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Field-controlled breaking and restoration of parity-time symmetry in Josephson interference
Authors:
Yi-Chen Tsai,
Yung-Yeh Chang,
Tao-Yi Hsu,
Thomas Kuo,
Chia-Nung Kuo,
Chin-Shan Lue,
Kuei-Lin Chiu,
Chen-Hsuan Hsu,
Chung-Ting Ke
Abstract:
Symmetry plays a fundamental role in determining the phases and physical properties of quantum matter. Controlling symmetry in mesoscopic superconducting devices provides a route to reconfigure their phase-coherent transport. Here we demonstrate symmetry-selective Josephson interferometry in lateral NbTi/PtTe2/NbTi junctions by controlling the relative orientations of the current and magnetic fiel…
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Symmetry plays a fundamental role in determining the phases and physical properties of quantum matter. Controlling symmetry in mesoscopic superconducting devices provides a route to reconfigure their phase-coherent transport. Here we demonstrate symmetry-selective Josephson interferometry in lateral NbTi/PtTe2/NbTi junctions by controlling the relative orientations of the current and magnetic field. From the supercurrent interference patterns, we construct a field-current symmetry map that identifies configurations exhibiting or violating the device-level parity (\mathcal{P}), time-reversal (\mathcal{T}) and their combined \mathcal{P}\mathcal{T} symmetry. In the absence of an in-plane field, the junction exhibits a symmetric Fraunhofer pattern. An in-plane field parallel to the current produces a pronounced side-lobe asymmetry, whereas reversing both the current and the complete magnetic-field configuration restores a generalized \mathcal{T} relation. Remarkably, orienting the in-plane field perpendicular to the current restores the \mathcal{P}\mathcal{T}-symmetric Fraunhofer response even at substantial field strengths. A microscopic model attributes this behavior to the interplay between disorder-induced potential variations and flux dipoles generated by in-plane-field Meissner focusing near the superconducting electrodes. Our results establish a reconfigurable Josephson interferometer in which the field-current geometry selects the symmetry operation being probed and switches the device between symmetry-broken and symmetry-restored interference states.
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Submitted 17 August, 2026;
originally announced August 2026.
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Emergence of millimeter-wave resonances in self-assembled ferroelectric metamaterials
Authors:
Florian Bergmann,
Peter Meisenheimer,
Aiden Ross,
Marvin Schewe,
Fernando Gómez-Ortiz,
Kaiwen Yang,
Xinyan Li,
Thomas J. Lee,
Pushpendra Gupta,
Liam G. Connolloy,
Tzu-Hsuan Hsu,
Jack Kramer,
Bryan T. Bosworth,
Nicholas R. Jungwirth,
Eric J. Marksz,
Aaron Hagerstrom,
Tomasz Karpisz,
Arundhati Ghosal,
Lane W. Martin,
Yimo Han,
Angela C. Stelson,
Christian J. Long,
Ruochen Lu,
Lucas Caretta,
Javier Junquera
, et al. (4 additional authors not shown)
Abstract:
Resonators are a key component in modern communications and computing. As demand and technological advances push component requirements into the terahertz regime, there is significant research devoted to the search for resonances at these frequencies. While uniform solid-state materials usually do not intrinsically feature resonances in this frequency range, self-assembled periodic arrays of ferro…
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Resonators are a key component in modern communications and computing. As demand and technological advances push component requirements into the terahertz regime, there is significant research devoted to the search for resonances at these frequencies. While uniform solid-state materials usually do not intrinsically feature resonances in this frequency range, self-assembled periodic arrays of ferroelectric nanodomains may provide an engineering route to design millimeter-wave properties. Here, we utilize prototypical dielectric-ferroelectric SrTiO3/PbTiO3 superlattices to robustly design periodic ferroelectric nano-scale domains. Phase field simulations predict an emergent domain breathing mode in complex polar textures and state-of-the-art millimeter-wave characterization shows evidence for such emergent resonances up to hundreds of GHz. Complex polar textures in these superlattices lead to emergent piezoelectric properties that also result in millimeter-wave resonances, which are predicted by second principles methods and confirmed by direct measurement. The principles investigated in this work suggest a new modality for ferroelectrics in the design of millimeter-wave electronics.
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Submitted 25 June, 2026;
originally announced June 2026.
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Dirac semimetal phases in chiral carbon nanoscrolls
Authors:
Tzu-Ching Hsu,
Jhih-Shih You,
Hsiu-Chuan Hsu,
Ion Cosma Fulga
Abstract:
Chirality induced by rolling a two-dimensional material into a spiral geometry reshapes its electronic band structure. In this work, we theoretically investigate the topological properties of carbon nanoscrolls under an axial magnetic field, focusing on structures in which chirality is encoded through shifted edge alignments. In contrast to unshifted structures, where mirror symmetry pins the Dira…
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Chirality induced by rolling a two-dimensional material into a spiral geometry reshapes its electronic band structure. In this work, we theoretically investigate the topological properties of carbon nanoscrolls under an axial magnetic field, focusing on structures in which chirality is encoded through shifted edge alignments. In contrast to unshifted structures, where mirror symmetry pins the Dirac cones to half a flux quantum, chiral carbon nanoscrolls lack this symmetry, and Dirac cones emerge at magnetic flux values away from half a flux quantum. We demonstrate that these Dirac cones are topologically protected by combined inversion-time reversal symmetry and remain robust even when sublattice symmetry is broken. Furthermore, we show that the number of Dirac cones and their real-space probability distributions depend on the number of turns and the magnetic field strength. Our study elucidates the role of chirality in the band topology of nanoscroll geometries.
