arXiv subjects

Qian Ye

Publications and source records attributed to Qian Ye.

17 recordsLinked to original sources

arXiv2026

On-demand thermal power amplification enabled by active heat $Q$-switching

Thermal management underpins essentially every energy technology, from solar harvesters and waste-heat recovery to industrial process heating and electronic cooling. Yet, thermal systems remain limited compared to their electrical and optical counterparts: they lack a direct equivalent of active control elements that enable on-demand pulse generation. As a result, in conventional thermal energy storage architectures, the amount of energy stored and the peak power at which it can be released are both fixed at design time by material properties and heat-exchanger geometry, locking each device to a single operating point in the energy--power plane. This rigidity is incompatible with applications that require short, high-power thermal bursts on demand. Here we show that a counter-flow heat oscillator admits an actively switchable effective thermal quality factor, $Q$, and that modulating $Q$ on sub-dwell-time scales generates transient outlet power exceeding the steady input by more than an order of magnitude. We formalize the system as a dissipative resonant thermal cavity with $Q$ controlled by the balance between advective and conductive transport and environmental losses, and we experimentally demonstrate, in a water-based dual-channel device, $\sim$5-fold transient power amplification through controlled flow detuning, in quantitative agreement with our thermofluidic model. Active $Q$-switching establishes a distinct mode of thermal power management, accessing $\sim$5$\times$ (demonstrated experimentally) to $\sim$40$\times$ (projected numerically) peak-power amplification on continuous input through a single architecture, a regime inaccessible to passive thermal storage and a missing analogue of the active pulse-generation tools long available in optics and electronics.

physics.app-ph↗

arXiv2025

Static magnetic control of light emission in plasmonic nanojunctions

Localized surface plasmon resonances (LSPRs) in metal nanoparticles have been studied extensively through scattering and absorption. Static magnetic field-induced changes in plasmonic far-field response stem from the classical Hall effect and are generally very small in noble metals within the visible frequency range at readily accessible magnetic fields. Planar plasmonic tunnel junctions allow the study of nanogap LSPRs through current-driven light emission. We find that the electroluminescence of such junctions is modulated by tens of percent with a magnetic field of a few Teslas, exceeding Hall-based expectations by orders of magnitude. Complementary quantum mechanical and electromagnetic modeling reveals that a modest static magnetic field can introduce significant chirality in the transition dipoles generated during the electron tunneling process. This strongly affects the excitation of LSPRs and leads to magnetic-field sensitive far-field electroluminescent emission. This is a new paradigm for tunable nanoscale light sources.

physics.optics↗

arXiv2025

Electron-Phonon Temperature Inversion in Nanostructures under Pulsed Photoexcitation

Photoexcitation of metallic nanostructures with short optical pulses can drive non-thermal electronic states, which, upon decay, lead to elevated electronic temperatures ($T_e \gtrapprox 1000\,\mathrm{K}$) eventually equilibrating with the lattice ($T_p$) through electron-phonon scattering. Here, we show that, in spatially extended nanostructures, the lattice temperature can locally exceed that of the electrons, a seemingly counterintuitive transient effect termed hereafter ``temperature inversion'' ($T_p > T_e$). This phenomenon, fundamentally due to inhomogeneous absorption patterns and absent in smaller particles, emerges from a complex spatio-temporal interplay, between the electron-phonon coupling and competing electronic thermal diffusion. By combining rigorous three-dimensional (3D) finite-element-method-based simulations with practical reduced zero-dimensional (0D) analytical models, we identify the electron-phonon coupling coefficient ($G_{e-p}$) as the critical parameter governing this behavior. An optimal $G_{e-p}$ range allows the inversion, whereas a weak or overly strong coupling suppresses it. Among common plasmonic metals, platinum (Pt) exhibits the most pronounced and long-lived inversion, while gold (Au) and silver (Ag) show no significant inversion. Moreover, the close agreement between the 0D and 3D results, once an appropriate characteristic length is selected, highlights that the essential physics governing the inversion can be captured without full spatial complexity. These results provide insights for optimizing nanoscale energy transfer and hot-carrier-driven processes, guiding the strategic design of materials, geometries, and excitation conditions for enhanced ultrafast photothermal control.

