arXiv subjects

Haonan Zheng

Publications and source records attributed to Haonan Zheng.

At least 19 recordsLinked to original sources

arXiv2026

The dark matter halo mass function in the $Λ\mathrm{CDM}$ cosmology at all times and over all scales -- from planetary to galaxy cluster masses

The dark matter halo mass function is one of the most fundamental predictions of structure formation theory and cosmological simulations. We present the full halo mass function in the $Λ$ cold dark matter ($Λ\mathrm{CDM}$) model, ranging from a planetary mass ($10^{-6}\,\mathrm{M}_\odot$; the thermal cutoff in the initial power spectrum for a fiducial CDM particle mass of $100\,\mathrm{GeV}$) to the mass of a rich galaxy cluster ($10^{15.5}\,\mathrm{M}_\odot$), and from redshift, $z=30$ to the present. To span this very large dynamic range, we combine our earlier Voids-within-Voids-within-Voids (VVV) set of simulations (Wang et al) with large volume, lower resolution cosmological simulations. We develop a subsampling method to extract subvolumes from the original simulations, allowing us to reconstruct the global halo mass function from the biased underdense VVV regions. We show that the results agree reasonably well among the sets of simulations on different scales and environments. We provide a fitting formula for the dark matter halo mass function based on the work of Reed et al. calibrated with our simulations, such that it can be applied at all scales, all environments and all times, with deviations of $\sim2-3\%$ at $z < 2$ and $\sim 7\%$ at higher redshift $z \gtrsim 5$. This formula is also accurate at least for a restricted set of models we tested with modest deviations from $Λ\mathrm{CDM}$ in the values of some of the cosmological parameters. A python code is publicly available at https://github.com/haonan-zheng/hmfc.

astro-ph.CO↗

arXiv2026

AgenticQwen: Training Small Agentic Language Models with Dual Data Flywheels for Industrial-Scale Tool Use

Modern industrial applications increasingly demand language models that act as agents, capable of multi-step reasoning and tool use in real-world settings. These tasks are typically performed under strict cost and latency constraints, making small agentic models highly desirable. In this paper, we introduce the AgenticQwen family of models, trained via multi-round reinforcement learning (RL) on synthetic data and a limited amount of open-source data. Our training framework combines reasoning RL and agentic RL with dual data flywheels that automatically generate increasingly challenging tasks. The reasoning flywheel increases task difficulty by learning from errors, while the agentic flywheel expands linear workflows into multi-branch behavior trees that better reflect the decision complexity of real-world applications. We validate AgenticQwen on public benchmarks and in an industrial agent system. The models achieve strong performance on multiple agentic benchmarks, and in our industrial agent system, close the gap with much larger models on search and data analysis tasks. Model checkpoints and part of the synthetic data: https://huggingface.co/collections/alibaba-pai/agenticqwen. Data synthesis and RL training code: https://github.com/haruhi-sudo/data_synth_and_rl. The data synthesis pipeline is also integrated into EasyDistill: https://github.com/modelscope/easydistill.

cs.CL↗

arXiv2026

Halo assembly bias in the early Universe: a clustering probe of the origin of the Little Red Dots

The clustering of galaxies encodes key information about the structure and assembly history of their host dark matter (DM) haloes, providing a powerful probe of the origin of extreme high-redshift systems. While halo assembly bias has been extensively studied at low redshift, its behavior in the early Universe remains poorly explored. Using the large-volume, high-resolution Shin-Uchuu cosmological $N$-body simulation, we characterize halo assembly bias associated with formation time, concentration, and angular momentum across a wide range of halo masses and redshifts. We find that the sign and amplitude of assembly bias depend on halo mass for both concentration and spin. High-concentration and low-spin haloes are more strongly clustered below characteristic peak heights of $ν\sim 1.5$ and $\sim 0.75$, respectively, while the trends weaken or reverse at higher masses. Halo age bias persists at all redshifts but decreases toward higher masses and earlier cosmic times. We apply these results to assess whether clustering can distinguish competing formation scenarios for the Little Red Dots (LRDs). We find that the direct-collapse-black-hole (DCBH) scenario predicts the strongest large-scale bias and enhanced pair fractions, the self-interacting-dark-matter (SIDM) core-collapse scenario and low-spin compact-galaxy scenarios yield weaker clustering due to lower characteristic halo masses and spin-related secondary bias, and a primordial-black-hole (PBH) scenario predicts unbiased clustering. Our results demonstrate that halo assembly bias and characteristic host masses provide powerful diagnostics for constraining the physical origin of LRDs, offering testable predictions for upcoming clustering measurements with JWST and future deep surveys.