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Submitted 2 April, 2026; v1 submitted 27 February, 2026;
originally announced February 2026.
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Bimorph Lithium Niobate Piezoelectric Micromachined Ultrasonic Transducers
Authors:
Vakhtang Chulukhadze,
Zihuan Liu,
Ziqian Yao,
Lezli Matto,
Tzu-Hsuan Hsu,
Nishanth Ravi,
Xiaoyu Niu,
Michael E. Liao,
Mark S. Goorsky,
Neal Hall,
Ruochen Lu
Abstract:
Piezoelectric micromachined ultrasonic transducers (PMUTs) are widely utilized in applications that demand mechanical resilience, thermal stability, and compact form factors. Recent efforts have sought to demonstrate that single-crystal lithium niobate (LN) is a promising PMUT material platform, offering high electromechanical coupling (k2) and bidirectional performance. In addition, advances in L…
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Piezoelectric micromachined ultrasonic transducers (PMUTs) are widely utilized in applications that demand mechanical resilience, thermal stability, and compact form factors. Recent efforts have sought to demonstrate that single-crystal lithium niobate (LN) is a promising PMUT material platform, offering high electromechanical coupling (k2) and bidirectional performance. In addition, advances in LN film transfer technology have enabled high quality periodically poled piezoelectric films (P3F), facilitating a bimorph piezoelectric stack without intermediate electrodes. In this work, we showcase a bimorph PMUT incorporating a mechanically robust, 20 $μ$m thick P3F LN active layer. We establish the motivation for LN PMUTs through a material comparison, followed by extensive membrane geometry optimization and subsequent enhancement of the PMUT's k2. We demonstrate a 775 kHz flexural mode device with a quality factor (Q) of 200 and an extracted k2 of 6.4\%, yielding a high transmit efficiency of 65 nm/V with a mechanically robust active layer. We leverage the high performance to demonstrate extreme-temperature resilience, showcasing stable device operation up to 600 $^\circ$C and survival up to 900 $^\circ$C, highlighting LN's potential as a resilient PMUT platform.
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Submitted 5 March, 2026; v1 submitted 8 December, 2025;
originally announced December 2025.
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A Machine Learning Framework for Modeling Ensemble Properties of Atomically Disordered Materials
Authors:
Zhenyao Fang,
Ting-Wei Hsu,
Qimin Yan
Abstract:
Disorder, though naturally present in experimental samples and strongly influencing a wide range of material phenomena, remains underexplored in first-principles studies due to the computational cost of sampling the large supercell and configurational space. The recent development of machine learning techniques, particularly graph neural networks (GNNs), has enabled the efficient and accurate pred…
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Disorder, though naturally present in experimental samples and strongly influencing a wide range of material phenomena, remains underexplored in first-principles studies due to the computational cost of sampling the large supercell and configurational space. The recent development of machine learning techniques, particularly graph neural networks (GNNs), has enabled the efficient and accurate predictions of complex material properties, offering promising tools for studying disordered systems. In this work, we introduce a computational framework that integrates GNNs with Monte Carlo simulations for efficient calculations of thermodynamic properties and ensemble-averaged functional properties of disordered materials. Using the surface-termination-disordered MXene monolayer \ch{Ti3C2T}$_{2-x}$ as a representative system, we investigate the effect of surface termination disorder involving \ch{-F}, \ch{-O}, and termination vacancies on the electrical and optical conductivity spectra. We find that surface termination disorder affects the temperature dependence of electrical conductivity, inducing a peak close to the order-disorder phase transition temperature that reflects the competition between scattering and electron filling effects of the surface termination groups across the phase transition. In contrast, optical conductivity remains robust to local disorder across a wide temperature range and is governed primarily by the global chemical composition of surface terminations. These results demonstrate the utility of our machine-learning-assisted framework for statistically modeling disorder effects and ensemble properties in complex materials, opening new avenues for future studies of disorder-driven phenomena in systems such as high-entropy alloys and disordered magnetic compounds.
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Submitted 18 June, 2025;
originally announced June 2025.
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Accurate Prediction of Tensorial Spectra Using Equivariant Graph Neural Network
Authors:
Ting-Wei Hsu,
Zhenyao Fang,
Arun Bansil,
Qimin Yan
Abstract:
Optical spectroscopies provide a powerful tool for harnessing light-matter interactions for unraveling complex electronic features such as the flat bands and nontrivial topologies of materials. These insights are crucial for the development and optimization of optoelectronic devices, including solar cells, light-emitting diodes, and photodetectors, where device performance is closely connected wit…
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Optical spectroscopies provide a powerful tool for harnessing light-matter interactions for unraveling complex electronic features such as the flat bands and nontrivial topologies of materials. These insights are crucial for the development and optimization of optoelectronic devices, including solar cells, light-emitting diodes, and photodetectors, where device performance is closely connected with the nature of the underlying electronic spectrum. Realistic modeling of tensor optical responses in materials, which are computationally quite demanding, however, remains challenging. Here we introduce the Tensorial Spectra Equivariant Neural Network (TSENN), which is a equivariant graph neural network architecture that maps crystal structures directly to their full photon-frequency-dependent optical tensors. By encoding the isotropic sequential scalar components along with the anisotropic sequential tensor components into l = 0 and l = 2 spherical tensor components, TSENN ensures symmetry-aware predictions that are consistent with the constraints of crystalline symmetries of materials. Trained on a dataset of frequency-dependent permittivity tensors of 1,432 bulk semiconductors computed using first-principles methods, our model achieves a mean absolute error (MAE) of 21.181 millifarads per meter (mF/m), demonstrating its potential for efficient modeling of other related properties such as the optical conductivities. Our framework opens new avenues for rational data-driven design of anisotropic optical responses for accelerating materials discovery for advancing optoelectronic applications.
