arXiv subjects

Long Ma

Publications and source records attributed to Long Ma.

At least 91 records · Page 5Linked to original sources

arXiv2024

Topologically nontrivial $1/3$-magnetization plateau state in a spin-1/2 trimer chain

Topologically nontrivial Haldane phase is theoretically proposed to be realized in the 1/3-magnetization ($M$) plateau of spin-1/2 trimer systems. However, the spin excitation gap, typical characteristic of Haldane phase, is not yet experimentally verified. Here, we report the nuclear magnetic resonance investigations into the low-energy spin dynamics in the $S=1/2$ spin-trimer antiferromagnetic chain compound Na$_2$Cu$_3$Ge$_{4-x}$Si$_{x}$O$_{12}$ ($x=0, 0.1\sim1.5$). In the parent compound ($x=0$), the spin-lattice relaxation rate (1/$T_1$) shows significantly different temperature dependence when the external magnetic field is increased above the critical field of $μ_0$$H_{c}$ = 29 T. The spin excitation gap is evidenced from the thermally activated behavior of $1/T_1(T)$ in the 1/3-$M$ plateau state. By substituting Ge$^{4+}$ with Si$^{4+}$, the critical field for the 1/3-$M$ plateau significantly decreases, e.g. $μ_0H_{c}=17$ T in $x=1.0$ samples, which results from the suppressed inter-trimer coupling $J_2$. The gapped spin excitation is confirmed again above 17 T, whose size shows temperature-dependent behavior for $μ_0H\geq25.72$ T. These observations provide further insights into the Haldane physics.

cond-mat.str-el↗

arXiv2024

Dynamic Response of Ionic Current in Conical Nanopores

Ionic current rectification (ICR) of charged conical nanopores has various applications in fields including nanofluidics, bio-sensing, and energy conversion, whose function is closely related to the dynamic response of nanopores. The occurrence of ICR originates from the ion enrichment and depletion in conical pores, whose formation is found to be affected by the scanning rate of voltages. Here, through time-dependent simulations, we investigate the variation of ion current under electric fields and the dynamic formation of ion enrichment and depletion, which can reflect the response time of conical nanopores. The response time of nanopores when ion enrichment forms i.e. at the on state is significantly longer than that with the formation of ion depletion i.e. at the off state. Our simulation results reveal the regulation of response time by different nanopore parameters including the surface charge density, pore length, tip, and base radius, as well as the applied conditions such as the voltage and bulk concentration. The response time of nanopores is closely related to the surface charge density, pore length, voltage, and bulk concentration. Our uncovered dynamic response mechanism of the ionic current can guide the design of nanofluidic devices with conical nanopores, including memristors, ionic switches, and rectifiers.

physics.chem-ph↗

arXiv2024

Seeing Text in the Dark: Algorithm and Benchmark

Localizing text in low-light environments is challenging due to visual degradations. Although a straightforward solution involves a two-stage pipeline with low-light image enhancement (LLE) as the initial step followed by detector, LLE is primarily designed for human vision instead of machine and can accumulate errors. In this work, we propose an efficient and effective single-stage approach for localizing text in dark that circumvents the need for LLE. We introduce a constrained learning module as an auxiliary mechanism during the training stage of the text detector. This module is designed to guide the text detector in preserving textual spatial features amidst feature map resizing, thus minimizing the loss of spatial information in texts under low-light visual degradations. Specifically, we incorporate spatial reconstruction and spatial semantic constraints within this module to ensure the text detector acquires essential positional and contextual range knowledge. Our approach enhances the original text detector's ability to identify text's local topological features using a dynamic snake feature pyramid network and adopts a bottom-up contour shaping strategy with a novel rectangular accumulation technique for accurate delineation of streamlined text features. In addition, we present a comprehensive low-light dataset for arbitrary-shaped text, encompassing diverse scenes and languages. Notably, our method achieves state-of-the-art results on this low-light dataset and exhibits comparable performance on standard normal light datasets. The code and dataset will be released.

