Quantum correlated photons via a passive nonlinear microcavity

Photons, by nature, typically do not exhibit interactions with each other. Creating photon-photon interactions holds immense importance in both fundamental physics and quantum technologies. Currently, such interactions have only been achieved indirectly as mediated by atomic-like quantum emitters with resonant photon-atom interactions. However, the use of these indirect interactions presents substantial fundamental challenges that impede scaling and practical applications. Here we demonstrate creation of non-classical photon correlations, including photon anti-bunching, via a passive InGaP photonic integrated circuit. Our approach employs the quantum interference between uncorrelated light and the two-photon bound state, the latter of which arises from the $\chi^{(2)}$-mediated photon interaction. Our work opens a new route in controlling quantum light by harnessing highly-engineerable bulk optical nonlinearities, which has significant implications for nonlinear optical quantum information processing and quantum networking.Comment: 26 pages, 15 figures, 2 table

Optimization for Variable Height Wind Farm Layout Model

The optimization of wind farm layouts is very important for the effective utilization of wind resources. A fixed wind turbine hub height in the layout of wind farms leads to a low wind energy utilization and a higher LCOE (levelized cost of electricity). WOMH (Wind Farm Layout Optimization Model Considering Multiple Hub Heights) is proposed in this paper to tackle the above problem. This model is different from the traditional fixed hub height model, as it uses a variable height wind turbine. In WOMH, the Jensen wake and Weibull distribution are used to describe the wake effect on the wind turbines and wind speed distribution, respectively. An algorithm called DEGM (differential evolution and greedy method with multiple strategies) is proposed to solve WOMH, which is NP hard. In the DEGM, seven strategies are designed to adjust the distribution coordinates of wind turbines so that the height of the wind turbines will be arranged from low to high in the wind direction. This layout reduces the Jensen wake effect, thus reducing the value of the LCOE. The experimental results show that in the DEGM, when the number of wind turbines is 5, 10, 20, 30 and 50, the WOMH reduces the LCOE by 13.96%, 12.54%, 8.22%, 6.14% and 7.77% compared with the fixed hub height model, respectively. In addition, the quality of the solution of the DEGM is more satisfactory than that of the three-dimensional greedy algorithm and the DEEM (differential evolution with a new encoding mechanism) algorithm. In the case of five different numbers of wind turbines, the LCOE of DEGM is at least 3.67% lower than that of DEEM, and an average of 6.83% lower than that of three-dimensional greedy. The model and algorithm in this paper provide an effective solution for the field of wind farm layout optimization

Calibration Method of Array Errors for Wideband MIMO Imaging Radar Based on Multiple Prominent Targets

Wideband multiple-input-multiple-output (MIMO) imaging radar can achieve high-resolution imaging with a specific multi-antenna structure. However, its imaging performance is severely affected by the array errors, including the inter-channel errors and the position errors of all the transmitting and receiving elements (TEs/REs). Conventional calibration methods are suitable for the narrow-band signal model, and cannot separate the element position errors from the array errors. This paper proposes a method for estimating and compensating the array errors of wideband MIMO imaging radar based on multiple prominent targets. Firstly, a high-precision target position estimation method is proposed to acquire the prominent targets’ positions without other equipment. Secondly, the inter-channel amplitude and delay errors are estimated by solving an equation-constrained least square problem. After this, the element position errors are estimated with the genetic algorithm to eliminate the spatial-variant error phase. Finally, the feasibility and correctness of this method are validated with both simulated and experimental datasets

Processing Sliding Mosaic Mode Data with Modified Full-Aperture Imaging Algorithm Integrating Scalloping Correction

In this study, we present a modified full-aperture imaging algorithm that includes scalloping correction and spike suppression for sliding-Mosaic-mode Synthetic Aperture Radar (SAR). It is innovational to correct the azimuth beam-pattern weighting altered by radar antenna rotation in the azimuth during the deramping preprocessing operation. The main idea of spike suppression is to substitute zeros between bursts with linear-predicted data extrapolated from adjacent bursts to suppress spikes caused by multiburst processing. We also integrate scalloping correction for the sliding mode into this algorithm. Finally, experiments are performed using the C-band airborne SAR system with a maximum bandwidth of 200 MHz to validate the effectiveness of this approach