Spin correlated interferometry for polarized and unpolarized photons on a beam splitter

Spin interferometry of the 4th order for independent polarized as well as unpolarized photons arriving simultaneously at a beam splitter and exhibiting spin correlation while leaving it, is formulated and discussed in the quantum approach. Beam splitter is recognized as a source of genuine singlet photon states. Also, typical nonclassical beating between photons taking part in the interference of the 4th order is given a polarization dependent explanation.Comment: RevTeX, 19 pages, 1 ps figure, author web page at http://m3k.grad.hr/pavici

Experience of producing natural gas from corn straw in China

This is the author accepted manuscript. The final version is available from the publisher via the DOI in this record.Globally, crop straw is a rich resource and further establishment of its use as an energy source is an important aspect in developing the circular economy. Projects in this vein can bring benefits such as improving energy access and living conditions as well as boosting the local economy and employment opportunities in rural communities. This paper presents a detailed case study on the production of bio-natural gas (BNG) from corn straw in China, using Life Cycle Analysis (LCA) to assess energy consumption and greenhouse gas (GHG) emissions, conducting economic analysis, and analyzing operation management models. The "Nongbaomu" business model (whereby professional personnel assist farmers in the management of straw collection, bundling, storage and transportation) and the "Mutual Offsetting in Kind" business model (whereby farmers can buy a quota of the project's BNG products at a lower price in return for selling straw to the project) can ensure the acquisition of straw by the BNG project at stable prices and high quality. Because the main product (BNG) replaces refined oil products used by automobiles and the byproduct (organic fertilizer) replaces traditional fertilizer (produced using coal), the project offers the potential for significant decreases (up to 80%) in life cycle GHG emissions and fossil fuel use. Benefited from the relatively high natural gas prices in the project location and applicable government subsidies, our studied case was found to be economically viable. The findings in this study are also likely to be relevant to other countries where governments should develop industrial policies that support the development of rural distributed energy, and introduce and implement appropriate subsidies to allow BNG to compete in the traditional natural gas market. Although, enterprises are responsible for selecting an effective business models and the most appropriate technological pathway, governments should also identify the ways in which they can support businesses to make these choices.This project was co-sponsored by the National Natural Science Foundation of China (71774095, 71690244 and 71673165) and International Science & Technology Cooperation Program of China (2016YFE0102200)

Minimum Throughput Maximization for Multi-UAV Enabled WPCN: A Deep Reinforcement Learning Method

This paper investigates joint unmanned aerial vehicle (UAV) trajectory planning and time resource allocation for minimum throughput maximization in a multiple UAV-enabled wireless powered communication network (WPCN). In particular, the UAVs perform as base stations (BS) to broadcast energy signals in the downlink to charge IoT devices, while the IoT devices send their independent information in the uplink by utilizing the collected energy. The formulated throughput optimization problem which involves joint optimization of 3D path design and channel resource assignment with the constraint of flight speed of UAVs and uplink transmit power of IoT devices, is not convex and thus is extremely difficult to solve directly. We take advantage of the multi-agent deep Q learning (DQL) strategy and propose a novel algorithm to tackle this problem. Simulation results indicate that the proposed DQL-based algorithm significantly improve performance gain in terms of minimum throughput maximization compared with the conventional WPCN scheme

Reversible Embedding to Covers Full of Boundaries

In reversible data embedding, to avoid overflow and underflow problem, before data embedding, boundary pixels are recorded as side information, which may be losslessly compressed. The existing algorithms often assume that a natural image has little boundary pixels so that the size of side information is small. Accordingly, a relatively high pure payload could be achieved. However, there actually may exist a lot of boundary pixels in a natural image, implying that, the size of side information could be very large. Therefore, when to directly use the existing algorithms, the pure embedding capacity may be not sufficient. In order to address this problem, in this paper, we present a new and efficient framework to reversible data embedding in images that have lots of boundary pixels. The core idea is to losslessly preprocess boundary pixels so that it can significantly reduce the side information. Experimental results have shown the superiority and applicability of our work

