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Xiaoping Ma

Publications and source records attributed to Xiaoping Ma.

17 recordsLinked to original sources
arXiv2026

Anomalous charge density wave in a two-dimensional superatomic superconductor

The spatial modulation of electron density into a wave-like pattern, known as charge density wave (CDW), represents a fundamental quantum state that often coexists with superconductivity, quantum Hall states, axion insulating phases and etc. Conventional CDWs are mediated by longitudinal acoustic phonons, exhibit picometer-scale lattice distortions ($10^{-12}$--$10^{-11}$ m), and typically vanish approaching the atomic limit. Here, we report a series of anomalous CDW behaviors in the 2D superatomic superconductor Au$_6$Te$_{12}$Se$_8$. Remarkably, its CDW is governed by transverse phonons, accompanied by an extraordinarily high real-space displacement of $\sim 4$ \AA ngstr\"om. Furthermore, we observe an exotic dimensional response persisting up to micrometer-scale thickness, a regime where other materials are already considered as bulk. Through liquid helium-temperature transmission electron microscopy, ultrafast pump-probe spectroscopy and transport measurements, we demonstrate a dramatic enhancement of the CDW transition temperature ($T_{\text{CDW}}$) from $<2$ K in the bulk to 110 K in approaching the ``superatomic limit''. Our findings not only reveal novel facets of both CDW and superatomic materials, but the competition between this anomalous CDW and superconductivity opens avenues for exploring unconventional electron-phonon interactions.

cond-mat.supr-con↗
arXiv2026

The superite phase and phase transition inducing multiscale solidification microstructures and segregations in steels

Based on classical concept, solidification of alloys is a direct transition from liquid phase to solid phase, by which dendrites and dendritic segregation are produced. Through in-situ and real time morphology observation and XRD test during solidification of three steels, a new superite phase featured as statistically oriented tiny structures was identified, and a general liquid-superite-solid phase transformation process is revealed. In the early solidification stage, the liquid alloys transit to dendrites composed of superite phase. Initiated from the boundaries of dendritic arms or dendrite grains, the superite phase transits to austenite grains within an initial dendritic arm, and expels solute elements to the residual superite phase. Mixed multi-phase microstructures are subsequently produced from the residual enriched superite phase. Here, although three steels exhibit different phase proportion and phase constitution in the superite-solid transition, they all follow above general transition mode. Multiscale microstructures and segregations are produced in the transition from superite to solid. These new findings change the basic understanding about the solidification of alloys, rediscover the formation mechanism on segregations and multiscale solidification microstructures, including dendrite pattern, solid dendritic arm, dendritic segregation, the mixed multi-phase microstructures, eutectic, inclusions and precipitate. These new findings are also crucial to the control of solidification microstructures and segregation in metals.

cond-mat.mtrl-sci↗
arXiv2026

Multitask-Informed Prior for In-Context Learning on Tabular Data: Application to Steel Property Prediction

Accurate prediction of mechanical properties of steel during hot rolling processes, such as Thin Slab Direct Rolling (TSDR), remains challenging due to complex interactions among chemical compositions, processing parameters, and resultant microstructures. Traditional empirical and experimental methodologies, while effective, are often resource-intensive and lack adaptability to varied production conditions. Moreover, most existing approaches do not explicitly leverage the strong correlations among key mechanical properties, missing an opportunity to improve predictive accuracy through multitask learning. To address this, we present a multitask learning framework that injects multitask awareness into the prior of TabPFN--a transformer-based foundation model for in-context learning on tabular data--through novel fine-tuning strategies. Originally designed for single-target regression or classification, we augment TabPFN's prior with two complementary approaches: (i) target averaging, which provides a unified scalar signal compatible with TabPFN's single-target architecture, and (ii) task-specific adapters, which introduce task-specific supervision during fine-tuning. These strategies jointly guide the model toward a multitask-informed prior that captures cross-property relationships among key mechanical metrics. Extensive experiments on an industrial TSDR dataset demonstrate that our multitask adaptations outperform classical machine learning methods and recent state-of-the-art tabular learning models across multiple evaluation metrics. Notably, our approach enhances both predictive accuracy and computational efficiency compared to task-specific fine-tuning, demonstrating that multitask-aware prior adaptation enables foundation models for tabular data to deliver scalable, rapid, and reliable deployment for automated industrial quality control and process optimization in TSDR.

