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Conclusions
Published in Ni-Bin Chang, Kaixu Bai, Multisensor Data Fusion and Machine Learning for Environmental Remote Sensing, 2018
Recently, quantum entanglement, a physical phenomenon that provides remote sensing an advanced basis for the future, has been well studied. Quantum entanglement occurs when pairs or groups of particles interact with one another in such a way that the quantum state of each particle cannot be described independently of the others. This is true even when the particles are divided by a large distance. Quantum sensing is thus deemed a new quantum technology that employs quantum coherence properties for ultrasensitive detection, which is especially useful for sensing weak signals. A quantum sensor is a device that exploits quantum correlations, such as quantum entanglement, to achieve a sensitivity or resolution that is better than can be achieved using only classical systems (Kapale et al., 2005). Quantum remote sensing, quantum sensors, and quantum sources have become hot topics in research. For example, infrared sensing technology has a central role to play in addressing 21st century global challenges in environmental sensing, and infrared imaging and sensing with the single-photon setting has been studied recently as a new quantum remote sensing technology (European Union, 2016). This type of new technology may deeply affect future environmental sensing (Han, 2014; Bi and Zhang, 2015).
Integrated State Awareness Through Secure Embedded Intelligence in Nuclear Systems: Opportunities and Implications
Published in Nuclear Science and Engineering, 2020
Humberto E. Garcia, Steven E. Aumeier, Ahmad Y. Al-Rashdan
Other technological areas under sensing where SEI is expected to impact sensor-system deployments in nuclear systems include MAS, data mining techniques, distributed sensing, and self-organizing systems. Advanced sensor approaches, including distributed temperature (DTS), acoustic (DAS), strain (DSS), and chemical (DCS) sensing can be used to improve the fidelity of the data collected and model characterization of the real environment (e.g., Refs. 47 and 48). For example, the use of functional coatings (e.g., Ref. 49) to enable DCS (Ref. 50) has received significant interest. Similarly, fiber-optics are being applied to the implementation of DTS, DAS, and DSS, with the fiber used as a sensor in DAS to measure strain along pipes, for example.51 Quantum sensing52 may also have an important applicability for the nuclear industry, having already received strong support from the O&G industry. Preliminary results suggest that quantum sensing can increase the signal-to-noise ratios and dynamic ranges of signals by decreasing the associated noise floor.
Improving phase sensitivity of interferometers by inverse operations
Published in Journal of Modern Optics, 2021
Quantum metrology is one of the most fascinating frontiers of the science of measurement, including parameter estimation [1] and precision measurement [2], among others. Phase estimation [3] is a significantly important issue in parameter estimation and it has been widely studied in various optical interferometers, such as MZI, SU(1,1) I [4,5] , and other modified interferometers [6–8]. The ultimate objective of phase estimation is to enhance the phase sensitivity of interferometers and attain the Heisenberg limit (HL) [9,10]. High precision quantum measurement is advantageous in various fields, such as gravitational-wave detection [11], quantum sensing [12], and imaging [13]. Theoretically, the phase sensitivity of interferometers can be primarily enhanced by three methods. First, specific quantum states, such as the squeezed, superposition, or entanglement states, can be used to decrease the quantum noise [14–16], thereby improving the phase sensitivity of interferometers. Second, nonlinear effects, such as nonlinear amplifiers or nonlinear phase shifters can be used to increase the coupling strength of phase information. For example, owing to the gain in optical parametric amplifiers (OPAs), SU(1,1)I has better sensitivity than traditional linear interferometers [17]. As shown in Refs. [18,19], the phase sensitivity of MZI can be significantly improved by adding the Kerr nonlinear phase shifter. Third, by implementing super-resolution detection, such as homodyne detection and parity detection, the acquisition rate of phase information can be enhanced [20,21]. In addition, the phase sensitivity of interferometers can be considerably improved by adding additional operations, such as quantum feedback [22,23], information recycling [24], adaptive protocols [25], and the inverse operation scheme [26,27]. Several studies have demonstrated that the phase sensitivity of interferometers can be improved by using additional inverse squeezed operator and approaching the HL [28,29]. The research on improving the phase sensitivity of interferometers using the aforementioned three methods is relatively mature; however, fewer studies have implemented additional inverse operations. Numerous research works [26,29,30] have demonstrated that the method of using unitary operations to improve the phase sensitivity of interferometers can reach the HL through coarse-grained detections; i.e. super resolution detections are not required. Correspondingly, in this study, we propose a theoretical model of the improved phase estimation scheme with inverse operations and analyse the phase sensitivity of MZI and SU(1,1)I with coherent or squeezed states as the input with intensity detection. Further more, we discuss the phase sensitivity of MZI and SU(1,1)I with inverse displaced and inverse squeezed operations considering intensity detection, and make a detailed comparison between with and without the inverse operation scheme. Our results demonstrated that the phase sensitivity of interferometers can be significantly enhanced by adding additional inverse operations.