arXiv subjects

Yang Sun

Publications and source records attributed to Yang Sun.

At least 109 records · Page 6Linked to original sources

arXiv2025

Spin state of iron in I-42d-type Mg2SiO4 at ultra-high pressures

At extreme pressures of approximately 500 GPa, conditions characteristic of the deep interiors of super-Earths, the combination of NaCl-type MgO and post-perovskite-type MgSiO3 (PPv) has been reported to produce a post-PPv phase of Mg2SiO4 with an I-42d symmetry. This post-PPv (pppv) silicate is proposed as the primary mantle silicate in these massive rocky exoplanets. Understanding the fundamental properties of pppv, particularly in solid solutions with Fe2SiO4, is crucial for insights into the interior dynamics and compositions of such planets. In this study, we conduct an ab initio investigation of the properties of Fe2+-bearing pppv at pressures ranging from 400 GPa to 1 TPa. Given the localized nature of 3d-electrons in iron, we employ the LDA+Usc method alongside conventional DFT functionals to probe the electronic structure of this system. The dependence of the Hubbard parameter U on volume and spin state is carefully evaluated. Furthermore, we systematically explore the effects of pressure, temperature, and structural variations on the spin state of iron in Fe2+-bearing pppv, providing valuable data to improve mantle modeling for super-Earth-type exoplanets.

cond-mat.mtrl-sci↗

arXiv2025

Understanding the two-step nucleation of iron at Earth's inner core conditions: a comparative molecular dynamics study

Metastable phases can lead to multistep nucleation processes, influencing the liquid-to-solid transition in various systems. In this study, we investigate the homogeneous nucleation of iron's crystalline phases under Earth's inner core conditions, employing two previously developed interatomic potentials. We compare the thermodynamic and kinetic properties of iron relevant to the nucleation as predicted by these potentials. While the potentials differ in their predictions of melting temperature by a few hundred Kelvin, they show a consistent description of the relative Gibbs free energy between solid and liquid phases with respect to the undercooling. Both potentials also predict that the metastable bcc phase exhibits a significantly higher nucleation rate than the hcp phase over a wide range of undercooling temperatures below the melting point. This substantially lowers the undercooling thresholds required for the initial nucleation of Earth's inner core. The results validate the commonality of the two-step nucleation mechanism of iron under Earth's inner core conditions for two different potentials, providing a foundation for future studies about the influence of other elements on the nucleation of Earth's core.

physics.geo-ph↗

arXiv2025

The $M_{*}-M_{\rm BH}$ Relation Evolution from z $\sim$ 6 to the Present Epoch

The ratio between the stellar mass of a galaxy, $M_{*}$, and that of its central supermassive black hole (SMBH), $M_\bullet$, the ``Magorrian'' relationship, traces their coevolution. JWST observations have suggested significant evolution in $M_\bullet/M_{*}$ relative to local scaling relationships both in low-mass galaxies and in quasars at z $\ge$ 4. We test this possibility by (1) determining the preferred $M_\bullet/M_{*}$ scaling relation among those proposed locally; and (2) providing uniform host galaxy stellar mass estimates. These steps reduce the prominence of the reported evolution. We then apply Monte Carlo simulations to account for observational biases. We still find a significant increase over the local scaling relation in $M_\bullet/M_{*}$ for z $\ge$ 4 SMBHs in very low-mass galaxies ($\log(M_*/M_{\odot})<10$). However, similarly high values of $M_\bullet/M_{*}$ are also found in low mass galaxies at $z \sim$ 0.5 to 3 that may be common at cosmic noon. Nonetheless, galaxies with similar behavior are rare locally and not accounted for in the local scaling relations. In contrast, z $\sim$ 6 quasars can have $M_\bullet/M_{*}$ well above the local relation value, but they can be explained as extreme cases still within the scaling relation for their higher mass host galaxies. Black holes in some of them and in the low-mass systems may be undergoing very high accretion episodes that result in high $M_\bullet/M_{*}$ but that will be followed by quiescent periods when growth of the host drives the systems toward more typical $M_\bullet/M_{*}$ values.

