Revisiting the holographic dark energy in a non-flat universe: alternative model and cosmological parameter constraints

We propose an alternative model for the holographic dark energy in a non-flat universe. This new model differs from the previous one in that the IR length cutoff $L$ is taken to be exactly the event horizon size in a non-flat universe, which is more natural and theoretically/conceptually concordant with the model of holographic dark energy in a flat universe. We constrain the model using the recent observational data including the type Ia supernova data from SNLS3, the baryon acoustic oscillation data from 6dF, SDSS-DR7, BOSS-DR11, and WiggleZ, the cosmic microwave background data from Planck, and the Hubble constant measurement from HST. In particular, since some previous studies have shown that the color-luminosity parameter $\beta$ of supernovae is likely to vary during the cosmic evolution, we also consider such a case that $\beta$ in SNLS3 is time-varying in our data fitting. Compared to the constant $\beta$ case, the time-varying $\beta$ case reduces the value of $\chi^2$ by about 35 and results in that $\beta$ deviates from a constant at about 5$\sigma$ level, well consistent with the previous studies. For the parameter $c$ of the holographic dark energy, the constant $\beta$ fit gives $c=0.65\pm 0.05$ and the time-varying $\beta$ fit yields $c=0.72\pm 0.06$. In addition, an open universe is favored (at about 2$\sigma$) for the model by the current data.Comment: 8 pages, 4 figure

Fast List Decoding of High-Rate Polar Codes

Due to the ability to provide superior error-correction performance, the successive cancellation list (SCL) algorithm is widely regarded as one of the most promising decoding algorithms for polar codes with short-to-moderate code lengths. However, the application of SCL decoding in low-latency communication scenarios is limited due to its sequential nature. To reduce the decoding latency, developing tailored fast and efficient list decoding algorithms of specific polar substituent codes (special nodes) is a promising solution. Recently, fast list decoding algorithms are proposed by considering special nodes with low code rates. Aiming to further speedup the SCL decoding, this paper presents fast list decoding algorithms for two types of high-rate special nodes, namely single-parity-check (SPC) nodes and sequence rate one or single-parity-check (SR1/SPC) nodes. In particular, we develop two classes of fast list decoding algorithms for these nodes, where the first class uses a sequential decoding procedure to yield decoding latency that is linear with the list size, and the second further parallelizes the decoding process by pre-determining the redundant candidate paths offline. Simulation results show that the proposed list decoding algorithms are able to achieve up to 70.7\% lower decoding latency than state-of-the-art fast SCL decoders, while exhibiting the same error-correction performance.Comment: 13 pages, 8 figure

Dynamic network Malmquist model based on green input-output table

Workshop 2013 on Dynamic and Network DEA (January 29-30, 2013)For revealing the influence of intermediate transactions between industrial sectors to the dynamic performance, this paper develops a framework of dynamic performance with network structure measurement by establishing a dynamic network Malmquist productivity index (DNMPI) model following the dynamic network slacks-based measure (DNSBM) model. In order to explore the performance, we decompose the model to identify the dynamic efficiency (inter-temporal influence) and the network efficiency (sector interaction) based on green accounting. Furthermore, this paper analyzes Chinese dynamic performance with network structure influenced by energy-economy-environment (3E) in the view of industrial chain effect. We apply it to analyze the data of 40 industrial sectors in China from 2002, 2005 and 2007. Based on empirical results, we systematically indicate the influence of energy efficiency and environment efficiency to the economic development in China.This workshop is supported by JSPS KAKENHI Grant Number 22310096 under the title “Theory and Applications of Dynamic DEA with Network Structure.