astro-ph.CO↗

arXiv2026

The impact of cosmic filaments on the abundance of satellite galaxies

The impact of cosmic web environments on galaxy properties plays a critical role in understanding galaxy formation. Using the state-of-the-art cosmological simulation IllustrisTNG, we investigate how satellite galaxy abundance differs between filaments and the field, with filaments identified using the DisPerSE algorithm. When filaments are identified using galaxies as tracers, we find that, across all magnitude bins, central galaxies in filaments tend to host more satellite galaxies than their counterparts in the field, in qualitative agreement with observational results from the Sloan Digital Sky Survey. The average ratios between satellite luminosity functions in filaments and the field are $3.49$, $2.61$, and $1.90$ in the central galaxy $r$-band magnitude bins of $M_{r, {\rm cen}} \sim -22$, $-21$, and $-20$, respectively. We show that much of this excess can be attributed to the higher host halo masses of galaxies in filaments. After resampling central galaxies in both environments to match the halo mass distributions within each magnitude bin, the satellite abundance enhancement in filaments is reduced by up to $79 \%$. Additionally, the choice of tracers used to identify filaments introduces a significant bias: when filaments are identified using the dark matter density field, the environmental difference in satellite abundance is reduced by more than $70 \%$; after further resampling in both magnitude and halo mass, the difference is further suppressed by another $\sim 60$--$95 \%$. Our results highlight the importance of halo mass differences and tracer choice biases when interpreting and understanding the impact of environment on satellite galaxy properties.

astro-ph.GA↗

arXiv2025

Ultra-diffuse galaxies in the EAGLE simulation

We use the highest-resolution EAGLE simulation, Recal-L025N0752, to study the properties and formation of ultra-diffuse galaxies (UDGs). We identify 181 UDGs and find their properties closely match observations. The total masses of EAGLE UDGs range from ${\sim}5\times 10^{8}~M_{\odot}$ to ${\sim}2\times 10^{11}~M_{\odot}$, indicating that they are dwarf galaxies rather than failed $L_\star$ galaxies. EAGLE UDGs are not a distinct population, but rather a subset of dwarf galaxies, as their properties generally form a continuous distribution with those of normal dwarf galaxies. Unlike the situations in previous studies, the extended sizes of field UDGs in EAGLE are not driven by high halos spin or by supernova-induced stellar expansion, but instead largely arise from high spins in their star-forming gas and thus the newly formed stars at large radii. This might be attributed to galactic fountains, by which star-forming gas are launched to large halo-centric distances and acquire additional angular momentum through interactions with the circumgalactic medium. For satellite UDGs, ${\sim} 60 \%$ of them were already UDGs before falling into the host galaxy, while the remaining ${\sim} 40\%$ were normal galaxies prior to infall and subsequently transformed into UDGs due to tidal effects after infall.

astro-ph.GA↗

arXiv2025

HIDES -- I. The population and diversity of HI-rich 'dark' galaxies in the Hestia and Auriga simulations

We present our investigation of HI-rich 'Dark' galaxiEs in Simulations (HIDES), specifically using the Hestia and Auriga simulations in this work. We select galaxies that are faint ($M_g > -10$) and contain sufficient HI ($M_\mathrm{HI} > 10^5\,M_\odot$), and identify 89 such objects, only one of which is completely starless. Their demographics generally converge across simulations of different resolution, with $M_{200} \sim 10^{9.5}\,M_\odot$, $M_\mathrm{gas} \sim 10^{7.4}\,M_\odot$, $M_\mathrm{HI} \sim 10^{6.5}\,M_\odot$, $M_\mathrm{*} \sim 10^{5.6}\,M_\odot$, low gas metallicity, little or no current star formation, and a mean stellar age of $\sim$ 11 Gyr, and with some of them can survive in dense environments as close as $\sim$ 300 kpc from a Milky-Way mass neighbor. We find a large scatter in their HI density profiles and $M_\mathrm{HI} - M_\mathrm{*}$ relation, which cannot be fully explained by current halo mass or concentration, but can be attributed to ram pressure stripping in dense environments, past mergers, and stellar feedback. In particular, close encounters with massive halos and dense environments can reshape the HI content, which may explain the asymmetric HI map of an intriguing observed analogue, Cloud-9. An empirical fit, $n = 0.25 \left(d_\mathrm{MW}/{1\,\mathrm{Mpc}}\right)^{-1.4}\, \mathrm{Mpc}^{-3}$, based on their number density extended to 3.7 Mpc in constrained local volume simulations, is also provided to aid observational forecasts. We conclude that both mass assembly history and environmental history play a crucial role in the formation and subsequent diversity of these galaxies.

