arXiv subjects

Zheng Han

Publications and source records attributed to Zheng Han.

At least 19 recordsLinked to original sources

arXiv2026

ARport: An Augmented Reality System for Markerless Image-Guided Port Placement in Robotic Surgery

Purpose: Precise port placement is a critical step in robot-assisted surgery, where port configuration influences both visual access to the operative field and instrument maneuverability. To bridge the gap between preoperative planning and intraoperative execution, we present ARport, an augmented reality (AR) system that automatically maps pre-planned trocar layouts onto the patient's body surface, providing intuitive spatial guidance during surgical preparation. Methods: ARport, implemented on an optical see-through head-mounted display (OST-HMD), operates without any external sensors or markers, simplifying setup and enhancing workflow integration. It reconstructs the operative scene from RGB, depth, and pose data captured by the OST-HMD, extracts the patient's body surface using a foundation model, and performs surface-based markerless registration to align preoperative anatomical models to the extracted patient's body surface, enabling in-situ visualization of planned trocar layouts. A demonstration video illustrating the overall workflow is available online. Results: In full-scale human-phantom experiments, ARport accurately overlaid pre-planned trocar sites onto the physical phantom, achieving consistent spatial correspondence between virtual plans and real anatomy. Conclusion: ARport provides a fully marker-free and hardware-minimal solution for visualizing preoperative trocar plans directly on the patient's body surface. The system facilitates efficient intraoperative setup and demonstrates potential for seamless integration into routine clinical workflows.

cs.CV↗

arXiv2025

Toward Reliable AR-Guided Surgical Navigation: Interactive Deformation Modeling with Data-Driven Biomechanics and Prompts

In augmented reality (AR)-guided surgical navigation, preoperative organ models are superimposed onto the patient's intraoperative anatomy to visualize critical structures such as vessels and tumors. Accurate deformation modeling is essential to maintain the reliability of AR overlays by ensuring alignment between preoperative models and the dynamically changing anatomy. Although the finite element method (FEM) offers physically plausible modeling, its high computational cost limits intraoperative applicability. Moreover, existing algorithms often fail to handle large anatomical changes, such as those induced by pneumoperitoneum or ligament dissection, leading to inaccurate anatomical correspondences and compromised AR guidance. To address these challenges, we propose a data-driven biomechanics algorithm that preserves FEM-level accuracy while improving computational efficiency. In addition, we introduce a novel human-in-the-loop mechanism into the deformation modeling process. This enables surgeons to interactively provide prompts to correct anatomical misalignments, thereby incorporating clinical expertise and allowing the model to adapt dynamically to complex surgical scenarios. Experiments on a publicly available dataset demonstrate that our algorithm achieves a mean target registration error of 3.42 mm. Incorporating surgeon prompts through the interactive framework further reduces the error to 2.78 mm, surpassing state-of-the-art methods in volumetric accuracy. These results highlight the ability of our framework to deliver efficient and accurate deformation modeling while enhancing surgeon-algorithm collaboration, paving the way for safer and more reliable computer-assisted surgeries.

cs.CV↗

arXiv2024

Quantized Landau-level crossing checkerboard in large-angle twisted graphene

When charge transport occurs under conditions like topological protection or ballistic motion, the conductance of low-dimensional systems often exhibits quantized values in units of $e^{2}/h$, where $e$ and $h$ are the elementary charge and Planck's constant. Such quantization has been pivotal in quantum metrology and computing. Here, we demonstrate a novel quantized quantity: the ratio of the displacement field to the magnetic field, $D/B$, in large-twist-angle bilayer graphene. In the high magnetic field limit, Landau level crossings between the top and bottom layers manifest equal-sized checkerboard patterns throughout the $D/B$-$\nu$ space. It stems from a peculiar electric-field-driven interlayer charge transfer at one elementary charge per flux quantum, leading to quantized intervals of critical displacement fields, (i.e., $\delta D$ = $\frac{e}{2\pi l_{B}^{2}}$, where $l_B$ is the magnetic length). Our findings suggest that interlayer charge transfer in the quantum Hall regime can yield intriguing physical phenomena, which has been overlooked in the past.

