Searching for Low Mass Dark Portal at the LHC

Light dark matter with mass smaller than about 10 GeV is difficult to probe from direct detection experiments. In order to have the correct thermal relic abundance, the mediator of the interaction between dark matter and the Standard Model (SM) should also be relatively light, $\sim 10^2$ GeV. If such a light mediator couples to charged leptons, it would already be strongly constrained by direct searches at colliders. In this work, we consider the scenario of a leptophobic light $Z'$ vector boson as the mediator, and study the the prospect of searching for it at the 8 TeV Large Hadron Collider (LHC). To improve the reach in the low mass region, we perform a detailed study of the processes that the $Z'$ is produced in association with jet, photon, $W^\pm$ and $Z^0$. We show that in the region where the mass of $Z'$ is between 80 and 400 GeV, the constraint from associated production can be comparable or even stronger than the known monojet and dijet constraints. Searches in these channels can be complementary to the monojet search, in particular if the $Z'$ couplings to quarks ($g_{Z'}$) and dark matter ($g_D$) are different. For $g_D < g_{Z'}$, we show that there is a larger region of parameter space which has correct thermal relic abundance and a light $Z'$, $M_{Z'} \sim 100$ GeV. This region, which cannot be covered by the mono-jet search, can be covered by the resonance searches described in this paper.Comment: 16 pages, 5 figure

Iterative source and channel decoding relying on correlation modelling for wireless video transmission

Since joint source-channel decoding (JSCD) is capable of exploiting the residual redundancy in the source signals for improving the attainable error resilience, it has attracted substantial attention. Motivated by the principle of exploiting the source redundancy at the receiver, in this treatise we study the application of iterative source channel decoding (ISCD) aided video communications, where the video signal is modelled by a first-order Markov process. Firstly, we derive reduced-complexity formulas for the first-order Markov modelling (FOMM) aided source decoding. Then we propose a bit-based iterative horizontal vertical scanline model (IHVSM) aided source decoding algorithm, where a horizontal and a vertical source decoder are employed for exchanging their extrinsic information using the iterative decoding philosophy. The iterative IHVSM aided decoder is then employed in a forward error correction (FEC) encoded uncompressed video transmission scenario, where the IHVSM and the FEC decoder exchange softbit-information for performing turbo-like ISCD for the sake of improving the reconstructed video quality. Finally, we benchmark the attainable system performance against a near-lossless H.264/AVC video communication system and the existing FOMM based softbit source decoding scheme, where The financial support of the RC-UK under the auspices of the India-UK Advanced Technology Centre (IU-ATC) and that of the EU under the CONCERTO project as well as that of the European Research Council’s Advanced Fellow Grant is gratefully acknowledged. The softbit decoding is performed by a one-dimensional Markov model aided decoder. Our simulation results show that Eb=N0 improvements in excess of 2.8 dB are attainable by the proposed technique in uncompressed video applications

Iterative two-dimensional error concealment for low-complexity wireless video uplink transmitters

Since joint source-channel decoding is capable of exploiting the residual redundancy in the encoded source signals for improving the attainable error resilience, it has attracted substantial attention. Motivated by the principle of exploiting the source redundancy at the receiver, in this treatise we study the application of iterative Error Concealment (EC) for low-complexity uplink video communications, where the video signal is modelled by a first-order Markov process. Firstly, we derive reduced-complexity formulas for the first-order Markov modelling aided source decoding. Then we propose a bit-based iterative EC algorithm, where a horizontal and a vertical source decoder are employed for exchanging their information using the iterative decoding philosophy. This scheme may be combined with low-complexity video codecs, provided that they retain some of the redundancy residing in the video signals and are capable of estimating the softbit information representing each bit of the video pixels. As application examples, we test our proposed two-dimensional iterative EC in both Wyner-Ziv video coded and uncompressed video transmission scenarios. Finally, we benchmark the attainable system performance against the existing first-order Markov process based softbit source decoding scheme, where the softbit decoding is performed by a one-dimensional Markov model aided decoder, as well as by the existing pixel-domain Wyner-Ziv video scheme. Our simulation results show that Eb/N0 improvements in excess of 6 dB are attainable by the proposed technique in uncompressed video home-networking applications. Furthermore, up to 21.5% bitrate reduction is achieved by employing our proposed iterative error concealment technique in a Wyner-Ziv video coding scheme

Effects of Metabolic Energy on Synaptic Transmission and Dendritic Integration in Pyramidal Neurons

As a sophisticated computing unit, the pyramidal neuron requires sufficient metabolic energy to fuel its powerful computational capabilities. However, the majority of previous works focus on nonlinear integration and energy consumption in individual pyramidal neurons but seldom on the effects of metabolic energy on synaptic transmission and dendritic integration. Here, we developed biologically plausible models to simulate the synaptic transmission and dendritic integration of pyramidal neurons, exploring the relations between synaptic transmission and metabolic energy and between dendritic integration and metabolic energy. We find that synaptic energy not only drives synaptic vesicle cycle, but also participates in the regulation of this cycle. Release probability of synapses adapts to synaptic energy levels by regulating the speed of synaptic vesicle cycle. Besides, we also find that to match neural energy levels, only a part of the synapses receive presynaptic signals during a given period so that neurons have a low action potential frequency. That is, the number of simultaneously active synapses over a period of time should be adapted to neural energy levels

Online auction-based relay selection for cooperative communication in CR networks

Cognitive radio and cooperative communication are two new network technologies. So, the combination of these two new technologies is a novel solution to solve the problem of spectrum scarcity. Two main challenges exist in the integration of cognitive radio and cooperative communication. First, there is a lack of incentives for the participating wireless devices to serve as relay nodes. Second, there is not an effective relay selection policy. In this paper, we propose an online auction-based relay selection scheme for cooperative communication in cognitive radio (CR) networks. Specifically, we design an auction scheme through adopting stopping theory. The proposed scheme ensures that the primary user (PU) can effectively select a CR relay to transmit its packets in a given time bound. In addition, we have analytically proven the truthfulness and the individual rationality of our online auction scheme. Extensive simulations demonstrate that the proposed relay selection scheme can always successfully and efficiently select a proper relay for a PU and can achieve a higher cooperative communication throughput compared with the conventional schemes