astro-ph.GA↗

arXiv2025

Particle loads for cosmological simulations with equal-mass dark matter and baryonic particles

Traditional cosmological hydrodynamical simulations usually assume equal-numbered but unequal-mass dark matter and baryonic particles, which can lead to spurious collisional heating due to energy equipartition. To avoid such a numerical heating effect, a simulation setup with equal-mass dark matter and baryonic particles, which corresponds to a particle number ratio of $N_{\rm DM}:N_{\rm gas} = Ω_{\rm cdm} / Ω_{\rm b}$, is preferred. However, previous studies have typically used grid-based particle loads to prepare such initial conditions, which can only reach specific values for $N_{\rm DM}:N_{\rm gas}$ due to symmetry requirements. In this study, we propose a method based on the glass approach that can generate two-component particle loads with more general $N_{\rm DM}:N_{\rm gas}$ ratios. The method simultaneously relaxes two Poisson particle distributions by introducing an additional repulsive force between particles of the same component. We show that the final particle load closely follows the expected minimal power spectrum, $P(k) \propto k^{4}$, exhibits good homogeneity and isotropy properties, and remains sufficiently stable under gravitational interactions. Both the dark matter and gas components individually also exhibit uniform and isotropic distributions. We apply our method to two-component cosmological simulations and demonstrate that an equal-mass particle setup effectively mitigates the spurious collisional heating that arises in unequal-mass simulations. Our method can be extended to generate multi-component uniform and isotropic distributions. Our code based on Gadget-2 is available at https://github.com/liaoshong/gadget-2glass .

astro-ph.CO↗

arXiv2025

Every Step Evolves: Scaling Reinforcement Learning for Trillion-Scale Thinking Model

We present Ring-1T, the first open-source, state-of-the-art thinking model with a trillion-scale parameter. It features 1 trillion total parameters and activates approximately 50 billion per token. Training such models at a trillion-parameter scale introduces unprecedented challenges, including train-inference misalignment, inefficiencies in rollout processing, and bottlenecks in the RL system. To address these, we pioneer three interconnected innovations: (1) IcePop stabilizes RL training via token-level discrepancy masking and clipping, resolving instability from training-inference mismatches; (2) C3PO++ improves resource utilization for long rollouts under a token budget by dynamically partitioning them, thereby obtaining high time efficiency; and (3) ASystem, a high-performance RL framework designed to overcome the systemic bottlenecks that impede trillion-parameter model training. Ring-1T delivers breakthrough results across critical benchmarks: 93.4 on AIME-2025, 86.72 on HMMT-2025, 2088 on CodeForces, and 55.94 on ARC-AGI-1. Notably, it attains a silver medal-level result on the IMO-2025, underscoring its exceptional reasoning capabilities. By releasing the complete 1T parameter MoE model to the community, we provide the research community with direct access to cutting-edge reasoning capabilities. This contribution marks a significant milestone in democratizing large-scale reasoning intelligence and establishes a new baseline for open-source model performance.

cs.CL↗

arXiv2025

Formation of the Little Red Dots from the Core-collapse of Self-interacting Dark Matter Halos