cond-mat.mes-hall↗

arXiv2023

The first Ka-band (26.1-35 GHz) blind line survey towards Orion KL

We conducted a Ka-band (26.1--35 GHz) line survey towards Orion KL using the TianMa 65-m Radio Telescope (TMRT). It is the first blind line survey in the Ka band, and achieves a sensitivity of mK level (1--3 mK at a spectral resolution of $\sim$1 km s$^{-1}$). In total, 592 Gaussian features are extracted. Among them, 257 radio recombination lines (RRLs) are identified. The maximum $Δn$ of RRLs of H, He and C are 20, 15, and 5, respectively. Through stacking, we have detected the $β$ lines of ion RRLs (RRLs of C$^+$ with possible contribution of other ions like O$^+$) for the first time, and tentative signal of the $γ$ lines of ion RRLs can also be seen on the stacked spectrum. Besides, 318 other line features were assigned to 37 molecular species, and ten of these species were not detected in the Q-band survey of TMRT. The vibrationally excited states of nine species were also detected. Emission of most species can be modeled under LTE. A number of transitions of E-CH3OH ($J_2-J_1$) display maser effects, which are confirmed by our modeling, and besides the bumping peak at $J\sim 6$ there is another peak at $J\sim 13$. Methylcyanoacetylene (CH$_3$C$_3$N) is detected in Orion KL for the first time. This work emphasizes that the Ka band, which was long-ignored for spectral line surveys, is very useful for surveying RRLs and molecular lines simultaneously.

astro-ph.GA↗

arXiv2023

The triggering process of an X-class solar flare on a small quadrupolar active region

The occurrence of X-class solar flares and their potential impact on the space weather often receive great attention than other flares. But predicting when and where an X-class flare will occur is still a challenge. With the multi-wavelength observation from the Solar Dynamics Observatory and FengYun- 3E satellite, we investigate the triggering of a GOES X1.0 flare occurring in the NOAA active region (AR) 12887. Our results show that this unique X-class flare is bred in a relatively small but complex quadrupolar AR. Before the X-class flare, two filaments (F1 and F2) exist below a null-point topology of the quadrupolar AR. Magnetic field extrapolation and observation reveal that F1 and F2 correspond to two magnetic flux ropes with the same chirality and their adjacent feet rooted at nonconjugated opposite polarities, respectively. Interestingly, these two polarities collide rapidly, accompanied by photospheric magnetic flux emergence, cancellation and shear motion in the AR center. Above this site, F1 and F2 subsequently intersect and merge to a longer filament (F3) via a tether-cutting-like reconnection process. As a result, the F3 rises and erupts, involving the large-scale arcades overlying filament and the quadrupolar magnetic field above the AR, and eventually leads to the eruption of the X-class flare with a quasi-X-shaped flare ribbon and a coronal mass ejection. It suggests that the rapid collision of nonconjugated opposite polarities provides a key condition for the triggering of this X-class flare, and also provides a featured case for flare trigger mechanism and space weather forecasting.

astro-ph.SR↗

arXiv2023

Quantifying efficiency of remote excitation for surface enhanced Raman spectroscopy in molecular junctions

Surface-enhanced Raman spectroscopy (SERS) is enabled by local surface plasmon resonances (LSPRs) in metallic nanogaps. When SERS is excited by direct illumination of the nanogap, the background heating of lattice and electrons can prevent further manipulation of the molecules. To overcome this issue, we report SERS in electromigrated gold molecular junctions excited remotely: surface plasmon polaritons (SPPs) are excited at nearby gratings, propagate to the junction, and couple to the local nanogap plasmon modes. Like direct excitation, remote excitation of the nanogap can generate both SERS emission and an open-circuit photovoltage (OCPV). We compare SERS intensity and OCPV in both direct and remote illumination configurations. SERS spectra obtained by remote excitation are much more stable than those obtained through direct excitation when photon count rates are comparable. By statistical analysis of 33 devices, coupling efficiency of remote excitation is calculated to be around 10%, consistent with the simulated energy flow.