cs.CV↗

arXiv2024

Low-energy spin dynamics in a Kitaev material Na3Ni2BiO6 investigated by NMR

We performed 23Na NMR and magnetization measurements on an S = 1, quasi-2D honeycomb lattice antiferromagnet Na3Ni2BiO6. A large positive Curie-Weiss constant of 22.9 K is observed. The NMR spectra at low fields are consistent with a "zigzag" magnetic order, indicating a large easy-axis anisotropy. With field applied along the c* axis, the NMR spectra confirm the existence of a 1/3-magnetization plateau phase between 5.1 T and 7.1 T. The transition from the zigzag order to the 1/3-magnetization plateau phase is also found to be a first-order type. A monotonic decrease of the spin gap is revealed in the 1/3-magnetization plateau phase, which reaches zero at a quantum critical field Hc = 8.35 T before entering the fully polarized phase. These data suggest the existence of exchange frustration in the system along with strong ferromagnetic interactions, hosting the possibility for Kitaev physics. Besides, well below the ordered phase, the 1/T1 at high fields shows either a level off or an enhancement upon cooling below 3 K, which suggests the existence of low-energy fluctuations.

cond-mat.str-el↗

arXiv2024

Improved theoretical prediction of nanoparticle sizes with the resistive-pulse technique

With the resistive-pulse technique (RPT), nanopores serve as the nanofluidic sensors of various analytes for their many physical and chemical properties. Here, we focus on the size measurement and its theoretical prediction for sub-200 nm nanoparticles with RPT. Through systematical investigation of the current blockade of nanoparticles across cylindrical nanopores with simulations, Maxwell method considering the shape coefficient and access resistances agrees well with simulation results. However, the widely used integration method of the resistance has distinct deviations in various cases. With the introduction of a correction factor \b{eta} to the integration method, our revised equations can provide good predictions for simulation results. \b{eta} shows a strong dependence on the diameter ratio (d over D) of the nanoparticle and nanopore. Following the same strategy, modified equations are provided for the accurate size prediction for nanoparticles across conical nanopores, where the integration method is the default convenient way. The correction factor \b{eta}' relates to \b{eta} in cylindrical nanopores. \b{eta}' exhibits independence on the pore geometry parameters and diameters of nanoparticles, but dependence on the surface charge density of conical nanopores. Our improved equations can provide theoretical predictions for the accurate size detection of 100-200 nm diameter nanoparticles across cylindrical and conical nanopores.

physics.chem-ph↗

arXiv2024

Ion Transport through Short Nanopores Modulated by Charged Exterior Surfaces

Short nanopores find extensive applications capitalizing on their high throughput and detection resolution. Ionic behaviors through long nanopores are mainly determined by charged inner-pore walls. When pore lengths decrease to sub-200 nm, charged exterior surfaces provide considerable modulation to ion current. We find that the charge status of inner-pore walls affects the modulation of ion current from charged exterior surfaces. For 50-nm-long nanopores with neutral inner-pore walls, charged exterior surfaces on the voltage (surfaceV) and ground (surfaceG) sides enhance and inhibit ion transport by forming ion enrichment and depletion zones inside nanopores, respectively. For nanopores with both charged inner-pore and exterior surfaces, continuous electric double layers enhance ion transport through nanopores significantly. The charged surfaceV results in higher ion current by simultaneously weakening ion depletion at pore entrances and enhancing the intra-pore ion enrichment. The charged surfaceG expedites the exit of ions from nanopores, resulting in a decrease in ion enrichment at pore exits. Through adjustment in the width of charged-ring regions near pore boundaries, the effective charged width of the charged exterior is explored at ~20nm. Our results may provide a theoretical guide for further optimizing the performance of nanopore-based applications, like seawater desalination, biosensing, and osmotic energy conversion.

physics.chem-ph↗

arXiv2024

Characterization of the Surface Charge Property and Porosity of Track-etched Polymer Membranes

As an important property of porous membranes, the surface charge property determines many ionic behaviors of nanopores, such as ionic conductance and selectivity. Based on the dependence of electric double layers on bulk concentrations, ionic conductance through nanopores at high and low concentrations is governed by the bulk conductance and surface charge density, respectively. Here, through the investigation of ionic conductance inside track-etched single polyethylene terephthalate (PET) nanopores under various concentrations, the surface charge density of PET membranes is extracted as around 0.021 C per m2 at pH 10 over measurements with 40 PET nanopores. Simulations show that surface roughness can cause underestimation in surface charge density due to the inhibited electroosmotic flow. Then, the averaged pore size and porosity of track-etched multipore PET membranes are characterized by the developed ionic conductance method. Through coupled theoretical predictions in ionic conductance under high and low concentrations, the averaged pore size and porosity of porous membranes can be obtained simultaneously. Our method provides a simple and precise way to characterize the pore size and porosity of multipore membranes, especially for those with sub-100 nm pores and low porosities.

