SearcharxivSearch

arXiv subjects

Jianwei Zhao

Publications and source records attributed to Jianwei Zhao.

12 recordsLinked to original sources

Purifying one-neutron removal as a probe of single-particle strength

One-neutron removal reactions exhibit a strong proton-neutron asymmetry dependence in the inclusive reduction factor $R_s$, a long-standing issue that has been discussed in terms of both possible intrinsic isospin dependence of single-particle strength and reaction-mechanism effects. We address this issue by reframing inclusive removal as a coupled fast-dynamics and deexcitation process, and by validating this transport-deexcitation chain against a global, mutually constraining data set. Confronting 73 one-neutron removal cross sections and 28 residue parallel-momentum distributions with isospin-dependent quantum molecular dynamics followed by GEMINI evaporation shows that the apparent $R_s$-$\Delta S$ trend is correlated with evaporation feeding and evaporation loss. By subtracting the feeding contribution and correcting for the loss component in the measured cross sections, we construct a purified reduction factor $R_{\rm dir}$, that more closely reflects single-particle strength than the inclusive $R_s$. The resulting $R_{\rm dir}$ exhibits a much weaker $\Delta S$ dependence within current uncertainties, consistent with the weak isospin-asymmetry dependence observed in nucleon-transfer and quasifree-knockout systematics.

nucl-th

Cooperative Multi-Static ISAC Networks: A Unified Design Framework for Active and Passive Sensing

Multi-static cooperative sensing emerges as a promising technology for advancing integrated sensing and communication (ISAC), enhancing sensing accuracy and range. In this paper, we develop a unified design framework for joint active and passive sensing (JAPS). In particular, we consider a JAPSbased cooperative multi-static ISAC system for coexisting downlink (DL) and uplink (UL) communications. An optimization problem is formulated for maximizing the sum rate of both the DL and UL transmissions via jointly optimizing beamforming, receive filters and power allocation, while guaranteeing the sensing requirements and transmission power constraints. However, the formulated problem is a non-convex optimization problem that is challenging to solve directly due to the tight coupling among optimization variables. To tackle this complicated issue, we employ an efficient algorithm architecture leveraging alternating optimization (AO). Specifically, with the given receive filters and transmission power for UL communication, the transmit beamforming subproblem is addressed by successive convex approximation (SCA)-based and penalty-based algorithms. A fractional programming (FP)-based algorithm is developed to tackle the receive filters and transmission power for UL communication optimization subproblem. Extensive numerical results validate the performance improvement of our proposed JAPS scheme and demonstrate the effectiveness of our proposed algorithms.

eess.SP

MExD: An Expert-Infused Diffusion Model for Whole-Slide Image Classification

Whole Slide Image (WSI) classification poses unique challenges due to the vast image size and numerous non-informative regions, which introduce noise and cause data imbalance during feature aggregation. To address these issues, we propose MExD, an Expert-Infused Diffusion Model that combines the strengths of a Mixture-of-Experts (MoE) mechanism with a diffusion model for enhanced classification. MExD balances patch feature distribution through a novel MoE-based aggregator that selectively emphasizes relevant information, effectively filtering noise, addressing data imbalance, and extracting essential features. These features are then integrated via a diffusion-based generative process to directly yield the class distribution for the WSI. Moving beyond conventional discriminative approaches, MExD represents the first generative strategy in WSI classification, capturing fine-grained details for robust and precise results. Our MExD is validated on three widely-used benchmarks-Camelyon16, TCGA-NSCLC, and BRACS consistently achieving state-of-the-art performance in both binary and multi-class tasks.

cs.CV

FocusDiffuser: Perceiving Local Disparities for Camouflaged Object Detection

Detecting objects seamlessly blended into their surroundings represents a complex task for both human cognitive capabilities and advanced artificial intelligence algorithms. Currently, the majority of methodologies for detecting camouflaged objects mainly focus on utilizing discriminative models with various unique designs. However, it has been observed that generative models, such as Stable Diffusion, possess stronger capabilities for understanding various objects in complex environments; Yet their potential for the cognition and detection of camouflaged objects has not been extensively explored. In this study, we present a novel denoising diffusion model, namely FocusDiffuser, to investigate how generative models can enhance the detection and interpretation of camouflaged objects. We believe that the secret to spotting camouflaged objects lies in catching the subtle nuances in details. Consequently, our FocusDiffuser innovatively integrates specialized enhancements, notably the Boundary-Driven LookUp (BDLU) module and Cyclic Positioning (CP) module, to elevate standard diffusion models, significantly boosting the detail-oriented analytical capabilities. Our experiments demonstrate that FocusDiffuser, from a generative perspective, effectively addresses the challenge of camouflaged object detection, surpassing leading models on benchmarks like CAMO, COD10K and NC4K.