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Submitted 9 December, 2025; v1 submitted 7 May, 2025;
originally announced May 2025.
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BOOM: Benchmarking Out-Of-distribution Molecular Property Predictions of Machine Learning Models
Authors:
Evan R. Antoniuk,
Shehtab Zaman,
Tal Ben-Nun,
Peggy Li,
James Diffenderfer,
Busra Sahin,
Obadiah Smolenski,
Tim Hsu,
Anna M. Hiszpanski,
Kenneth Chiu,
Bhavya Kailkhura,
Brian Van Essen
Abstract:
Data-driven molecular discovery leverages artificial intelligence/machine learning (AI/ML) and generative modeling to filter and design novel molecules. Discovering novel molecules requires accurate out-of-distribution (OOD) predictions, but ML models struggle to generalize OOD. Currently, no systematic benchmarks exist for molecular OOD prediction tasks. We present $\mathbf{BOOM}$, $\mathbf{b}$en…
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Data-driven molecular discovery leverages artificial intelligence/machine learning (AI/ML) and generative modeling to filter and design novel molecules. Discovering novel molecules requires accurate out-of-distribution (OOD) predictions, but ML models struggle to generalize OOD. Currently, no systematic benchmarks exist for molecular OOD prediction tasks. We present $\mathbf{BOOM}$, $\mathbf{b}$enchmarks for $\mathbf{o}$ut-$\mathbf{o}$f-distribution $\mathbf{m}$olecular property predictions: a chemically-informed benchmark for OOD performance on common molecular property prediction tasks. We evaluate over 150 model-task combinations to benchmark deep learning models on OOD performance. Overall, we find that no existing model achieves strong generalization across all tasks: even the top-performing model exhibited an average OOD error 3x higher than in-distribution. Current chemical foundation models do not show strong OOD extrapolation, while models with high inductive bias can perform well on OOD tasks with simple, specific properties. We perform extensive ablation experiments, highlighting how data generation, pre-training, hyperparameter optimization, model architecture, and molecular representation impact OOD performance. Developing models with strong OOD generalization is a new frontier challenge in chemical ML. This open-source benchmark is available at https://github.com/FLASK-LLNL/BOOM
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Submitted 19 December, 2025; v1 submitted 3 May, 2025;
originally announced May 2025.
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Database of Tensorial Optical and Transport Properties of Materials From the Wannier Function Method
Authors:
Zhenyao Fang,
Ting-Wei Hsu,
Qimin Yan
Abstract:
The discovery and design of functional materials for energy harvesting and electronic applications require accurate predictions of their optical and transport properties. While several existing databases contain the first-order optical properties and the electron transport properties calculated from high-throughput first-principles calculations, the amount of material entries is often limited and…
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The discovery and design of functional materials for energy harvesting and electronic applications require accurate predictions of their optical and transport properties. While several existing databases contain the first-order optical properties and the electron transport properties calculated from high-throughput first-principles calculations, the amount of material entries is often limited and those functional properties are often reported in scalar form. Comprehensive databases for the tensorial properties still remain inadequate, which prevents from capturing the anisotropic effect in materials and the development of advanced machine learning models that incorporate the space group symmetry of materials. Therefore, in this work we present the largest-to-date database of tensorial optical properties (optical conductivity, shift current) and the database of tensorial transport properties (electrical conductivity, thermal conductivity, Seebeck coefficient, thermoelectric figure of merit zT) for 7301 materials, calculated from the Wannier function method. The quality of the Wannier functions were validated by the maximal spread of the Wannier functions and by the comparison with the band structures from first-principles calculations, ensuring the accuracy of the calculated properties. These results contribute to the systematic study the functional properties for diverse materials and can benefit future data-driven discovery of candidate materials for optoelectronic and thermoelectric applications.
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Submitted 1 April, 2025;
originally announced April 2025.
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A high optical access cryogenic system for Rydberg atom arrays with a 3000-second trap lifetime
Authors:
Zhenpu Zhang,
Ting-Wei Hsu,
Ting You Tan,
Daniel H. Slichter,
Adam M. Kaufman,
Matteo Marinelli,
Cindy A. Regal
Abstract:
We present an optical tweezer array of $^{87}$Rb atoms housed in an cryogenic environment that successfully combines a 4 K cryopumping surface, a <50 K cold box surrounding the atoms, and a room-temperature high-numerical-aperture objective lens. We demonstrate a 3000 s atom trap lifetime, which enables us to optimize and measure losses at the $10^{-4}$ level that arise during imaging and cooling,…
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We present an optical tweezer array of $^{87}$Rb atoms housed in an cryogenic environment that successfully combines a 4 K cryopumping surface, a <50 K cold box surrounding the atoms, and a room-temperature high-numerical-aperture objective lens. We demonstrate a 3000 s atom trap lifetime, which enables us to optimize and measure losses at the $10^{-4}$ level that arise during imaging and cooling, which are important to array rearrangement. We perform both ground-state qubit manipulation with an integrated microwave antenna and two-photon coherent Rydberg control, with the local electric field tuned to zero via integrated electrodes. We anticipate that the reduced blackbody radiation at the atoms from the cryogenic environment, combined with future electrical shielding, should decrease the rate of undesired transitions to nearby strongly-interacting Rydberg states, which cause many-body loss and impede Rydberg gates. This low-vibration, high-optical-access cryogenic platform can be used with a wide range of optically trapped atomic or molecular species for applications in quantum computing, simulation, and metrology.
