papers

Publications (19)

quant-ph2022

Titanium Nitride Film on Sapphire Substrate with Low Dielectric Loss for Superconducting Qubits

Hao Deng, Zhijun Song, Ran Gao +19

Dielectric loss is one of the major decoherence sources of superconducting qubits. Contemporary high-coherence superconducting qubits are formed by material systems mostly consisti…

cond-mat.mtrl-sci2021

Microwave response in a topological superconducting quantum interference device

Wei Pan, Daniel Soh, Wenlong Yu +2

Photon detection at microwave frequency is of great interest due to its application in quantum computation information science and technology. Herein are results from studying micr…

cs.CR2026

SFCoT: Safer Chain-of-Thought via Active Safety Evaluation and Calibration

Yu Pan, Wenlong Yu, Tiejun Wu +4

Large language models (LLMs) have demonstrated remarkable capabilities in complex reasoning tasks. However, they remain highly susceptible to jailbreak attacks that undermine their…

quant-ph2021

Fluxonium: an alternative qubit platform for high-fidelity operations

Feng Bao, Hao Deng, Dawei Ding +25

Superconducting qubits provide a promising path toward building large-scale quantum computers. The simple and robust transmon qubit has been the leading platform, achieving multipl…

cs.CV2025

CoE: Chain-of-Explanation via Automatic Visual Concept Circuit Description and Polysemanticity Quantification

Wenlong Yu, Qilong Wang, Chuang Liu +2

Explainability is a critical factor influencing the wide deployment of deep vision models (DVMs). Concept-based post-hoc explanation methods can provide both global and local insig…

cs.CV2026

Fine-Grained Generalization via Structuralizing Concept and Feature Space into Commonality, Specificity and Confounding

Zhen Wang, Jiaojiao Zhao, Qilong Wang +2

Fine-Grained Domain Generalization (FGDG) presents greater challenges than conventional domain generalization due to the subtle inter-class differences and relatively pronounced in…

physics.app-ph2023

Epitaxial titanium nitride microwave resonators: Structural, chemical, electrical, and microwave properties

Ran Gao, Wenlong Yu, Hao Deng +6

Titanium nitride is an attractive material for a range of superconducting quantum-circuit applications owing to its low microwave losses, high surface inductance, and chemical stab…

hep-ph2025

Scalable architecture for dark photon searches: Superconducting-qubit proof of principle

Runqi Kang, Qingqin Hu, Xiao Cai +4

The dark photon is a well-motivated candidate of dark matter due to its potential to open the window of new physics beyond the Standard Model. A fundamental mass-range-sensitivity…

cond-mat.supr-con2022

Leggett Modes in Dirac Semimetals

Joseph J. Cuozzo, Wenlong Yu, Paul Davids +4

In recent years experimentalists have been able to clearly show that several materials, such as MgB2, iron-based superconductors3, monolayer NbSe2, are multiband superconductors. S…

cond-mat.mes-hall2017

Strong Photothermoelectric Response and Contact Reactivity of the Dirac Semimetal ZrTe5

François Léonard, Wenlong Yu, Kimberlee C. Collins +4

The family of three-dimensional topological insulators opens new avenues to discover novel photophysics and to develop novel types of photodetectors. ZrTe5 has been shown to be a D…

cond-mat.supr-con2014

Giant supercurrent states in a superconductor-InAs/GaSb-superconductor junction

Xiaoyan Shi, Wenlong Yu, Zhigang Jiang +4

Superconductivity in topological materials has attracted a great deal of interest in both electron physics and material sciences since the theoretical predictions that Majorana fer…

cs.AI2026

Teaching the Way, Not the Answer: Privileged Tutoring Distillation for Multimodal Policy Optimization

Shizhe Xiang, Ke An, Wenlong Yu +4

Recent post-training methods, particularly Reinforcement Learning with Verifiable Rewards (RLVR), have significantly enhanced the reasoning ability of Large Vision-Language Models…

quant-ph2023

Ultrahigh-inductance materials from spinodal decomposition

Ran Gao, Hsiang-Sheng Ku, Hao Deng +10

Disordered superconducting nitrides with kinetic inductance have long been considered a leading material candidate for high-inductance quantum-circuit applications. Despite continu…

cond-mat.supr-con2026

Buried Dirac points in quantum spin Hall insulators: Implications for Majorana Kramers pair-based quantum computing

Joseph J. Cuozzo, Wenlong Yu, Xiaoyan Shi +5

For heterostructures formed by a quantum spin Hall insulator (QSHI) placed in proximity to a superconductor (SC), no external magnetic field is necessary to drive the system into a…

cond-mat.mes-hall2013

Probing terahertz surface plasmon waves in graphene structures

Oleg Mitrofanov, Wenlong Yu, Robert J. Thompson +6

Epitaxial graphene mesas and ribbons are investigated using terahertz (THz) nearfield microscopy to probe surface plasmon excitation and THz transmission properties on the sub-wave…

cond-mat.supr-con2018

π and 4π Josephson Effects Mediated by a Dirac Semimetal

Wenlong Yu, Wei Pan, Douglas L. Medlin +4

Cd3As2 is a three-dimensional topological Dirac semimetal with connected Fermi-arc surface states. It has been suggested that topological superconductivity can be achieved in the n…

cs.CV2026

Histopathological Spectrum-Guided Prostate Stratification via Segmentation-Assisted Diagnostic Transformer

Leyang Li, Lihua Chen, Huangang Hu +7

Prostate cancer diagnosis with multiparametric MRI (mpMRI) is commonly based on PI-RADS assessment or binary classification, which suffer from subjectivity and fail to capture clin…

cond-mat.mes-hall2014

Superconducting proximity effect in inverted InAs/GaSb quantum well structures with Ta electrodes

Wenlong Yu, Yuxuan Jiang, Chao Huan +5

We present our recent electronic transport results in top-gated InAs/GaSb quantum well hybrid structures with superconducting Ta electrodes. We show that the transport across the I…

cs.CV2025

Fine-Grained Domain Generalization with Feature Structuralization

Wenlong Yu, Dongyue Chen, Qilong Wang +1

Fine-grained domain generalization (FGDG) is a more challenging task than traditional DG tasks due to its small inter-class variations and relatively large intra-class disparities.…