Scalable Bell inequalities for multiqubit systems

Based on Clauser-Horner-Shimony-Holt inequality, we show a fruitful method to exploit Bell inequalities for multipartite qubit systems. These Bell inequalities are designed with a simpler architecture tailored to experimental demonstration. Under the optimal setting we derive a set of compact Mermin-type inequalities and discuss quantum violations for generalized Greenberger-Horne-Zeilinger (GGHZ) states. Also, we reveal relationship between quantum nonlocality and four-partite entanglement for four-qubit GGHZ states.Comment: 4 pages, 1 figur

An optical fiber tip micrograting thermometer

An ~12 µm long Bragg grating was engraved in an ~5 µm diameter optical fiber tip by focused ion beam (FIB) milling. An ~10-dB extinction was achieved at 1570 nm with only 11 indentations. The grating was used for temperature sensing, and it exhibited a temperature sensitivity of ~22 pm/°C

A double neutron star merger origin for the cosmological relativistic fading source PTF11agg?

The Palomar Transient Factory (PTF) team recently reported the discovery of a rapidly fading optical transient source, PTF11agg. A long-lived scintillating radio counterpart was identified, but the search for a high energy counterpart showed negative results. The PTF team speculated that PTF11agg may represent a new class of relativistic outbursts. Here we suggest that a neutron star (NS)-NS merger system with a supra-massive magnetar central engine could be a possible source to power such a transient, if our line of sight is not on the jet axis direction of the system. These systems are also top candidates for gravitational wave sources to be detected in the advanced LIGO/Virgo era. We find that the PTF11agg data could be explained well with such a model, suggesting that at least some gravitational wave bursts due to NS-NS mergers may be associated with such a bright electromagnetic counterpart without a \gamma-ray trigger.Comment: Accepted for publication in ApJ Letter

N-(4-Chloro­benzyl­idene)-4-methoxy­aniline

The title compound, C14H12ClNO, was prepared by the reaction of 4-methoxy­aniline and 4-chloro­benzaldehyde in ethanol at 367 K. The mol­ecule is almost planar, with a dihedral angle between the two benzene rings of 9.1 (2)° and an r.m.s. deviation from the mean plane through all non-H atoms in the mol­ecule of 0.167 Å

TrTr: A Versatile Pre-Trained Large Traffic Model based on Transformer for Capturing Trajectory Diversity in Vehicle Population

Understanding trajectory diversity is a fundamental aspect of addressing practical traffic tasks. However, capturing the diversity of trajectories presents challenges, particularly with traditional machine learning and recurrent neural networks due to the requirement of large-scale parameters. The emerging Transformer technology, renowned for its parallel computation capabilities enabling the utilization of models with hundreds of millions of parameters, offers a promising solution. In this study, we apply the Transformer architecture to traffic tasks, aiming to learn the diversity of trajectories within vehicle populations. We analyze the Transformer's attention mechanism and its adaptability to the goals of traffic tasks, and subsequently, design specific pre-training tasks. To achieve this, we create a data structure tailored to the attention mechanism and introduce a set of noises that correspond to spatio-temporal demands, which are incorporated into the structured data during the pre-training process. The designed pre-training model demonstrates excellent performance in capturing the spatial distribution of the vehicle population, with no instances of vehicle overlap and an RMSE of 0.6059 when compared to the ground truth values. In the context of time series prediction, approximately 95% of the predicted trajectories' speeds closely align with the true speeds, within a deviation of 7.5144m/s. Furthermore, in the stability test, the model exhibits robustness by continuously predicting a time series ten times longer than the input sequence, delivering smooth trajectories and showcasing diverse driving behaviors. The pre-trained model also provides a good basis for downstream fine-tuning tasks. The number of parameters of our model is over 50 million.Comment: 16 pages, 6 figures, under reviewed by Transportation Research Board Annual Meeting, work in updat