physics.chem-ph↗

arXiv2024

Influences of Divalent Ions in Natural Seawater/River Water on Nanofluidic Osmotic Energy Generation

Besides the dominant NaCl, natural seawater/river water contains trace multivalent ions, which can provide effective screening to surface charges. Here, in both negatively and positively charged nanopores, influences from divalent ions as counterions and coions have been investigated on the performance of osmotic energy conversion (OEC) under natural salt gradients. As counterions, trace Ca2+ ions can suppress the electric power and conversion efficiency significantly. The reduced OEC performance is due to the bivalence and low diffusion coefficient of Ca2 ions, instead of the uphill transport of divalent ions discovered in the previous work. Effectively screened charged surfaces by Ca2+ ions induce enhanced diffusion of Cl ions which simultaneously decreases the net ion penetration and ionic selectivity of the nanopore. While as coions, Ca2+ ions have weak effects on the OEC performance. The promotion from charged exterior surfaces on OEC processes for ultra-short nanopores is also studied, which effective region is ~200 nm in width beyond pore boundaries independent of the presence of Ca2+ ions. Our results shed light on the physical details of the nanofluidic OEC process under natural seawater/river water conditions, which can provide a useful guide for high-performance osmotic energy harvesting.

physics.chem-ph↗

arXiv2024

Modulation Mechanism of Ionic Transport through Short Nanopores by Charged Exterior Surfaces

Short nanopores have various applications in biosensing, desalination, and energy conversion. Here, the modulation of charged exterior surfaces on ionic transport is investigated through simulations with sub-200 nm long nanopores under applied voltages. Detailed analysis of ionic current, electric field strength, and fluid flow inside and outside nanopores reveals that charged exterior surfaces can increase ionic conductance by increasing both the concentration and migration speed of charge carriers. The electric double layers near charged exterior surfaces provide an ion pool and an additional passageway for counterions, which lead to enhanced exterior surface conductance and ionic concentrations at pore entrances and inside the nanopore. We also report that charges on the membrane surfaces increase electric field strengths inside nanopores. The effective width of a ring with surface charges placed at pore entrances (Lcs) is considered as well by studying the dependence of the current on Lcs. We find a linear relationship between the effective Lcs and the surface charge density and voltage, and an inverse relationship between the geometrical pore length and salt concentration. Our results elucidate the modulation mechanism of charged exterior surfaces on ionic transport through short nanopores, which is important for the design and fabrication of porous membranes.

cond-mat.soft↗

arXiv2024

Influences of Electroosmotic Flow on Ionic Current through Nanopores: a Comprehensive Understanding

Continuum simulations become an important tool to uncover the mysteries in nanofluidic experiments. However, fluid flow in simulation models is usually unconsidered. Here, systematical simulations are conducted to provide a quantitative understanding of influences from electroosmotic flow (EOF) on ionic transport through nanopores by both types of models with and without consideration of EOF. In nanopores of less than ~10 nm in diameter, counterions dominate ionic current which is always promoted obviously by the convective effect of EOF. In the diameter range from ~10 to ~30 nm, strong EOF induces ion concentration polarization or ion depletion inside nanopores which causes significant decreases in ionic current. For nanopores larger than ~30 nm, due to convective promotion and inhibition of EOF on the transport of counterions and anions, considerable nanopore selectivity to counterions maintains in cases with EOF. Though the difference in total current between both cases decreases with further pore size increasing, the difference in cation/anion current is still considerable. From our results under various pore parameters and applied conditions, the fluid flow should be considered in the simulation cases when EOF is strong. Our work may provide useful guidance for simulation conductance.

physics.chem-ph↗

arXiv2023

From Text to Pixels: A Context-Aware Semantic Synergy Solution for Infrared and Visible Image Fusion

