arXiv subjects

Fei Ding

Publications and source records attributed to Fei Ding.

At least 73 records · Page 4Linked to original sources

arXiv2024

High-rate intercity quantum key distribution with a semiconductor single-photon source

Quantum key distribution (QKD) enables the transmission of information that is secure against general attacks by eavesdroppers. The use of on-demand quantum light sources in QKD protocols is expected to help improve security and maximum tolerable loss. Semiconductor quantum dots (QDs) are a promising building block for quantum communication applications because of the deterministic emission of single photons with high brightness and low multiphoton contribution. Here we report on the first intercity QKD experiment using a bright deterministic single photon source. A BB84 protocol based on polarisation encoding is realised using the high-rate single photons in the telecommunication C-band emitted from a semiconductor QD embedded in a circular Bragg grating structure. Utilising the 79 km long link with 25.49 dB loss (equivalent to 130 km for the direct-connected optical fibre) between the German cities of Hannover and Braunschweig, a record-high secret key bits per pulse of 4.8 * 10^{-5} with an average quantum bit error ratio of ~ 0.65 % are demonstrated. An asymptotic maximum tolerable loss of 28.11 dB is found, corresponding to a length of 144 km of standard telecommunication fibre. Deterministic semiconductor sources therefore challenge state-of-the-art QKD protocols and have the potential to excel in measurement device independent protocols and quantum repeater applications.

quant-ph↗

arXiv2024

Equity-aware Load Shedding Optimization

Load shedding is usually the last resort to balance generation and demand to maintain stable operation of the electric grid after major disturbances. Current load-shedding optimization practices focus mainly on the physical optimality of the network power flow. This might lead to an uneven allocation of load curtailment, disadvantaging some loads more than others. Addressing this oversight, this paper introduces an innovative equity-aware load-shedding optimization model that emphasizes a fair allocation of load curtailment across the network. By proposing a novel equity indicator for load shedding and integrating it into an ACOPF-based optimization framework, we offer grid operators a more balanced and equitable load shedding strategy. Case studies highlight the importance of equity considerations in determining optimal load curtailment between buses.

eess.SY↗

arXiv2024

Unveiling the 3D Morphology of Epitaxial GaAs/AlGaAs Quantum Dots

Strain-free GaAs/AlGaAs semiconductor quantum dots (QDs) grown by droplet etching and nanohole infilling (DENI) are highly promising candidates for the on-demand generation of indistinguishable and entangled photon sources. The spectroscopic fingerprint and quantum optical properties of QDs are significantly influenced by their morphology. The effects of nanohole geometry and infilled material on the exciton binding energies and fine structure splitting are well understood. However, a comprehensive understanding of GaAs/AlGaAs QD morphology remains elusive. To address this, we employ high-resolution scanning transmission electron microscopy (STEM) and reverse engineering through selective chemical etching and atomic force microscopy (AFM). Cross-sectional STEM of uncapped QDs reveals an inverted conical nanohole with Al-rich sidewalls and defect-free interfaces. Subsequent selective chemical etching and AFM measurements further reveal asymmetries in element distribution. This study enhances the understanding of DENI QD morphology and provides a fundamental three-dimensional structural model for simulating and optimizing their optoelectronic properties.

quant-ph↗

arXiv2024

MSSTNet: A Multi-Scale Spatio-Temporal CNN-Transformer Network for Dynamic Facial Expression Recognition

Unlike typical video action recognition, Dynamic Facial Expression Recognition (DFER) does not involve distinct moving targets but relies on localized changes in facial muscles. Addressing this distinctive attribute, we propose a Multi-Scale Spatio-temporal CNN-Transformer network (MSSTNet). Our approach takes spatial features of different scales extracted by CNN and feeds them into a Multi-scale Embedding Layer (MELayer). The MELayer extracts multi-scale spatial information and encodes these features before sending them into a Temporal Transformer (T-Former). The T-Former simultaneously extracts temporal information while continually integrating multi-scale spatial information. This process culminates in the generation of multi-scale spatio-temporal features that are utilized for the final classification. Our method achieves state-of-the-art results on two in-the-wild datasets. Furthermore, a series of ablation experiments and visualizations provide further validation of our approach's proficiency in leveraging spatio-temporal information within DFER.