We present a statistical study of black hole (BH) formation and growth seeded by gravothermal core collapse of self-interacting dark matter (SIDM) halos at high redshift, using a cosmological semi-analytical framework based on Monte Carlo merger trees. We demonstrate that gravothermal collapse naturally leads to BH formation in high-concentration halos at a characteristic mass scale set by the SIDM cross section, and occurs predominantly in the early Universe. This mechanism is particularly promising for explaining the abundance of the little red dots (LRDs) -- a population of early, apparently galaxy-less active galactic nuclei hosting supermassive BHs. By incorporating this seeding process with simple models of BH growth and assuming a 100% duty cycle, we reproduce the observed LRD mass function for velocity-dependent cross sections of $σ_{0m} \sim 30\,\mathrm{cm}^2\,\mathrm{g}^{-1}$ and $ω\sim 80\,\mathrm{km}\,\mathrm{s}^{-1}$, which are consistent with independent constraints from local galaxies. While higher values of $σ_{0m}$ (or $ω$) would overpredict the low-mass (or high-mass) end of the BH mass function, such deviations could be reconciled by invoking a reduced duty cycle or lower Eddington ratio. Our results suggest that the demographics of high-redshift BHs can serve as a novel and complementary probe of SIDM physics.

astro-ph.GA↗

arXiv2025

The mass accretion history of dark matter haloes down to Earth mass

We take advantage of the unprecedented dynamical range provided by the "Cosmic-Zoom" project to study the mass accretion history (MAH) of present-day dark matter haloes over the entire mass range present in the $Λ$CDM paradigm when the dark matter is made of weakly interacting massive particles of mass $100\ \mathrm{GeV}$. In particular, we complement previous studies by exploring the MAHs of haloes with mass from $10^8\ h^{-1}\mathrm{M_{\odot}}$ down to Earth mass, $10^{-6}\ h^{-1}\mathrm{M_{\odot}}$. The formation redshift of low-mass haloes anti-correlates weakly with mass, peaking at $z=3$ for haloes of mass $10^{-4}\ h^{-1}\mathrm{M_{\odot}}$. Even lower masses are affected by the free-streaming cutoff in the primordial spectrum of density fluctuations and form at lower redshift. We compare MAHs in our simulations with predictions from two analytical models based on the extended Press-Schechter theory (EPS), and three empirical models derived by fitting and extrapolating either results from cosmological $N$-body simulations or Monte Carlo realizations of halo growth. All models fit our simulations reasonably well over the mass range for which they were calibrated. While the empirical models match better for more massive haloes, $M>10^{10}\ h^{-1}\mathrm{M_{\odot}}$, the analytical models do better when extrapolated down to Earth mass. At the higher masses, we explore the correlation between local environment density and MAH, finding that biases are relatively weak, with typical MAHs for haloes in extremely low-density and in typical regions differing by less than $20$ percent at high redshift. If this result can be extrapolated to lower halo masses, we conclude that EPS theory predicts the hierarchical build-up of dark matter haloes quite well over the entire halo mass range.

astro-ph.GA↗

arXiv2024

The influence of baryons on low-mass haloes

The Voids-within-Voids-within-Voids (VVV) project used dark-matter-only simulations to study the abundance and structure of dark matter haloes over the full mass range populated in the standard $Λ\mathrm{CDM}$ cosmology. Here we explore how baryonic effects modify these results for $z=0$ halo masses in the range $10^4$ to $10^7~\mathrm{M_\odot}$, below the threshold for galaxy formation. Our main study focuses on three simulations from identical initial conditions at $z=127$, one following dark matter only, one including non-radiative gas, and one additionally including the baryonic physics relevant in this halo mass range (cooling and photoheating). In the non-radiative simulation, above $10^{5.5}~\mathrm{M_\odot}$, halo abundance and internal structure are very similar to the dark-matter-only simulation, and the baryon to dark matter ratio is everywhere close to the cosmic value. At lower mass, this ratio drops and haloes are less concentrated and less massive in the non-radiative case. Test simulations at higher resolution show this to be mainly a resolution effect; the expected drop in baryon content due to residual pressure effects only becomes substantial for $z=0$ haloes below $\sim 10^{2.7}~\mathrm{M_\odot}$. However, gas is heated by reionization at $z=6$ in our "full physics" run, and this results in almost complete expulsion of gas from all haloes in our simulated mass range. This suppresses the halo mass function by $\sim 30 \%$, lowers halo concentration, and consequently weakens the dark matter annihilation signal by $\sim 40-60 \%$.