With the rapid progression of deep learning technologies, multi-modality image fusion has become increasingly prevalent in object detection tasks. Despite its popularity, the inherent disparities in how different sources depict scene content make fusion a challenging problem. Current fusion methodologies identify shared characteristics between the two modalities and integrate them within this shared domain using either iterative optimization or deep learning architectures, which often neglect the intricate semantic relationships between modalities, resulting in a superficial understanding of inter-modal connections and, consequently, suboptimal fusion outcomes. To address this, we introduce a text-guided multi-modality image fusion method that leverages the high-level semantics from textual descriptions to integrate semantics from infrared and visible images. This method capitalizes on the complementary characteristics of diverse modalities, bolstering both the accuracy and robustness of object detection. The codebook is utilized to enhance a streamlined and concise depiction of the fused intra- and inter-domain dynamics, fine-tuned for optimal performance in detection tasks. We present a bilevel optimization strategy that establishes a nexus between the joint problem of fusion and detection, optimizing both processes concurrently. Furthermore, we introduce the first dataset of paired infrared and visible images accompanied by text prompts, paving the way for future research. Extensive experiments on several datasets demonstrate that our method not only produces visually superior fusion results but also achieves a higher detection mAP over existing methods, achieving state-of-the-art results.

cs.CV↗

arXiv2023

Fearless Luminance Adaptation: A Macro-Micro-Hierarchical Transformer for Exposure Correction

Photographs taken with less-than-ideal exposure settings often display poor visual quality. Since the correction procedures vary significantly, it is difficult for a single neural network to handle all exposure problems. Moreover, the inherent limitations of convolutions, hinder the models ability to restore faithful color or details on extremely over-/under- exposed regions. To overcome these limitations, we propose a Macro-Micro-Hierarchical transformer, which consists of a macro attention to capture long-range dependencies, a micro attention to extract local features, and a hierarchical structure for coarse-to-fine correction. In specific, the complementary macro-micro attention designs enhance locality while allowing global interactions. The hierarchical structure enables the network to correct exposure errors of different scales layer by layer. Furthermore, we propose a contrast constraint and couple it seamlessly in the loss function, where the corrected image is pulled towards the positive sample and pushed away from the dynamically generated negative samples. Thus the remaining color distortion and loss of detail can be removed. We also extend our method as an image enhancer for low-light face recognition and low-light semantic segmentation. Experiments demonstrate that our approach obtains more attractive results than state-of-the-art methods quantitatively and qualitatively.

cs.CV↗

arXiv2023

Theoretical prediction of diffusive ionic current through nanopores under salt gradients

In charged nanopores, ionic diffusion current reflects the ionic selectivity and ionic permeability of nanopores which determines the performance of osmotic energy conversion, i.e. the output power and efficiency. Here, theoretical predictions of the diffusive currents through cation-selective nanopores have been developed based on the investigation of diffusive ionic transport under salt gradients with simulations. The ionic diffusion current I satisfies a reciprocal relationship with the pore length I correlates with a/L (a is a constant) in long nanopores. a is determined by the cross-sectional areas of diffusion paths for anions and cations inside nanopores which can be described with a quadratic power of the diameter, and the superposition of a quadratic power and a first power of the diameter, respectively. By using effective concentration gradients instead of nominal ones, the deviation caused by the concentration polarization can be effectively avoided in the prediction of ionic diffusion current. With developed equations of effective concentration difference and ionic diffusion current, the diffusion current across nanopores can be well predicted in cases of nanopores longer than 100 nm and without overlapping of electric double layers. Our results can provide a convenient way for the quantitative prediction of ionic diffusion currents under salt gradients.

physics.chem-ph↗

arXiv2023

Transient analysis of arm locking controller

Arm locking is one of the key technologies to suppress the laser phase noise in spaced-based gravitational waves observatories. Since arm locking was proposed, phase margin criterion was always used as the fundamental design strategy for the controller development. In this paper, we find that this empirical method from engineering actually cannot guarantee the arm locking stability. Therefore, most of the advanced arm locking controllers reported so far may have instable problems. After comprehensive analysis of the single arm locking's transient responses, strict analytical stability criterions are summarized for the first time. These criterions are then generalized to dual arm locking, modified-dual arm locking and common arm locking, and special considerations for the design of arm locking controllers in different architectures are also discussed. It is found that PI controllers can easily meet our stability criterions in most of the arm locking systems. Using a simple high gain PI controller, it is possible to suppress the laser phase noise by 5 orders of magnitude within the science band. Our stability criterions can also be used in other feedback systems, where several modules with different delays are connected in parallel.