cs.LG↗
arXiv2025

Pronounced orbital-selective electron-electron correlation and electron-phonon coupling in V2Se2O

Orbital-selective many-body effects, in which electrons occupying different orbitals experience distinct interaction strengths, play a crucial role in correlated multiorbital materials. However, these effects usually manifest in a complex manner, obscuring their microscopic origins. Here, by combining angle-resolved photoemission spectroscopy measurements with theoretical calculations, we reveal pronounced orbital selectivity in both electron-electron correlation and electron-phonon coupling in the van der Waals material V2Se2O. Electron correlation induces distinct bandwidth renormalization exclusively in the V d_xy-derived band, while the bands mainly composed of the other d orbitals remain essentially unrenormalized. Orbital-resolved analyses identify that the filling number and the bandwidth are decisive factors governing orbital-dependent correlation. Simultaneously, the d_(xz/yz)-derived band exhibits a sharp kink anomaly, arising from enhanced coupling to high-energy phonon modes dominated by oxygen vibrations. Such pronounced orbital selectivity positions V2Se2O as a rare and prototypical platform for unravelling the microscopic mechanisms of orbital-selective electron-electron and electron-phonon interactions, and offers guiding principles for the design of correlated multiorbital materials.

cond-mat.str-el↗
arXiv2025

Exceedingly large in-plane critical field of finite-momentum pairing state in bulk superlattices

Magnetic flux profoundly influences the phase factor of charge particles, leading to exotic quantum phenomena. A recent example is that the orbital effect of magnetic field could induce finite-momentum pairing state in nanoflakes, which offers a new pathway to realize the spatially modulated superconductivity distinct from the Fulde-Ferrell-Larkin-Ovchinnikov (FFLO) state induced by Zeeman effect. However, whether such intriguing state can exist in the bulk materials under extremely large magnetic field remains elusive. Here we report the orbital effect induced finite-momentum pairing state with exceedingly large in-plane critical field in a bulk superconducting superlattice. Remarkably, the in-plane critical field shows a pronounced upturn behavior, exceeding eight times the Pauli limit which is comparable to monolayer Ising superconductor. Under high in-plane magnetic fields, significant anisotropic transport behavior between the interlayer and intralayer directions is detected, highlighting the critical role of suppressed interlayer coherence in the orbital effect induced finite-momentum pairing state. Crucially, this finite-momentum pairing state remains robust against moderate disorder. Our findings suggest that van der Waals superlattices, with strong Ising spin-orbit coupling and tunable interlayer coherence, offer new avenues for constructing and modulating unconventional superconducting states.

cond-mat.supr-con↗
arXiv2025

Absence of diode effect in chiral type-I superconductor NbGe2

Symmetry elegantly governs the fundamental properties and derived functionalities of condensed matter. For instance, realizing the superconducting diode effect (SDE) demands breaking space-inversion and time-reversal symmetries simultaneously. Although the SDE is widely observed in various platforms, its underlying mechanism remains debated, particularly regarding the role of vortices. Here, we systematically investigate the nonreciprocal transport in the chiral type-I superconductor NbGe2. Moreover, we induce type-II superconductivity with elevated superconducting critical temperature on the artificial surface by focused ion beam irradiation, enabling control over vortex dynamics in NbGe2 devices. Strikingly, we observe negligible diode efficiency (Q < 2%) at low magnetic fields, which rises significantly to Q ~ 50% at high magnetic fields, coinciding with an abrupt increase in vortex creep rate when the superconductivity of NbGe2 bulk is suppressed. These results unambiguously highlight the critical role of vortex dynamics in the SDE, in addition to the established symmetry rules.

cond-mat.supr-con↗
arXiv2024

Bulk high-temperature superconductivity in the high-pressure tetragonal phase of bilayer La2PrNi2O7

