arXiv subjects

Xuejie Li

Publications and source records attributed to Xuejie Li.

17 recordsLinked to original sources

arXiv2026

A graph-based Neural Network surrogate model for accelerating semi-analytical model of galaxy formation and evolution

Understanding how galaxy populations emerge and evolve from the growth of dark matter structure is a central challenge in galaxy formation theory. Semi-analytic models (SAMs) provide an efficient framework to address this problem, but exploring large ensembles of merger trees across broad parameter spaces remains computationally demanding. We develop a conditional graph neural network surrogate model that combines merger tree information with SAM parameters to predict galaxy properties across cosmic time. Using merger trees of dark matter halos from the Uchuu simulation and the Galacticus SAM, the model predicts stellar mass, luminosity, angular momentum, gas metal mass, and specific star formation rate across the wide redshift range of 0 <= z <= 5. For instance, the model can predict stellar mass at 0 <= z <= 3 with a scatter of 0.19-0.28 dex and coefficient of determination R^2 of 0.946-0.973 (R^2 close to 1 indicates prediction closely matching the truth). The results show that a single graph based model can reproduce these galaxy properties with good accuracy over multiple SAM realizations, merger trees and redshifts. This catalog-level model provides a practical route for accelerating SAM based studies of galaxy formation to enable a more detailed investigation of the model parameter space. The inference code, trained models, and example data products are publicly available at https://github.com/MutongCat/sam2galaxy-gnn.

astro-ph.GA↗

arXiv2026

Four-phonon scattering and coherent heat transport in ultrawide-bandgap SrSnO3

SrSnO3 is a promising ultrawide-bandgap perovskite oxide whose thermal transport is governed by structural distortions and anharmonic lattice dynamics. Here, we investigate the lattice thermal conductivity (kL) of orthorhombic and cubic SrSnO3 within a unified first-principles framework combining self-consistent phonon renormalization, three- and four-phonon scattering, and coherent heat transport. Bonding analysis reveals a rigid Sn-O octahedral framework embedded in a weakly bonded Sr sublattice, giving rise to low-frequency vibrational modes susceptible to strong anharmonic effects. Four-phonon scattering is identified as a key mechanism limiting particle-like heat conduction, reducing the Peierls thermal conductivity by 19.4% at 300 K in the orthorhombic phase and by 52.1% at 1300 K in the cubic phase, while the coherent contribution provides a finite channel that partially compensates this reduction. We further show that the apparent agreement between three-phonon calculations and experimental thermal conductivity at room temperature is not indicative of a complete physical description. Instead, it arises from a near cancellation between four-phonon suppression of the particle-like channel and the neglected coherent contribution. This cancellation breaks down when the full temperature dependence is considered, where only the combined treatment improves agreement with the experimentally observed scaling behavior. A physically consistent description of kL therefore requires phonon renormalization, four-phonon scattering, and coherent transport to be treated on equal footing rather than inferred from three-phonon agreement at a single temperature. These results provide microscopic insight into thermal transport in ultrawide-bandgap stannate perovskites and establish a benchmark for anharmonic transport in strongly distorted oxides.

cond-mat.mtrl-sci↗

arXiv2026

Achieving 100$\,$MHz Instantaneous Bandwidth in a Broadband Rydberg Microwave Sensor

Rydberg atoms have attracted considerable attention in recent years as a novel platform for microwave sensing, owing to their unique physical merits: large transition dipole moments between Rydberg levels and broad frequency coverage. As a critical figure of merit for Rydberg microwave sensors, instantaneous bandwidth serves as a key benchmark for evaluating their viability in practical applications. Previous studies on instantaneous bandwidth remain limited to single-frequency operation, with typical demonstrated values of only tens of megahertz, a constraint that hampers the real-world deployment of this sensing technology. Here, we experimentally achieve an instantaneous bandwidth of over 100$\,$MHz across a broad frequency range of 2.7-20$\,$GHz and realize a sensitivity in the hundreds of nV$\,$cm$^{-1}\,$Hz$^{-1/2}$ range. The physical mechanism lies in the dressed-state coherence and the interference effect between different transition channels. Our work substantially broadens the instantaneous bandwidth of Rydberg microwave sensors and paves the way for their practical deployment in fields such as radar and wireless communications.

physics.atom-ph↗

arXiv2026

Broadband Rydberg Atomic Microwave Sensing with 44.6$\,$MHz Instantaneous Bandwidth