cond-mat.mes-hall↗

arXiv2023

Deep Progressive Feature Aggregation Network for High Dynamic Range Imaging

High dynamic range (HDR) imaging is an important task in image processing that aims to generate well-exposed images in scenes with varying illumination. Although existing multi-exposure fusion methods have achieved impressive results, generating high-quality HDR images in dynamic scenes is still difficult. The primary challenges are ghosting artifacts caused by object motion between low dynamic range images and distorted content in under and overexposed regions. In this paper, we propose a deep progressive feature aggregation network for improving HDR imaging quality in dynamic scenes. To address the issues of object motion, our method implicitly samples high-correspondence features and aggregates them in a coarse-to-fine manner for alignment. In addition, our method adopts a densely connected network structure based on the discrete wavelet transform, which aims to decompose the input features into multiple frequency subbands and adaptively restore corrupted contents. Experiments show that our proposed method can achieve state-of-the-art performance under different scenes, compared to other promising HDR imaging methods. Specifically, the HDR images generated by our method contain cleaner and more detailed content, with fewer distortions, leading to better visual quality.

cs.CV↗

arXiv2023

First Detection of Radio Recombination Lines of Ions Heavier than Helium

We report the first detection of radio recombination lines (RRLs) of ions heavier than helium. In a highly sensitive multi-band (12--50 GHz) line survey toward Orion KL with the TianMa 65-m Radio Telescope (TMRT), we successfully detected more than fifteen unblended $α$ lines of RRLs of singly ionized species (XII) recombined from XIII. The Ka-band (35--50 GHz) spectrum also shows tentative signals of $β$ lines of ions. The detected lines can be successfully crossmatched with the the rest frequencies of RRLs of CII and/or OII. This finding greatly expands the connotation of ion RRLs, since before this work only two blended lines (105$α$ and 121$α$) of HeII had been reported. Our detected lines can be fitted simultaneously under assumption of local thermodynamic equilibrium (LTE). An abundance of CIII and OIII of 8.8$\times$10$^{-4}$ is obtained, avoiding the complexities of optical/infrared observations and the blending of RRLs of atoms. It is consistent with but approaches the upper bound of the value (10$^{-4}$--$10^{-3}$) estimated from optical/infrared observations. The effects of dielectronic recombination may contribute to enhancing the level populations even at large $n$. We expect future observations using radio interferometers could break the degeneracy between C and O, and help to reveal the ionization structure and dynamical evolution of various ionized regions.

astro-ph.GA↗

arXiv2022

Consistency of Implicit and Explicit Features Matters for Monocular 3D Object Detection

Low-cost autonomous agents including autonomous driving vehicles chiefly adopt monocular 3D object detection to perceive surrounding environment. This paper studies 3D intermediate representation methods which generate intermediate 3D features for subsequent tasks. For example, the 3D features can be taken as input for not only detection, but also end-to-end prediction and/or planning that require a bird's-eye-view feature representation. In the study, we found that in generating 3D representation previous methods do not maintain the consistency between the objects' implicit poses in the latent space, especially orientations, and the explicitly observed poses in the Euclidean space, which can substantially hurt model performance. To tackle this problem, we present a novel monocular detection method, the first one being aware of the poses to purposefully guarantee that they are consistent between the implicit and explicit features. Additionally, we introduce a local ray attention mechanism to efficiently transform image features to voxels at accurate 3D locations. Thirdly, we propose a handcrafted Gaussian positional encoding function, which outperforms the sinusoidal encoding function while retaining the benefit of being continuous. Results show that our method improves the state-of-the-art 3D intermediate representation method by 3.15%. We are ranked 1st among all the reported monocular methods on both 3D and BEV detection benchmark on KITTI leaderboard as of th result's submission time.

