryon Surveyor (HUBS) mission, which is designed with eV-level energy resolution in the 0.1-2.0 keV band and a one-square-degree field of view, thus complementing other planned microcalorimetry missions such as Athena. We built a sample of 1577 inter-cluster filaments based on the eRASS1 supercluster catalog and estimated their soft X-ray emission. Their modeled emission and geometrical properties were used to select candidate targets for HUBS observations. Four inter-cluster filaments were selected as the most appropriate candidates. By simulating and analyzing their mock observations, we demonstrated that with 200 ks HUBS exposure for each candidate, the gas properties of individual filaments can be accurately determined, with the temperature constrained to $\pm0.01$ keV, metallicity constrained to $\leq\pm0.03$ solar, and density constrained to $<\pm10\%$. Elemental abundances of O, Ne, Mg, and Fe can be measured separately, providing unprecedented insights into the chemical history of the filament gas. We also show that direct mapping of the WHIM distribution is promising with narrowband imaging of the Oviii line.

astro-ph.GA↗

arXiv2025

Differentiable Information Enhanced Model-Based Reinforcement Learning

Differentiable environments have heralded new possibilities for learning control policies by offering rich differentiable information that facilitates gradient-based methods. In comparison to prevailing model-free reinforcement learning approaches, model-based reinforcement learning (MBRL) methods exhibit the potential to effectively harness the power of differentiable information for recovering the underlying physical dynamics. However, this presents two primary challenges: effectively utilizing differentiable information to 1) construct models with more accurate dynamic prediction and 2) enhance the stability of policy training. In this paper, we propose a Differentiable Information Enhanced MBRL method, MB-MIX, to address both challenges. Firstly, we adopt a Sobolev model training approach that penalizes incorrect model gradient outputs, enhancing prediction accuracy and yielding more precise models that faithfully capture system dynamics. Secondly, we introduce mixing lengths of truncated learning windows to reduce the variance in policy gradient estimation, resulting in improved stability during policy learning. To validate the effectiveness of our approach in differentiable environments, we provide theoretical analysis and empirical results. Notably, our approach outperforms previous model-based and model-free methods, in multiple challenging tasks involving controllable rigid robots such as humanoid robots' motion control and deformable object manipulation.

cs.LG↗

arXiv2025

HeadGAP: Few-Shot 3D Head Avatar via Generalizable Gaussian Priors

In this paper, we present a novel 3D head avatar creation approach capable of generalizing from few-shot in-the-wild data with high-fidelity and animatable robustness. Given the underconstrained nature of this problem, incorporating prior knowledge is essential. Therefore, we propose a framework comprising prior learning and avatar creation phases. The prior learning phase leverages 3D head priors derived from a large-scale multi-view dynamic dataset, and the avatar creation phase applies these priors for few-shot personalization. Our approach effectively captures these priors by utilizing a Gaussian Splatting-based auto-decoder network with part-based dynamic modeling. Our method employs identity-shared encoding with personalized latent codes for individual identities to learn the attributes of Gaussian primitives. During the avatar creation phase, we achieve fast head avatar personalization by leveraging inversion and fine-tuning strategies. Extensive experiments demonstrate that our model effectively exploits head priors and successfully generalizes them to few-shot personalization, achieving photo-realistic rendering quality, multi-view consistency, and stable animation.

cs.CV↗

arXiv2024

The hot circumgalactic medium in the eROSITA All-Sky Survey III. Star-forming and quiescent galaxies