cs.CV↗

arXiv2024

Photoneutralization of charges in GaAs quantum dot based entangled photon emitters

Semiconductor-based emitters of pairwise photonic entanglement are a promising constituent of photonic quantum technologies. They are known for the ability to generate discrete photonic states on-demand with low multiphoton emission, near-unity entanglement fidelity, and high single photon indistinguishability. However, quantum dots typically suffer from luminescence blinking, lowering the efficiency of the source and hampering their scalable application in quantum networks. In this paper, we investigate and adjust the intermittence of the neutral exciton emission in a GaAs/AlGaAs quantum dot under two-photon resonant excitation of the neutral biexciton. We investigate the spectral and quantum optical response of the quantum dot emission to an additional wavelength tunable gate laser, revealing blinking caused by the intrinsic Coulomb blockade due to charge capture processes. Our finding demonstrates that the emission quenching can be actively suppressed by controlling the balance of free electrons and holes in the vicinity of the quantum dot and thereby significantly increasing the quantum efficiency by 30%.

quant-ph↗

arXiv2024

Circular photonic crystal grating design for charge-tunable quantum light sources in the telecom C-band

Efficient generation of entangled photon pairs at telecom wavelengths is a key ingredient for long-range quantum networks. While embedding semiconductor quantum dots into hybrid circular Bragg gratings has proven effective, it conflicts with $p$-$i$-$n$ diode heterostructures which offer superior coherence. We propose and analyze hybrid circular photonic crystal gratings, incorporating air holes to facilitate charge carrier transport without compromising optical properties. Through numerical simulations, a broad cavity mode with a Purcell factor of 23 enhancing both exciton and biexciton transitions, and exceptional collection efficiency of 92.4% into an objective with numerical aperture of 0.7 are achieved. Furthermore, our design demonstrates direct coupling efficiency over 90% into a single-mode fiber over the entire telecom C-band. The hybrid circular photonic crystal grating thereby emerges as a promising solution for the efficient generation of highly coherent, polarization-entangled photon pairs.

quant-ph↗

arXiv2023

DreamTuner: Single Image is Enough for Subject-Driven Generation

Diffusion-based models have demonstrated impressive capabilities for text-to-image generation and are expected for personalized applications of subject-driven generation, which require the generation of customized concepts with one or a few reference images. However, existing methods based on fine-tuning fail to balance the trade-off between subject learning and the maintenance of the generation capabilities of pretrained models. Moreover, other methods that utilize additional image encoders tend to lose important details of the subject due to encoding compression. To address these challenges, we propose DreamTurner, a novel method that injects reference information from coarse to fine to achieve subject-driven image generation more effectively. DreamTurner introduces a subject-encoder for coarse subject identity preservation, where the compressed general subject features are introduced through an attention layer before visual-text cross-attention. We then modify the self-attention layers within pretrained text-to-image models to self-subject-attention layers to refine the details of the target subject. The generated image queries detailed features from both the reference image and itself in self-subject-attention. It is worth emphasizing that self-subject-attention is an effective, elegant, and training-free method for maintaining the detailed features of customized subjects and can serve as a plug-and-play solution during inference. Finally, with additional subject-driven fine-tuning, DreamTurner achieves remarkable performance in subject-driven image generation, which can be controlled by a text or other conditions such as pose. For further details, please visit the project page at https://dreamtuner-diffusion.github.io/.

cs.CV↗

arXiv2023

Converse Flexoelectricity of Low-Dimensional Bismuth Selenite (Bi2Se3) Revealed by Piezoresponse Force Microscopy (PFM)

