arXiv subjects

Zhihao Jiang

Publications and source records attributed to Zhihao Jiang.

At least 19 recordsLinked to original sources

arXiv2026

Lindbladian Phase Geometry and Hall Transport in Open Bloch Systems

Quantum geometry underlies a wide range of transport phenomena in Bloch systems. How quantum-geometric transport is modified when Bloch electrons are coupled to an environment, however, remains largely unexplored, even though the environment can alter both the electronic state and the physical current operator. Here we formulate dc linear response within a trace-preserving Lindblad kinetic theory by defining the physical velocity as the Liouvillian time derivative of the position operator. This construction reveals an environment-induced contribution to the current vertex whose momentum-space curl generates new Hall responses governed by the gauge-invariant phase geometry encoded by Lindblad jump amplitudes, which characterize electron-environment coupling. To leading order in the dissipative coupling, this geometry gives rise to interband shift-vector and diagonal-vorticity Hall responses arising from off-diagonal and diagonal jump amplitudes, respectively. Remarkably, both mechanisms can produce a finite Hall conductivity even when the conventional Berry-curvature anomalous Hall effect vanishes identically. Our work establishes Lindbladian phase geometry as an independent geometric origin of transverse transport in open quantum matter.

cond-mat.mes-hall↗

arXiv2026

Nash Core in Multiwinner Election

In the approval-based committee selection problem, a committee is said to be in the core if no subset of voters has an incentive to deviate by selecting a \emph{blocking} committee of proportional size, such that every voter in the deviating group strictly prefers the blocking committee. We consider the setting where candidates can be selected fractionally. Under a mild regularity assumption, we show that there always exists a weighting of candidates such that the fractional committee maximizing the candidate-weighted Nash Social Welfare is in the core. We refer to such a solution as being in the \emph{Nash core}. Additionally, we show that a Nash core solution admits a payment assignment between voters and candidates, where each voter pays a candidate they approve in proportion to the weight. For the discrete setting, where each candidate is either included or excluded from the committee, we prove that every approval-based committee election with at most eight equally weighted voters has a core committee by rounding the fractional Nash core solution. Although the non-emptiness of the core in this setting remains an open question and checking core membership is coNP-hard, we extend the notion of the Nash core to the discrete case, yielding a formulation that is efficiently verifiable and offers a promising path toward establishing core existence in discrete settings. Finally, we test our approach on real voting data using a payment-guided heuristic. We empirically show that the Nash core solution can be efficiently computed through an iterative algorithm in both the fractional and discrete settings.

cs.GT↗

arXiv2026

Observation of dodecagonal replica bands in 30$^{\circ}$-twisted bilayer WSe$_2$

Twisted bilayers of two-dimensional (2D) transition metal dichalcogenides are promising systems for achieving tunable quasicrystalline orders with emergent properties. The underpinning electronic structure and scattering processes in 2D quasicrystals with multiorbital dodecagonal replica bands have so far not been determined. Here, we utilize angle-resolved photoemission spectroscopy (ARPES) with micrometer spatial resolution to directly observe replica bands in 30$^{\circ}$-twisted bilayer WSe$_2$. The symmetry and intensity distribution of the observed replicas are explained by interlayer Umklapp scattering from bottom to top WSe$_2$ layers. Our spectral function measurements are consistent with the presence of a van Hove singularity adjacent to the $\mathrm{K}$-valleys, which underlines the possibility of inducing electronic reconstructions in bilayers with a large interlayer twist angle.

cond-mat.mes-hall↗

arXiv2026

Micro- and nanoscale focusing across the XUV range of the ASTRID2 light source with a capillary optic