Rydberg atoms have become a promising novel type of microwave sensor due to their excellent physical properties -- broad frequency coverage and large electric dipole moments. High sensitivity and broad instantaneous bandwidth are two indispensable requirements for deployable Rydberg microwave sensors. However, enabling broadband operation while retaining high sensitivity has been a longstanding barrier limiting their applications. We propose and experimentally demonstrate a Rydberg microwave sensor whose instantaneous bandwidth is significantly enhanced via an auxiliary microwave field. By finely modulating the Rydberg energy levels with this field, we broaden the bandwidth substantially while retaining the sensor's inherent high sensitivity. An instantaneous bandwidth of 44.6$\,$MHz ($\pm$22.3$\,$MHz) with a sensitivity of 225.7$\,$nV$\,$cm$^{-1}\,$Hz$^{-1/2}$ is realized in a thermal $^{87}$Rb vapor with the local microwave frequency of 16.03$\,$GHz. Our work delivers concurrent broad instantaneous bandwidth and high sensitivity for Rydberg microwave sensors, paving a technically viable path for their practical deployment in broadband microwave metrology, radar, and wireless communication.

physics.atom-ph↗

arXiv2026

Multi-Dressed-State Engineered Rydberg Electrometry

Rydberg atoms, with their giant transition electric dipole moments and abundant energy-level transitions, offer exceptional potential for microwave (MW) electric field sensing, combining high sensitivity and broad frequency coverage. However, simultaneously achieving high sensitivity and broad instantaneous bandwidth in a Rydberg-based MW sensor remains a critical challenge. Here, we propose a multi-dressed-state engineered superheterodyne detection scheme for Rydberg electrometry to overcome this challenge. It is found that the key to simultaneously achieving large instantaneous bandwidth and high sensitivity lies in the coherence of dressed states and the interference between transition channels of dressed states. By strategically engineering the multiple dressed states of Rydberg atoms, we demonstrate a thermal $\mathrm{^{87}Rb}$ vapor-based sensor with a sensitivity of 222.6$\,$nV$\,$cm$^{-1}\,$Hz$^{-1/2}$ and a record instantaneous bandwidth of 76.8$\,$MHz with the local microwave frequency 16.03$\,$GHz. This advancement paves the way for Rydberg-atom technologies in radar, wireless communication, and spectrum monitoring.

physics.atom-ph↗

arXiv2026

LLM-driven discovery for carbon allotropes with bond-network entropy

The discovery of novel carbon allotropes with tailored thermal and mechanical properties is critical for advanced thermal management. However, exploring the vast configurational space of carbon using \textit{ab initio} calculations remains computationally prohibitive. Driven by the rich topological landscape of carbon, where the competition between $sp, sp^2,$ and $sp^3$ hybridization states dictates material performance, we establish a closed-loop AI framework to explore this complex configurational space. We introduce a hybridization entropy descriptor to guide the search beyond conventional forms. Here, we establish a closed-loop AI framework that synergizes a Large Language Model (LLM) for structural generation with a Machine Learning Potential (MLP) for accelerated evaluation. Leveraging CrystaLLM to generate candidates and an iteratively refined MLP for high-fidelity validation, we screened thousands of structures to identify several stable allotropes with exotic properties. Specifically, we report ``yne-diamond C$_{12}$'' and ``yne-hex-diamond C$_{8}$'', which exhibit extreme thermal anisotropy and ultralow in-plane shear stiffness arising from their mixed $sp$-$sp^3$ hybridization. Furthermore, we discovered a complex $sp$-$sp^2$-$sp^3$ hybridized C$_{12}$ phase that combines metallic conductivity with an anomalous negative Poisson's ratio. Notably, we identified a superhard phase (C16_3) possessing a calculated Vickers hardness (103.3 GPa) exceeding that of diamond 96 GPa). Microscopic analysis reveals that thermal transport in these materials is governed by the interplay between rigid frameworks and flexible linkers. This work expands the known carbon phase space and demonstrates the efficacy of coupling generative AI with machine learning potentials for the accelerated inverse design of functional materials.