The circumgalactic medium (CGM), as the gas repository for star formation, might contain the answer to the mysterious galaxy quenching and bimodal galaxy population origin. We measured the X-ray emission of the hot CGM around star-forming and quiescent galaxies. We detect extended X-ray emission from the hot CGM around star-forming galaxies with $\log(M_*/M_\odot)>11.0$ and quiescent galaxies with $\log(M_*/M_\odot)>10.5$, extending out to $R_{\rm 500c}$. $L_{\rm X, CGM}$ of star-forming galaxies with median stellar masses $\log(M_{\rm *,med}/M_\odot) = 10.7, 11.1, 11.3$ are approximately $0.8\,, 2.3\,, 4.0 \times 10^{40}\,\rm erg/s$, while for quiescent galaxies with $\log(M_{\rm *,med}/M_\odot) = 10.8, 11.1, 11.4$, they are $1.1\,, 6.2\,, 30 \times 10^{40}\,\rm erg/s$. Notably, quiescent galaxies with $\log(M_{\rm *,med}/M_\odot) > 11.0$ exhibit brighter hot CGM than their star-forming counterparts. In halo mass bins, we detect similar X-ray emission around star-forming and quiescent galaxies with $\log(M_{\rm 200m}/M_\odot) > 12.5$, suggesting that galaxies in the same mass dark matter halos host equally bright hot CGM. We emphasize the observed $L_{\rm X, CGM} - M_{\rm 500c}$ relations of star-forming and quiescent galaxies are sensitive to the stellar-to-halo mass relation (SHMR). A comparison with cosmological hydrodynamical simulations (EAGLE, TNG100, and SIMBA) reveals varying degrees of agreement, contingent on the simulation and the specific stellar or halo mass ranges considered. Either selected in stellar mass or halo mass, the star-forming galaxies do not host brighter stacked X-ray emission from the hot CGM than their quiescent counterparts at the same mass range. The result provides useful constraints on the extent of feedback's impacts as a mechanism for quenching star formation as implemented in current cosmological simulations.

astro-ph.GA↗

arXiv2024

The Three-Point Energy Correlator in the Coplanar Limit

Energy correlators are a type of observables that measure how energy is distributed across multiple detectors as a function of the angles between pairs of detectors. In this paper, we study the three-point energy correlator (EEEC) at lepton colliders in the three-particle near-to-plane (coplanar) limit. The leading-power contribution in this limit is governed by the three-jet (trijet) configuration. We introduce a new approach by projecting the EEEC onto the volume of the parallelepiped formed by the unit vectors aligned with three detected final-state particles. Analogous to the back-to-back limit of the two-point energy correlator probing the dijet configuration, the small-volume limit of the EEEC probes the trijet configuration. We derive a transverse momentum dependent (TMD) based factorization theorem that captures the soft and collinear logarithms in the coplanar limit, which enables us to achieve the next-to-next-to-next-to-leading logarithm (N$^3$LL) resummation. To our knowledge, this is the first N$^3$LL result for a trijet event shape. Additionally, we demonstrate that a similar factorization theorem can be applied to the fully differential EEEC in the three-particle coplanar limit, which provides a clean environment for studying different coplanar trijet shapes.

hep-ph↗

arXiv2024

Gas thermodynamics meets galaxy kinematics: Joint mass measurements for eROSITA galaxy clusters

The mass of galaxy clusters is a critical quantity for probing cluster cosmology and testing theories of gravity, but its measurement could be biased given assumptions are inevitable. In this paper, we employ and compare two mass proxies for galaxy clusters: thermodynamics of the intracluster medium and kinematics of member galaxies. We select 22 galaxy clusters from the cluster catalog in the first SRG/eROSITA All-Sky Survey (eRASS1) that have sufficient optical and near-infrared observations. We generate multi-band images in the energy range of (0.3, 7) keV for each cluster, and derive their temperature profiles, gas mass profiles and hydrostatic mass profiles using a parametric approach that does not assume dark matter halo models. With spectroscopically confirmed member galaxies collected from multiple surveys, we numerically solve the spherical Jeans equation for their dynamical mass profiles. Our results quantify the correlation between dynamical mass and line-of-sight velocity dispersion with an rms scatter of 0.14 dex. We find the two mass proxies lead to roughly the same total mass, with no observed systematic bias. As such, the $σ_8$ tension is not specific to hydrostatic mass or weak lensing shears, but also appears with galaxy kinematics. We also compare our hydrostatic masses with the latest weak lensing masses inferred with scaling relations. The comparison shows the weak lensing mass is significantly higher than our hydrostatic mass by $\sim$110%. This might explain the significantly larger value of $σ_8$ from the latest measurement using eRASS1 clusters than almost all previous estimates in the literature. Finally, we test the radial acceleration relation (RAR) established in disk galaxies. We confirm the missing baryon problem in the inner region of galaxy clusters using three independent mass proxies for the first time.

