Quantum effect on luminosity-redshift relation

There are many different proposals for a theory of quantum gravity. Even leaving aside the fundamental difference among theories such as the string theory and the non-perturbative quantum gravity, we are still left with many ambiguities (and/or parameters to be determined) with regard to the choice of variables, the choice of related groups, etc. Loop quantum gravity is also in such a state. It is interesting to search for experimental observables to distinguish these quantum schemes. This paper investigates the loop quantum gravity effect on luminosity-redshift relation. The quantum bounce behavior of loop quantum cosmology is found to result in multivalued correspondence in luminosity-redshift relation. And the detail multivalued behavior can tell the difference of different quantum parameters. The inverse volume quantum correction does not result in bounce behavior in this model, but affects luminosity-redshift relation also significantly.Comment: 11 pages, 3 figures; revised versio

Dynamical Horizon Entropy Bound Conjecture in Loop Quantum Cosmology

The covariant entropy bound conjecture is an important hint for the quantum gravity, with several versions available in the literature. For cosmology, Ashtekar and Wilson-Ewing ever show the consistence between the loop gravity theory and one version of this conjecture. Recently, S. He and H. Zhang proposed a version for the dynamical horizon of the universe, which validates the entropy bound conjecture for the cosmology filled with perfect fluid in the classical scenario when the universe is far away from the big bang singularity. However, their conjecture breaks down near big bang region. We examine this conjecture in the context of the loop quantum cosmology. With the example of photon gas, this conjecture is protected by the quantum geometry effects as expected.Comment: 4 pages, 2 figures, revised versio

Stochastic resonance with matched filtering

Along with the development of interferometric gravitational wave detector, we enter into an epoch of gravitational wave astronomy, which will open a brand new window for astrophysics to observe our universe. Almost all of the data analysis methods in gravitational wave detection are based on matched filtering. Gravitational wave detection is a typical example of weak signal detection, and this weak signal is buried in strong instrument noise. So it seems attractable if we can take advantage of stochastic resonance. But unfortunately, almost all of the stochastic resonance theory is based on Fourier transformation and has no relation to matched filtering. In this paper we try to relate stochastic resonance to matched filtering. Our results show that stochastic resonance can indeed be combined with matched filtering for both periodic and non-periodic input signal. This encouraging result will be the first step to apply stochastic resonance to matched filtering in gravitational wave detection. In addition, based on matched filtering, we firstly proposed a novel measurement method for stochastic resonance which is valid for both periodic and non-periodic driven signal.Comment: 5 pages, 3 figure

SpecWatch: A Framework for Adversarial Spectrum Monitoring with Unknown Statistics

In cognitive radio networks (CRNs), dynamic spectrum access has been proposed to improve the spectrum utilization, but it also generates spectrum misuse problems. One common solution to these problems is to deploy monitors to detect misbehaviors on certain channel. However, in multi-channel CRNs, it is very costly to deploy monitors on every channel. With a limited number of monitors, we have to decide which channels to monitor. In addition, we need to determine how long to monitor each channel and in which order to monitor, because switching channels incurs costs. Moreover, the information about the misuse behavior is not available a priori. To answer those questions, we model the spectrum monitoring problem as an adversarial multi-armed bandit problem with switching costs (MAB-SC), propose an effective framework, and design two online algorithms, SpecWatch-II and SpecWatch-III, based on the same framework. To evaluate the algorithms, we use weak regret, i.e., the performance difference between the solution of our algorithm and optimal (fixed) solution in hindsight, as the metric. We prove that the expected weak regret of SpecWatch-II is O(T^{2/3}), where T is the time horizon. Whereas, the actual weak regret of SpecWatch-III is O(T^{2/3}) with probability 1 - {\delta}, for any {\delta} in (0, 1). Both algorithms guarantee the upper bounds matching the lower bound of the general adversarial MAB- SC problem. Therefore, they are all asymptotically optimal

Effects of the temperature and magnetic-field dependent coupling on the properties of QCD matter

To reflect the asymptotic freedom in the thermal direction, a temperature-dependent coupling was proposed in the literature. We investigate its effect on QCD matter with and without strong magnetic fields. Compared with the fixed coupling constant, the running coupling leads to a drastic change in the dynamical quark mass, entropy density, sound velocity, and specific heat. The crossover transition of QCD matter at finite temperature is characterized by the pseudocritical temperature $T_\mathrm{pc}$, which is generally determined by the peak of the derivative of the quark condensate with respect to the temperature $d\phi/dT$, or equivalently, by the derivative of the quark dynamical mass $d M/dT$. In a strong magnetic field, the temperature- and magnetic-field-dependent coupling $G(eB,T)$ was recently introduced to account for inverse magnetic catalysis. We propose an analytical relation between the two criteria $d\phi/dT$ and $dM/dT$ and show a discrepancy between them in finding the pseudocritical temperature. The magnitude of the discrepancy depends on the behavior of $dG/dT$.Comment: 7 pages, 7 figures, version accepted for publication in Phys. Rev.