cond-mat.mtrl-sci↗

arXiv2025

Metavalent Bonding-Induced Phonon Hardening and Giant Anharmonicity in BeO

The search for materials with intrinsically low thermal conductivity ($κ_L$) is critical for energy applications, yet conventional descriptors often fail to capture the complex interplay between bonding and lattice dynamics. Here, first-principles calculations are used to contrast the thermal transport in covalent zincblende (zb) and metavalent rocksalt (rs) BeO. We find that the metavalent bonding in rs-BeO enhances lattice anharmonicity, activating multi-phonon scattering channels and suppressing phonon transport. This results in an ultralow $κ_L$ of 24 W m$^{-1}$ K$^{-1}$ at 300 K, starkly contrasting with the zb phase (357 W m$^{-1}$ K$^{-1}$). Accurately modeling such strongly anharmonic systems requires explicit inclusion of temperature-dependent phonon renormalization and four-phonon scattering. These contributions, negligible in zb-BeO, are essential for high-precision calculations of the severely suppressed $κ_L$ in rs-BeO. Finally, we identify three key indicators to guide the discovery of metavalently bonded, incipient-metallic materials: (i) an NaCl-type crystal structure, (ii) large Grüneisen parameters ($\textgreater$2), and (iii) a breakdown of the Lyddane-Sachs-Teller relation. These findings provide microscopic insight into thermal transport suppression by metavalent bonding and offer a predictive framework for identifying promising thermoelectrics and phase-change materials.

cond-mat.mtrl-sci↗

arXiv2025

Ambient-pressure superconductivity above 22 K in hole-doped YB2

Recent studies of hydrogen-dominant (superhydride) materials, such as LaH10 have led to putative discoveries of near-room temperature superconductivity at high pressures, with a superconducting transition temperature (Tc) of 250 K observed at 170 GPa. While these findings are promising, achieving such high superconductivity requires challenging experimental conditions typically exceeding 100 GPa. In this study, we utilize first-principles calculations and Migdal-Eliashberg theory to examine the superconducting properties of the stable boron-based compound YB2 at atmospheric pressure, where yttrium and boron atoms form a layered structure. Our results indicate that YB2 exhibits a Tc of 2.14 K at 0 GPa. We find that doping with additional electrons (0 to 0.3) leads to a monotonic decrease in Tc as the electron concentration increases. Conversely, introducing holes significantly enhances Tc, raising it to 22.83 K. Although our findings do not surpass the superconducting temperature of the well-known MgB2, our doping strategy highlights a method for tuning electron-phonon coupling strength in metal borides. This insight could be valuable for future experi-mental applications. Overall, this study not only deepens our understanding of YB2 superconducting properties but also contributes to the ongoing search for high-temperature superconductors.

cond-mat.supr-con↗

arXiv2025

Same-group element replacement enhances superconductivity in clathrate-like YH4

H3S, LaH10, and hydrogen-based compounds have garnered significant interest due to their high-temperature superconducting properties. However, the requirement for extremely high pressures limits their practical applications. In this study, YH4 is adopted as a base material, with partial substitution of Yttrium (Y) by Scandium (Sc), Lanthanum (La), and Zirconium (Zr). Pure YH4, stable at 120 GPa, exhibits a critical temperature (Tc) of 84-95 K. Substituting half of the Y atoms increases Tc to 124.43 K for (Y,Sc)H4 at 100 GPa but reduces it to 101.24 K for (Y,La)H4 at 120 GPa. In contrast, (Y,Zr)H4 at 200 GPa shows a further suppressed Tc of 69.55 K. The remarkable superconductivity in (Y,Sc)H4 might be related to its unique phonon dispersion without optical-acoustic gap, compressed Y-H bonds, and significant electron delocalization under pressure, collectively boosting electron-phonon interactions. Furthermore, the lowest optical phonons play a crucial role in the superconductivity of these materials. This work suggests that substituting Y with same-group metal elements is an effective strategy to enhance Tc in hydride superconductors.

cond-mat.supr-con↗

arXiv2025

Copper delocalization leads to ultralow thermal conductivity in chalcohalide CuBiSeCl2

Mixed anion halide-chalcogenide materials have attracted considerable attention due to their exceptional optoelectronic properties, making them promising candidates for various applications. Among these, CuBiSeCl_2 has recently been experimentally identified with remarkably low lattice thermal conductivity (k_L). In this study, we employ Wigner transport theory combined with neuroevolution machine learning potential (NEP)-assisted self-consistent phonon calculations to unravel the microscopic origins of this low k_L. Our findings reveal that the delocalization and weak bonding of copper atoms are key contributors to the strong phonon anharmonicity and wavelike tunneling (random walk diffusons). These insights deepen our understanding of the relationship between bonding characteristics, anharmonicity, delocalization, and vibrational dynamics, paving the way for the design and optimization of CuBiSeCl_2 and analogous materials for advanced phonon engineering applications.