Focusing of synchrotron light across extreme ultraviolet (XUV) and soft X-ray regimes is increasingly desired for photoemission-based techniques where reduced beam width gives access to smaller samples such as microscopic single crystals and functioning two-dimensional (2D) heterostructures and devices. Many existing focusing methods, however, are not able to take full advantage of the synchrotron beam due to limited photon energy range or low transmission. Modern capillary optics have enabled achromatic, high transmission focusing of XUV and X-ray light. Here, we present a detailed characterisation of such an achromatic capillary optic installed at the AU-SGM4 beamline for spatial- and angle-resolved photoemission spectroscopy (ARPES) experiments at the ASTRID2 light source. The transmission of the capillary as a function of photon energy is given, and the dependence of the beam width, position, and transmission are measured against the source size. Analysis of the far-field image of the beam allows for slope errors on the inner surface of the capillary to be overcome by selectively aperturing the beam, resulting in a minimum beam width of 900 nm measured in a photoemission geometry.

physics.optics↗

arXiv2026

UMCP: A Unified Multi-Task Collaborative Perception Network for Luggage Trolley Pose Estimation

In robotic autonomous luggage trolley collection, robots must continuously localize scattered luggage trolleys in cluttered and dynamic environments. This requires the vision system to achieve both high accuracy and real-time performance. However, existing visual perception approaches for luggage trolleys often rely on cascaded multi-model inference, leading to increased inference latency and high deployment costs. To address these limitations, this article presents a unified multi-task collaborative perception network (UMCP) that simultaneously performs luggage trolley detection, keypoint detection and orientation estimation. Based on the YOLOv12 architecture, keypoint features are fused with orientation features and then fed into an orientation feature enhancement module (OFEM), thereby improving orientation estimation accuracy. In addition, circular probability distribution modeling with a Kullback-Leibler (KL) divergence loss is adopted to enhance orientation estimation accuracy further. Experimental results demonstrate that the proposed method achieves competitive overall accuracy while substantially reducing model complexity and computational cost compared with existing methods. A website about this work is available at https://sites.google.com/view/robot-umcp.

cs.RO↗

arXiv2026

Band offsets and stability of WSe$_2$/RuCl$_3$ van der Waals charge-transfer contacts

The layered Mott insulator $α$-RuCl$_3$ induces degenerate hole-doping in two-dimensional semiconductors due to its large electron affinity, making it a promising charge-transfer material for establishing ohmic contacts in electronic devices. In order to assess the applicability and guide the design of devices incorporating RuCl$_3$ it is critical to determine the electronic structure and robustness of the band offsets that underpin the transport properties of semiconductors in contact with RuCl$_3$. Here, we apply micro-focused angle-resolved photoemission spectroscopy to determine the electronic structure of single-layer WSe$_2$ contacted to RuCl$_3$ on hexagonal boron nitride substrates. We find that formation of a functioning WSe$_2$/RuCl$_3$ contact leads to a valence band shift of $(0.68 \pm 0.05)$ eV towards the Fermi energy in WSe$_2$. The charge transfer effect is challenging to observe as it depends sensitively on fabrication conditions such as solvent exposure, quality of interface encapsulation and heating of RuCl$_3$, imposing strict requirements on device design to attain high-quality contacts.

cond-mat.mes-hall↗

arXiv2026

LoRA-DA: Data-Aware Initialization for Low-Rank Adaptation via Asymptotic Analysis

LoRA has become a widely adopted method for PEFT, and its initialization methods have attracted increasing attention. However, existing methods have notable limitations: many methods do not incorporate target-domain data, while gradient-based methods exploit data only at a shallow level by relying on one-step gradient decomposition. In this paper, we establish a theoretical framework for data-aware LoRA initialization. Starting from minimizing the expectation of the parameter discrepancy between the fine-tuned and target models, we derive an optimization problem with two components: a bias term, which is related to the parameter distance between the fine-tuned and target models, and is approximated using a Fisher-gradient formulation to preserve anisotropy; and a variance term, which accounts for the uncertainty introduced by sampling stochasticity through the Fisher information. Solving this problem yields an optimal initialization strategy for LoRA, based on which we develop an efficient algorithm, LoRA-DA. Empirical results across multiple benchmarks demonstrate that LoRA-DA consistently improves final accuracy over existing initialization methods. Additional studies show faster, more stable convergence, robustness across ranks, and only a small initialization overhead for LoRA-DA. The source code is available at https://github.com/zqy0126/LoRA-DA.