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Submitted 8 July, 2025; v1 submitted 12 December, 2024;
originally announced December 2024.
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Grand canonical generative diffusion model for crystalline phases and grain boundaries
Authors:
Bo Lei,
Enze Chen,
Hyuna Kwon,
Tim Hsu,
Babak Sadigh,
Vincenzo Lordi,
Timofey Frolov,
Fei Zhou
Abstract:
The diffusion model has emerged as a powerful tool for generating atomic structures for materials science. This work calls attention to the deficiency of current particle-based diffusion models, which represent atoms as a point cloud, in generating even the simplest ordered crystalline structures. The problem is attributed to particles being trapped in local minima during the score-driven simulate…
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The diffusion model has emerged as a powerful tool for generating atomic structures for materials science. This work calls attention to the deficiency of current particle-based diffusion models, which represent atoms as a point cloud, in generating even the simplest ordered crystalline structures. The problem is attributed to particles being trapped in local minima during the score-driven simulated annealing of the diffusion process, similar to the physical process of force-driven simulated annealing. We develop a solution, the grand canonical diffusion model, which adopts an alternative voxel-based representation with continuous rather than fixed number of particles. The method is applied towards generation of several common crystalline phases as well as the technologically important and challenging problem of grain boundary structures.
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Submitted 28 August, 2024;
originally announced August 2024.
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Ice phase classification made easy with score-based denoising
Authors:
Hong Sun,
Sebastien Hamel,
Tim Hsu,
Babak Sadigh,
Vince Lordi,
Fei Zhou
Abstract:
Accurate identification of ice phases is essential for understanding various physicochemical phenomena. However, such classification for structures simulated with molecular dynamics is complicated by the complex symmetries of ice polymorphs and thermal fluctuations. For this purpose, both traditional order parameters and data-driven machine learning approaches have been employed, but they often re…
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Accurate identification of ice phases is essential for understanding various physicochemical phenomena. However, such classification for structures simulated with molecular dynamics is complicated by the complex symmetries of ice polymorphs and thermal fluctuations. For this purpose, both traditional order parameters and data-driven machine learning approaches have been employed, but they often rely on expert intuition, specific geometric information, or large training datasets. In this work, we present an unsupervised phase classification framework that combines a score-based denoiser model with a subsequent model-free classification method to accurately identify ice phases. The denoiser model is trained on perturbed synthetic data of ideal reference structures, eliminating the need for large datasets and labeling efforts. The classification step utilizes the Smooth Overlap of Atomic Positions (SOAP) descriptors as the atomic fingerprint, ensuring Euclidean symmetries and transferability to various structural systems. Our approach achieves a remarkable 100\% accuracy in distinguishing ice phases of test trajectories using only seven ideal reference structures of ice phases as model inputs. This demonstrates the generalizability of the score-based denoiser model in facilitating phase identification for complex molecular systems. The proposed classification strategy can be broadly applied to investigate structural evolution and phase identification for a wide range of materials, offering new insights into the fundamental understanding of water and other complex systems.
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Submitted 11 July, 2024; v1 submitted 10 May, 2024;
originally announced May 2024.
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Dynamic evolution of internal stress, grain growth, and crystallographic texture in arc-evaporated AlTiN thin films using in-situ synchrotron x-ray diffraction
Authors:
Sanjay Nayak,
Tun-Wei Hsu,
Robert Boyd,
Jens Gibmeier,
Norbert Schell,
Jens Birch,
Lina Rogström,
Magnus Odén
Abstract:
Understanding the nucleation and growth of polycrystalline thin films is a long-standing goal. Polycrystalline films have many grains with different orientations that affect thin-film properties. Numerous studies have been done to determine these grain size and their preferred crystallographic orientation as well as stress in films. However most past studies have either employed an ex-situ methodo…
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Understanding the nucleation and growth of polycrystalline thin films is a long-standing goal. Polycrystalline films have many grains with different orientations that affect thin-film properties. Numerous studies have been done to determine these grain size and their preferred crystallographic orientation as well as stress in films. However most past studies have either employed an ex-situ methodology or only monitor the development of macroscopic stress in real-time. There has never been any research done on the simultaneous determination of crystallographic texture, grain size, and microscopic stress in polycrystalline thin films. In this study, we simultaneously monitored the generation and temporal evolution of texture, grain size, and internal stress in cathodic arc evaporated Al0.50Ti0.50N thin films using a bespoke deposition apparatus designed for use with 2-dimensional synchrotron x-ray diffraction technique. The influence of the substrate temperature is investigated in terms of the emergence and development of texture, grain size and stress evolution. A dynamic evolution of the crystallographic texture is observed as the overall film thickness varies. We clearly resolved two regime of films growth based on stress evolution. Beyond a threshold grain size (~ 14 nm), the stress scales inversely to the average grain sizes, and as the film thickness increases, immediate compressive stress relaxation was seen. An extensive ex-situ evaluation of thin films using electron microscopies and electron diffraction was performed to support the in-situ x-ray diffraction results.
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Submitted 20 December, 2023;
originally announced December 2023.