astro-ph.CO↗

arXiv2024

LibMOON: A Gradient-based MultiObjective OptimizatioN Library in PyTorch

Multiobjective optimization problems (MOPs) are prevalent in machine learning, with applications in multi-task learning, learning under fairness or robustness constraints, etc. Instead of reducing multiple objective functions into a scalar objective, MOPs aim to optimize for the so-called Pareto optimality or Pareto set learning, which involves optimizing more than one objective function simultaneously, over models with thousands / millions of parameters. Existing benchmark libraries for MOPs mainly focus on evolutionary algorithms, most of which are zeroth-order / meta-heuristic methods that do not effectively utilize higher-order information from objectives and cannot scale to large-scale models with thousands / millions of parameters. In light of the above gap, this paper introduces LibMOON, the first multiobjective optimization library that supports state-of-the-art gradient-based methods, provides a fair benchmark, and is open-sourced for the community.

cs.MS↗

arXiv2024

Revisiting Single Inclusive Jet Production: Small-$R$ Resummation at Next-to-Leading Logarithm

The precision description of jet production plays an important role in many aspects of collider physics. In a recent paper we have presented a new factorization theorem for inclusive small radius jet production. The jet function appearing in our factorization theorem exhibits a non-standard renormalization group evolution, which, starting at next-to-leading logarithm (NLL), differs from previous results in the literature. In this paper we perform a first phenomenological study using our newly developed formalism, applying it to compute the spectrum of small radius jets in $e^+e^-\to J+X$ at NLL. We compare our results with previous predictions, highlighting the numerical impact of previously neglected terms throughout phase space. Our approach can be used for a variety of different collider systems, in particular, $ep$ and $pp$ collisions, with broad applications to the jet substructure program. Most importantly, since our factorization theorem is valid to all orders, the approach developed here will enable NNLL resummation of small radius logarithms in inclusive jet production, extending the precision of jet substructure calculations.

hep-ph↗

arXiv2024

Revisiting Single Inclusive Jet Production: Timelike Factorization and Reciprocity

Factorization theorems for single inclusive jet production play a crucial role in the study of jets and their substructure. In the case of small radius jets, the dynamics of the jet clustering can be factorized from both the hard production dynamics, and the dynamics of the low scale jet substructure measurement, and is described by a matching coefficient that can be computed in perturbative Quantum Chromodynamics (QCD). A proposed factorization formula describing this process has been previously presented in the literature, and is referred to as the semi-inclusive, or fragmenting jets formalism. By performing an explicit two-loop calculation, we show the inconsistency of this factorization formula, in agreement with another recent result in the literature. Building on recent progress in the factorization of single logarithmic observables, and the understanding of reciprocity, we then derive a new all-order factorization theorem for inclusive jet production. Our factorization involves a non-trivial convolution structure, that maintains the universality of the hard function from inclusive fragmentation. We perform an explicit two-loop calculation of the jet function in both $\mathcal{N}=4$ super Yang-Mills (SYM), and for all color channels in QCD, finding exact agreement with the structure derived from our renormalization group equations. In addition, we derive several new results, including an extension of our factorization formula to jet substructure observables, a jet algorithm definition of a generating function for the energy correlators, and new results for exclusive jet functions. Our results are a key ingredient for achieving precision jet substructure at colliders.