cs.LG↗

arXiv2026

Direct nanoscale mapping of band alignment in single-layer semiconducting lateral heterojunctions

Atomic-scale control over band alignment in single-layer lateral heterostructures (LHSs) of dissimilar transition metal dichalcogenides (TMDCs) is critical for nextgeneration electronic, optoelectronic, and quantum technologies. However, direct experimental access to interfacial electronic states with nanometer precision remains a significant challenge. Here, we employ angle-resolved photoemission spectroscopy with nanoscale spatial resolution (nanoARPES) to directly map the epitaxial alignment and valence band evolution across MoSe2-WSe2 LHSs. By combining nanoARPES with spatially resolved photoluminescence, we correlate the evolution of the valence band maximum and exciton features across both atomically sharp and compositionally graded diffusive interfaces. We identified type-II band alignments governed by both material composition and interstitial-induced modifications of band offsets, in close agreement with density functional theory calculations. These results reveal fundamental mechanisms of electronic structure modulation at 1D TMDC heterointerfaces and provide a robust platform for tailored band engineering in van der Waals materials.

cond-mat.mes-hall↗

arXiv2025

Quasiparticle gap renormalization driven by internal and external screening in a WS$_2$ device

The electronic band gap of a two-dimensional semiconductor within a device architecture is sensitive to variations in screening properties of adjacent materials in the device and to gate-controlled doping. Here, we employ micro-focused angle resolved photoemission spectroscopy to separate band gap renormalization effects stemming from environmental screening and electron-doping during \textit{in situ} gating of a single-layer WS$_{2}$ device. The WS$_{2}$ is supported on hBN and contains a section that is exposed to vacuum and another section that is encapsulated by a graphene contact. We directly observe the doping-induced semiconductor-metal transition and band gap renormalization in the two sections of WS$_2$. Surprisingly, a larger band gap renormalization is observed in the vacuum-exposed section than in the graphene-encapsulated - and thus ostensibly better screened - section of the WS$_2$. Using $GW$ calculations, we determine that intrinsic screening due to stronger doping in vacuum exposed WS$_2$ exceeds the external environmental screening in graphene-encapsulated WS$_2$.

cond-mat.mes-hall↗

arXiv2025

Multi-Selection for Recommendation Systems

We present the construction of a multi-selection model to answer differentially private queries in the context of recommendation systems. The server sends back multiple recommendations and a ``local model'' to the user, which the user can run locally on its device to select the item that best fits its private features. We study a setup where the server uses a deep neural network (trained on the Movielens 25M dataset as the ground truth for movie recommendation. In the multi-selection paradigm, the average recommendation utility is approximately 97\% of the optimal utility (as determined by the ground truth neural network) while maintaining a local differential privacy guarantee with $ε$ ranging around 1 with respect to feature vectors of neighboring users. This is in comparison to an average recommendation utility of 91\% in the non-multi-selection regime under the same constraints.

cs.LG↗

arXiv2024

Direct view of gate-tunable miniband dispersion in graphene superlattices near the magic twist angle

Superlattices from twisted graphene mono- and bi-layer systems give rise to on-demand many-body states such as Mott insulators and unconventional superconductors. These phenomena are ascribed to a combination of flat bands and strong Coulomb interactions. However, a comprehensive understanding is lacking because the low-energy band structure strongly changes when the electron filling is varied. Here, we gain direct access to the filling-dependent low energy bands of twisted bilayer graphene (TBG) and twisted double bilayer graphene (TDBG) by applying micro-focused angle-resolved photoemission spectroscopy to in situ gated devices. Our findings for the two systems are in stark contrast: The doping dependent dispersion for TBG can be described in a simple model, combining a filling-dependent rigid band shift with a many-body related bandwidth change. In TDBG, on the other hand, we find a complex behaviour of the low-energy bands, combining non-monotonous bandwidth changes and tuneable gap openings. Our work establishes the extent of electric field tunability of the low energy electronic states in twisted graphene superlattices and can serve to underpin the theoretical understanding of the resulting phenomena.