cs.CV

Integrated Sensing and Communications in Clutter Environment

In this paper, we propose a practical integrated sensing and communications (ISAC) framework to sense dynamic targets from clutter environment while ensuring users communications quality. To implement communications function and sensing function simultaneously, we design multiple communications beams that can communicate with the users as well as one sensing beam that can rotate and scan the entire space. To minimize the interference of sensing beam on existing communications systems, we divide the service area into sensing beam for sensing (S4S) sector and communications beam for sensing (C4S) sector, and provide beamforming design and power allocation optimization strategies for each type sector. Unlike most existing ISAC studies that ignore the interference of static environmental clutter on target sensing, we construct a mixed sensing channel model that includes both static environment and dynamic targets. When base station receives the echo signals, the mean phasor cancellation (MPC) method is employed to filter out the interference from static environmental clutter and to extract the effective dynamic target echoes. Then a complete and practical dynamic target sensing scheme is designed to detect the presence of dynamic targets and to estimate their angles, distances, and velocities. In particular, dynamic target detection and angle estimation are realized through angle-Doppler spectrum estimation (ADSE) and joint detection over multiple subcarriers (MSJD), while distance and velocity estimation are realized through the extended subspace algorithm. Simulation results demonstrate the effectiveness of the proposed scheme and its superiority over the existing methods that ignore environmental clutter.

eess.SP

Topological design and synthesis of high-spin aza-triangulenes without Jahn-Teller distortions

The atomic doping of open-shell nanographenes enables the precise tuning of their electronic and magnetic state, which is crucial for their promising potential applications in optoelectronics and spintronics. Among this intriguing class of molecules, triangulenes stand out with their size-dependent electronic properties and spin states, which can also be influenced by the presence of dopant atoms and functional groups. However, the occurrence of Jahn-Teller distortions in such systems can have a crucial impact on their total spin and requires further theoretical and experimental investigation. In this study, we examine the nitrogen-doped aza-triangulene series via a combination of density functional theory and on-surface synthesis. We identify a general trend in the calculated spin states of aza-[n]triangulenes of various sizes, separating them into two symmetry classes, one of which features molecules that are predicted to undergo Jahn-Teller distortions that reduce their symmetry and thus their total spin. We link this behavior to the location of the central nitrogen atom relative to the two underlying carbon sublattices of the molecules. Consequently, our findings reveal that centrally-doped aza-triangulenes have one less radical than their undoped counterparts, irrespective of their predicted symmetry. We follow this by demonstrating the on-surface synthesis of π-extended aza-[5]triangulene, a large member of the higher symmetry class without Jahn-Teller distortions, via a simple one-step annealing process on Cu(111) and Au(111). Using scanning probe microscopy and spectroscopy combined with theoretical calculations, we prove that the molecule is positively charged on the Au(111) substrate, with a high-spin quintet state of S = 2, the same total spin as undoped neutral [5]triangulene.

cond-mat.mtrl-sci

Mean range bunching of exotic nuclei produced by in-flight fragmentation and fission -- Stopped-beam experiments with increased efficiency

The novel technique of mean range bunching has been developed and applied at the projectile fragment separator FRS at GSI in four experiments of the FAIR phase-0 experimental program. Using a variable degrader system at the final focal plane of the FRS, the ranges of the different nuclides can be aligned, allowing to efficiently implant a large number of different nuclides simultaneously in a gas-filled stopping cell or an implantation detector. Stopping and studying a cocktail beam overcomes the present limitations of stopped-beam experiments. The conceptual idea of mean range bunching is described and illustrated using simulations. In a single setting of the FRS, 37 different nuclides were stopped in the cryogenic stopping cell and were measured in a single setting broadband mass measurement with the multiple-reflection time-of-flight mass spectrometer of the FRS Ion Catcher.

physics.ins-det

Co-visual pattern augmented generative transformer learning for automobile geo-localization

Geolocation is a fundamental component of route planning and navigation for unmanned vehicles, but GNSS-based geolocation fails under denial-of-service conditions. Cross-view geo-localization (CVGL), which aims to estimate the geographical location of the ground-level camera by matching against enormous geo-tagged aerial (\emph{e.g.}, satellite) images, has received lots of attention but remains extremely challenging due to the drastic appearance differences across aerial-ground views. In existing methods, global representations of different views are extracted primarily using Siamese-like architectures, but their interactive benefits are seldom taken into account. In this paper, we present a novel approach using cross-view knowledge generative techniques in combination with transformers, namely mutual generative transformer learning (MGTL), for CVGL. Specifically, by taking the initial representations produced by the backbone network, MGTL develops two separate generative sub-modules -- one for aerial-aware knowledge generation from ground-view semantics and vice versa -- and fully exploits the entirely mutual benefits through the attention mechanism. Moreover, to better capture the co-visual relationships between aerial and ground views, we introduce a cascaded attention masking algorithm to further boost accuracy. Extensive experiments on challenging public benchmarks, \emph{i.e.}, {CVACT} and {CVUSA}, demonstrate the effectiveness of the proposed method which sets new records compared with the existing state-of-the-art models.

