arXiv subjects

Haojie Zhao

Publications and source records attributed to Haojie Zhao.

5 recordsLinked to original sources

arXiv2026

Achieving 100$\,$MHz Instantaneous Bandwidth in a Broadband Rydberg Microwave Sensor

Rydberg atoms have attracted considerable attention in recent years as a novel platform for microwave sensing, owing to their unique physical merits: large transition dipole moments between Rydberg levels and broad frequency coverage. As a critical figure of merit for Rydberg microwave sensors, instantaneous bandwidth serves as a key benchmark for evaluating their viability in practical applications. Previous studies on instantaneous bandwidth remain limited to single-frequency operation, with typical demonstrated values of only tens of megahertz, a constraint that hampers the real-world deployment of this sensing technology. Here, we experimentally achieve an instantaneous bandwidth of over 100$\,$MHz across a broad frequency range of 2.7-20$\,$GHz and realize a sensitivity in the hundreds of nV$\,$cm$^{-1}\,$Hz$^{-1/2}$ range. The physical mechanism lies in the dressed-state coherence and the interference effect between different transition channels. Our work substantially broadens the instantaneous bandwidth of Rydberg microwave sensors and paves the way for their practical deployment in fields such as radar and wireless communications.

physics.atom-ph↗

arXiv2026

Broadband Rydberg Atomic Microwave Sensing with 44.6$\,$MHz Instantaneous Bandwidth

Rydberg atoms have become a promising novel type of microwave sensor due to their excellent physical properties -- broad frequency coverage and large electric dipole moments. High sensitivity and broad instantaneous bandwidth are two indispensable requirements for deployable Rydberg microwave sensors. However, enabling broadband operation while retaining high sensitivity has been a longstanding barrier limiting their applications. We propose and experimentally demonstrate a Rydberg microwave sensor whose instantaneous bandwidth is significantly enhanced via an auxiliary microwave field. By finely modulating the Rydberg energy levels with this field, we broaden the bandwidth substantially while retaining the sensor's inherent high sensitivity. An instantaneous bandwidth of 44.6$\,$MHz ($\pm$22.3$\,$MHz) with a sensitivity of 225.7$\,$nV$\,$cm$^{-1}\,$Hz$^{-1/2}$ is realized in a thermal $^{87}$Rb vapor with the local microwave frequency of 16.03$\,$GHz. Our work delivers concurrent broad instantaneous bandwidth and high sensitivity for Rydberg microwave sensors, paving a technically viable path for their practical deployment in broadband microwave metrology, radar, and wireless communication.

physics.atom-ph↗

arXiv2026

Multi-Dressed-State Engineered Rydberg Electrometry

Rydberg atoms, with their giant transition electric dipole moments and abundant energy-level transitions, offer exceptional potential for microwave (MW) electric field sensing, combining high sensitivity and broad frequency coverage. However, simultaneously achieving high sensitivity and broad instantaneous bandwidth in a Rydberg-based MW sensor remains a critical challenge. Here, we propose a multi-dressed-state engineered superheterodyne detection scheme for Rydberg electrometry to overcome this challenge. It is found that the key to simultaneously achieving large instantaneous bandwidth and high sensitivity lies in the coherence of dressed states and the interference between transition channels of dressed states. By strategically engineering the multiple dressed states of Rydberg atoms, we demonstrate a thermal $\mathrm{^{87}Rb}$ vapor-based sensor with a sensitivity of 222.6$\,$nV$\,$cm$^{-1}\,$Hz$^{-1/2}$ and a record instantaneous bandwidth of 76.8$\,$MHz with the local microwave frequency 16.03$\,$GHz. This advancement paves the way for Rydberg-atom technologies in radar, wireless communication, and spectrum monitoring.

physics.atom-ph↗

arXiv2023

ARKitTrack: A New Diverse Dataset for Tracking Using Mobile RGB-D Data

Compared with traditional RGB-only visual tracking, few datasets have been constructed for RGB-D tracking. In this paper, we propose ARKitTrack, a new RGB-D tracking dataset for both static and dynamic scenes captured by consumer-grade LiDAR scanners equipped on Apple's iPhone and iPad. ARKitTrack contains 300 RGB-D sequences, 455 targets, and 229.7K video frames in total. Along with the bounding box annotations and frame-level attributes, we also annotate this dataset with 123.9K pixel-level target masks. Besides, the camera intrinsic and camera pose of each frame are provided for future developments. To demonstrate the potential usefulness of this dataset, we further present a unified baseline for both box-level and pixel-level tracking, which integrates RGB features with bird's-eye-view representations to better explore cross-modality 3D geometry. In-depth empirical analysis has verified that the ARKitTrack dataset can significantly facilitate RGB-D tracking and that the proposed baseline method compares favorably against the state of the arts. The code and dataset is available at https://arkittrack.github.io.

cs.CV↗

arXiv2019

'Skimming-Perusal' Tracking: A Framework for Real-Time and Robust Long-term Tracking

Compared with traditional short-term tracking, long-term tracking poses more challenges and is much closer to realistic applications. However, few works have been done and their performance have also been limited. In this work, we present a novel robust and real-time long-term tracking framework based on the proposed skimming and perusal modules. The perusal module consists of an effective bounding box regressor to generate a series of candidate proposals and a robust target verifier to infer the optimal candidate with its confidence score. Based on this score, our tracker determines whether the tracked object being present or absent, and then chooses the tracking strategies of local search or global search respectively in the next frame. To speed up the image-wide global search, a novel skimming module is designed to efficiently choose the most possible regions from a large number of sliding windows. Numerous experimental results on the VOT-2018 long-term and OxUvA long-term benchmarks demonstrate that the proposed method achieves the best performance and runs in real-time. The source codes are available at https://github.com/iiau-tracker/SPLT.

cs.CV↗