astro-ph.GA↗

arXiv2025

Stellar weak rates of the $rp$-process waiting points: Effects of strong magnetic fields

Incorporating microscopic nuclear-structure information into the discussion of bulk properties of astronomical objects such as neutron stars has always been a challenging issue in interdisciplinary nuclear astrophysics. Using the $rp$-process nucleosynthesis as an example, we studied the effective stellar $β^+$ and electron capture (EC) rates of eight waiting-point (WP) nuclei with realistic stellar conditions and presence of strong magnetic fields. The relevant nuclear transition strengths are provided by the projected shell model. We have found that, on average, due to the magnetic field effect, the $β^+$ and EC rates can increase by more than an order of magnitude for all combinations of density and temperature, as well as in each of WPs studied. We relate the onset field strength, at which the weak rates begin to increase, to nuclear structure quantities, $Q$ value or electronic chemical potential $μ_e$. The enhanced weak rates may change considerably the lifetime of WPs, thereby modifying the current understanding of the $rp$-process.

nucl-th↗

arXiv2025

FixDrive: Automatically Repairing Autonomous Vehicle Driving Behaviour for $0.08 per Violation

Autonomous Vehicles (AVs) are advancing rapidly, with Level-4 AVs already operating in real-world conditions. Current AVs, however, still lag behind human drivers in adaptability and performance, often exhibiting overly conservative behaviours and occasionally violating traffic laws. Existing solutions, such as runtime enforcement, mitigate this by automatically repairing the AV's planned trajectory at runtime, but such approaches lack transparency and should be a measure of last resort. It would be preferable for AV repairs to generalise beyond specific incidents and to be interpretable for users. In this work, we propose FixDrive, a framework that analyses driving records from near-misses or law violations to generate AV driving strategy repairs that reduce the chance of such incidents occurring again. These repairs are captured in μDrive, a high-level domain-specific language for specifying driving behaviours in response to event-based triggers. Implemented for the state-of-the-art autonomous driving system Apollo, FixDrive identifies and visualises critical moments from driving records, then uses a Multimodal Large Language Model (MLLM) with zero-shot learning to generate μDrive programs. We tested FixDrive on various benchmark scenarios, and found that the generated repairs improved the AV's performance with respect to following traffic laws, avoiding collisions, and successfully reaching destinations. Furthermore, the direct costs of repairing an AV -- 15 minutes of offline analysis and $0.08 per violation -- are reasonable in practice.

cs.SE↗

arXiv2025

Theoretical lower limit of coercive field in ferroelectric hafnia

The high coercive field ($E_c$) of hafnia-based ferroelectrics presents a major obstacle to their applications. The ferroelectric switching mechanisms in hafnia that dictate $E_c$, especially those related to domain nucleation in the Nucleation-Limited-Switching (NLS) model and domain wall motion in the Kolmogorov-Avrami-Ishibas (KAI) model, have remained elusive. We develop a deep-learning-assisted multiscale approach, incorporating atomistic insights into the critical nucleus, to predict both NLS- and KAI-type coercive fields. The theoretical NLS-type $E_c$ values agree with previous experimental results as well as our own measurements and also exhibit the correct thickness scaling for films between 3 and 20 nm. Combined theoretical and experimental investigations reveal that the giant $E_c$ in hafnia-based ferroelectrics arises from the ultra-thin geometry, which confines switching to the NLS mechanism. We predict that the theoretical lower limit for KAI-type $E_c$ is 0.1 MV/cm arsing from mobile domain walls. The activation of KAI-type switching to achieve lower $E_c$ is supported by our experimental demonstration of a low coercive field of 1 MV/cm in a 60 nm ferroelectric (HfO$_2$)$_n$/(ZrO$_2$)$_n$ ($n=3$ unit cells) superlattices. These findings establish a comprehensive framework for understanding ferroelectric switching in hafnia and highlight the potential of geometry and domain-wall engineering to achieve low-$E_c$ devices.