cond-mat.mtrl-sci↗

arXiv2025

PINK: physical-informed machine learning for lattice thermal conductivity

Lattice thermal conductivity ($κ_L$) is crucial for efficient thermal management in electronics and energy conversion technologies. Traditional methods for predicting \k{appa}L are often computationally expensive, limiting their scalability for large-scale material screening. Empirical models, such as the Slack model, offer faster alternatives but require time-consuming calculations for key parameters such as sound velocity and the Gruneisen parameter. This work presents a high-throughput framework, physical-informed kappa (PINK), which combines the predictive power of crystal graph convolutional neural networks (CGCNNs) with the physical interpretability of the Slack model to predict \k{appa}L directly from crystallographic information files (CIFs). Unlike previous approaches, PINK enables rapid, batch predictions by extracting material properties such as bulk and shear modulus from CIFs using a well-trained CGCNN model. These properties are then used to compute the necessary parameters for $κ_L$ calculation through a simplified physical formula. PINK was applied to a dataset of 377,221 stable materials, enabling the efficient identification of promising candidates with ultralow $κ_L$ values, such as Ag$_3$Te$_4$W and Ag$_3$Te$_4$Ta. The platform, accessible via a user-friendly interface, offers an unprecedented combination of speed, accuracy, and scalability, significantly accelerating material discovery for thermal management and energy conversion applications.

cond-mat.mtrl-sci↗

arXiv2024

Bonding Hierarchy and Coordination Interaction Leading to High Thermoelectricity in Wide Bandgap TlAgI2

High thermoelectric properties are associated with the phonon-glass electron-crystal paradigm. Conventional wisdom suggests that the optimal bandgap of semiconductor to achieve the largest power factor should be between 6 and 10 kbT. To address challenges related to the bipolar effect and temperature limitations, we present findings on Zintl-type TlAgI2, which demonstrates an exceptionally low lattice thermal conductivity of 0.3 W m-1 K-1 at 300 K. The achieved figure of merit (ZT) for TlAgI2, featuring a 1.55 eV bandgap, reaches a value of 2.20 for p-type semiconductor. This remarkable ZT is attributed to the existence of extended antibonding states Ag-I in the valence band. Furthermore, the bonding hierarchy, influencing phonon anharmonicity, and coordination bonds, facilitating electron transfer between the ligand and the central metal ion, significantly contribute to electronic transport. This finding serves as a promising avenue for the development of high ZT materials with wide bandgaps at elevated temperatures.

cond-mat.mtrl-sci↗

arXiv2024

Machine learning for predicting ultralow thermal conductivity and high ZT in complex thermoelectric materials

Efficient and precise calculations of thermal transport properties and figure of merit, alongside a deep comprehension of thermal transport mechanisms, are essential for the practical utilization of advanced thermoelectric materials. In this study, we explore the microscopic processes governing thermal transport in the distinguished crystalline material Tl$_9$SbTe$_6$ by integrating a unified thermal transport theory with machine learning-assisted self-consistent phonon calculations. Leveraging machine learning potentials, we expedite the analysis of phonon energy shifts, higher-order scattering mechanisms, and thermal conductivity arising from various contributing factors like population and coherence channels. Our finding unveils an exceptionally low thermal conductivity of 0.31 W m$^{-1}$ K$^{-1}$ at room temperature, a result that closely correlates with experimental observations. Notably, we observe that the off-diagonal terms of heat flux operators play a significant role in shaping the overall lattice thermal conductivity of Tl$_9$SbTe$_6$, where the ultralow thermal conductivity resembles that of glass due to limited group velocities. Furthermore, we achieve a maximum $ZT$ value of 3.17 in the $c$-axis orientation for \textit{p}-type Tl$_9$SbTe$_6$ at 600 K, and an optimal $ZT$ value of 2.26 in the $a$-axis and $b$-axis direction for \textit{n}-type Tl$_9$SbTe$_6$ at 500 K. The crystalline Tl$_9$SbTe$_6$ not only showcases remarkable thermal insulation but also demonstrates impressive electrical properties owing to the dual-degeneracy phenomenon within its valence band. These results not only elucidate the underlying reasons for the exceptional thermoelectric performance of Tl$_9$SbTe$_6$ but also suggest potential avenues for further experimental exploration.

cond-mat.mtrl-sci↗

arXiv2024

Anomalous thermal conductivity in 2D silica nanocages of immobilizing noble gas atom

