A Beam-Steering Reflectarray Antenna with Arbitrary Linear-Polarization Reconfiguration

This work presents a beam-steering reflectarray antenna capable of achieving arbitrary linear polarization (LP) reconfiguration. It utilizes a dual-circular polarization (CP) reconfigurable reflectarray, along with an LP feed horn, to synthesize a LP beam by combining two reflected CP beams in the same direction. The LP states can be dynamically adjusted by tuning the phase constants of the array, which correspondingly modify the wave phases. Experimental validation of the proposed polarization synthesis concept is conducted using a 16$\times$16 dual-CP 1-bit reconfigurable reflectarray operating at 16.8 GHz. This reflectarray generates reconfigurable LP waves with polarization states of LP(0$^\circ$), LP(45$^\circ$), LP(90$^\circ$) and LP(135$^\circ$). Furthermore, it demonstrates the capability to perform beam scanning, allowing for versatile beam manipulation. The application of this polarization-reconfigurable beam-steering reflectarray is pertinent to beam alignment and polarization synchronization in various wireless communication scenarios, including satellite communication and mobile communication

Individual-atom control in array through phase modulation

Performing parallel gate operations while retaining low crosstalk is an essential step in transforming neutral atom arrays into powerful quantum computers and simulators. Tightly focusing control beams in small areas for crosstalk suppression is typically challenging and can lead to imperfect polarization for certain transitions. We tackle such a problem by introducing a method to engineer single qubit gates through phase-modulated continuous driving. Distinct qubits can be individually addressed to high accuracy by simply tuning the modulation parameters, which significantly suppresses crosstalk effects. When arranged in a lattice structure, individual control with optimal crosstalk suppression is achieved. With the assistance of additional addressing light or multiple modulation frequencies, we develop two efficient implementations of parallel-gate operations. Our results pave the way to scaling up atom-array platforms with low-error parallel-gate operations, without requiring complicated wavefront design or high-power laser beams

Exponentially Enhanced non-Hermitian Cooling

Certain non-Hermitian systems exhibit the skin effect, whereby the wavefunctions become exponentially localized at one edge of the system. Such exponential amplification of wavefunction has received significant attention due to its potential applications in e.g., classical and quantum sensing. However, the opposite edge of the system, featured by the exponentially suppressed wavefunctions, remains largely unexplored. Leveraging this phenomenon, we introduce a non-Hermitian cooling mechanism, which is fundamentally distinct from traditional refrigeration or laser cooling techniques. Notably, non-Hermiticity will not amplify thermal excitations, but rather redistribute them. Hence, thermal excitations can be cooled down at one edge of the system, and the cooling effect can be exponentially enhanced by the number of auxiliary modes, albeit with a lower bound that depends on the dissipative interaction with the environment. Non-Hermitian cooling does not rely on intricate properties such as exceptional points or non-trivial topology, and it can apply to a wide range of Bosonic modes such as photons, phonons, magnons, etc.Comment: 12 pages, 4 figure

Efficient Quantum Transduction Using Anti-Ferromagnetic Topological Insulators

Transduction of quantum information between distinct quantum systems is an essential step in various applications, including quantum networks and quantum computing. However, quantum transduction needs to mediate between photons with vastly different frequencies, making it challenging to design high-performance transducers, due to multifaceted and sometimes conflicting requirements. In this work, we first discuss some general principles for quantum transducer design, and then propose solid-state anti-ferromagnetic topological insulators to serve as highly effective transducers. First, topological insulators exhibit band-inversion, which can greatly enhance their optical responses. Coupled with their robust spin-orbit coupling and high spin density, this property leads to strong nonlinear interaction in topological insulators, thereby substantially improving transduction efficiency. Second, the anti-ferromagnetic order can minimize the detrimental influence on other neighboring quantum systems due to magnetic interactions. Using $\rm MnBi_2Te_4$ as an example, we showcase that unit transduction fidelity can be achieved with modest experimental requirements, while the transduction bandwidth can reach the GHz range. The strong nonlinear interaction in magnetic topological insulators can find diverse applications, including the generation of entanglement between photons of distinct frequencies.Comment: 15 pages, 3 figure

A Comprehensive Survey on Orbital Edge Computing: Systems, Applications, and Algorithms

The number of satellites, especially those operating in low-earth orbit (LEO), is exploding in recent years. Additionally, the use of COTS hardware into those satellites enables a new paradigm of computing: orbital edge computing (OEC). OEC entails more technically advanced steps compared to single-satellite computing. This feature allows for vast design spaces with multiple parameters, rendering several novel approaches feasible. The mobility of LEO satellites in the network and limited resources of communication, computation, and storage make it challenging to design an appropriate scheduling algorithm for specific tasks in comparison to traditional ground-based edge computing. This article comprehensively surveys the significant areas of focus in orbital edge computing, which include protocol optimization, mobility management, and resource allocation. This article provides the first comprehensive survey of OEC. Previous survey papers have only concentrated on ground-based edge computing or the integration of space and ground technologies. This article presents a review of recent research from 2000 to 2023 on orbital edge computing that covers network design, computation offloading, resource allocation, performance analysis, and optimization. Moreover, having discussed several related works, both technological challenges and future directions are highlighted in the field.Comment: 18 pages, 9 figures and 5 table

DevNet: Self-supervised Monocular Depth Learning via Density Volume Construction

Self-supervised depth learning from monocular images normally relies on the 2D pixel-wise photometric relation between temporally adjacent image frames. However, they neither fully exploit the 3D point-wise geometric correspondences, nor effectively tackle the ambiguities in the photometric warping caused by occlusions or illumination inconsistency. To address these problems, this work proposes Density Volume Construction Network (DevNet), a novel self-supervised monocular depth learning framework, that can consider 3D spatial information, and exploit stronger geometric constraints among adjacent camera frustums. Instead of directly regressing the pixel value from a single image, our DevNet divides the camera frustum into multiple parallel planes and predicts the pointwise occlusion probability density on each plane. The final depth map is generated by integrating the density along corresponding rays. During the training process, novel regularization strategies and loss functions are introduced to mitigate photometric ambiguities and overfitting. Without obviously enlarging model parameters size or running time, DevNet outperforms several representative baselines on both the KITTI-2015 outdoor dataset and NYU-V2 indoor dataset. In particular, the root-mean-square-deviation is reduced by around 4% with DevNet on both KITTI-2015 and NYU-V2 in the task of depth estimation. Code is available at https://github.com/gitkaichenzhou/DevNet.Comment: Accepted by European Conference on Computer Vision 2022 (ECCV2022