cond-mat.mtrl-sci↗

arXiv2025

Discovery of a Unique Close Quasar-DSFG Pair Linked by a [C II] Bridge at $z=5.63$

We report the discovery of a unique quasar-dusty star-forming galaxy (DSFG) system at $z = 5.63$, consisting of the bright quasar J1133+1603 ($M_{\rm UV} = -27.42$) and its compact, dust-obscured companion, J1133c. ALMA observations reveal a prominent [C II] bridge connecting the quasar and DSFG, indicating ongoing interaction at a projected separation of 1.8 arcsec ($\sim$10 proper kpc). J1133c exhibits unusually bright and broad [C II] emission ($L_{\rm [CII]} > 10^{43}$ erg s$^{-1}$, FWHM $> 500$ km s$^{-1}$), with a [C II] luminosity five times that of the quasar, suggesting intense star formation or potential AGN activity. The inferred star formation rate from [C II] is approximately $10^3$ M$_\odot$ yr$^{-1}$. The remarkable properties of this pair strongly suggest that galaxy interactions may simultaneously trigger both starburst and quasar activity, driving rapid evolution in the early universe.

astro-ph.GA↗

arXiv2025

Open set label noise learning with robust sample selection and margin-guided module

In recent years, the remarkable success of deep neural networks (DNNs) in computer vision is largely due to large-scale, high-quality labeled datasets. Training directly on real-world datasets with label noise may result in overfitting. The traditional method is limited to deal with closed set label noise, where noisy training data has true class labels within the known label space. However, there are some real-world datasets containing open set label noise, which means that some samples belong to an unknown class outside the known label space. To address the open set label noise problem, we introduce a method based on Robust Sample Selection and Margin-Guided Module (RSS-MGM). Firstly, unlike the prior clean sample selection approach, which only select a limited number of clean samples, a robust sample selection module combines small loss selection or high-confidence sample selection to obtain more clean samples. Secondly, to efficiently distinguish open set label noise and closed set ones, margin functions are designed to filter open-set data and closed set data. Thirdly, different processing methods are selected for different types of samples in order to fully utilize the data's prior information and optimize the whole model. Furthermore, extensive experimental results with noisy labeled data from benchmark datasets and real-world datasets, such as CIFAR-100N-C, CIFAR80N-O, WebFG-469, and Food101N, indicate that our approach outperforms many state-of-the-art label noise learning methods. Especially, it can more accurately divide open set label noise samples and closed set ones.

cs.CV↗

arXiv2024

Learning Implicit Features with Flow Infused Attention for Realistic Virtual Try-On

Image-based virtual try-on is challenging since the generated image should fit the garment to model images in various poses and keep the characteristics and details of the garment simultaneously. A popular research stream warps the garment image firstly to reduce the burden of the generation stage, which relies highly on the performance of the warping module. Other methods without explicit warping often lack sufficient guidance to fit the garment to the model images. In this paper, we propose FIA-VTON, which leverages the implicit warp feature by adopting a Flow Infused Attention module on virtual try-on. The dense warp flow map is projected as indirect guidance attention to enhance the feature map warping in the generation process implicitly, which is less sensitive to the warping estimation accuracy than an explicit warp of the garment image. To further enhance implicit warp guidance, we incorporate high-level spatial attention to complement the dense warp. Experimental results on the VTON-HD and DressCode dataset significantly outperform state-of-the-art methods, demonstrating that FIA-VTON is effective and robust for virtual try-on.