Directional fast neutron detection using a time projection chamber and plastic scintillation detectors

A new method for directional fast neutron detection is proposed based on a neutron time projection chamber (TPC) and position-sensitive plastic scintillation detectors. The detection system can efficiently locate the approximate location of a hot spot with 4{\pi} field-of-view using only the neutron TPC. Then, the system generates a high-resolution image of the hot spot using selected coincidence events in the TPC and the scintillation detectors. A prototype was built and tested using a Cf-252 source. An efficiency of 7.1x10-3 was achieved for fast searching. The angular resolution was 7.8{\deg} (full width at half maximum, FWHM) for high-resolution imaging using the simple back projection method.Comment: 12 pages, 11 figures, SORMA XVI

Information transport in multiplex networks

In this paper, we study information transport in multiplex networks comprised of two coupled subnetworks. The upper subnetwork, called the logical layer, employs the shortest paths protocol to determine the logical paths for packets transmission, while the lower subnetwork acts as the physical layer, in which packets are delivered by the biased random walk mechanism characterized with a parameter $\alpha$. Through simulation, we obtain the optimal $\alpha$ corresponding to the maximum network lifetime and the maximum number of the arrival packets. Assortative coupling is better than the random coupling and the disassortative coupling, since it achieves much better transmission performances. Generally, the more homogeneous the lower subnetwork, the better the transmission performances are, which is opposite for the upper subnetwork. Finally, we propose an attack centrality for nodes based on the topological information of both subnetworks, and further investigate the transmission performances under targeted attacks. Our work helps to understand the spreading and robustness issues of multiplex networks and provides some clues about the designing of more efficient and robust routing architectures in communication systems.Comment: 7figure

Traffic-driven SIR epidemic model on networks

We propose a novel SIR epidemic model which is driven by the transmission of infection packets in networks. Specifically, infected nodes generate and deliver infection packets causing the spread of the epidemic, while recovered nodes block the delivery of infection packets, and this inhibits the epidemic spreading. The efficient routing protocol governed by a control parameter $\alpha$ is used in the packet transmission. We obtain the maximum instantaneous population of infected nodes, the maximum population of ever infected nodes, as well as the corresponding optimal $\alpha$ through simulation. We find that generally more balanced load distribution leads to more intense and wide spread of an epidemic in networks. Increasing either average node degree or homogeneity of degree distribution will facilitate epidemic spreading. When packet generation rate $\rho$ is small, increasing $\rho$ favors epidemic spreading. However, when $\rho$ is large enough, traffic congestion appears which inhibits epidemic spreading.Comment: 12 pages, 11 figure

Thermal effect on primordial black holes in standard Higgs minimum double-well potential

We attempt a new scheme to combine the Higgs field in the minimal standard model and the statistic physics with thermal effect together. By introducing the stochastic differential equation in FRW metric frame which is something like the warm inflation model but not exactly the same. By using the previous researches on Fokker-Planck equation with double-well potential, we find the abundance of primordial black holes (PBHs) dominate at a special mass and the PBHs with extremely large or extremely small mass could be almost excluded. In addition, two perturbed model within this frame are employed, one is the model with symmetry breaking and another is stochastic resonance. The former may increase the probability to the generation of PBHs, while the latter may both increase and decrease the probability. Finally, we also discuss the possibility on extension this scenario to other models.Comment: 9 pages, 3 figure

Triple Attention Mixed Link Network for Single Image Super Resolution

Single image super resolution is of great importance as a low-level computer vision task. Recent approaches with deep convolutional neural networks have achieved im-pressive performance. However, existing architectures have limitations due to the less sophisticated structure along with less strong representational power. In this work, to significantly enhance the feature representation, we proposed Triple Attention mixed link Network (TAN) which consists of 1) three different aspects (i.e., kernel, spatial and channel) of attention mechanisms and 2) fu-sion of both powerful residual and dense connections (i.e., mixed link). Specifically, the network with multi kernel learns multi hierarchical representations under different receptive fields. The output features are recalibrated by the effective kernel and channel attentions and feed into next layer partly residual and partly dense, which filters the information and enable the network to learn more powerful representations. The features finally pass through the spatial attention in the reconstruction network which generates a fusion of local and global information, let the network restore more details and improves the quality of reconstructed images. Thanks to the diverse feature recalibrations and the advanced information flow topology, our proposed model is strong enough to per-form against the state-of-the-art methods on the bench-mark evaluations