The Ruddlesden-Popper (R-P) bilayer nickelate, La3Ni2O7, was recently found to show signatures of high-temperature superconductivity (HTSC) at pressures above 14 GPa. Subsequent investigations achieved zero resistance in single- and poly-crystalline samples under hydrostatic pressure conditions. Yet, obvious diamagnetic signals, the other hallmark of superconductors, are still lacking owing to the filamentary nature with low superconducting volume fraction. The presence of a novel "1313" polymorph and competing R-P phases obscured proper identification of the phase for HTSC. Thus, achieving bulk HTSC and identifying the phase at play are the most prominent tasks at present. Here, we address these issues in the praseodymium (Pr)-doped La2PrNi2O7 polycrystalline samples. We find that the substitutions of Pr for La effectively inhibits the intergrowth of different R-P phases, resulting in nearly pure bilayer structure. For La2PrNi2O7, pressure-induced orthorhombic-to-tetragonal structural transition takes place at Pc ~ 11 GPa, above which HTSC emerges gradually upon further compression. The superconducting transition temperatures at 18-20 GPa reach Tconset = 82.5 K and Tczero = 60 K, which are the highest values among known nickelate superconductors. More importantly, bulk HTSC was testified by detecting clear diamagnetic signals below ~75 K corresponding to an estimated superconducting volume fraction ~ 57(5)% at 20 GPa. Our results not only resolve the existing controversies but also illuminate directions for exploring bulk HTSC in the bilayer nickelates.

cond-mat.supr-con↗
arXiv2023

Enhanced phase sensitivity in a Mach-Zehnder interferometer via photon recycling

We propose an alternative scheme for phase estimation in a Mach-Zehnder interferometer (MZI) with photon recycling. It is demonstrated that with the same coherent-state input and homodyne detection, our proposal possesses a phase sensitivity beyond the traditional MZI. For instance, it can achieve an enhancement factor of 9.32 in the phase sensitivity compared with the conventional scheme even with a photon loss of 10% on the photon-recycled arm. From another point of view, the quantum Cramer-Rao bound (QCRB) is also investigated. It is found that our scheme is able to achieve a lower QCRB than the traditional one. Intriguingly, the QCRB of our scheme is dependent of the phase shift phi while the traditional scheme has a constant QCRB regardless of the phase shift. Finally, we present the underlying mechanisms behind the enhanced phase sensitivity. We believe that our results provide another angle from which to enhance the phase sensitivity in a MZI via photon recycling.

quant-ph↗
arXiv2022

Optimizing Ghost Imaging via Analysis and Design of Speckle Patterns

We study the influence rules of the speckle size of light source on ghost imaging, and propose a new type of speckle patterns to improve the quality of ghost imaging. The results show that the image quality will first increase and then decrease with the increase of the speckle size, and there is an optimal speckle size for a specific object. Moreover, by using the random distribution of speckle positions, a new type of displacement speckle patterns is designed, and the imaging quality is better than that of the random speckle patterns. These results are of great significances for finding the best speckle patterns suitable for detecting targets, which further promotes the practical applications of ghost imaging.

physics.optics↗
arXiv2019

Deep Single Image Deraining Via Estimating Transmission and Atmospheric Light in rainy Scenes

Rain removal in images/videos is still an important task in computer vision field and attracting attentions of more and more people. Traditional methods always utilize some incomplete priors or filters (e.g. guided filter) to remove rain effect. Deep learning gives more probabilities to better solve this task. However, they remove rain either by evaluating background from rainy image directly or learning a rain residual first then subtracting the residual to obtain a clear background. No other models are used in deep learning based de-raining methods to remove rain and obtain other information about rainy scenes. In this paper, we utilize an extensively-used image degradation model which is derived from atmospheric scattering principles to model the formation of rainy images and try to learn the transmission, atmospheric light in rainy scenes and remove rain further. To reach this goal, we propose a robust evaluation method of global atmospheric light in a rainy scene. Instead of using the estimated atmospheric light directly to learn a network to calculate transmission, we utilize it as ground truth and design a simple but novel triangle-shaped network structure to learn atmospheric light for every rainy image, then fine-tune the network to obtain a better estimation of atmospheric light during the training of transmission network. Furthermore, more efficient ShuffleNet Units are utilized in transmission network to learn transmission map and the de-raining image is then obtained by the image degradation model. By subjective and objective comparisons, our method outperforms the selected state-of-the-art works.

cs.CV↗
arXiv2018

Conclusive Precision Bounds for SU(1,1) Interferometers

In this paper, we revisit the quantum Fisher information (QFI) calculation in SU(1,1) interferometer considering different phase configurations. When one of the input modes is a vacuum state, we show by using phase averaging, different phase configurations give same QFI. In addition, by casting the phase estimation as a two-parameter estimation problem, we show that the calculation of the quantum Fisher information matrix (QFIM) is necessary in general. Particularly, within this setup, the phase averaging method is equivalent to a two parameter estimation problem. We also calculate the phase sensitivity for different input states using QFIM approach.