cs.CV↗

arXiv2024

Complex-Cycle-Consistent Diffusion Model for Monaural Speech Enhancement

In this paper, we present a novel diffusion model-based monaural speech enhancement method. Our approach incorporates the separate estimation of speech spectra's magnitude and phase in two diffusion networks. Throughout the diffusion process, noise clips from real-world noise interferences are added gradually to the clean speech spectra and a noise-aware reverse process is proposed to learn how to generate both clean speech spectra and noise spectra. Furthermore, to fully leverage the intrinsic relationship between magnitude and phase, we introduce a complex-cycle-consistent (CCC) mechanism that uses the estimated magnitude to map the phase, and vice versa. We implement this algorithm within a phase-aware speech enhancement diffusion model (SEDM). We conduct extensive experiments on public datasets to demonstrate the effectiveness of our method, highlighting the significant benefits of exploiting the intrinsic relationship between phase and magnitude information to enhance speech. The comparison to conventional diffusion models demonstrates the superiority of SEDM.

cs.SD↗

arXiv2024

An Investigation Into The Selection and Colors of Little Red Dots and Active Galactic Nuclei

Recently, a large number of compact sources at $z > 4$ with blue UV slopes and extremely red rest-frame optical slopes have been found in James Webb Space Telescope (JWST) extragalactic surveys. As a subsample of these sources, commonly called ``little red dots'' (LRDs), have been spectroscopically observed to host a broad-line active galactic nucleus (AGN), they have been the focus of multiple recent studies in an attempt to understand the origin of their UV and optical emission. Here, we assemble a sample of 123 LRDs from the literature along with spectroscopic and photometric JWST-identified samples of AGNs to compare their colors and spectral slopes. We find that while obscured AGNs at $z < 6$ have highly dissimilar colors to LRDs, unobscured AGNs at $z < 6$ span a wide range of colors, with only a subsample showing colors similar to LRDs. At $z > 6$, the majority of the unobscured AGNs that have been found in these samples are LRDs, but this may be related to the fact that these sources are at large bolometric luminosities. Because LRDs occupy a unique position in galaxy color space, they are more straightforward to target, and the large number of broad-line AGNs that do not have LRD colors and slopes are therefore underrepresented in many spectroscopic surveys because they are more difficult to pre-select. Current LRD selection techniques return a large and disparate population, including many sources having $2-5μ$m colors impacted by emission line flux boosting in individual filters.

astro-ph.GA↗

arXiv2024

No evidence for a significant evolution of $M_{\bullet}$-$M_*$ relation in massive galaxies up to z$\sim$4

Over the past two decades, tight correlations between black hole masses ($M_\bullet$) and their host galaxy properties have been firmly established for massive galaxies ($\log(M_*/M_{\odot})\gtrsim10$) at low-$z$ ($z<1$), indicating coevolution of supermassive black holes and galaxies. However, the situation at high-$z$, especially beyond cosmic noon ($z\gtrsim2.5$), is controversial. With a combination of \emph{JWST} NIRCam/wide field slitless spectroscopy (WFSS) from FRESCO, CONGRESS and deep multi-band NIRCam/image data from JADES in the GOODS fields, we study the black hole to galaxy mass relation at z$\sim$1--4. After identifying 18 broad-line active galactic nuclei (BL AGNs) at $1 2.5$) from the WFSS data, we measure their black hole masses based on broad near-infrared lines (Pa $α$, Pa $β$, and He\,I $λ$10833\,Å), and constrain their stellar masses ($M_{*}$) from AGN-galaxy image decomposition or SED decomposition. Taking account of the observational biases, the intrinsic scatter of the $M_{\bullet}-M_{*}$ relation, and the errors in mass measurements, we find no significant difference in the $M_{\bullet}/M_{*}$ ratio for 2.5 $< $ z $ <$ 4 compared to that at lower redshifts ($1 < z < 2.5$), suggesting no evolution of the $M_{\bullet} - M_{*}$ relation at $\log(M_*/M_{\odot})\gtrsim10$ up to z$\sim$4.

