Constraints on interacting dark energy models from time-delay cosmography with seven lensed quasars

Measurements of time-delay cosmography of lensed quasars can provide an independent probe to explore the expansion history of the late-time universe. In this paper, we employ the time-delay cosmography measurements from seven lenses (here abbreviated as the TD data) to constrain interacting dark energy (IDE) models. We mainly focus on the scenario of vacuum energy (with $w=-1$) interacting with cold dark matter, and consider four typical cases of the interaction form $Q$. When the TD data alone is employed, we find that the IDE models with $Q\propto \rho_{\rm de}$ seem to have an advantage in relieving the $H_{0}$ tension between the cosmic microwave background (CMB) and TD data. When the TD data is added to the CMB+BAO+SN+$H_0$ data, we find that: (i) the coupling parameter $\beta$ in all the considered IDE models is positive within 1$\sigma$ range, implying a mild preference for the case of cold dark matter decaying into dark energy; (ii) all the considered IDE models aggravate the $\sigma_8$ tension, while the $S_8$ tension could be slightly relieved in the IDE model with $Q = \beta H_{0} \rho_{\rm c}$; (iii) the Akaike information criteria of the IDE models with $Q \propto \rho_{\rm c}$ are lower than that of the $\Lambda$CDM model, indicating that these IDE models are more preferred by the current mainstream data. We conclude that the considered IDE models have their own different advantages when the TD data is employed, and none of them can achieve good scores in all aspects.Comment: 10 pages, 4 figure

Constraints on the DGP Universe using observational Hubble parameter

AbstractIn this work, we use observations of the Hubble parameter from the differential ages of passively evolving galaxies and the recent detection of the Baryon Acoustic Oscillations (BAO) at z1=0.35 to constrain the Dvali–Gabadadze–Porrati (DGP) Universe. For the case with a curvature term, we set a prior h=0.73±0.03 and the best-fit values suggest a spatially closed Universe. For a flat Universe, we set h free and we get consistent results with other recent analyses

LF-PGVIO: A Visual-Inertial-Odometry Framework for Large Field-of-View Cameras using Points and Geodesic Segments

In this paper, we propose LF-PGVIO, a Visual-Inertial-Odometry (VIO) framework for large Field-of-View (FoV) cameras with a negative plane using points and geodesic segments. The purpose of our research is to unleash the potential of point-line odometry with large-FoV omnidirectional cameras, even for cameras with negative-plane FoV. To achieve this, we propose an Omnidirectional Curve Segment Detection (OCSD) method combined with a camera model which is applicable to images with large distortions, such as panoramic annular images, fisheye images, and various panoramic images. The geodesic segment is sliced into multiple straight-line segments based on the radian and descriptors are extracted and recombined. Descriptor matching establishes the constraint relationship between 3D line segments in multiple frames. In our VIO system, line feature residual is also extended to support large-FoV cameras. Extensive evaluations on public datasets demonstrate the superior accuracy and robustness of LF-PGVIO compared to state-of-the-art methods. The source code will be made publicly available at https://github.com/flysoaryun/LF-PGVIO.Comment: Accepted to IEEE Transactions on Intelligent Vehicles (T-IV). The source code will be made publicly available at https://github.com/flysoaryun/LF-PGVI

Accumulative time-based ranking method to reputation evaluation in information networks

With the rapid development of modern technology, the Web has become an important platform for users to make friends and acquire information. However, since information on the Web is over-abundant, information filtering becomes a key task for online users to obtain relevant suggestions. As most Websites can be ranked according to users' rating and preferences, relevance to queries, and recency, how to extract the most relevant item from the over-abundant information is always a key topic for researchers in various fields. In this paper, we adopt tools used to analyze complex networks to evaluate user reputation and item quality. In our proposed accumulative time-based ranking (ATR) algorithm, we incorporate two behavioral weighting factors which are updated when users select or rate items, to reflect the evolution of user reputation and item quality over time. We showed that our algorithm outperforms state-of-the-art ranking algorithms in terms of precision and robustness on empirical datasets from various online retailers and the citation datasets among research publications

Study on cosmogenic activation in copper for rare event search experiments

The rare event search experiments using germanium detectors are performed in the underground laboratories to prevent cosmic rays. However, the cosmogenic activation of the cupreous detector components on the ground will generate long half-life radioisotopes and contribute continually to the expected background level. We present a study on the cosmogenic activation of copper after 504 days of exposure at an altitude of 2469.4 m outside the China Jinping Underground Laboratory (CJPL). The specific activities of the cosmogenic nuclides produced in the copper bricks were measured using a low background germanium gamma-ray spectrometer at CJPL. The production rates at sea level, in units of nuclei/kg/day, are 18.6 \pm 2.0 for Mn-54, 9.9 \pm 1.3 for Co-56, 48.3 \pm 5.5 for Co-57, 51.8 \pm 2.5 for Co-58 and 39.7 \pm 5.7 for Co-60, respectively. Given the expected exposure history of the germanium detectors, a Monte Carlo simulation is conducted to assess the cosmogenic background contributions of the detectors' cupreous components.Comment: 6 pages, 4 figure