cond-mat.mes-hall↗

arXiv2024

A spiral sampling method for calculating the complex orbital angular momentum spectrum

OAM spectrum reflects the OAM component included in measured light field which is crucial in OAM -based application. However, traditional definition-based OAM spectrum algorithm is extraordinary time-consuming and limited to prior knowledge severely. To overcome it, in this paper, we propose a novel method to calculate the complex spectrum. After spiral sampling and Fourier transform, one can retrieve the radial coefficient of arbitrary OAM component by proper filtering and inverse Fourier transform. The simulation results reveal that the Mean Absolute Error (MAE) between retrieved one and target could reach at 0.0221 and 0.0199 on average for amplitude and phase respectively after normalized. This method could provide a powerful tool for future OAM-based and application.

physics.optics↗

arXiv2024

A Review on Organ Deformation Modeling Approaches for Reliable Surgical Navigation using Augmented Reality

Augmented Reality (AR) holds the potential to revolutionize surgical procedures by allowing surgeons to visualize critical structures within the patient's body. This is achieved through superimposing preoperative organ models onto the actual anatomy. Challenges arise from dynamic deformations of organs during surgery, making preoperative models inadequate for faithfully representing intraoperative anatomy. To enable reliable navigation in augmented surgery, modeling of intraoperative deformation to obtain an accurate alignment of the preoperative organ model with the intraoperative anatomy is indispensable. Despite the existence of various methods proposed to model intraoperative organ deformation, there are still few literature reviews that systematically categorize and summarize these approaches. This review aims to fill this gap by providing a comprehensive and technical-oriented overview of modeling methods for intraoperative organ deformation in augmented reality in surgery. Through a systematic search and screening process, 112 closely relevant papers were included in this review. By presenting the current status of organ deformation modeling methods and their clinical applications, this review seeks to enhance the understanding of organ deformation modeling in AR-guided surgery, and discuss the potential topics for future advancements.

physics.med-ph↗

arXiv2023

Oxidation kinetics and non-Marcusian charge transfer in dimensionally confined semiconductors

Electrochemical reactions represent essential processes in fundamental chemistry that foster a wide range of applications. Although most electrochemical reactions in bulk substances can be well described by the classical Marcus-Gerischer charge transfer theory, the realistic reaction character and mechanism in dimensionally confined systems remain unknown. Here, we report the multiparametric survey on the kinetics of lateral photooxidation in structurally identical WS2 and MoS2 monolayers, where electrochemical oxidation occurs at the atomically thin monolayer edges. The oxidation rate is correlated quantitatively with various crystallographic and environmental parameters, including the density of reactive sites, humidity, temperature, and illumination fluence. In particular, we observe distinctive reaction barriers of 1.4 and 0.9 eV for the two structurally identical semiconductors and uncover an unusual non-Marcusian charge transfer mechanism in these dimensionally confined monolayers due to the limit in reactant supplies. A scenario of band bending is proposed to explain the discrepancy in reaction barriers. These results add important knowledge into the fundamental electrochemical reaction theory in low-dimensional systems.

cond-mat.mtrl-sci↗

arXiv2023

Evidence for chiral supercurrent in quantum Hall Josephson junctions

Hybridizing superconductivity with the quantum Hall (QH) effects has major potential for designing novel circuits capable of inducing and manipulating non-Abelian states for topological quantum computation. However, despite recent experimental progress towards this hybridization, concrete evidence for a chiral QH Josephson junction -- the elemental building block for coherent superconducting-QH circuits -- is still lacking. Its expected signature is an unusual chiral supercurrent flowing in QH edge channels, which oscillates with a specific $2\phi_0$ magnetic flux periodicity ($\phi_0=h/2e$ is the superconducting flux quantum, $h$ the Planck constant and $e$ the electron charge). Here, we show that ultra-narrow Josephson junctions defined in encapsulated graphene nanoribbons exhibit such a chiral supercurrent, visible up to 8 teslas, and carried by the spin-degenerate edge channel of the QH plateau of resistance $h/2e^2\simeq 12.9$ k$\Omega$. We observe reproducible $2\phi_0$-periodic oscillation of the supercurrent, which emerges at constant filling factor when the area of the loop formed by the QH edge channel is constant, within a magnetic-length correction that we resolve in the data. Furthermore, by varying the junction geometry, we show that reducing the superconductor/normal interface length is pivotal to obtain a measurable supercurrent on QH plateaus, in agreement with theories predicting dephasing along the superconducting interface. Our findings mark a critical milestone along the path to explore correlated and fractional QH-based superconducting devices that should host non-Abelian Majorana and parafermion zero modes.