astro-ph.GA↗

arXiv2024

Sample-agnostic Adversarial Perturbation for Vision-Language Pre-training Models

Recent studies on AI security have highlighted the vulnerability of Vision-Language Pre-training (VLP) models to subtle yet intentionally designed perturbations in images and texts. Investigating multimodal systems' robustness via adversarial attacks is crucial in this field. Most multimodal attacks are sample-specific, generating a unique perturbation for each sample to construct adversarial samples. To the best of our knowledge, it is the first work through multimodal decision boundaries to explore the creation of a universal, sample-agnostic perturbation that applies to any image. Initially, we explore strategies to move sample points beyond the decision boundaries of linear classifiers, refining the algorithm to ensure successful attacks under the top $k$ accuracy metric. Based on this foundation, in visual-language tasks, we treat visual and textual modalities as reciprocal sample points and decision hyperplanes, guiding image embeddings to traverse text-constructed decision boundaries, and vice versa. This iterative process consistently refines a universal perturbation, ultimately identifying a singular direction within the input space which is exploitable to impair the retrieval performance of VLP models. The proposed algorithms support the creation of global perturbations or adversarial patches. Comprehensive experiments validate the effectiveness of our method, showcasing its data, task, and model transferability across various VLP models and datasets. Code: https://github.com/LibertazZ/MUAP

cs.CV↗

arXiv2024

A Unified Understanding of Adversarial Vulnerability Regarding Unimodal Models and Vision-Language Pre-training Models

With Vision-Language Pre-training (VLP) models demonstrating powerful multimodal interaction capabilities, the application scenarios of neural networks are no longer confined to unimodal domains but have expanded to more complex multimodal V+L downstream tasks. The security vulnerabilities of unimodal models have been extensively examined, whereas those of VLP models remain challenging. We note that in CV models, the understanding of images comes from annotated information, while VLP models are designed to learn image representations directly from raw text. Motivated by this discrepancy, we developed the Feature Guidance Attack (FGA), a novel method that uses text representations to direct the perturbation of clean images, resulting in the generation of adversarial images. FGA is orthogonal to many advanced attack strategies in the unimodal domain, facilitating the direct application of rich research findings from the unimodal to the multimodal scenario. By appropriately introducing text attack into FGA, we construct Feature Guidance with Text Attack (FGA-T). Through the interaction of attacking two modalities, FGA-T achieves superior attack effects against VLP models. Moreover, incorporating data augmentation and momentum mechanisms significantly improves the black-box transferability of FGA-T. Our method demonstrates stable and effective attack capabilities across various datasets, downstream tasks, and both black-box and white-box settings, offering a unified baseline for exploring the robustness of VLP models.

cs.CV↗

arXiv2024

The abundance of dark matter haloes down to Earth mass

We use the Voids-within-Voids-within-Voids (VVV) simulations, a suite of successive nested N-body simulations with extremely high resolution (denoted, from low to high resolution, by L0 to L7), to test the Press-Schechter (PS), Sheth-Tormen (ST), and extended Press-Schechter (EPS) formulae for the halo abundance over the entire mass range, from mini-haloes of $10^{-6}\ \mathrm{M_\odot}$, to cluster haloes of $10^{15}\ \mathrm{M_\odot}$, at different redshifts, from $z=30$ to the present. We find that at $z=0$ and $z=2$, ST best reproduces the results of L0, which has the mean cosmic density (overdensity $δ=0$), at $10^{11-15} ~\mathrm{M_\odot}$. The higher resolution levels (L1-L7) are biased underdense regions ($δ<-0.6$). The EPS formalism takes this into account since it gives the mass function of a region conditioned, in this case, on having a given underdensity. EPS provides good matches to these higher levels, with deviations $\lesssim 20\%$, at $10^{-6-12.5} ~\mathrm{M_\odot}$. At $z \sim 7-15$, the ST predictions for L0 and the EPS for L1-L7 show somewhat larger deviations from the simulation results. However, at even higher redshifts, $z \sim 30$, EPS fits the simulations well again. We confirm our results by picking more subvolumes from the L0 simulation, finding that our conclusions depend only weakly on the size and overdensity of the region. The good agreement of EPS with the higher-level simulations implies that PS (or ST) gives an accurate description of the total halo mass function in representative regions of the universe.