cond-mat.mes-hall↗

arXiv2024

Unraveling the origin of antiferromagnetic coupling at YIG/permalloy interface

We investigate the structural and electronic origin of antiferromagnetic (AFM) coupling in the Yttrium iron garnet (YIG) and permalloy (Py) bilayer system at the atomic level. Ferromagnetic Resonance (FMR) reveal unique hybrid modes in samples prepared with surface ion milling, indicative of antiferromagnetic exchange coupling at the YIG/Py interface. Using atomic resolution scanning transmission electron microscopy (STEM), we found that AFM coupling appears at the YIG/Py interface of the tetrahedral YIG surface formed with ion milling. The STEM measurements suggest that the interfacial AFM coupling is predominantly driven by an oxygen-mediated super-exchange coupling mechanism, which is confirmed by the density functional theory (DFT) calculations to be energetically favorable. Thus, the combined experimental and theoretical results reveal the critical role of interfacial atomic structure in determining the type magnetic coupling in a YIG/ferromagnet heterostructure, and prove that the interfacial structure can be experimentally tuned by surface ion-milling.

cond-mat.mtrl-sci↗

arXiv2024

Differential Privacy with Multiple Selections

We consider the setting where a user with sensitive features wishes to obtain a recommendation from a server in a differentially private fashion. We propose a ``multi-selection'' architecture where the server can send back multiple recommendations and the user chooses one from these that matches best with their private features. When the user feature is one-dimensional -- on an infinite line -- and the accuracy measure is defined w.r.t some increasing function $\mathfrak{h}(.)$ of the distance on the line, we precisely characterize the optimal mechanism that satisfies differential privacy. The specification of the optimal mechanism includes both the distribution of the noise that the user adds to its private value, and the algorithm used by the server to determine the set of results to send back as a response and further show that Laplace is an optimal noise distribution. We further show that this optimal mechanism results in an error that is inversely proportional to the number of results returned when the function $\mathfrak{h}(.)$ is the identity function.

cs.DS↗

arXiv2024

Learning-Based Modeling of Human-Autonomous Vehicle Interaction for Improved Safety in Mixed-Vehicle Platooning Control

The rising presence of autonomous vehicles (AVs) on public roads necessitates the development of advanced control strategies that account for the unpredictable nature of human-driven vehicles (HVs). This study introduces a learning-based method for modeling HV behavior, combining a traditional first-principles approach with a Gaussian process (GP) learning component. This hybrid model enhances the accuracy of velocity predictions and provides measurable uncertainty estimates. We leverage this model to develop a GP-based model predictive control (GP-MPC) strategy to improve safety in mixed vehicle platoons by integrating uncertainty assessments into distance constraints. Comparative simulations between our GP-MPC approach and a conventional model predictive control (MPC) strategy reveal that the GP-MPC ensures safer distancing and more efficient travel within the mixed platoon. By incorporating sparse GP modeling for HVs and a dynamic GP prediction in MPC, we significantly reduce the computation time of GP-MPC, making it only marginally longer than standard MPC and approximately 100 times faster than previous models not employing these techniques. Our findings underscore the effectiveness of learning-based HV modeling in enhancing safety and efficiency in mixed-traffic environments involving AV and HV interactions.

cs.RO↗

arXiv2024

Improving safety in mixed traffic: A learning-based model predictive control for autonomous and human-driven vehicle platooning

As autonomous vehicles (AVs) become more common on public roads, their interaction with human-driven vehicles (HVs) in mixed traffic is inevitable. This requires new control strategies for AVs to handle the unpredictable nature of HVs. This study focused on safe control in mixed-vehicle platoons consisting of both AVs and HVs, particularly during longitudinal car-following scenarios. We introduce a novel model that combines a conventional first-principles model with a Gaussian process (GP) machine learning-based model to better predict HV behavior. Our results showed a significant improvement in predicting HV speed, with a 35.64% reduction in the root mean square error compared with the use of the first-principles model alone. We developed a new control strategy called GP-MPC, which uses the proposed HV model for safer distance management between vehicles in the mixed platoon. The GP-MPC strategy effectively utilizes the capacity of the GP model to assess uncertainties, thereby significantly enhancing safety in challenging traffic scenarios, such as emergency braking scenarios. In simulations, the GP-MPC strategy outperformed the baseline MPC method, offering better safety and more efficient vehicle movement in mixed traffic.