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Spectroscopy-Guided Discovery of Three-Dimensional Structures of Disordered Materials with Diffusion Models
Authors:
Hyuna Kwon,
Tim Hsu,
Wenyu Sun,
Wonseok Jeong,
Fikret Aydin,
James Chapman,
Xiao Chen,
Matthew R. Carbone,
Deyu Lu,
Fei Zhou,
Tuan Anh Pham
Abstract:
The ability to rapidly develop materials with desired properties has a transformative impact on a broad range of emerging technologies. In this work, we introduce a new framework based on the diffusion model, a recent generative machine learning method to predict 3D structures of disordered materials from a target property. For demonstration, we apply the model to identify the atomic structures of…
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The ability to rapidly develop materials with desired properties has a transformative impact on a broad range of emerging technologies. In this work, we introduce a new framework based on the diffusion model, a recent generative machine learning method to predict 3D structures of disordered materials from a target property. For demonstration, we apply the model to identify the atomic structures of amorphous carbons ($a$-C) as a representative material system from the target X-ray absorption near edge structure (XANES) spectra--a common experimental technique to probe atomic structures of materials. We show that conditional generation guided by XANES spectra reproduces key features of the target structures. Furthermore, we show that our model can steer the generative process to tailor atomic arrangements for a specific XANES spectrum. Finally, our generative model exhibits a remarkable scale-agnostic property, thereby enabling generation of realistic, large-scale structures through learning from a small-scale dataset (i.e., with small unit cells). Our work represents a significant stride in bridging the gap between materials characterization and atomic structure determination; in addition, it can be leveraged for materials discovery in exploring various material properties as targeted.
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Submitted 9 December, 2023;
originally announced December 2023.
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Integration of graphene-based superconducting quantum circuits in 3D cavity
Authors:
Kuei-Lin Chiu,
Youyi Chang,
Avishma J. Lasrado,
Cheng-Han Lo,
Yung-Hsiang Chen,
Tao-Yi Hsu,
Yen-Chih Chen,
Yi-Chen Tsai,
Samina,
Yen-Hsiang Lin,
Chung-Ting Ke
Abstract:
Integrating 2D materials into circuit quantum electrodynamics (c-QED) devices is an emerging filed in recent years. This integration not only facilitates the exploration of potential applications in quantum information processing but also enables the study of material's fundamental properties using microwave techniques. While most studies employ 2D coplanar architectures with scalability potential…
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Integrating 2D materials into circuit quantum electrodynamics (c-QED) devices is an emerging filed in recent years. This integration not only facilitates the exploration of potential applications in quantum information processing but also enables the study of material's fundamental properties using microwave techniques. While most studies employ 2D coplanar architectures with scalability potential, 3D cavity based c-QED devices, due to their simpler design, offer the advantage of a quicker turnaround to probe the composite Josephson junctions (JJs). Here, we construct the first flux-tunable, 3D cavity-compatible superconducting quantum circuit based on 2D materials, featuring a graphene superconducting quantum interference device (SQUID) shunted by a capacitor that is accessible by both DC and microwave probes. We have shown how flux-modulated cavity frequency can be linked to the SQUID critical current under the influence of Fraunhofer pattern. In addition, we extracted the symmetry information of the SQUIDs based on DC analysis, and correlated this with the flux-modulated cavity frequency observed in microwave measurements. Our platform can extend to topological materials, holding the prospect of establishing valid topological JJs with DC probe while allowing fast microwave probe to avoid quasiparticle poisoning.
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Submitted 2 March, 2025; v1 submitted 6 December, 2023;
originally announced December 2023.
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Numerical investigation of mode failures in submerged granular columns
Authors:
Eduard Puig Montellà,
Julien Chauchat,
Cyrille Bonamy,
Dave Weij,
Geert Keetels,
Tian-Jian Hsu
Abstract:
In submerged sandy slopes, soil is frequently eroded as a combination of two main mechanisms: breaching, which refers to the retrogressive failure of a steep slope forming a turbidity current, and, instantaneous sliding wedges, known as shear failure, that also contribute to shape the morphology of the soil deposit. Although there are several modes of failures, in this paper we investigate breachi…
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In submerged sandy slopes, soil is frequently eroded as a combination of two main mechanisms: breaching, which refers to the retrogressive failure of a steep slope forming a turbidity current, and, instantaneous sliding wedges, known as shear failure, that also contribute to shape the morphology of the soil deposit. Although there are several modes of failures, in this paper we investigate breaching and shear failures of granular columns using the two-fluid approach. The numerical model is first applied to simulate small scale granular column collapses with different initial volume fractions to study the role of the initial conditions on the main flow dynamics. For loosely packed granular columns, the porous medium initially contracts and the resulting positive pore pressure leads to a rapid collapse. Whereas in initially dense-packing columns, the porous medium initially dilates and negative pore pressure is generated stabilizing the granular column, which results in a slow collapse. The proposed numerical approach shows good agreement with the experimental data in terms of morphology and excess of pore pressure. Numerical results are extended to a large-scale application known as the breaching process. This phenomenon may occur naturally at coasts or on dykes and levees in rivers but it can also be triggered by humans during dredging operations. The results indicate that the two-phase flow model correctly predicts the dilative behavior and, the subsequent turbidity currents, associated to the breaching process.
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Submitted 12 August, 2023; v1 submitted 18 April, 2023;
originally announced April 2023.
