measurement rate
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Author(s):  
Elze Porte ◽  
Thomas Sipple ◽  
Lina Sanchez Botero ◽  
Dylan Shah ◽  
Rebecca Kramer-Bottiglio

Sensors ◽  
2021 ◽  
Vol 21 (7) ◽  
pp. 2341
Author(s):  
Chengkai Pang ◽  
Qiongqiong Zhang ◽  
Zhaohui Li ◽  
Guang Wu

The decoherence in coherent lidar becomes serious with the increase in distance. A small laser spot can suppress the decoherence of the echo light from noncooperation targets. However, it is very difficult to keep a small light spot over a long distance. In this paper, a pulsed coherent lidar with high sensitivity at the few-photon level was demonstrated. A phase plate was used to modulate the wavefront of the laser to achieve 100 m focusing which reduced the decoherence effect. Based on coherent detection and time-of-flight (TOF) measurements, long-distance laser ranging and imaging on all days was realized. A signal classification and superposition method was used to extract the echo signal submerged in noise. The system was experimentally demonstrated by ranging different noncooperation targets within 105.0 m. The measurement rate was 10 k/s, and the measurement uncertainty was 1.48 cm. In addition, laser imaging was realized at ~50.0 m. The system was simple and portable as well as eye safe, and it may offer new application possibilities in automated vehicle lidar.


2021 ◽  
Vol 13 (2) ◽  
pp. 288
Author(s):  
Yong Zhang ◽  
Jie Jiang ◽  
Guangjun Zhang

Compression of remotely sensed astronomical images is an essential part of deep space exploration. This study proposes a wavelet-based compressed sensing (CS) algorithm for astronomical image compression in a miniaturized independent optical sensor system, which introduces a new framework for CS in the wavelet domain. The algorithm starts with a traditional 2D discrete wavelet transform (DWT), which provides frequency information of an image. The wavelet coefficients are rearranged in a new structured manner determined by the parent–child relationship between the sub-bands. We design scanning modes based on the direction information of high-frequency sub-bands, and propose an optimized measurement matrix with a double allocation of measurement rate. Through a single measurement matrix, higher measurement rates can be simultaneously allocated to sparse vectors containing more information and coefficients with higher energy in sparse vectors. The double allocation strategy can achieve better image sampling. At the decoding side, orthogonal matching pursuit (OMP) and inverse discrete wavelet transform (IDWT) are used to reconstruct the image. Experimental results on simulated image and remotely sensed astronomical images show that our algorithm can achieve high-quality reconstruction with a low measurement rate.


Author(s):  
Sajede Harraz ◽  
Shuang Cong ◽  
Kezhi Li

In this paper, we propose an online state tomography method for [Formula: see text]-qubit quantum system based on the continuous weak measurement and compressed sensing (CS). The quantum system is described by stochastic master equation. The continuous weak measurement operators for the [Formula: see text]-qubit quantum system, which are indirectly acted on the quantum system, are derived according to the measurement operator results of two-level quantum system. The online time-varying measurement operators are obtained by means of the dynamic evolution equation of the system. The quantum state is online estimated by solving the optimization problem of minimizing the two-norm with the positive definite constraints of density matrix, and we use the nonnegative least squares algorithm to solve the optimization problem. CS theory is used to reduce the number of the measurements in the process of online state estimation. In the numerical experiments, we study the effects of external control field, measurement rate and the different numbers of qubits on the performance in the proposed method. The minimum required numbers of measurements for 2, 3, 4 and 5 qubits are found. The normalized distance and fidelity of our proposed method can achieve satisfying accuracy with small number of measurements.


2020 ◽  
Vol 5 (1) ◽  
pp. 101
Author(s):  
Arif Indra Irawan ◽  
Raditiana Patmasari ◽  
Muhammad Rahmat Hidayat

Pada proses pemeliharaan ikan, penentuan suhu air kolam merupakah salah satu faktor penting bagi kualitas pertumbuhan ikan. Bahkan dalam suatu penelitian mengenai ikan Betutu perbedaan suhu sekitar 2°C dapat menurukan survival rate ikan sebesar 20%. Penelitian ini bertujuan untuk meningkatkan kinerja sensor suhu DS18B20 yang digunakan pada sistem Internet of Things (IoT) untuk monitoring suhu kolam ikan. Parameter yang digunakan untuk menguji kualitas sistem sensor suhu tersebut adalah akurasi, Root Mean Square Error (RMSE), dan response time.  Analisis dilakukan menggunakan metode regresi linier dan measurement rate berdistribusi normal. Kemudian hasil analisis dibandingkan untuk mengetahui pengaruh penggunaan metode regresi linier dan pengaruh measurement rate pada sistem monitoring suhu kolam ikan ini. Hasil penelitian menunjukkan bahwa setelah digunakannya metode regresi linier saat kalibrasi, akurasi pengukuran, RMSE, dan response time mengalami peningkatan.


2020 ◽  
pp. 189-202
Author(s):  
Gershon Kurizki ◽  
Goren Gordon

Henry is trapped in a burning building because of Eve’s mischief. Henry’s entanglement with the hot environment is ominous: his states receive excessive energy from the environment, threatening his physiology. Can quantum effects rescue Henry from the fire? Unexpectedly, Eve comes to his rescue. She frequently measures his energy in a “quantum non-demolition” (QND) fashion which is expected to keep his state intact. Surprisingly, Henry grows hotter or colder depending on Eve’s measurement rate! These quantum effects seem to violate the laws of thermodynamics. Engraved in stone as these laws and the ensuing time directionality (time arrow) may be, they fail if the system is examined too frequently, whence time arrow loses its meaning. One may speculate over the role of such anomalies in the Big Bang. These anomalies support Parmenides’ view that time flow is determined by the observer’s choices. The appendix to this chapter elaborates on the dynamics induced by system–environment interaction changes.


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