cs.RO↗

arXiv2024

Revealing flat bands and hybridization gaps in a twisted bilayer graphene device with microARPES

Controlling the electronic structure of two-dimensional materials using the combination of twist angle and electrostatic doping is an effective means to induce emergent phenomena. In bilayer graphene with an interlayer twist angle near the magic angle, the electronic dispersion is strongly modified by a manifold of hybridizing moiré Dirac cones leading to flat band segments with strong electronic correlations. Numerous technical challenges arising from spatial inhomogeneity of interlayer interactions, twist angle and device functionality have so far limited momentum-resolved electronic structure measurements of these systems to static conditions. Here, we present a detailed characterization of the electronic structure exhibiting miniband dispersions for twisted bilayer graphene, near the magic angle, integrated in a functional device architecture using micro-focused angle-resolved photoemission spectroscopy. The optimum conditions for visualizing the miniband dispersion are determined by exploiting the spatial resolution and photon energy tunability of the light source and applied to extract a hybridization gap size of $(0.14 \pm 0.03)$~eV and flat band segments extending across a moiré mini Brillouin zone. \textit{In situ} electrostatic gating of the sample enables significant electron-doping, causing the conduction band states to shift below the Fermi energy. Our work emphasizes key challenges in probing the electronic structure of magic angle bilayer graphene devices and outlines conditions for exploring the doping-dependent evolution of the dispersion that underpins the ability to control many-body interactions in the material.

cond-mat.mes-hall↗

arXiv2024

Influence of temperature, doping, and amorphization on the electronic structure and magnetic damping of iron

Hybrid magnonic quantum systems have drawn increased attention in recent years for coherent quantum information processing, but too large magnetic damping is a persistent concern when metallic magnets are used. Their intrinsic damping is largely determined by electron-magnon scattering induced by spin-orbit interactions. In the low scattering limit, damping is dominated by intra-band electronic transitions, which has been theoretically shown to be proportional to the electronic density of states at the Fermi level. In this work, we focus on body-centered-cubic iron as a paradigmatic ferromagnetic material. We comprehensively study its electronic structure using first-principles density functional theory simulations and account for finite lattice temperature, boron (B) doping, and structure amorphization. Our results indicate that temperature induced atomic disorder and amorphous atomic geometries only have a minor influence. Instead, boron doping noticeably decreases the density of states near the Fermi level with an optimal doping level of 6.25%. In addition, we show that this reduction varies significantly for different atomic geometries and report that the highest reduction correlates with a large magnetization of the material. This may suggest materials growth under external magnetic fields as a route to explore in experiment.

cond-mat.mtrl-sci↗

arXiv2023

Zero-field magnetic structure and metamagnetic phase transitions of the cobalt chain compound Li$_2$CoCl$_4$

Exploring the uncharacterized magnetic phases of Co$^{2+}$ chain compounds is critical for finding new low-dimensional magnets hosting quantized excitations. We map the unexplored magnetic phases of the Co$^{2+}$ chain compound Li$_2$CoCl$_4$. Magnetometry reveals magnetic ordering below 7 K with a metamagnetic transition near 16.5 kOe and a gradual transition to a field-aligned paramagnetic state above 31 kOe. Curie-Weiss fits to the high temperature susceptibility reveal a high-spin (spin-$\frac{3}{2}$) state for cobalt. Heat capacity data, though, give a magnetic entropy change of 5.46 J/mol, consistent with cobalt effective spin-$\frac{1}{2}$ systems. To characterize the zero-field antiferromagnetic ordering, we separately calculated the energy of proposed magnetic structures with density functional theory and collected 3.5 K neutron diffraction data, finding that Li$_2$CoCl$_4$ has ferromagnetic chains with antiferromagnetic interactions between them. Increasing field rotates these spin chains, producing the antiferromagnetic to intermediate to paramagnetic transition sequence.

cond-mat.str-el↗