astro-ph.GA↗

arXiv2024

Computational electron-phonon superconductivity: from theoretical physics to material science

The search for room-temperature superconductors is a major challenge in modern physics. The discovery of copper-oxide superconductors in 1986 brought hope but also revealed complex mechanisms that are difficult to analyze and compute. In contrast, the traditional electron-phonon coupling (EPC) mechanism facilitated the practical realization of superconductivity in metallic hydrogen. Since 2015, the discovery of new hydrogen compounds has shown that EPC can enable room-temperature superconductivity under high pressures, driving extensive research. Advances in computational capabilities, especially exascale computing, now allow for the exploration of millions of materials. This paper reviews newly predicted superconducting systems in 2023-2024, focusing on hydrides, boron-carbon systems, and compounds with nitrogen, carbon, and pure metals. Although many computationally predicted high-Tc superconductors were not experimentally confirmed, some low-temperature superconductors were successfully synthesized. This paper provides a review of these developments and future research directions.

cond-mat.mtrl-sci↗

arXiv2024

Extended hot dust emission around the earliest massive quiescent galaxy

A major unsolved problem in galaxy evolution is the early appearance of massive quiescent galaxies that no longer actively form stars only $ \sim 1$ billion years after the Big Bang. Their high stellar masses and extremely compact structure indicate that they formed through rapid bursts of star formation between redshift $z \sim 6-11$. Theoretical models of galaxy evolution cannot explain their high number density, rapid growth and truncation of star formation at such early times, which likely requires extreme feedback to destroy the cold interstellar medium (the fuel for star formation). We report the discovery of a significant reservoir of hot dust in one of the most distant known examples at $z = 4.658$, GS-9209. The dust was identified using JWST's Mid-Infrared Instrument (MIRI), whose unprecedented sensitivity and high spatial resolution, for the first time, firmly show that this dust is significantly more extended than the stars by $\gtrsim 3$ times. We find that the dust has preferentially been evacuated or diluted in the galaxy center. Our analysis finds that the extended hot dust emission is consistent with recent heating by a younger and more spatially extended generation of star formation. This reveals that the earliest quiescent galaxies did not form in a single rapid burst; instead, similar to galaxy growth at later times, the center formed first with star formation continuing in an extended envelope. The growth of this galaxy is truncating from the inside out, consistent with central gas depletion from early AGN feedback.

astro-ph.GA↗

arXiv2024

A new census of dust and polycyclic aromatic hydrocarbons at z=0.7-2 with JWST MIRI

This paper utilizes the JWST MIRI multi-band imaging data from the SMILES survey (5-25micron), complemented with HST and NIRCam photometric and spectroscopic data from the JADES and FRESCO surveys for 443 star-forming (non-AGN) galaxies at z=0.7-2.0 to extend the study of dust and PAH emission to a new mass and SFR parameter space beyond our local universe. We find a strong correlation between the fraction of dust in PAHs (PAH fraction, q_PAH) with stellar mass. Moreover, the PAH fraction behavior as a function of gas-phase metallicity is similar to that at z~0 from previous studies, suggesting a universal relation: q_PAH is constant (~3.4%) above a metallicity of ~ 0.5$Z_{\odot}$ and decreases to <1% at metallicities $<0.3Z_{\odot}$. This indicates that metallicity is a good indicator of the ISM properties that affect the balance between the formation and destruction of PAHs. The lack of a redshift evolution from z~0-2 also implies that above $0.5\,Z_{\odot}$, the PAH emission effectively traces obscured luminosity and the previous locally-calibrated PAH-SFR calibrations remain applicable in this metallicity regime. We observe a strong correlation between obscured UV luminosity fraction (ratio of obscured to total luminosity) and stellar mass. Above the stellar mass of $>5\times 10^9M_{\odot}$, on average, more than half of the emitted luminosity is obscured, while there exists a non-negligible population of lower mass galaxies with >50% obscured fractions. At a fixed mass, the obscured fraction correlates with SFR surface density. This is a result of higher dust covering fractions in galaxies with more compact star forming regions. Similarly, galaxies with high IRX (IR to UV luminosity) at a given mass or UV continuum slope tend to have higher SFR surface density and shallower attenuation curves, owing to their higher effective dust optical depths and more compact star forming regions.