astro-ph.GA↗

arXiv2022

Meshless Methods for Magnetohydrodynamics with Vector Potential

We present a meshless method for magnetohydrodynamics by evolving the vector potential of magnetic fields. A novel scheme and numerical techniques are developed to restrict the divergence of magnetic field, based on the Meshless Finite Mass/Volume with HLLD Riemann solver for conservative flux calculation. We found the magnetic field could be stabilized by a proper smoothing process and so the long-term evolution becomes available. To verify the new scheme, we perform the Brio-Wu shock tube, 2D and 3D Orszag-Tang vortex and Magnetorotational Instability test problems. Our results suggest that our method is robust and has better precision on central offset, amplitude and detailed pattern than an existing meshless code$-$GIZMO.

astro-ph.IM↗

arXiv2022

The impact of filaments on dwarf galaxy properties in the Auriga simulations

With a hydrodynamical simulation using a simple galaxy formation model without taking into account feedback, our previous work has shown that dense and massive filaments at high redshift can provide potential wells to trap and compress gas, and hence affect galaxy formation in their resident low-mass haloes. In this paper, we make use of the Auriga simulations, a suite of high-resolution zoom-in hydrodynamical simulations of Milky Way-like galaxies, to study whether the conclusion still holds in the simulations with a sophisticated galaxy formation model. In agreement with the results of our previous work, we find that, comparing to their counterparts with similar halo masses in field, dwarf galaxies residing in filaments tend to have higher baryonic and stellar fractions. At the fixed parent halo mass, the filament dwarfs tend to have slightly higher star formation rates than those of field ones. But overall we do not find a clear difference in galaxy g - r colours between the filament and field populations. We also show that at high redshifts, the gas components in dwarf galaxies tend to have their spins aligned with the filaments in which they reside. Our results support a picture in which massive filaments at high redshift assist gas accretion and enhance star formation in their resident dwarf sized dark matter haloes.

astro-ph.GA↗

arXiv2020

Wind Driven Semiconductor Electricity Generator With High Direct Current Output Based On a Dynamic Schottky Junction

As the fast development of internet of things (IoTs), distributed sensors have been frequently used and the small and portable power sources are highly demanded. However, the present portable power source such as lithium battery has low capacity and need to be replaced or recharged frequently. A portable power source which can continuously generate electrical power in situ will be an idea solution. Herein, we demonstrate a wind driven semiconductor electricity generator based on a dynamic Schottky junction, which can output a continuous direct current with an average value of 4.4 mA (the maximum value of 8.4 mA) over 360 seconds. Compared with the previous metal/semiconductor generator, the output current is one thousand times higher. Furthermore, this wind driven generator has been explored to function as a turn counter due to its stable output and also to drive a graphene ultraviolet photodetector, which shows a responsivity of 35.8 A/W under the 365 nm ultraviolet light. Our research provides a feasible method to achieve wind power generation and power supply for distributed sensors in the future.

physics.app-ph↗

arXiv2020

Galaxy properties in the cosmic web of EAGLE simulation

We investigate the dependence of the galaxy properties on cosmic web environments using the most up-to-date hydrodynamic simulation: Evolution and Assembly of Galaxies and their Environments (EAGLE). The baryon fractions in haloes and the amplitudes of the galaxy luminosity function decrease going from knots to filaments to sheets to voids. Interestingly, the value of L$^*$ varies dramatically in different cosmic web environments. At z = 0, we find a characteristic halo mass of $10^{12} h^{-1}\rm M_{\odot}$, below which the stellar-to-halo mass ratio is higher in knots while above which it reverses. This particular halo mass corresponds to a characteristic stellar mass of $1.8\times 10^{10} h^{-1}\rm M_{\odot}$. Below the characteristic stellar mass central galaxies have redder colors, lower sSFRs and higher metallicities in knots than those in filaments, sheets and voids, while above this characteristic stellar mass, the cosmic web environmental dependences either reverse or vanish. Such dependences can be attributed to the fact that the active galaxy fraction decreases along voids, sheets, filaments and knots. The cosmic web dependences get weaker towards higher redshifts for most of the explored galaxy properties and scaling relations, except for the gas metallicity vs. stellar mass relation.

astro-ph.GA↗