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In-situ real-time evolution of intrinsic stresses and microstructure during growth of cathodic arc deposited (Al,Ti)N coatings
Authors:
Sanjay Nayak,
Tun-Wei Hsu,
Lina Rogström,
Maiara Moreno,
Jon M. Andersson,
Mats P. Johansson-Jöesaar,
Robert Boyd,
Norbert Schell,
Jens Gibmeier,
Jens Birch,
Magnus Odén
Abstract:
The residual stress plays a vital role in determination of the device performance that uses thin films coating and thus the accurate determination of stress and its optimization with process parameters is an ongoing research work for many decades. In line with this, the microscopic origin of the stress at the atomic scale and its development during the thin film deposition is a matter of major sci…
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The residual stress plays a vital role in determination of the device performance that uses thin films coating and thus the accurate determination of stress and its optimization with process parameters is an ongoing research work for many decades. In line with this, the microscopic origin of the stress at the atomic scale and its development during the thin film deposition is a matter of major scientific interests. The development of stress is a complex phenomenon and has a complex dependence to process parameters, film microstructure and its morphology. In this work, by utilizing a custom-designed cathodic arc deposition system and synchrotron radiation based 2D x-ray diffraction (XRD) technique, we determine the real-time evolution of stress, crystallite sizes and their preferential orientations of Aluminum-Titanium-Nitride (AlxTi1-xN) films with varied Al-content (x=0.0, 0.25, 0.50, and 0.67) on Si-100 substrate. The energies of incoming ions and hence stress in the films is tuned by applying different direct current substrate bias (Vs = floating potential, -20, -40, -60, -80, and -100 V). The instantaneous stress is evaluated by the well-known d vs. sin2ψ technique, while crystallite sizes are determined by analyzing line profiles of x-ray diffractograms. The evolution of stress and crystallite sizes are modelled with multiple numerical models from which kinetic parameters associated with the thin film depositions are extracted. The ex-situ microstructure characterizations of AlxTi1-xN coatings are carried out by scanning electron microscopy (SEM) and transmission electron microscopy (TEM). The formation of ex-situ microstructure of the films is discussed considering the results obtained from in-situ XRD data. Finally, we demonstrate that the method utilized here is a powerful approach towards estimation of the fracture toughness of thin film coatings.
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Submitted 10 January, 2023;
originally announced January 2023.
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Score-based denoising for atomic structure identification
Authors:
Tim Hsu,
Babak Sadigh,
Nicolas Bertin,
Cheol Woo Park,
James Chapman,
Vasily Bulatov,
Fei Zhou
Abstract:
We propose an effective method for removing thermal vibrations that complicate the task of analyzing complex dynamics in atomistic simulation of condensed matter. Our method iteratively subtracts thermal noises or perturbations in atomic positions using a denoising score function trained on synthetically noised but otherwise perfect crystal lattices. The resulting denoised structures clearly revea…
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We propose an effective method for removing thermal vibrations that complicate the task of analyzing complex dynamics in atomistic simulation of condensed matter. Our method iteratively subtracts thermal noises or perturbations in atomic positions using a denoising score function trained on synthetically noised but otherwise perfect crystal lattices. The resulting denoised structures clearly reveal underlying crystal order while retaining disorder associated with crystal defects. Purely geometric, agnostic to interatomic potentials, and trained without inputs from explicit simulations, our denoiser can be applied to simulation data generated from vastly different interatomic interactions. The denoiser is shown to improve existing classification methods such as common neighbor analysis and polyhedral template matching, reaching perfect classification accuracy on a recent benchmark dataset of thermally perturbed structures up to the melting point. Demonstrated here in a wide variety of atomistic simulation contexts, the denoiser is general, robust, and readily extendable to delineate order from disorder in structurally and chemically complex materials.
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Submitted 3 May, 2023; v1 submitted 5 December, 2022;
originally announced December 2022.
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Elucidating dislocation core structures in titanium nitride through high-resolution imaging and atomistic simulations
Authors:
J. Salamania,
D. G. Sangiovanni,
A. Kraych,
K. M. Calamba Kwick,
I. C. Schramm,
L. J. S. Johnson,
R. Boyd,
B. Bakhit,
T. W. Hsu,
M. Mrovec,
L. Rogström,
F. Tasnádi,
I. A. Abrikosov,
M. Odén
Abstract:
Although titanium nitride (TiN) is among the most extensively studied and thoroughly characterized thin-film ceramic materials, detailed knowledge of relevant dislocation core structures is lacking. By high-resolution scanning transmission electron microscopy (STEM) of epitaxial single crystal (001)-oriented TiN films, we identify different dislocation types and their core structures. These includ…
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Although titanium nitride (TiN) is among the most extensively studied and thoroughly characterized thin-film ceramic materials, detailed knowledge of relevant dislocation core structures is lacking. By high-resolution scanning transmission electron microscopy (STEM) of epitaxial single crystal (001)-oriented TiN films, we identify different dislocation types and their core structures. These include, besides the expected primary full a/2{110}<1$\bar{1}$0> dislocation, Shockley partial dislocations a/6{111}<11$\bar{2}$> and sessile Lomer edge dislocations a/2{100}<011>. Density-functional theory and classical interatomic potential simulations complement STEM observations by recovering the atomic structure of the different dislocation types, estimating Peierls stresses, and providing insights on the chemical bonding nature at the core. The generated models of the dislocation cores suggest locally enhanced metal-metal bonding, weakened Ti-N bonds, and N vacancy-pinning that effectively reduces the mobilities of {110}<1$\bar{1}$0> and {111}<11$\bar{2}$> dislocations. Our findings underscore that the presence of different dislocation types and their effects on chemical bonding should be considered in the design and interpretations of nanoscale and macroscopic properties of TiN.
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Submitted 28 October, 2022; v1 submitted 13 June, 2022;
originally announced June 2022.