cs.CV

Studying Gamow-Teller transitions and the assignment of isomeric and ground states at $N=50$

Direct mass measurements of neutron-deficient nuclides around the $N=50$ shell closure below $^{100}$Sn were performed at the FRS Ion Catcher (FRS-IC) at GSI, Germany. The nuclei were produced by projectile fragmentation of $^{124}$Xe, separated in the fragment separator FRS and delivered to the FRS-IC. The masses of 14 ground states and two isomers were measured with relative mass uncertainties down to $1\times 10^{-7}$ using the multiple-reflection time-of-flight mass spectrometer of the FRS-IC, including the first direct mass measurements of $^{98}$Cd and $^{97}$Rh. A new $Q_\mathrm{EC} = 5437\pm67$ keV was obtained for $^{98}$Cd, resulting in a summed Gamow-Teller (GT) strength for the five observed transitions ($0^+\longrightarrow1^+$) as $B(\text{GT})=2.94^{+0.32}_{-0.28}$. Investigation of this result in state-of-the-art shell model approaches sheds light into a better understanding of the GT transitions in even-even isotones at $N=50$. The excitation energy of the long-lived isomeric state in $^{94}$Rh was determined for the first time to be $293\pm 21$ keV. This, together with the shell model calculations, allows the level ordering in $^{94}$Rh to be understood.

nucl-ex

Time Varying Channel Tracking for Multi-UAV Wideband Communications with Beam Squint

Unmanned aerial vehicle (UAV) has become an appealing solution for a wide range of commercial and civilian applications because of its high mobility and flexible deployment. Due to the continuous UAV navigation, the channel between UAV and base station (BS) is subject to the Doppler effect. Meanwhile, when the BS is equipped with massive number of antennas, the non-negligible propagation delay across the array aperture would cause beam squint effect. In this paper, we first investigate the channel of UAV communications under both Doppler shift effect and beam squint effect. Then, we design a gridless compressed sensing (GCS) based channel tracking method, where the high dimension uplink channel can be derived by estimating a few physical parameters such as the direction of arrival (DOA), Doppler shift, and the complex gain information. Besides, with the Doppler shift reciprocity and angular reciprocity, the downlink channel can be derived by only one pilot symbol, which greatly decreases the downlink channel training overhead. Various simulation results are provided to verify the effectiveness of the proposed methods.

cs.IT

Time Varying Channel Tracking with Spatial and Temporal BEM for Massive MIMO Systems

In this paper, we propose a channel tracking method for massive multi-input and multi-output systems under both time-varying and spatial-varying circumstance. Exploiting the characteristics of massive antenna array, a spatial-temporal basis expansion model is designed to reduce the effective dimensions of up-link and down-link channel, which decomposes channel state information into the time-varying spatial information and gain information. We firstly model the users movements as a one-order unknown Markov process, which is blindly learned by the expectation and maximization (EM) approach. Then, the up-link time varying spatial information can be blindly tracked by Taylor series expansion of the steering vector, while the rest up-link channel gain information can be trained by only a few pilot symbols. Due to angle reciprocity (spatial reciprocity), the spatial information of the down-link channel can be immediately obtained from the up-link counterpart, which greatly reduces the complexity of down-link channel tracking. Various numerical results are provided to demonstrate the effectiveness of the proposed method.

eess.SP

Beam Tracking for UAV Mounted SatCom on-the-Move with Massive Antenna Array

Unmanned aerial vehicle (UAV)-satellite communication has drawn dramatic attention for its potential to build the integrated space-air-ground network and the seamless wide-area coverage. The key challenge to UAV-satellite communication is its unstable beam pointing due to the UAV navigation, which is a typical SatCom on-the-move scenario. In this paper, we propose a blind beam tracking approach for Ka-band UAVsatellite communication system, where UAV is equipped with a large-scale antenna array. The effects of UAV navigation are firstly released through the mechanical adjustment, which could approximately point the beam towards the target satellite through beam stabilization and dynamic isolation. Specially, the attitude information can be realtimely derived from data fusion of lowcost sensors. Then, the precision of the beam pointing is blindly refined through electrically adjusting the weight of the massive antennas, where an array structure based simultaneous perturbation algorithm is designed. Simulation results are provided to demonstrate the superiority of the proposed method over the existing ones.

eess.SY