hep-ph↗

arXiv2024

The SRG/eROSITA All-Sky Survey: View of the Virgo Cluster

As the closest galaxy cluster, the Virgo Cluster is an exemplary environment for the study of the large-scale filamentary structure and physical effects that are present in cluster outskirts but absent from the more easily studied inner regions. Here, we present an analysis of the SRG/eROSITA data from five all-sky surveys. eROSITA allows us to resolve the entire Virgo cluster and its outskirts on scales between 1 kpc and 3 Mpc, covering a total area on the sky of about 25$^\circ$ by 25$^\circ$. We utilized image manipulation techniques and surface brightness profiles to search for extended emission, surface brightness edges, and features in the outskirts. We employed a method of comparing mean and median profiles to measure gas clumping out to and beyond the virial radius. Surface brightness analysis of the cluster and individual sectors of the cluster reveal the full extent of previously identified cold fronts to the north and south. The emissivity bias due to gas clumping, which we quantify over three orders of magnitude in the radial range, is found to be mild, consistent with previous findings. We find uniform clumping measurements in all directions, with no enhancements along candidate filaments. We find an estimated virial gas mass of $M_{\mathrm{gas},r<r_{200}} = (1.98 \pm 0.70) \times 10^{13}$ M$_\odot$. Through imaging analysis we detect the presence of extended emission spanning 320\,kpc to the southwest of M49. The extension has a significance of 3.15$σ$ and is coincident with radio emission detected with LOFAR, which could be evidence of an accretion shock or turbulent reacceleration as the M49 group or background W' cloud falls into the cluster and interacts with the intracluster medium.

astro-ph.CO↗

arXiv2024

The hot circumgalactic medium in the eROSITA All-Sky Survey I. X-ray surface brightness profiles

The circumgalactic medium (CGM) provides the material needed for galaxy formation and influences galaxy evolution. The hot ($T>10^6K$) CGM is poorly detected around galaxies with stellar masses ($M_*$) lower than $3\times10^{11}M_\odot$ due to the low surface brightness. We used the X-ray data from the first four SRG/eROSITA All-Sky Surveys (eRASS:4). Based on the SDSS spectroscopic survey and halo-based group finder algorithm, we selected central galaxies with spectroscopic redshifts of $z_{\rm spec}<0.2$ and stellar masses of $10.0<\log(M_*/M_\odot)<11.5$ (85,222 galaxies) -- or halo masses of $11.5<\log(M_{\rm 200m}/M_\odot)<14.0$ (125,512 galaxies). By stacking the X-ray emission around galaxies, masking the detected X-ray point sources and carefully modeling the X-ray emission from the unresolved active galactic nuclei (AGN) and X-ray binaries (XRB), we obtain the X-ray emission from the hot CGM. We detected the X-ray emission around MW-mass and more massive central galaxies extending up to the virial radius ($R_{\rm vir}$). We used a $β$ model to describe the X-ray surface brightness profile and found $β=0.43^{+0.10}_{-0.06}\,(0.37^{+0.04}_{-0.02})$ for MW-mass (M31-mass) galaxies.We estimated the baryon budget of the hot CGM and obtained a value that is lower than the prediction of $Λ$CDM cosmology, indicating significant gas depletion in these halos. We extrapolated the hot CGM profile measured within $R_{\rm vir}$ to larger radii and found that within $\approx 3 R_{\rm vir}$, the baryon budget is close to the $Λ$CDM cosmology prediction. Our results set a firm footing for the presence of the hot CGM around such galaxies. These measurements constitute a new benchmark for galaxy evolution models and possible implementations of feedback processes therein.

astro-ph.GA↗

arXiv2024

The hot circumgalactic medium in the eROSITA All-Sky Survey II. Scaling relations between X-ray luminosity and galaxies' mass