Many kinds of two-dimensional (2D) van der Waals (vdW) have been demonstrated to exhibit electromechanical coupling effects, which makes them promising candidates for next-generation devices, such as piezotronics and nanogenerators. Recently, flexoelectricity was found to account for the out-of-plane electromechanical coupling in many 2D transition metal dichalcogenides (TMDs) who only exhibit in-plane piezoelectricity. However, low dimensional vdW three-dimensional (3D) topological insulators (TIs) have been overlooked regarding their electromechanical properties. In this study, for the first time, we experimentally investigate the electromechanical coupling of low dimensional 3D TIs with a centrosymmetric crystal structure, where a binary compound, bismuth selenite (Bi2Se3), is taken as an example. The results of piezoresponse force microscope (PFM) tests on the Bi2Se3 nanoflakes show that the material exhibits both out-of-plane and in-plane electromechanical responses. The Bi2Se3 nanoflake with a thickness of 37 nm possesses an effective out-of-plane piezoelectric coefficient of ~0.65 pm V-1. With careful analyses, the electromechanical responses are verified to arise from the converse flexoelectricity. The measured effective out-of-plane piezoelectric coefficient is mainly contributed by flexoelectric coefficient, μ_39, which is estimated to be approximately 0.13 nC m-1. However, it is rather difficult to obtain the in-plane component of the flexoelectric tensor from the in-plane PFM measurements since the direction of the in-plane stress is always not normal to the AFM cantilever axis. The results provide useful guidance for understanding the flexoelectric effect of low dimensional vdW materials with centrosymmetric crystal structures. Moreover, the work can pave to way to explore the electromechanical devices based on the flexoelectricity of vdW TIs.

cond-mat.mes-hall↗

arXiv2023

Anomalous tensile strength and thermal expansion, and low thermal conductivity in wide band gap boron monoxide monolayer

Most recently the formation of boron monoxide (BO) in the two-dimensional (2D) form has been confirmed experimentally (J. Am. Chem. Soc. 2023, 145, 14660). Motivated by the aforementioned finding, herein we theoretically explore the key physical properties of the single-layer and suspended BO. Density functional theory (DFT) results reveal that BO monolayer yields a large indirect band gap of 3.78 (2.18) eV on the basis of HSE06(PBE) functional. Ab-initio molecular dynamics results reveal the remarkable thermal stability of the BO monolayer at 1000 K. The thermal and mechanical properties at room temperature are furthermore investigated using a machine learning interatomic potential (MLIP). The developed MLIP-based model close to the ground state could very precisely reproduce the DFT predictions for the mechanical properties of the BO monolayer. The elastic modulus, tensile strength and lattice thermal conductivity of the BO monolayer at room temperature are predicted to be 107 GPa, 25 GPa and 5.6 W/mK, respectively. At the room temperature the BO monolayer is noticeably predicted to yield an ultrahigh negative thermal expansion coefficient, by almost 17 folds larger than that of the single-layer graphene. The presented results reveal the large indirect electronic band gap, decent thermal and dynamical stability, anomalously low elastic modulus to tensile strength ratio, ultrahigh negative thermal expansion coefficients and low lattice thermal conductivity of the BO monolayer.

cond-mat.mes-hall↗

arXiv2023

Functional PCA with Covariate Dependent Mean and Covariance Structure

Incorporating covariates into functional principal component analysis (PCA) can substantially improve the representation efficiency of the principal components and predictive performance. However, many existing functional PCA methods do not make use of covariates, and those that do often have high computational cost or make overly simplistic assumptions that are violated in practice. In this article, we propose a new framework, called Covariate Dependent Functional Principal Component Analysis (CD-FPCA), in which both the mean and covariance structure depend on covariates. We propose a corresponding estimation algorithm, which makes use of spline basis representations and roughness penalties, and is substantially more computationally efficient than competing approaches of adequate estimation and prediction accuracy. A key aspect of our work is our novel approach for modeling the covariance function and ensuring that it is symmetric positive semi-definite. We demonstrate the advantages of our methodology through a simulation study and an astronomical data analysis.