cond-mat.mes-hall↗

arXiv2022

Data-driven and machine-learning based prediction of wave propagation behavior in dam-break flood

The computational prediction of wave propagation in dam-break floods is a long-standing problem in hydrodynamics and hydrology. Until now, conventional numerical models based on Saint-Venant equations are the dominant approaches. Here we show that a machine learning model that is well-trained on a minimal amount of data, can help predict the long-term dynamic behavior of a one-dimensional dam-break flood with satisfactory accuracy. For this purpose, we solve the Saint-Venant equations for a one-dimensional dam-break flood scenario using the Lax-Wendroff numerical scheme and train the reservoir computing echo state network (RC-ESN) with the dataset by the simulation results consisting of time-sequence flow depths. We demonstrate a good prediction ability of the RC-ESN model, which ahead predicts wave propagation behavior 286 time-steps in the dam-break flood with a root mean square error (RMSE) smaller than 0.01, outperforming the conventional long short-term memory (LSTM) model which reaches a comparable RMSE of only 81 time-steps ahead. To show the performance of the RC-ESN model, we also provide a sensitivity analysis of the prediction accuracy concerning the key parameters including training set size, reservoir size, and spectral radius. Results indicate that the RC-ESN are less dependent on the training set size, a medium reservoir size K=1200~2600 is sufficient. We confirm that the spectral radius \r{ho} shows a complex influence on the prediction accuracy and suggest a smaller spectral radius \r{ho} currently. By changing the initial flow depth of the dam break, we also obtained the conclusion that the prediction horizon of RC-ESN is larger than that of LSTM.

physics.flu-dyn↗

arXiv2022

Multi-state data storage in a two-dimensional stripy antiferromagnet implemented by magnetoelectric effect

A promising approach to the next generation of low-power, functional, and energy-efficient electronics relies on novel materials with coupled magnetic and electric degrees of freedom. In particular, stripy antiferromagnets often exhibit broken crystal and magnetic symmetries, which may bring about the magnetoelectric (ME) effect and enable the manipulation of intriguing properties and functionalities by electrical means. The demand for expanding the boundaries of data storage and processing technologies has led to the development of spintronics toward two-dimensional (2D) platforms. This work reports the ME effect in the 2D stripy antiferromagnetic insulator CrOCl down to a single layer. By measuring the tunneling resistance of CrOCl on the parameter space of temperature, magnetic field, and applied voltage, we verified the ME coupling down to the 2D limit and unraveled its mechanism. Utilizing the multi-stable states and ME coupling at magnetic phase transitions, we realize multi-state data storage in the tunneling devices. Our work not only advances the fundamental understanding of spin-charge coupling but also demonstrates the great potential of 2D antiferromagnetic materials to deliver devices and circuits beyond the traditional binary operations.

cond-mat.mtrl-sci↗

arXiv2022

Strong bulk-surface interaction dominated in-plane anisotropy of electronic structure in GaTe

Recently, intriguing physical properties have been unraveled in anisotropic layered semiconductors, in which the in-plane electronic band structure anisotropy often originates from the low crystallographic symmetry and thus a thickness-independent character emerges. Here, we apply high-resolution angle-resolved photoemission spectroscopy to directly image the in-plane anisotropic energy bands in monoclinic gallium telluride (GaTe). Our first-principles calculations reveal the in-plane anisotropic energy band structure of GaTe measured experimentally is dominated by a strong bulk-surface interaction rather than geometric factors, surface effect and quantum confinement effect. Furthermore, accompanied by the thickness of GaTe increasing from mono- to few-layers, the strong interlayer coupling of GaTe induces direct-indirect-direct band gap transitions and the in-plane anisotropy of hole effective mass is reversed. Our results shed light on the physical origins of in-plane anisotropy of electronic structure in GaTe, paving the way for the design and device applications of nanoelectronics and optoelectronics based on anisotropic layered semiconductors.

