arXiv subjects

Jingchao Liu

Publications and source records attributed to Jingchao Liu.

4 recordsLinked to original sources

arXiv2026

Signatures of spin-polarized p-wave superconductivity in the kagome material RbV$_3$Sb$_5$

The study of kagome materials has attracted much attention in the past few years due to the presence of many electron-electron interaction-driven phases in a single material. These include charge density waves, nematic phases, superconducting phases, and pair density waves. In this work, we report the discovery of intrinsic spin-polarized p-wave superconductivity in the thin-flake kagome material RbV$_3$Sb$_5$. Firstly, when an in-plane magnetic field is swept in opposite directions, we observe a unique form of hysteresis in magnetoresistance which is different from the hysteresis induced by extrinsic mechanisms such as flux-trapping or superheating and supercooling effects. The unconventional hysteresis indicates the emergence of an intrinsic time-reversal symmetry-breaking superconducting phase. Strikingly, at a fixed magnetic field, the finite-resistance state can be transitioned into the superconducting state by applying and subsequently removing a large current. Secondly, at temperatures around 400 mK, the re-entrance of superconductivity occurs during an in-plane field-sweeping process. This kind of re-entrance is asymmetric about the zero field axis and observed in all field directions for a fixed current direction, which is different from the re-entrance observed in conventional superconductors. These findings put very strong constraints on the possible superconducting pairing symmetry of RbV$_3$Sb$_5$. We point out that the pairing symmetry, which is consistent with the crystal symmetry and all the observed novel properties, is possibly a time-reversal symmetry-breaking, p-wave pairing with net spin polarization. Importantly, this p-wave pairing gives rise to a nodal topological superconducting state with Majorana flat bands on the sample edges.

cond-mat.str-el↗

arXiv2025

Switchable half-quantum flux states in a ring of the kagome superconductor CsV$_3$Sb$_5$

Magnetic flux quantization in units of $Φ_0 = h/2e$ is a defining feature of superconductivity, rooted in the charge-2e nature of Cooper pairs. In a ring geometry, the flux quantization leads to oscillations in the critical temperature with magnetic flux, known as the Little-Parks effect. While the maximal critical temperature is conventionally at zero flux, departures from this rule, for instance shifts by a half-quantum flux $Φ_0/2$, clearly signal unconventional superconducting states and require sign-changing order parameters. Historically, such $π$-phase shifts in Little-Parks oscillations have been found in tricrystals or engineered ring structures that intentionally incorporate a $π$-phase shift. Here we report the discovery of switchable half-quantum flux states in rings made from single crystals of the kagome superconductor CsV$_3$Sb$_5$. We observe Little-Parks oscillations with a $π$-phase shift at zero bias current, which can be reversibly tuned to conventional Little-Parks oscillations upon applying a bias current. Between the $π$-phase and 0-phase regimes, $h/4e$ periodic oscillations appear. Our observations suggest unconventional pairing, potentially in the form of a multicomponent order parameter in the kagome superconductor CsV$_3$Sb$_5$, and reveal an electrically tunable landscape of competing superconducting condensates and fractional flux states.

cond-mat.supr-con↗

arXiv2021

ARM: A Confidence-Based Adversarial Reweighting Module for Coarse Semantic Segmentation

Coarsely-labeled semantic segmentation annotations are easy to obtain, but therefore bear the risk of losing edge details and introducing background pixels. Impeded by the inherent noise, existing coarse annotations are only taken as a bonus for model pre-training. In this paper, we try to exploit their potentials with a confidence-based reweighting strategy. To expand, loss-based reweighting strategies usually take the high loss value to identify two completely different types of pixels, namely, valuable pixels in noise-free annotations and mislabeled pixels in noisy annotations. This makes it impossible to perform two tasks of mining valuable pixels and suppressing mislabeled pixels at the same time. However, with the help of the prediction confidence, we successfully solve this dilemma and simultaneously perform two subtasks with a single reweighting strategy. Furthermore, we generalize this strategy into an Adversarial Reweighting Module (ARM) and prove its convergence strictly. Experiments on standard datasets shows our ARM can bring consistent improvements for both coarse annotations and fine annotations. Specifically, built on top of DeepLabv3+, ARM improves the mIoU on the coarsely-labeled Cityscapes by a considerable margin and increases the mIoU on the ADE20K dataset to 47.50.

cs.CV↗

arXiv2019

Pyramid Mask Text Detector

Scene text detection, an essential step of scene text recognition system, is to locate text instances in natural scene images automatically. Some recent attempts benefiting from Mask R-CNN formulate scene text detection task as an instance segmentation problem and achieve remarkable performance. In this paper, we present a new Mask R-CNN based framework named Pyramid Mask Text Detector (PMTD) to handle the scene text detection. Instead of binary text mask generated by the existing Mask R-CNN based methods, our PMTD performs pixel-level regression under the guidance of location-aware supervision, yielding a more informative soft text mask for each text instance. As for the generation of text boxes, PMTD reinterprets the obtained 2D soft mask into 3D space and introduces a novel plane clustering algorithm to derive the optimal text box on the basis of 3D shape. Experiments on standard datasets demonstrate that the proposed PMTD brings consistent and noticeable gain and clearly outperforms state-of-the-art methods. Specifically, it achieves an F-measure of 80.13% on ICDAR 2017 MLT dataset.

cs.CV↗