Understanding how the properties of galaxies relate to the properties of the hot circum-galactic medium (CGM) around them can constrain galaxy evolution models. We measured the X-ray luminosity of the hot CGM based on the surface brightness profiles of central galaxy samples measured from Spectrum Roentgen Gamma (SRG)/eROSITA all-sky survey data. We related the X-ray luminosity to the galaxies' stellar and halo mass, and we compared the observed relations to the self-similar model and intrinsic (i.e., not forward-modeled) output of the IllustrisTNG, EAGLE, and SIMBA simulations. The average hot CGM X-ray luminosity ($L_{\rm X,CGM}$) correlates with the galaxy's stellar mass ($M_*$). It increases from $(1.6 \pm 2.1)\times10^{39} \rm erg\,s^{-1}$ to $(3.4 \pm 0.3)\times10^{41} \rm erg\,s^{-1}$, when $\log(M_*)$ increases from 10.0 to 11.5. A power law describes the correlation as $\log(L_{\rm X,CGM})= (2.4\pm 0.1)\times \log(M_*)+(14.6\pm1.5)$. The hot CGM X-ray luminosity as a function of halo mass is measured within $\log(M_{\rm 500c})=11.3-13.7$, extending our knowledge of the scaling relation by more than two orders of magnitude. $L_{\rm X,CGM}$ increases with $M_{\rm 500c}$ from $(3.0 \pm 1.6)\times10^{39}\ \rm erg\,s^{-1}$ at $\log(M_{\rm 500c})=11.3$ to $(1.3 \pm 0.1)\times10^{42}\ \rm erg\,s^{-1}$ at $\log(M_{\rm 500c})=13.7$. The relation follows a power law of $\log(L_{\rm X,CGM})= (1.32\pm 0.05)\times \log(M_{\rm 500c})+(24.1\pm0.7)$. Our observations highlight the necessity of non-gravitational processes at the galaxy group scale while suggesting these processes are sub-dominant at the galaxy scale. We show that the outputs of current cosmological galaxy simulations generally align with the observational results uncovered here but with possibly important deviations in selected mass ranges.

astro-ph.GA↗

arXiv2024

Smooth Tchebycheff Scalarization for Multi-Objective Optimization

Multi-objective optimization problems can be found in many real-world applications, where the objectives often conflict each other and cannot be optimized by a single solution. In the past few decades, numerous methods have been proposed to find Pareto solutions that represent optimal trade-offs among the objectives for a given problem. However, these existing methods could have high computational complexity or may not have good theoretical properties for solving a general differentiable multi-objective optimization problem. In this work, by leveraging the smooth optimization technique, we propose a lightweight and efficient smooth Tchebycheff scalarization approach for gradient-based multi-objective optimization. It has good theoretical properties for finding all Pareto solutions with valid trade-off preferences, while enjoying significantly lower computational complexity compared to other methods. Experimental results on various real-world application problems fully demonstrate the effectiveness of our proposed method.

cs.LG↗

arXiv2024

Panacea: Pareto Alignment via Preference Adaptation for LLMs

Current methods for large language model alignment typically use scalar human preference labels. However, this convention tends to oversimplify the multi-dimensional and heterogeneous nature of human preferences, leading to reduced expressivity and even misalignment. This paper presents Panacea, an innovative approach that reframes alignment as a multi-dimensional preference optimization problem. Panacea trains a single model capable of adapting online and Pareto-optimally to diverse sets of preferences without the need for further tuning. A major challenge here is using a low-dimensional preference vector to guide the model's behavior, despite it being governed by an overwhelmingly large number of parameters. To address this, Panacea is designed to use singular value decomposition (SVD)-based low-rank adaptation, which allows the preference vector to be simply injected online as singular values. Theoretically, we prove that Panacea recovers the entire Pareto front with common loss aggregation methods under mild conditions. Moreover, our experiments demonstrate, for the first time, the feasibility of aligning a single LLM to represent an exponentially vast spectrum of human preferences through various optimization methods. Our work marks a step forward in effectively and efficiently aligning models to diverse and intricate human preferences in a controllable and Pareto-optimal manner.

cs.CL↗

arXiv2024

MeerKAT discovery of a double radio relic and odd radio circle: connecting cluster and galaxy merger shocks

