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Quantum sources that provide broadband biphotons entangled in both polarization and time-energy degrees of freedom are a rich quantum resource that finds many applications in quantum communication, sensing, and metrology. Creating such a source while maintaining high entanglement quality over a broad spectral range is a challenge, which conventionally requires various compensation steps to erase temporal, spectral, or spatial distinguishabilities. Here, we point out that in fact compensation is not always necessary. The key to generate broadband polarization-entangled biphotons via type-II spontaneous parametric downcoversion (SPDC) without compensation is to use nonlinear materials with sufficiently low group birefringence that the biphoton bandwidth becomes dispersion-limited. Most nonlinear crystals or waveguides cannot meet this condition, but it is easily met in fiber-based systems. We reveal the interplay of group birefringence and dispersion on SPDC bandwidth and polarization entanglement quality. We show that periodically poled silica fiber (PPSF) is an ideal medium to generate high-concurrence (>0.977) polarization-entangled photons over a broad spectral range (>77nm), directly and without compensation. This is the highest polarization-entanglement concurrence reported that is maintained over a broad spectral range from a compensation-free source.

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We have fabricated an Yb-doped passively Q-switching fiber laser based on WS(2) saturable absorber. Both the operating wavelength and the repetition rate can be tuned in a wide range. The operating wavelength can be continuously tuned from 1027 nm to 1065 nm under the Q-switching state at a fixed pump power, while the repetition rate increases from 60.2 kHz to 97.0 kHz by varying pump power at a fixed wavelength of 1048.1 nm. The shortest pulse duration of 1.58 µs was observed. To the best of our knowledge, it's the first demonstration of WS(2)-based passively Q-switching fiber laser with a wide tunable range at 1.0 μm band.

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Despite its importance in macroscopic traffic flow modeling, comprehensive method for the calibration of fundamental diagram is very limited. Conventional empirical methods adopt a steady state analysis of the aggregate traffic data collected from measurement devices installed on a particular site without considering the traffic dynamics, which renders the simulation may not be adaptive to the variability of data. Nonetheless, determining the fundamental diagram for each detection site is often infeasible. To remedy these, this study presents an automatic calibration method to estimate the parameters of a fundamental diagram through a dynamic approach. Simulated flow from the cell transmission model is compared against the measured flow wherein an optimization merit is conducted to minimize the discrepancy between model-generated data and real data. The empirical results prove that the proposed automatic calibration algorithm can significantly improve the accuracy of traffic state estimation by adapting to the variability of traffic data when compared with several existing methods under both recurrent and abnormal traffic conditions. Results also highlight the robustness of the proposed algorithm. The automatic calibration algorithm provides a powerful tool for model calibration when freeways are equipped with sparse detectors, new traffic surveillance systems lack of comprehensive traffic data, or the case that lots of detectors lose their effectiveness for aging systems. Furthermore, the proposed method is useful for off-line model calibration under abnormal traffic conditions, for example, incident scenarios.The boundary conditions are not in the exact form as those in [10,23], but an equivalent formulation derived to convert the MCTM into a uniform characteristics of the sending and receiving functions as will be shown later. This formulation also makes the MCTM more suitable as a network loading model for the automatic calibration method. AUTOMATIC CALIBRATION OF FUNDAMENTAL DIAGRAM

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