stat.ME↗

arXiv2023

Contrastive Representation Disentanglement for Clustering

Clustering continues to be a significant and challenging task. Recent studies have demonstrated impressive results by applying clustering to feature representations acquired through self-supervised learning, particularly on small datasets. However, when dealing with datasets containing a large number of clusters, such as ImageNet, current methods struggle to achieve satisfactory clustering performance. In this paper, we introduce a novel method called Contrastive representation Disentanglement for Clustering (CDC) that leverages contrastive learning to directly disentangle the feature representation for clustering. In CDC, we decompose the representation into two distinct components: one component encodes categorical information under an equipartition constraint, and the other component captures instance-specific factors. To train our model, we propose a contrastive loss that effectively utilizes both components of the representation. We conduct a theoretical analysis of the proposed loss and highlight how it assigns different weights to negative samples during the process of disentangling the feature representation. Further analysis of the gradients reveals that larger weights emphasize a stronger focus on hard negative samples. As a result, the proposed loss exhibits strong expressiveness, enabling efficient disentanglement of categorical information. Through experimental evaluation on various benchmark datasets, our method demonstrates either state-of-the-art or highly competitive clustering performance. Notably, on the complete ImageNet dataset, we achieve an accuracy of 53.4%, surpassing existing methods by a substantial margin of +10.2%.

cs.LG↗

arXiv2023

Surface quantum dots with pure, coherent, and blinking-free single photon emission

The surface of semiconductor nanostructures has a major impact on their electronic and optical properties. Disorder and defects in the surface layer typically cause degradation of charge carrier transport and radiative recombination dynamics. However, surface vicinity is inevitable for many scalable nano-optical applications. Epitaxially grown quantum dots are the best candidate for high-performance single photon emission and show great potential for quantum technologies. Yet, these emitters only reveal their excellent properties if they are deeply embedded in a semiconductor host. Until today, quantum dots close to surfaces yield weak, broad, and unstable emissions. Here, we show the complete restoration of optical properties from quantum dots grown directly on a semiconductor surface. The vanishing luminescence from the as-grown sample turns into bright, ultra-stable, coherent and blinking-free single photon emission after sulphur passivation. Under quasi-resonant excitation, single photons are generated with 98.8% purity, 77% indistinguishability, linewidths down to 4 $μ$eV and 99.69% persistency across 11 orders of magnitude in time. The emission is stable even after two years and when being subjected to nanomanufacturing processes. Some long-standing stumbling blocks for surface-dominated quantum dots are thereby removed, unveiling new possibilities for hybrid nano-devices and applications in quantum communication or sensing.

cond-mat.mes-hall↗

arXiv2023

A solid-state source of single and entangled photons at diamond SiV$^-$-center transitions operating at 80K

Large-scale quantum networks require the implementation of long-lived quantum memories as stationary nodes interacting with qubits of light. Epitaxially grown quantum dots hold great potential for the on-demand generation of single and entangled photons with high purity and indistinguishability. Coupling these emitters to memories with long coherence times enables the development of hybrid nanophotonic devices incorporating the advantages of both systems. Here we report the first GaAs/AlGaAs quantum dots grown by droplet etching and nanohole infilling method, emitting single photons with a narrow wavelength distribution (736.2 $\pm$ 1.7 nm) close to the zero-phonon line of Silicon-vacancy centers. Polarization entangled photons are generated via the biexciton-exciton cascade with a fidelity of (0.73 $\pm$ 0.09). High single photon purity is maintained from 4 K (g$^($$^2$$^)$(0) = 0.07 $\pm$ 0.02) up to 80 K (g$^($$^2$$^)$(0) = 0.11 $\pm$ 0.01), therefore making this hybrid system technologically attractive for real-world quantum photonic applications.

quant-ph↗

arXiv2023

A Voice Disease Detection Method Based on MFCCs and Shallow CNN

The incidence rate of voice diseases is increasing year by year. The use of software for remote diagnosis is a technical development trend and has important practical value. Among voice diseases, common diseases that cause hoarseness include spasmodic dysphonia, vocal cord paralysis, vocal nodule, and vocal cord polyp. This paper presents a voice disease detection method that can be applied in a wide range of clinical. We cooperated with Xiangya Hospital of Central South University to collect voice samples from sixty-one different patients. The Mel Frequency Cepstrum Coefficient (MFCC) parameters are extracted as input features to describe the voice in the form of data. An innovative model combining MFCC parameters and single convolution layer CNN is proposed for fast calculation and classification. The highest accuracy we achieved was 92%, it is fully ahead of the original research results and internationally advanced. And we use Advanced Voice Function Assessment Databases (AVFAD) to evaluate the generalization ability of the method we proposed, which achieved an accuracy rate of 98%. Experiments on clinical and standard datasets show that for the pathological detection of voice diseases, our method has greatly improved in accuracy and computational efficiency.