cond-mat.mtrl-sci↗

arXiv2022

Ultra-efficient magnetism modulation in a Weyl ferromagnet by current-assisted domain wall motion

Flexible and efficient manipulation of magnetic configurations can be challenging. In the design of practical devices, achieving a high effective magnetic field with a low working current is under tight demand. Here, we report a unique method for efficient magnetism modulation by direct current injection in magnetic Weyl semimetal Co3Sn2S2. We demonstrate that the modulation process stems from current-assisted domain wall motion. Through two independent methods, we reveal that the spin-transfer torque efficiency of Co3Sn2S2 reaches as high as 2.4-5.6 kOe MA^(-1) cm^2, and the threshold current density for driving the magnetic domain walls is as low as <5.1*10^5 A/cm^2 without an external field, and <1.5*10^5 A/cm^2 with a moderate external field. Our findings manifest a new and powerful approach for sub-micron magnetism manipulation, and also open the door towards a new paradigm of spintronics that combines magnetism, topology, and metallicity for low-energy consumption memory and computing.

cond-mat.mtrl-sci↗

arXiv2021

Learning Aligned Cross-Modal Representation for Generalized Zero-Shot Classification

Learning a common latent embedding by aligning the latent spaces of cross-modal autoencoders is an effective strategy for Generalized Zero-Shot Classification (GZSC). However, due to the lack of fine-grained instance-wise annotations, it still easily suffer from the domain shift problem for the discrepancy between the visual representation of diversified images and the semantic representation of fixed attributes. In this paper, we propose an innovative autoencoder network by learning Aligned Cross-Modal Representations (dubbed ACMR) for GZSC. Specifically, we propose a novel Vision-Semantic Alignment (VSA) method to strengthen the alignment of cross-modal latent features on the latent subspaces guided by a learned classifier. In addition, we propose a novel Information Enhancement Module (IEM) to reduce the possibility of latent variables collapse meanwhile encouraging the discriminative ability of latent variables. Extensive experiments on publicly available datasets demonstrate the state-of-the-art performance of our method.

cs.CV↗

arXiv2021

Van der Waals Ferromagnetic Josephson Junctions

Superconductor-ferromagnet (S-F) interfaces in two-dimensional (2D) heterostructures present a unique opportunity to study the interplay between superconductivity and ferromagnetism. The realization of such nanoscale heterostructures in van der Waals (vdW) crystals remains largely unexplored due to the challenge of making an atomically-sharp interface from their layered structures. Here, we build a vdW ferromagnetic Josephson junction (JJ) by inserting a few-layer ferromagnetic insulator Cr2Ge2Te6 into two layers of superconductor NbSe2. Owing to the remanent magnetic moment of the barrier, the critical current and the corresponding junction resistance exhibit a hysteretic and oscillatory behavior against in-plane magnetic fields, manifesting itself as a strong Josephson coupling state. Through the control of this hysteresis, we can effectively trace the magnetic properties of atomic Cr2Ge2Te6 in response to the external magnetic field. Also, we observe a central minimum of critical current in some thick JJ devices, evidencing the coexistence of 0 and π phase coupling in the junction region. Our study paves the way to exploring the sensitive probes of weak magnetism and multifunctional building blocks for phase-related superconducting circuits with the use of vdW heterostructures.

cond-mat.mes-hall↗

arXiv2020

Asymptotic behavior for a dissipative nonlinear Schrödinger equation

We consider the Schrödinger equation with nonlinear dissipation \begin{equation*} i \partial _t u +Δu=λ|u|^αu \end{equation*} in ${\mathbb R}^N $, $N\geq1$, where $λ\in {\mathbb C} $ with $\Imλ<0$. Assuming $\frac {2} {N+2}<α<\frac2N$, we give a precise description of the long-time behavior of the solutions (including decay rates in $L^2$ and $L^\infty $, and asymptotic profile), for a class of arbitrarily large initial data.