Hertz-level Measurement of the 40Ca+ 4s 2S1/2-3d 2D5/2 Clock Transition Frequency With Respect to the SI Second through GPS

We report a frequency measurement of the clock transition of a single ^40Ca^+ ion trapped and laser cooled in a miniature ring Paul trap with 10^-15 level uncertainty. In the measurement, we used an optical frequency comb referenced to a Hydrogen maser, which was calibrated to the SI second through the Global Positioning System (GPS). Two rounds of measurements were taken in May and June 2011, respectively. The frequency was measured to be 411 042 129 776 393.0(1.6) Hz with a fractional uncertainty of 3.9{\times}10^-15 in a total averaging time of > 2{\times}10^6 s within 32 days

Three-dimensional ionospheric tomography algebraic reconstruction technique

An improved algebraic reconstruction technique (IART) is presented for the tomographic reconstruction of ionospheric electron density (IED). This method applies the total electron content (TEC) measurements to invert the spatial distribution of the IED from a set of apriori IED distributions. In this new method, a data-driven adjustment of the relaxation parameter is performed to improve the computation efficiency and image quality of the classical algebraic reconstruction technique (ART). In addition, the new algorithm is also combined with ionospheric space discretization technique to simplify the inversion of IED, and it applies CHAMP occultation data to improve the vertical resolution. A numerical simulation experiment is carried out to validate the reliability of the new method. It is then applied to the inversion of IED from real GPS data. Inverted results show that the IART algorithm has better accuracy and efficiency than the conventional ART algorithm. The reliability of the IART algorithm is also validated by ionosonde data recorded at Wuhan station

Electronic tuning and uniform superconductivity in CeCoIn5

We report a globally reversible effect of electronic tuning on the magnetic phase diagram in CeCoIn_{5} driven by electron (Pt and Sn) and hole (Cd, Hg) doping. Consequently, we are able to extract the superconducting pair breaking component for hole and electron dopants with pressure and co-doping studies, respectively. We find that these nominally non-magnetic dopants have a remarkably weak pair breaking effect for a d-wave superconductor. The pair breaking is weaker for hole dopants, which induce magnetic moments, than for electron dopants. Furthermore, both Pt and Sn doping have a similar effect on superconductivity despite being on different dopant sites, arguing against the notion that superconductivity lives predominantly in the CeIn_{3} planes of these materials. In addition, we shed qualitative understanding on the doping dependence with density functional theory calculations.Comment: Accepted for publication in Phys. Rev. Lett. (October 1, 2012

Evolution of the Electronic Structure of 1T-CuxTiSe2

The electronic structure of a new charge-density-wave/ superconductor system, 1T-CuxTiSe2, has been studied by photoemission spectroscopy. A correlated semiconductor band structure is revealed for the undoped case. With Cu doping, the charge density wave is suppressed by the raising of the chemical potential, while the superconductivity is enhanced by the enhancement of the density of states. Moreover, the strong scattering at high doping might be responsible for the suppression of superconductivity in that regime.Comment: 5 pages, 4 figure

Joint Power Allocation and Splitting Control in SWIPT-Aided Multi-carrier NOMA System

The combination of non-orthogonal multiple access (NOMA) and simultaneous wireless information and power transfer (SWIPT) contributes to improve the spectral efficiency (SE) and the energy efficiency (EE) at the same time. In this paper, we investigate the throughput maximization problem for the downlink multi-carrier NOMA (MC-NOMA) system with the application of power splitting (PS)-based SWIPT, in which power allocation and splitting are jointly optimized with the constraints of maximum transmit power supply as well as the minimum demand for energy harvesting (EH). To tackle the non-convex problem, a dual-layer approach is developed, in which the power allocation and splitting control are separated and the corresponding sub-problems are respectively solved through Lagrangian duality method. Simulation results validate the theoretical findings and demonstrate the superiority of the application of PS-based SWIPT to MC-NOMA over SWIPT-aided single-carrier NOMA (SC-NOMA) and SWIPT-aided orthogonal multiple access (OMA)