cs.CV↗

arXiv2022

A Q-band line survey towards Orion KL using the Tianma radio telescope

We have conducted a line survey towards Orion KL using the Q-band receiver of Tianma 65 m radio telescope (TMRT), covering 34.8--50 GHz with a velocity resolution between 0.79 km s$^{-1}$ and 0.55 km s$^{-1}$ respectively. The observations reach a sensitivity on the level of 1-8 mK, proving that the TMRT is sensitive for conducting deep line surveys. In total, 597 Gaussian features are extracted. Among them, 177 radio recombination lines (RRLs) are identified, including 126, 40 and 11 RRLs of hydrogen, helium and carbon, with a maximum $Δn$ of 16, 7, and 3, respectively. The carbon RRLs are confirmed to originate from photodissociation regions with a $V_{\rm LSR}\sim$9 km s$^{-1}$. In addition, 371 molecular transitions of 53 molecular species are identified. Twenty-one molecular species of this survey were not firmly detected in the Q band by Rizzo et al. (2017), including species such as H$_2$CS, HCOOH, C$_2$H$_5$OH, H$_2^{13}$CO, H$_2$CCO, CH$_3$CHO, CH$_2$OCH$_2$, HCN $v_2=1$, and CH$_3$OCHO $v_t=1$. In particular, the vibrationally excited states of ethyl cyanide (C$_2$H$_5$CN $v$13/$v$21) are for the first time firmly detected in the Q band. NH$_3$ (15,15) and (16,16) are identified, and they are so far the highest transitions of the NH$_3$ inversion lines detected towards Orion KL. All the identified lines can be reproduced by a radiative transfer model.

astro-ph.GA↗

arXiv2022

Single-image Defocus Deblurring by Integration of Defocus Map Prediction Tracing the Inverse Problem Computation

In this paper, we consider the problem in defocus image deblurring. Previous classical methods follow two-steps approaches, i.e., first defocus map estimation and then the non-blind deblurring. In the era of deep learning, some researchers have tried to address these two problems by CNN. However, the simple concatenation of defocus map, which represents the blur level, leads to suboptimal performance. Considering the spatial variant property of the defocus blur and the blur level indicated in the defocus map, we employ the defocus map as conditional guidance to adjust the features from the input blurring images instead of simple concatenation. Then we propose a simple but effective network with spatial modulation based on the defocus map. To achieve this, we design a network consisting of three sub-networks, including the defocus map estimation network, a condition network that encodes the defocus map into condition features, and the defocus deblurring network that performs spatially dynamic modulation based on the condition features. Moreover, the spatially dynamic modulation is based on an affine transform function to adjust the features from the input blurry images. Experimental results show that our method can achieve better quantitative and qualitative evaluation performance than the existing state-of-the-art methods on the commonly used public test datasets.

cs.CV↗

arXiv2022

Learning Regularized Multi-Scale Feature Flow for High Dynamic Range Imaging

Reconstructing ghosting-free high dynamic range (HDR) images of dynamic scenes from a set of multi-exposure images is a challenging task, especially with large object motion and occlusions, leading to visible artifacts using existing methods. To address this problem, we propose a deep network that tries to learn multi-scale feature flow guided by the regularized loss. It first extracts multi-scale features and then aligns features from non-reference images. After alignment, we use residual channel attention blocks to merge the features from different images. Extensive qualitative and quantitative comparisons show that our approach achieves state-of-the-art performance and produces excellent results where color artifacts and geometric distortions are significantly reduced.

cs.CV↗

arXiv2022

Qtrade AI at SemEval-2022 Task 11: An Unified Framework for Multilingual NER Task

This paper describes our system, which placed third in the Multilingual Track (subtask 11), fourth in the Code-Mixed Track (subtask 12), and seventh in the Chinese Track (subtask 9) in the SemEval 2022 Task 11: MultiCoNER Multilingual Complex Named Entity Recognition. Our system's key contributions are as follows: 1) For multilingual NER tasks, we offer an unified framework with which one can easily execute single-language or multilingual NER tasks, 2) for low-resource code-mixed NER task, one can easily enhance his or her dataset through implementing several simple data augmentation methods and 3) for Chinese tasks, we propose a model that can capture Chinese lexical semantic, lexical border, and lexical graph structural information. Finally, our system achieves macro-f1 scores of 77.66, 84.35, and 74.00 on subtasks 11, 12, and 9, respectively, during the testing phase.