quant-ph↗
arXiv2017

Enhanced signal-to-noise ratio in Hanbury Brown Twiss interferometry by parametric amplification

The Hanbury Brown Twiss (HBT) interferometer was proposed to observe intensity correlations of starlight to measure a star's angular diameter. As the intensity of light that reaches the detector from a star is very weak, one cannot usually get a workable signal-to-noise ratio. We propose an improved HBT interferometric scheme introducing optical parametric amplifiers into the system, to amplify the correlation signal, which is used to calculate the angular diameter. With the use of optical parametric amplifiers, the signal-to-noise ratio can be increased up to 400 percent.

quant-ph↗
arXiv2013

The interface heterogeneous nucleation and dynamic dispersion of nuclei in solidification process

By comparing the grain sizes under different nucleation conditions, the different nucleation mechanisms were investigated. The primitive nuclei origin at some specific interface, and subsequently disperse into the bulk melt with melt flow. The survival probability of nuclei decides the nuclei density in bulk melt, and the growth of survived nuclei finally constitutes the solidified grains. The nucleation process is highly dynamic, evolving and variable with actual experimental condition and production condition.

cond-mat.mtrl-sci↗
arXiv2013

Innate character and theory model about channel segregation in a sand mold steel ingot

The channel segregation is a severe casting defect in steel ingots. The formation of channel segregation is generally attributed to the solute partition and the interdendritic thermosolutal convection in the mushy zone. In this article, the channel segregation in a steel ingot was carefully characterized by detailed experimental observation. A different formation mechanism for the channel segregation was revealed. In the mushy zone of the ingot, large amount of separate MnS inclusions move laterally and upwards. Some MnS inclusions will remain in the moving trace of inclusions. Such residual MnS inclusions appear as large amount of separate MnS inclusion chains. In the subsequent solid phase transition process, promoted by the MnS chains, ferrite prefers to forms form the austenite near the MnS inclusions and shows as large amount of separate ferrite chains. Large amount of ferrite chains align in a strip-like zone, which results in so called channel segregation in macro-etching. The physical model about the driving force for the MnS movement is further theoretically analyzed. In the mushy zone, the interface tension resultant applied on the MnS inclusions can act as the drive force for the lateral movement of MnS inclusions. And the buoyance applied on the MnS inclusions act as the drive force for the upwards movement.

cond-mat.mtrl-sci↗
arXiv2013

Microsegregation and dendritic growth mode of Al-5wt%Cu alloy based on non-equilibrium mush zone model

The microsegregation and dendritic growth mode of Al-5wt%Cu alloy was investigated. In the early solidification stage, the crystal growth mode of interrupted growth and periodic boundary trapping will happen, which results in the segregationless dendritic grains. Microsegregation only exists at the final solidification stage with extremely tiny residual melt fraction. In the tiny residual melt zone, the diffusion of solute from the enriched boundary layer to the residual melt and the convergence of enriched boundaries produce the final microsegregation.

cond-mat.mtrl-sci↗
arXiv2013

How Channel Segregates Originates: The Flow of Accumulated Impurity Clusters in Solidifying Steels

The phenomenon, channel segregates (CS) as a result of gravity-driven flow due to density contrast occurred in the solid-liquid mushy zones1during solidification, often causes the severe destruction of homogeneity and even some fatal damages. Investigation on its mechanism sheds light on the understanding and controlling of the formation of solidifying metals,earth's core, igneous rock and sea ice. Until now, it still remains controversial what composes the density contrasts and, to what extent, how it affects channel segregates. Here, we show that in experimental 500kg and 100 ton commercial cast steel ingots CS originates from oxide Al2O3/MnS impurity clusters (OICs) initially nucleated from the oxide (Al2O3) particles, which induce an extra flow due to sharp density contrast between clusters and melt. The results uncover that, as OICs enrich and grow, their driven flow becomes stronger than the traditionally recognized inter-dendritic thermo-solutal convection, dominating the subsequent opening of the channels. This study extends the classical macrosegregation theory, highlights a significant technological breakthrough to control CS, and could quickly yield practical benefits to the worldwide manufacture of over 50 million tons of ingots, super-thick slab and heavy castings annually, as well as has general implications for the elaboration of other related natural phenomena.

cond-mat.mtrl-sci↗