cs.SD↗

arXiv2023

Strain control of exciton and trion spin-valley dynamics in monolayer transition metal dichalcogenides

The electron-hole exchange interaction is a fundamental mechanism that drives valley depolarization via intervalley exciton hopping in semiconductor multi-valley systems. Here, we report polarization-resolved photoluminescence spectroscopy of neutral excitons and negatively charged trions in monolayer MoSe$_2$ and WSe$_2$ under biaxial strain. We observe a marked enhancement(reduction) on the WSe$_2$ triplet trion valley polarization with compressive(tensile) strain while the trion in MoSe$_2$ is unaffected. The origin of this effect is shown to be a strain dependent tuning of the electron-hole exchange interaction. A combined analysis of the strain dependent polarization degree using ab initio calculations and rate equations shows that strain affects intervalley scattering beyond what is expected from strain dependent bandgap modulations. The results evidence how strain can be used to tune valley physics in energetically degenerate multi-valley systems.

cond-mat.mes-hall↗

arXiv2022

Multi-level Distillation of Semantic Knowledge for Pre-training Multilingual Language Model

Pre-trained multilingual language models play an important role in cross-lingual natural language understanding tasks. However, existing methods did not focus on learning the semantic structure of representation, and thus could not optimize their performance. In this paper, we propose Multi-level Multilingual Knowledge Distillation (MMKD), a novel method for improving multilingual language models. Specifically, we employ a teacher-student framework to adopt rich semantic representation knowledge in English BERT. We propose token-, word-, sentence-, and structure-level alignment objectives to encourage multiple levels of consistency between source-target pairs and correlation similarity between teacher and student models. We conduct experiments on cross-lingual evaluation benchmarks including XNLI, PAWS-X, and XQuAD. Experimental results show that MMKD outperforms other baseline models of similar size on XNLI and XQuAD and obtains comparable performance on PAWS-X. Especially, MMKD obtains significant performance gains on low-resource languages.

cs.CL↗

arXiv2022

60-nm-span wavelength-tunable vortex fiber laser with intracavity plasmon metasurfaces

Wavelength-tunable vortex fiber lasers that could generate beams carrying orbital angular momentum (OAM) hold great interest in large-capacity optical communications. The wavelength tunability of conventional vortex fiber lasers is however limited by the range of 35 nm due to narrow bandwidth and/or insertion loss of mode conversion components. Optical metasurfaces apart from being compact planar components can flexibly manipulate light with high efficiency in a broad wavelength range. Here, we propose and demonstrate for the first time, to the best of our knowledge, a metasurface-assisted vortex fiber laser that can directly generate OAM beams with changeable topological charges. Due to the designed broadband gap-surface plasmon metasurface, combined with an intracavity tunable filter, the laser enables OAM beam with center wavelength continuously tunable from 1015 nm to 1075 nm, nearly twice of other vortex fiber lasers ever reported. The metasurface can be designed at will to satisfy requirements for either low pump threshold or high slope efficiency of the laser. Furthermore, the cavity-metasurface configuration can be extended to generate higher-order OAM beams or more complex structured beams in different wavelength regions, which greatly broadens the possibilities for developing low-cost and high-quality structured-beam laser sources.

physics.optics↗

arXiv2022

Statistical limits for quantum networks with semiconductor entangled photon sources

Semiconductor quantum dots are promising building blocks for quantum communication applications. Although deterministic, efficient, and coherent emission of entangled photons has been realized, implementing a practical quantum repeater remains outstanding. Here we explore the statistical limits for entanglement swapping with sources of polarization-entangled photons from the commonly used biexciton-exciton cascade. We stress the necessity of tuning the exciton fine structure, and explain why the often observed time evolution of photonic entanglement in quantum dots is not applicable for large quantum networks. We identify the critical, statistically distributed device parameters for entanglement swapping based on two sources. A numerical model for benchmarking the consequences of device fabrication, dynamic tuning techniques, and statistical effects is developed, in order to bring the realization of semiconductor-based quantum networks one step closer to reality.

quant-ph↗