Tootfinder

Thermal Property Microscopy with Compressive Sensing Frequency-Domain Thermoreflectance
Haobo Yang, Zhenguo Zhu, Zhongnan Xie, Jinhong Du, Shuo Bai, Hong Guo, Te-Huan Liu, Ronggui Yang, Xin Qian
https://arxiv.org/abs/2506.04728

Thermal Property Microscopy with Compressive Sensing Frequency-Domain Thermoreflectance
Spatial mapping of thermal properties is critical for unveiling the structure-property relation of materials, heterogeneous interfaces, and devices. These property images can also serve as datasets for training artificial intelligence models for material discoveries and optimization. Here we introduce a high-throughput thermal property imaging method called compressive sensing frequency domain thermoreflectance (CS-FDTR), which can robustly profile thermal property distributions with micrometer…

Robust Distributed Phase Retrieval for Multi-View Compressive Networked Sensing With Outliers
Ming-Hsun Yang
https://arxiv.org/abs/2505.24651 https://

Robust Distributed Phase Retrieval for Multi-View Compressive Networked Sensing With Outliers
This work examines the multi-view compressive phase retrieval problem in a distributed sensor network, where each sensor device, limited by storage and sensing capabilities, can access only intensity measurements from an unknown part of the global sparse vector. The goal is to enable each sensor to recover its observable sparse signal when measurements are corrupted by outliers. To achieve reliable local signal recovery with limited data access, we propose a distributed reconstruction algorithm…

This https://arxiv.org/abs/2502.06466 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csRO_…

Inflatable Kirigami Crawlers
Kirigami offers unique opportunities for guided morphing by leveraging the geometry of the cuts. This work presents inflatable kirigami crawlers created by introducing cut patterns into heat-sealable textiles to achieve locomotion upon cyclic pneumatic actuation. Inflating traditional air pouches results in symmetric bulging and contraction. In inflated kirigami actuators, the accumulated compressive forces uniformly break the symmetry, enhance contraction compared to simple air pouches by two …

Joint Data Hiding and Partial Encryption of Compressive Sensed Streams
Cristina-Elena Popa, Cristian Damian, Daniela Coltuc
https://arxiv.org/abs/2505.23357

Joint Data Hiding and Partial Encryption of Compressive Sensed Streams
The paper proposes a method to secure the Compressive Sensing (CS) streams. It consists in protecting part of the measurements by a secret key and inserting the code into the rest. The secret key is generated via a cryptographically secure pseudo-random number generator (CSPRNG) and XORed with the measurements to be inserted. For insertion, we use a reversible data hiding (RDH) scheme, which is a prediction error expansion algorithm, modified to match the statistics of CS measurements. The reco…

Training Beam Design for Channel Estimation in Hybrid mmWave MIMO Systems
Xiaochun Ge, Wenqian Shen, Chengwen Xing, Lian Zhao, Jianping An
https://arxiv.org/abs/2506.00913

Training Beam Design for Channel Estimation in Hybrid mmWave MIMO Systems
Training beam design for channel estimation with infinite-resolution and low-resolution phase shifters (PSs) in hybrid analog-digital milimeter wave (mmWave) massive multiple-input multiple-output (MIMO) systems is considered in this paper. By exploiting the sparsity of mmWave channels, the optimization of the sensing matrices (corresponding to training beams) is formulated according to the compressive sensing (CS) theory. Under the condition of infinite-resolution PSs, we propose relevant algo…

The Density Distribution of Compressively-Forced Supersonic Turbulence Depends on the Driving Correlation Time
Philipp Grete, Evan Scannapieco, Marcus Br\"uggen, Liubin Pan
https://arxiv.org/abs/2505.23898

The Density Distribution of Compressively-Forced Supersonic Turbulence Depends on the Driving Correlation Time
Supersonic turbulence plays a critical role in shaping astrophysical systems, from molecular clouds to the circumgalactic medium. Key properties of this turbulence include the Mach number, driving scale, and nature of the driving mechanism, which can be solenoidal (divergence-free), compressive (curl-free), or a mix of the two. A less studied property is the correlation time of the driving accelerations, $τ_{\rm a}.$ While this timescale has a minimal impact on solenoidally-driven turbulence, …