astro-ph.GA↗

arXiv2024

Overview of AI-Debater 2023: The Challenges of Argument Generation Tasks

In this paper we present the results of the AI-Debater 2023 Challenge held by the Chinese Conference on Affect Computing (CCAC 2023), and introduce the related datasets. We organize two tracks to handle the argumentative generation tasks in different scenarios, namely, Counter-Argument Generation (Track 1) and Claim-based Argument Generation (Track 2). Each track is equipped with its distinct dataset and baseline model respectively. In total, 32 competing teams register for the challenge, from which we received 11 successful submissions. In this paper, we will present the results of the challenge and a summary of the systems, highlighting commonalities and innovations among participating systems. Datasets and baseline models of the AI-Debater 2023 Challenge have been already released and can be accessed through the official website of the challenge.

cs.CL↗

arXiv2024

$μ$Drive: User-Controlled Autonomous Driving

Autonomous Vehicles (AVs) rely on sophisticated Autonomous Driving Systems (ADSs) to provide passengers a satisfying and safe journey. The individual preferences of riders plays a crucial role in shaping the perception of safety and comfort while they are in the car. Existing ADSs, however, lack mechanisms to systematically capture and integrate rider preferences into their planning modules. To bridge this gap, we propose $μ$Drive, an event-based Domain-Specific Language (DSL) designed for specifying autonomous vehicle behaviour. $μ$Drive enables users to express their preferences through rules triggered by contextual events, such as encountering obstacles or navigating complex traffic situations. These rules dynamically adjust the parameter settings of the ADS planning module, facilitating seamless integration of rider preferences into the driving plan. In our evaluation, we demonstrate the feasibility and efficacy of $μ$Drive by integrating it with the Apollo ADS framework. Our findings show that users can effectively influence Apollo's planning through $μ$Drive, assisting ADS in achieving improved compliance with traffic regulations. The response time for $μ$Drive commands remains consistently at the second or millisecond level. This suggests that $μ$Drive may help pave the way to more personalizsed and user-centric AV experiences.

cs.SE↗

arXiv2024

FuncEvalGMN: Evaluating Functional Correctness of SQL via Graph Matching Network

In this paper, we propose a novel graph-based methodology to evaluate the functional correctness of SQL generation. Conventional metrics for assessing SQL code generation, such as matching-based and execution-based methods (e.g., exact set match and execution accuracy), are subject to two primary limitations. Firstly, the former fails to effectively assess functional correctness, as different SQL queries may possess identical functionalities. Secondly, the latter is susceptible to producing false positive samples in evaluations. Our proposed evaluation method, \texttt{FuncEvalGMN}, does not depend on the sufficient preparation of the test data, and it enables precise testing of the functional correctness of the code. Firstly, we parse SQL using a relational operator tree (ROT) called \textit{Relnode}, which contains rich semantic information from the perspective of logical execution.Then, we introduce a GNN-based approach for predicting the functional correctness of generated SQL. This approach incorporates global positional embeddings to address the limitations with the loss of topological information in conventional graph matching frameworks. As an auxiliary contribution, we propose a rule-based matching algorithm, Relnode Partial Matching (\texttt{RelPM}) as a baseline. Finally, we contribute a dataset, \texttt{Pair-Aug-Spider} with a training set and two testing sets, each comprising pairs of SQL codes to simulate various SQL code evaluation scenarios. The training set and one testing dataset focus on code generation using large language models (LLMs), while the other emphasizes SQL equivalence rewriting.

cs.DB↗