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Quantifying Disorder One Atom at a Time Using an Interpretable Graph Neural Network Paradigm
Authors:
James Chapman,
Tim Hsu,
Xiao Chen,
Tae Wook Heo,
Brandon C. Wood
Abstract:
Quantifying the level of atomic disorder within materials is critical to understanding how evolving local structural environments dictate performance and durability. Here, we leverage graph neural networks to define a physically interpretable metric for local disorder. This metric encodes the diversity of the local atomic configurations as a continuous spectrum between the solid and liquid phases,…
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Quantifying the level of atomic disorder within materials is critical to understanding how evolving local structural environments dictate performance and durability. Here, we leverage graph neural networks to define a physically interpretable metric for local disorder. This metric encodes the diversity of the local atomic configurations as a continuous spectrum between the solid and liquid phases, quantified against a distribution of thermal perturbations. We apply this novel methodology to three prototypical examples with varying levels of disorder: (1) solid-liquid interfaces, (2) polycrystalline microstructures, and (3) grain boundaries. Using elemental aluminum as a case study, we show how our paradigm can track the spatio-temporal evolution of interfaces, incorporating a mathematically defined description of the spatial boundary between order and disorder. We further show how to extract physics-preserved gradients from our continuous disorder fields, which may be used to understand and predict materials performance and failure. Overall, our framework provides an intuitive and generalizable pathway to quantify the relationship between complex local atomic structure and coarse-grained materials phenomena.
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Submitted 16 June, 2022; v1 submitted 18 March, 2022;
originally announced March 2022.
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Multi-scale simulation of the adsorption of lithium ion on graphite surface: from Quantum Monte Carlo to Molecular Density Functional Theory
Authors:
Michele Ruggeri,
Kyle Reeves,
Tzu-Yao Hsu,
Guillaume Jeanmairet,
Mathieu Salanne,
Carlo Pierleoni
Abstract:
The structure of the double-layer formed at the surface of carbon electrodes is governed by the interactions between the electrode and the electrolyte species. However, carbon is notoriously difficult to simulate accurately, even with well-established methods such as electronic Density Functional Theory and Molecular Dynamics. Here we focus on the important case of a lithium ion in contact with th…
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The structure of the double-layer formed at the surface of carbon electrodes is governed by the interactions between the electrode and the electrolyte species. However, carbon is notoriously difficult to simulate accurately, even with well-established methods such as electronic Density Functional Theory and Molecular Dynamics. Here we focus on the important case of a lithium ion in contact with the surface of graphite, and we perform a series of reference Quantum Monte Carlo calculations that allow us to benchmark various electronic Density Functional Theory functionals. We then fit an accurate carbon--lithium pair potential, which is used in molecular Density Functional Theory calculations to determine the free energy of the adsorption of the ion on the surface in the presence of water. The adsorption profile in solution differs markedly from the gas phase results, which emphasize the role of the solvent on the properties of the double-layer.
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Submitted 20 December, 2021;
originally announced December 2021.
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Microstructure Generation via Generative Adversarial Network for Heterogeneous, Topologically Complex 3D Materials
Authors:
Tim Hsu,
William K. Epting,
Hokon Kim,
Harry W. Abernathy,
Gregory A. Hackett,
Anthony D. Rollett,
Paul A. Salvador,
Elizabeth A. Holm
Abstract:
Using a large-scale, experimentally captured 3D microstructure dataset, we implement the generative adversarial network (GAN) framework to learn and generate 3D microstructures of solid oxide fuel cell electrodes. The generated microstructures are visually, statistically, and topologically realistic, with distributions of microstructural parameters, including volume fraction, particle size, surfac…
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Using a large-scale, experimentally captured 3D microstructure dataset, we implement the generative adversarial network (GAN) framework to learn and generate 3D microstructures of solid oxide fuel cell electrodes. The generated microstructures are visually, statistically, and topologically realistic, with distributions of microstructural parameters, including volume fraction, particle size, surface area, tortuosity, and triple phase boundary density, being highly similar to those of the original microstructure. These results are compared and contrasted with those from an established, grain-based generation algorithm (DREAM.3D). Importantly, simulations of electrochemical performance, using a locally resolved finite element model, demonstrate that the GAN generated microstructures closely match the performance distribution of the original, while DREAM.3D leads to significant differences. The ability of the generative machine learning model to recreate microstructures with high fidelity suggests that the essence of complex microstructures may be captured and represented in a compact and manipulatable form.
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Submitted 22 June, 2020;
originally announced June 2020.
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Momentum-space entanglement for interacting fermions at finite density
Authors:
Ting-Chen Leo Hsu,
Michael B. McDermott,
Mark Van Raamsdonk
Abstract:
We investigate the entanglement between individual field theory modes in finite-density systems of interacting relativistic and non-relativistic fermions in one spatial dimension. We calculate the entanglement entropy for a single field theory mode and the mutual information between any two modes. The calculation is perturbative in the four-fermion (two-body) coupling, with the leading contributio…
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We investigate the entanglement between individual field theory modes in finite-density systems of interacting relativistic and non-relativistic fermions in one spatial dimension. We calculate the entanglement entropy for a single field theory mode and the mutual information between any two modes. The calculation is perturbative in the four-fermion (two-body) coupling, with the leading contribution at order lambda^2 log(lambda^2). At this leading order, the perturbative expression for the entanglement entropy of a mode diverges logarithmically as the momentum of the mode approaches the Fermi surface from above or below. The mutual information between modes is largest for pairs of modes just above and below the Fermi momentum. The entanglement properties of modes near the Fermi surface are qualitatively the same if the field theory is cut off to eliminate modes away from the Fermi surface.
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Submitted 28 September, 2012;
originally announced October 2012.