We present the serendipitous discovery of (1) a large double radio relic associated with the galaxy cluster PSZ2 G277.93+12.34 and (2) a new odd radio circle, ORC J1027-4422, both found in the same deep MeerKAT 1.3 GHz wide-band radio continuum image. The angular separation of the two arc-shaped cluster relics is ~16 arcmin or ~2.6 Mpc for a cluster redshift of z ~ 0.158. The thin southern relic, which shows several ridges/shocks including one possibly moving inwards, has a linear extent of ~1.64 Mpc. In contrast, the northern relic is about twice as wide, twice as bright, but only has a largest linear size of ~0.66 Mpc. Complementary SRG/eROSITA X-ray images reveal extended emission from hot intracluster gas between the two relics and around the narrow-angle tail (NAT) radio galaxy PMN J1033-4335 (z ~ 0.153) located just east of the northern relic. The radio morphologies of the NAT galaxy and the northern relic, which are also detected with the Australian Square Kilometer Array Pathfinder (ASKAP) at 888 MHz, suggest both are moving in the same outward direction. The discovery of ORC J1027-4422 in a different part of the same MeerKAT image makes it the 4th known single ORC. It has a diameter of ~90 arcsec corresponding to 400 kpc at a tentative redshift of z ~ 0.3 and remains undetected in X-ray emission. Supported by simulations, we discuss similarities between outward moving galaxy and cluster merger shocks as the formation mechanisms for ORCs and radio relics, respectively.

astro-ph.GA↗

arXiv2024

Dealing with Structure Constraints in Evolutionary Pareto Set Learning

In the past few decades, many multiobjective evolutionary optimization algorithms (MOEAs) have been proposed to find a finite set of approximate Pareto solutions for a given problem in a single run, each with its own structure. However, in many real-world applications, it could be desirable to have structure constraints on the entire optimal solution set, which define the patterns shared among all solutions. The current population-based MOEAs cannot properly handle such requirements. In this work, we make the first attempt to incorporate the structure constraints into the whole solution set by a single Pareto set model, which can be efficiently learned by a simple evolutionary stochastic optimization method. With our proposed method, the decision-makers can flexibly trade off the Pareto optimality with preferred structures among all solutions, which is not supported by previous MOEAs. A set of experiments on benchmark test suites and real-world application problems fully demonstrates the efficiency of our proposed method.

cs.NE↗

arXiv2024

CivRealm: A Learning and Reasoning Odyssey in Civilization for Decision-Making Agents

The generalization of decision-making agents encompasses two fundamental elements: learning from past experiences and reasoning in novel contexts. However, the predominant emphasis in most interactive environments is on learning, often at the expense of complexity in reasoning. In this paper, we introduce CivRealm, an environment inspired by the Civilization game. Civilization's profound alignment with human history and society necessitates sophisticated learning, while its ever-changing situations demand strong reasoning to generalize. Particularly, CivRealm sets up an imperfect-information general-sum game with a changing number of players; it presents a plethora of complex features, challenging the agent to deal with open-ended stochastic environments that require diplomacy and negotiation skills. Within CivRealm, we provide interfaces for two typical agent types: tensor-based agents that focus on learning, and language-based agents that emphasize reasoning. To catalyze further research, we present initial results for both paradigms. The canonical RL-based agents exhibit reasonable performance in mini-games, whereas both RL- and LLM-based agents struggle to make substantial progress in the full game. Overall, CivRealm stands as a unique learning and reasoning challenge for decision-making agents. The code is available at https://github.com/bigai-ai/civrealm.

cs.AI↗

arXiv2024

PMGDA: A Preference-based Multiple Gradient Descent Algorithm

It is desirable in many multi-objective machine learning applications, such as multi-task learning with conflicting objectives and multi-objective reinforcement learning, to find a Pareto solution that can match a given preference of a decision maker. These problems are often large-scale with available gradient information but cannot be handled very well by the existing algorithms. To tackle this critical issue, this paper proposes a novel predict-and-correct framework for locating a Pareto solution that fits the preference of a decision maker. In the proposed framework, a constraint function is introduced in the search progress to align the solution with a user-specific preference, which can be optimized simultaneously with multiple objective functions. Experimental results show that our proposed method can efficiently find a particular Pareto solution under the demand of a decision maker for standard multiobjective benchmark, multi-task learning, and multi-objective reinforcement learning problems with more than thousands of decision variables. Code is available at: https://github.com/xzhang2523/pmgda. Our code is current provided in the pgmda.rar attached file and will be open-sourced after publication.}

cs.LG↗