gr-qc↗

arXiv2023

Trash to Treasure: Low-Light Object Detection via Decomposition-and-Aggregation

Object detection in low-light scenarios has attracted much attention in the past few years. A mainstream and representative scheme introduces enhancers as the pre-processing for regular detectors. However, because of the disparity in task objectives between the enhancer and detector, this paradigm cannot shine at its best ability. In this work, we try to arouse the potential of enhancer + detector. Different from existing works, we extend the illumination-based enhancers (our newly designed or existing) as a scene decomposition module, whose removed illumination is exploited as the auxiliary in the detector for extracting detection-friendly features. A semantic aggregation module is further established for integrating multi-scale scene-related semantic information in the context space. Actually, our built scheme successfully transforms the "trash" (i.e., the ignored illumination in the detector) into the "treasure" for the detector. Plenty of experiments are conducted to reveal our superiority against other state-of-the-art methods. The code will be public if it is accepted.

cs.CV↗

arXiv2023

Enhancing Infrared Small Target Detection Robustness with Bi-Level Adversarial Framework

The detection of small infrared targets against blurred and cluttered backgrounds has remained an enduring challenge. In recent years, learning-based schemes have become the mainstream methodology to establish the mapping directly. However, these methods are susceptible to the inherent complexities of changing backgrounds and real-world disturbances, leading to unreliable and compromised target estimations. In this work, we propose a bi-level adversarial framework to promote the robustness of detection in the presence of distinct corruptions. We first propose a bi-level optimization formulation to introduce dynamic adversarial learning. Specifically, it is composited by the learnable generation of corruptions to maximize the losses as the lower-level objective and the robustness promotion of detectors as the upper-level one. We also provide a hierarchical reinforced learning strategy to discover the most detrimental corruptions and balance the performance between robustness and accuracy. To better disentangle the corruptions from salient features, we also propose a spatial-frequency interaction network for target detection. Extensive experiments demonstrate our scheme remarkably improves 21.96% IOU across a wide array of corruptions and notably promotes 4.97% IOU on the general benchmark. The source codes are available at https://github.com/LiuZhu-CV/BALISTD.

cs.CV↗

arXiv2023

AdvMono3D: Advanced Monocular 3D Object Detection with Depth-Aware Robust Adversarial Training

Monocular 3D object detection plays a pivotal role in the field of autonomous driving and numerous deep learning-based methods have made significant breakthroughs in this area. Despite the advancements in detection accuracy and efficiency, these models tend to fail when faced with such attacks, rendering them ineffective. Therefore, bolstering the adversarial robustness of 3D detection models has become a crucial issue that demands immediate attention and innovative solutions. To mitigate this issue, we propose a depth-aware robust adversarial training method for monocular 3D object detection, dubbed DART3D. Specifically, we first design an adversarial attack that iteratively degrades the 2D and 3D perception capabilities of 3D object detection models(IDP), serves as the foundation for our subsequent defense mechanism. In response to this attack, we propose an uncertainty-based residual learning method for adversarial training. Our adversarial training approach capitalizes on the inherent uncertainty, enabling the model to significantly improve its robustness against adversarial attacks. We conducted extensive experiments on the KITTI 3D datasets, demonstrating that DART3D surpasses direct adversarial training (the most popular approach) under attacks in 3D object detection $AP_{R40}$ of car category for the Easy, Moderate, and Hard settings, with improvements of 4.415%, 4.112%, and 3.195%, respectively.

cs.CV↗

arXiv2023

Hybrid-Supervised Dual-Search: Leveraging Automatic Learning for Loss-free Multi-Exposure Image Fusion

Multi-exposure image fusion (MEF) has emerged as a prominent solution to address the limitations of digital imaging in representing varied exposure levels. Despite its advancements, the field grapples with challenges, notably the reliance on manual designs for network structures and loss functions, and the constraints of utilizing simulated reference images as ground truths. Consequently, current methodologies often suffer from color distortions and exposure artifacts, further complicating the quest for authentic image representation. In addressing these challenges, this paper presents a Hybrid-Supervised Dual-Search approach for MEF, dubbed HSDS-MEF, which introduces a bi-level optimization search scheme for automatic design of both network structures and loss functions. More specifically, we harnesses a unique dual research mechanism rooted in a novel weighted structure refinement architecture search. Besides, a hybrid supervised contrast constraint seamlessly guides and integrates with searching process, facilitating a more adaptive and comprehensive search for optimal loss functions. We realize the state-of-the-art performance in comparison to various competitive schemes, yielding a 10.61% and 4.38% improvement in Visual Information Fidelity (VIF) for general and no-reference scenarios, respectively, while providing results with high contrast, rich details and colors.

cs.CV↗