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Magneto-Optics of type-II superconductors
Authors:
E. Choi,
H. -T. S. Lihn,
H. D. Drew,
T. C. Hsu
Abstract:
The magneto-optical activity of superconducting ${\rm YBa}_{2}{\rm Cu}_{3}{\rm O}_{7}$ observed by Karrai {\it et al.} is not present in many commonly employed models of vortex dynamics. Here we propose a simple, unifying picture for the frequency dependent magneto-optic response of type-II superconductors at low temperatures. We bring together Kohn's theorem, vortex core excitations, and vortex…
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The magneto-optical activity of superconducting ${\rm YBa}_{2}{\rm Cu}_{3}{\rm O}_{7}$ observed by Karrai {\it et al.} is not present in many commonly employed models of vortex dynamics. Here we propose a simple, unifying picture for the frequency dependent magneto-optic response of type-II superconductors at low temperatures. We bring together Kohn's theorem, vortex core excitations, and vortex pinning and damping into a single expression for the conductivity tensor. The theory describes magneto-optical activity observed in infrared transmission measurements of thin films of ${\rm YBa}_{2}{\rm Cu}_{3}{\rm O}_{7}$.
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Submitted 13 October, 1993;
originally announced October 1993.
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Effect of three-particle correlations in low dimensional Hubbard models
Authors:
Ted Hsu,
Benoit Doucot
Abstract:
A simple approximation which captures some non-perturbative aspects of the one electron Green function of strongly interacting Fermion systems is developed. It provides a way to go one step beyond the usual dilute limit since particle-particle as well as particle-hole scattering are treated on the same footing. Intermediate states are constrained to contain only one particle-hole excitation besi…
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A simple approximation which captures some non-perturbative aspects of the one electron Green function of strongly interacting Fermion systems is developed. It provides a way to go one step beyond the usual dilute limit since particle-particle as well as particle-hole scattering are treated on the same footing. Intermediate states are constrained to contain only one particle-hole excitation besides the incoming particle. The Faddeev equations resulting from an exact treatment of this three-body problem are investigated. In one dimension the method is able to show spin and charge decoupling, but does not reproduce the exact nature of power-law singularities. Hey dudes, check out the analytical solution in section III!
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Submitted 16 February, 1993;
originally announced February 1993.
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Level repulsion in integrable and almost-integrable quantum spin models
Authors:
Theodore C. Hsu,
J. C. Angles d'Auriac
Abstract:
The repartition of the separation between energy levels of various isotropic S=1/2 antiferromagnetic chains is studied numerically with the aim of investigating the transition from integrable to non-integrable systems. We begin by displaying the level separation distribution of the integrable Bethe chain. Then two non-integrable systems, two coupled chains and a next-nearest-neighbor coupled cha…
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The repartition of the separation between energy levels of various isotropic S=1/2 antiferromagnetic chains is studied numerically with the aim of investigating the transition from integrable to non-integrable systems. We begin by displaying the level separation distribution of the integrable Bethe chain. Then two non-integrable systems, two coupled chains and a next-nearest-neighbor coupled chain, are studied as a function of the coupling. We examine how the level spacing evolves from the Poisson distribution to the GOE distribution. Finally we consider the Haldane-Shastry $1/r^{2}$ model. A number of conclusions regarding the behaviour and relevance of the level spacing distribution in these spin systems is drawn.
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Submitted 3 November, 1992;
originally announced November 1992.
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Frequency dependent conductivity of vortex cores in type II superconductors
Authors:
Ted Hsu
Abstract:
This paper is relevant to the recent optical transmission experiments of Karrai et al. for vortices in high Tc superconductors. We begin with a substantial review and introduction. The microscopic response of vortices is calculated from the Bogoliubov-deGennes equation, including an equation of motion and conductivity. We find that the expected resonant dipole transtition is not present because…
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This paper is relevant to the recent optical transmission experiments of Karrai et al. for vortices in high Tc superconductors. We begin with a substantial review and introduction. The microscopic response of vortices is calculated from the Bogoliubov-deGennes equation, including an equation of motion and conductivity. We find that the expected resonant dipole transtition is not present because of translation invariance. We consider the effect of pinning and show that in the presence of pinning one recovers the dipole resonance. Thus we conclude that pinning may play an important role in the experiment.
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Submitted 26 August, 1992;
originally announced August 1992.
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Absence of Dipole Transitions in Vortices of Type II Superconductors
Authors:
Theodore C. Hsu
Abstract:
The response of a single vortex to a time dependent field is examined microscopically and an equation of motion for vortex motion at non-zero frequencies is derived. Of interest are frequencies near $Δ^{2}/E_{F}$, where $Δ$ is the bulk energy gap and $E_{F}$ is the fermi energy. The low temperature, clean, extreme type II limit and maintaining of equilibrium with the lattice are assumed. A simpl…
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The response of a single vortex to a time dependent field is examined microscopically and an equation of motion for vortex motion at non-zero frequencies is derived. Of interest are frequencies near $Δ^{2}/E_{F}$, where $Δ$ is the bulk energy gap and $E_{F}$ is the fermi energy. The low temperature, clean, extreme type II limit and maintaining of equilibrium with the lattice are assumed. A simplification occurs for large planar mass anisotropy. Thus the results may be pertinent to materials such as $NbSe_2$ and high temperature superconductors. The expected dipole transition between core states is hidden because of the self consistent nature of the vortex potential. Instead the vortex itself moves and has a resonance at the frequency of the transition.
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Submitted 30 April, 1992;
originally announced April 1992.