math.AP↗

arXiv2019

Asymptotic behavior for a Schrödinger equation with nonlinear subcritical dissipation

We study the time-asymptotic behavior of solutions of the Schrödinger equation with nonlinear dissipation \begin{equation*} \partial _t u = i Δu + λ|u|^αu \end{equation*} in ${\mathbb R}^N $, $N\geq1$, where $λ\in {\mathbb C}$, $\Re λ<0$ and $0<α<\frac2N$. We give a precise description of the behavior of the solutions (including decay rates in $L^2$ and $L^\infty $, and asymptotic profile), for a class of arbitrarily large initial data, under the additional assumption that $α$ is sufficiently close to $\frac2N$.

math.AP↗

arXiv2019

Blowup on an arbitrary compact set for a Schödinger equation with nonlinear source term

We consider the nonlinear Schrödinger equation on ${\mathbb R}^N $, $N\ge 1$, \begin{equation*} \partial _t u = i Δu + λ| u |^αu \quad \mbox{on ${\mathbb R}^N $, $α>0$,} \end{equation*} with $λ\in {\mathbb C}$ and $\Re λ>0$, for $H^1$-subcritical nonlinearities, i.e. $α>0$ and $(N-2) α< 4$. Given a compact set $K \subset {\mathbb R}^N $, we construct $H^1$ solutions that are defined on $(-T,0)$ for some $T>0$, and blow up on $K $ at $t=0$. The construction is based on an appropriate ansatz. The initial ansatz is simply $U_0(t,x) = ( \Re λ)^{- \frac {1} {α}} (-αt + A(x) )^{ -\frac {1} {α} - i \frac {\Im λ} {α\Re λ} }$, where $A\ge 0$ vanishes exactly on $ K $, which is a solution of the ODE $u'= λ| u |^αu$. We refine this ansatz inductively, using ODE techniques. We complete the proof by energy estimates and a compactness argument. This strategy is reminiscent of~[3, 4].

math.AP↗

arXiv2019

Current-driven magnetization switching in a van der Waals ferromagnet Fe3GeTe2

The recent discovery of ferromagnetism in two-dimensional (2D) van der Waals (vdW) materials holds promises for novel spintronic devices with exceptional performances. However, in order to utilize 2D vdW magnets for building spintronic nanodevices such as magnetic memories, key challenges remain in terms of effectively switching the magnetization from one state to the other electrically. Here, we devise a bilayer structure of Fe3GeTe2/Pt, in which the magnetization of few-layered Fe3GeTe2 can be effectively switched by the spin-orbit torques (SOTs) originated from the current flowing in the Pt layer. The effective magnetic fields corresponding to the SOTs are further quantitatively characterized using harmonic measurements. Our demonstration of the SOT-driven magnetization switching in a 2D vdW magnet could pave the way for implementing low-dimensional materials in the next-generation spintronic applications.

cond-mat.mes-hall↗

arXiv2017

Tunable transmission of quantum Hall edge channels with full degeneracy lifting in split-gated graphene devices

Charge carriers in the quantum Hall regime propagate via one-dimensional conducting channels that form along the edges of a two-dimensional electron gas. Controlling their transmission through a gate-tunable constriction, also called quantum point contact (QPC), is fundamental for many coherent transport experiments. However, in graphene, tailoring a QPC with electrostatic gates remains challenging due to the formation of p-n junctions below gate electrodes along which electron and hole edge channels co-propagate and mix, short-circuiting the constriction. Here we show that this electron-hole mixing is drastically reduced in high mobility boron-nitride/graphene/boron-nitride van-der-Waals heterostructures thanks to the full degeneracy lifting of the Landau levels, enabling QPC operation with full channel pinch-off. We demonstrate gate-tunable selective transmission of quantum Hall edge channels through the QPC, both in the integer and the fractional quantum Hall regimes. This gate-control of edge channel propagation in graphene van-der-Waals heterostructures opens the door to quantum Hall interferometry and electron quantum optics experiments in the integer and fractional quantum Hall regimes of graphene.

cond-mat.mes-hall↗