The quantum synchronization based on frequency-correlated photon pairs and HOM interference has shown femtosecond-level precision and great application prospect in numerous fields depending on high-precision timefrequency signals. Due to the difficul
ty of achieving stable HOM interference fringe after long-distance fiber transmission, this quantum synchronization is hampered from long-haul field application. Utilizing segmented fibers instead of a single long-length fiber, we successfully achieved the stable observation of the two-photon interference of the lab-developed broadband frequency-correlated photon pairs after 20 km-long fiber transmission, without employing auxiliary phase stabilization method. Referenced to this interference fringe, the balance of the two fiber arms is successfully achieved with a long-term stability of 20 fs. The HOM-interference-based synchronization over a 20-km fiber link is thus demonstrated and a minimum stability of 74 fs has been reached at 48,000 s. This result not only provides a simple way to stabilize the fiber-optic two-photon interferometer for long-distance quantum communication systems, but also makes a great stride forward in extending the quantum-interference-based synchronization scheme to the long-haul field applications.
The redshift distribution of galactic-scale lensing systems provides a laboratory to probe the velocity dispersion function (VDF) of early-type galaxies (ETGs) and measure the evolution of early-type galaxies at redshift z ~ 1. Through the statistica
l analysis of the currently largest sample of early-type galaxy gravitational lenses, we conclude that the VDF inferred solely from strong lensing systems is well consistent with the measurements of SDSS DR5 data in the local universe. In particular, our results strongly indicate a decline in the number density of lenses by a factor of two and a 20% increase in the characteristic velocity dispersion for the early-type galaxy population at z ~ 1. Such VDF evolution is in perfect agreement with the $Lambda$CDM paradigm (i.e., the hierarchical build-up of mass structures over cosmic time) and different from stellar mass-downsizing evolutions obtained by many galaxy surveys. Meanwhile, we also quantitatively discuss the evolution of the VDF shape in a more complex evolution model, which reveals its strong correlation with that of the number density and velocity dispersion of early-type galaxies. Finally, we evaluate if future missions such as LSST can be sensitive enough to place the most stringent constraints on the redshift evolution of early-type galaxies, based on the redshift distribution of available gravitational lenses.
A model-independent test of the cosmic curvature parameter $Omega_k$ is very important in cosmology. In order to estimate cosmic curvature from cosmological probes like standard candles, one has to be able to measure the luminosity distance $D_L(z)$,
its derivative with respect to redshift $D_L(z)$ and independently know the expansion rate $H(z)$ at the same redshift. In this paper, we study how such an idea could be implemented with the future generation of space-based DECi-hertz Interferometer Gravitational-wave Observatory (DECIGO), in combination with cosmic chronometers providing cosmology-independent $H(z)$ data. Our results show that for the Hubble diagram of simulated DECIGO data acting as a new type of standard siren, it would be able to constrain cosmic curvature with the precision of $Delta Omega_k= 0.09$ with the currently available sample of 31 measurements of Hubble parameters. In the framework of the third generation ground-based gravitational wave detectors, the spatial curvature is constrained to be $DeltaOmega_k= 0.13$ for Einstein Telescope (ET). More interestingly, compared to other approaches aiming for model-independent estimations of spatial curvature, our analysis also achieves the reconstruction of the evolution of $Omega_k(z)$, in the framework of a model-independent method of Gaussian processes (GP) without assuming a specific form. Therefore, one can expect that the newly emerged gravitational wave astronomy can become useful in local measurements of cosmic curvature using distant sources.
The cosmic curvature ($Omega_k$) is a fundamental parameter for cosmology. In this paper, we propose an improved model-independent method to constrain the cosmic curvature, which is geometrically related to the Hubble parameter $H(z)$ and luminosity
distance $D_L(z)$. Using the currently largest $H(z)$ sample from the well-known cosmic chronometers, as well as the luminosity distance $D_L(z)$ from the relation between the UV and X-ray luminosities of 1598 quasars and the newly-compiled Pantheon sample including 1048 SNe Ia, 31 independent measurements of the cosmic curvature $Omega_k(z)$ can be expected covering the redshift range of $0.07<z<2$. Our estimation of $Omega_k(z)$ is fully compatible with flat Universe at the current level of observational precision. Meanwhile, we find that, for the Hubble diagram of 1598 quasars as a new type of standard candle, the spatial curvature is constrained to be $Omega_k=0.08pm0.31$. For the latest Pantheon sample of SNe Ia observations, we obtain $Omega_k= -0.02pm0.14$. Compared to other approaches aiming for model-independent estimations of spatial curvature, our analysis also achieves constraints with competitive precision. More interestingly, it is suggested that the reconstructed curvature $Omega_k$ is negative in the high redshift region, which is also consistent with the results from the model-dependent constraints in the literature. Such findings are confirmed by our reconstructed evolution of $Omega_k(z)$, in the framework of a model-independent method of Gaussian processes (GP) without assuming a specific form.
Spin-orbit torques (SOTs), which rely on spin current generation from charge current in a nonmagnetic material, promise an energy-efficient scheme for manipulating magnetization in magnetic devices. A critical topic for spintronic devices using SOTs
is to enhance the charge to spin conversion efficiency. Besides, the current-induced spin polarization is usually limited to in-plane, whereas out-of-plane spin polarization could be favored for efficient perpendicular magnetization switching. Recent advances in utilizing two important classes of van der Waals materials$-$topological insulators and transition-metal dichalcogenides$-$as spin sources to generate SOT shed light on addressing these challenges. Topological insulators such as bismuth selenide have shown a giant SOT efficiency, which is larger than those from three-dimensional heavy metals by at least one order of magnitude. Transition-metal dichalcogenides such as tungsten telluride have shown a current-induced out-of-plane spin polarization, which is allowed by the reduced symmetry. In this review, we use symmetry arguments to predict and analyze SOTs in van der Waal material-based heterostructures. We summarize the recent progress of SOT studies based on topological insulators and transition-metal dichalcogenides and show how these results are in line with the symmetry arguments. At last, we identify unsolved issues in the current studies and suggest three potential research directions in this field.
Modern crowd counting methods usually employ deep neural networks (DNN) to estimate crowd counts via density regression. Despite their significant improvements, the regression-based methods are incapable of providing the detection of individuals in c
rowds. The detection-based methods, on the other hand, have not been largely explored in recent trends of crowd counting due to the needs for expensive bounding box annotations. In this work, we instead propose a new deep detection network with only point supervision required. It can simultaneously detect the size and location of human heads and count them in crowds. We first mine useful person size information from point-level annotations and initialize the pseudo ground truth bounding boxes. An online updating scheme is introduced to refine the pseudo ground truth during training; while a locally-constrained regression loss is designed to provide additional constraints on the size of the predicted boxes in a local neighborhood. In the end, we propose a curriculum learning strategy to train the network from images of relatively accurate and easy pseudo ground truth first. Extensive experiments are conducted in both detection and counting tasks on several standard benchmarks, e.g. ShanghaiTech, UCF_CC_50, WiderFace, and TRANCOS datasets, and the results show the superiority of our method over the state-of-the-art.