cs.CL↗

arXiv2021

Progressive and Selective Fusion Network for High Dynamic Range Imaging

This paper considers the problem of generating an HDR image of a scene from its LDR images. Recent studies employ deep learning and solve the problem in an end-to-end fashion, leading to significant performance improvements. However, it is still hard to generate a good quality image from LDR images of a dynamic scene captured by a hand-held camera, e.g., occlusion due to the large motion of foreground objects, causing ghosting artifacts. The key to success relies on how well we can fuse the input images in their feature space, where we wish to remove the factors leading to low-quality image generation while performing the fundamental computations for HDR image generation, e.g., selecting the best-exposed image/region. We propose a novel method that can better fuse the features based on two ideas. One is multi-step feature fusion; our network gradually fuses the features in a stack of blocks having the same structure. The other is the design of the component block that effectively performs two operations essential to the problem, i.e., comparing and selecting appropriate images/regions. Experimental results show that the proposed method outperforms the previous state-of-the-art methods on the standard benchmark tests.

cs.CV↗

arXiv2021

Deformation measurement by single spherical near-field intensity measurement for large reflector antenna

This paper presents a new method to obtain the deformation distribution on the main reflector of an antenna only by measuring the electric intensity on a spherical surface with the focal point as the center of the sphere, regardless of phase. Combining the differential geometry theory with geometric optics method, this paper has derived a deformation-intensity equation to relate the surface deformation to the intensity distribution of a spherical near-field directly. Based on the Finite difference method (FDM) and Gauss-Seidel iteration, deformation has been calculated from intensity simulated by GO and PO method, respectively, with relatively small errors, which prove the effectiveness of the equation proposed in this paper. By means of this method , it is possible to measure the deformation only by scanning the electric intensity of a single hemispherical near-field whose area is only about $1/15$ of the aperture. And the measurement only needs a plane wave at any frequency as the incident wave, which means that both the signals from the outer space satellite and the far-field artificial beacon could be used as the sources. The scanning can be realized no matter what attitude and elevation angle the antenna is in because the size and angle of the hemisphere are changeable.

astro-ph.IM↗

arXiv2020

Non-interferometric accurate phase imaging via a linear-convergence iterative optimization

This paper reported a general noninterferometric high-accuracy quantitative phase imaging (QPI) method for arbitrary complex valued objects. Given by a typical 4f optical configuration as the imaging system, three frames of small-window phase modulation are applied on the object Fourier spectrum so that redistributed intensity patterns are produced on the image plane, in which the object phase emerges at different degree. Then, an algebraic relationship that connects the object phase with the output intensity is established to provide us with an approximate closed form phase recovery. Further, an efficient iterative optimization strategy is developed to turn that approximate solution into an accurate one. Due to the linear convergence property of the iteration, a high accuracy phase recovery is achieved without requiring heavy iterations. The feasibility and accuracy of the proposed method are verified by both numerical simulations and experiments on diverse phase objects.

eess.IV↗

arXiv2020

Using LDA and LSTM Models to Study Public Opinions and Critical Groups Towards Congestion Pricing in New York City through 2007 to 2019

This study explores how people view and respond to the proposals of NYC congestion pricing evolve in time. To understand these responses, Twitter data is collected and analyzed. Critical groups in the recurrent process are detected by statistically analyzing the active users and the most mentioned accounts, and the trends of people's attitudes and concerns over the years are identified with text mining and hybrid Nature Language Processing techniques, including LDA topic modeling and LSTM sentiment classification. The result shows that multiple interest groups were involved and played crucial roles during the proposal, especially Mayor and Governor, MTA, and outer-borough representatives. The public shifted the concern of focus from the plan details to a wider city's sustainability and fairness. Furthermore, the plan's approval relies on several elements, the joint agreement reached in the political process, strong motivation in the real-world, the scheme based on balancing multiple interests, and groups' awareness of tolling's benefits and necessity.

cs.CY↗