Noble gas atoms such as Kr and Xe are byproducts of nuclear fission in nuclear plants. How to trap and confine these volatile even radioactive gases is particularly challenging. Recent studies have shown that they can be trapped in nanocages of ultrathin silica. Here, we exhibit with self-consistent phonon theory and four-phonon (4ph) scattering where the adsorption of noble gases results in an anomalous increase in lattice thermal conductivity, while the presence of Cu atoms doping leads to a reduction in lattice thermal conductivity. We trace this behavior in host-guest 2D silica to an interplay of tensile strain, rattling phonon modes, and redistribution of electrons. We also find that 4ph scatterings play indispensable roles in the lattice thermal conductivity of 2D silica. Our work illustrates the microscopic heat transfer mechanism in 2D silica nanocages with the immobilization of noble gas atoms and inspires further exploring materials with the kagome and glasslike lattice thermal conductivity.

cond-mat.mtrl-sci↗

arXiv2024

Measuring the X-ray luminosities of DESI groups from eROSITA Final Equatorial-Depth Survey: I. X-ray luminosity -- halo mass scaling relation

We use the eROSITA Final Equatorial-Depth Survey (eFEDS) to measure the rest-frame 0.1-2.4 keV band X-ray luminosities of $\sim$ 600,000 DESI groups using two different algorithms in the overlap region of the two observations. These groups span a large redshift range of $0.0 \le z_g \le 1.0$ and group mass range of $10^{10.76}h^{-1}M_{\odot} \le M_h \le 10^{15.0}h^{-1}M_{\odot}$. (1) Using the blind detection pipeline of eFEDS, we find that 10932 X-ray emission peaks can be cross matched with our groups, $\sim 38 \%$ of which have signal-to-noise ratio $\rm{S}/\rm{N} \geq 3$ in X-ray detection. Comparing to the numbers reported in previous studies, this matched sample size is a factor of $\sim 6$ larger. (2) By stacking X-ray maps around groups with similar masses and redshifts, we measure the average X-ray luminosity of groups as a function of halo mass in five redshift bins. We find, in a wide halo mass range, the X-ray luminosity, $L_{\rm X}$, is roughly linearly proportional to $M_{h}$, and is quite independent to the redshift of the groups. (3) We use a Poisson distribution to model the X-ray luminosities obtained using two different algorithms and obtain best-fit $L_{\rm X}=10^{28.46\pm0.03}M_{h}^{1.024\pm0.002}$ and $L_{\rm X}=10^{26.73 \pm 0.04}M_{h}^{1.140 \pm 0.003}$ scaling relations, respectively. The best-fit slopes are flatter than the results previously obtained, but closer to a self-similar prediction.

astro-ph.GA↗

arXiv2023

High-Sensitive Microwave Electrometry with Enhanced Instantaneous Bandwidth

Rydberg microwave (MW) sensors are superior to conventional antenna-based techniques because of their wide operating frequency range and outstanding potential sensitivity. Here, we demonstrate a Rydberg microwave receiver with a high sensitivity of $62\,\mathrm{nV} \mathrm{cm}^{-1} \mathrm{Hz}^{-1/2}$ and broad instantaneous bandwidth of up to $10.2\,\mathrm{MHz}$. Such excellent performance was achieved by the amplification of one generated sideband wave induced by the strong coupling field in the six-wave mixing process of the Rydberg superheterodyne receiver, which was well predicted by our theory. Our system, which possesses a uniquely enhanced instantaneous bandwidth and high-sensitivity features that can be improved further, will promote the application of Rydberg microwave electrometry in radar and communication.

quant-ph↗

arXiv2021

Determine the Masses and Ages of Red Giant Branch Stars from Low-resolution LAMOST Spectra Using DenseNet

We propose a new model to determine the ages and masses of red giant branch (RGB) stars from the low-resolution large sky area multi-object fiber spectroscopic telescope (LAMOST) spectra. The ages of RGB stars are difficult to determine using classical isochrone fitting techniques in the Hertzsprung-Russell diagram, because isochrones of RGB stars are tightly crowned. With the help of the asteroseismic method, we can determine the masses and ages of RGB stars accurately. Using the ages derived from the asteroseismic method, we train a deep learning model based on DenseNet to calculate the ages of RGB stars directly from their spectra. We then apply this model to determine the ages of 512 272 RGB stars from LAMOST DR7 spectra (see http://dr7.lamost.org/). The results show that our model can estimate the ages of RGB stars from low-resolution spectra with an accuracy of 24.3%. The results on the open clusters M 67, Berkeley 32, and NGC 2420 show that our model performs well in estimating the ages of RGB stars. Through comparison, we find that our method performs better than other methods in determining the ages of RGB stars. The proposed method can be used in the stellar parameter pipeline of upcoming large surveys such as 4MOST, WEAVES, and MOONS.

astro-ph.SR↗