Exact Eigenfunctions of NN-Body system with Quadratic Pair Potential

We obtain all the exact eigenvalues and the corresponding eigenfunctions of $N$-body Bose and Fermi systems with Quadratic Pair Potentials in one dimension. The originally existed first excited state level is missing in one dimension, which results from the operation of symmetry or antisymmetry of identical particles. In two and higher dimensions, we give all the eigenvalues and the analytical ground state wave functions and the number of degeneracy. Through the comparison with Avinash Khare's results, we have perfected his results.Comment: 7 pages,1 figur

Potential and Actual impacts of deforestation and afforestation on land surface temperature

Forests are undergoing significant changes throughout the globe. These changes can modify water, energy, and carbon balance of the land surface, which can ultimately affect climate. We utilize satellite data to quantify the potential and actual impacts of forest change on land surface temperature (LST) from 2003 to 2013. The potential effect of forest change on temperature is calculated by the LST difference between forest and nearby nonforest land, whereas the actual impact on temperature is quantified by the LST trend difference between deforested (afforested) and nearby unchanged forest (nonforest land) over several years. The good agreement found between potential and actual impacts both at annual and seasonal levels indicates that forest change can have detectable impacts on surface temperature trends. That impact, however, is different for maximum and minimum temperatures. Overall, deforestation caused a significant warming up to 0.28 K/decade on average temperature trends in tropical regions, a cooling up to -0.55 K/decade in boreal regions, a weak impact in the northern temperate regions, and strong warming (up to 0.32 K/decade) in the southern temperate regions. Afforestation induced an opposite impact on temperature trends. The magnitude of the estimated temperature impacts depends on both the threshold and the data set (Moderate Resolution Imaging Spectroradiometer and Landsat) by which forest cover change is defined. Such a latitudinal pattern in temperature impact is mainly caused by the competing effects of albedo and evapotranspiration on temperature. The methodology developed here can be used to evaluate the temperature change induced by forest cover change around the globe.Maryland Council on the Environment [1357928]; National Natural Science Foundation of China [41371096, 41130534]; China Scholar Council fellowship [201306010169]; National Socio-Environmental Synthesis Center-NSF [DBI-1052875]SCI(E)[email protected]

Neutrino Halos in Clusters of Galaxies and their Weak Lensing Signature

We study whether non-linear gravitational effects of relic neutrinos on the development of clustering and large-scale structure may be observable by weak gravitational lensing. We compute the density profile of relic massive neutrinos in a spherical model of a cluster of galaxies, for several neutrino mass schemes and cluster masses. Relic neutrinos add a small perturbation to the mass profile, making it more extended in the outer parts. In principle, this non-linear neutrino perturbation is detectable in an all-sky weak lensing survey such as EUCLID by averaging the shear profile of a large fraction of the visible massive clusters in the universe, or from its signature in the general weak lensing power spectrum or its cross-spectrum with galaxies. However, correctly modeling the distribution of mass in baryons and cold dark matter and suppressing any systematic errors to the accuracy required for detecting this neutrino perturbation is severely challenging.Comment: 13 pages, 11 figures. Submitted to JCA

Spin-Phonon Coupling in Iron Pnictide Superconductors

The magnetic moment in the parent phase of the iron-pnictide superconductors varies with composition even when the nominal charge of iron is unchanged. We propose the spin-lattice coupling due to the magneto-volume effect as the primary origin of this effect, and formulate a Landau theory to describe the dependence of the moment to the Fe-As layer separation. We then compare the superconductive critical temperature of doped iron pnictides to the local moment predicted by the theory, and suggest that the spin-phonon coupling may play a role in the superconductivity of this compound

An effective local routing strategy on the BA network

In this paper, We propose a effective routing strategy on the basis of the so-called nearest neighbor search strategy by introducing a preferential delivering exponent alpha. we assume that the handling capacity of one vertex is proportional to its degree when the degree is smaller than a cut-off value $K$, and is infinite otherwise. It is found that by tuning the parameter alpha, the scale-free network capacity measured by the order parameter is considerably enhanced compared to the normal nearest-neighbor strategy. Traffic dynamics both near and far away from the critical generating rate R_c are discussed. We also investigate R_c as functions of m (connectivity density), K (cutoff value). Due to the low cost of acquiring nearest-neighbor information and the strongly improved network capacity, our strategy may be useful and reasonable for the protocol designing of modern communication networks.Comment: 9 pages, 5 figure

Carbon nanotubes : from molecular to macroscopic sensors

The components that contribute to Raman spectral shifts of single-wall carbon nanotubes (SWNT’s) embedded in polymer systems have been identified. The temperature dependence of the Raman shift can be separated into the temperature dependence of the nanotubes, the cohesive energy density of the polymer, and the buildup of thermal strain. Discounting all components apart from the thermal strain from the Raman shift-temperature data, it is shown that the mechanical response of single-wall carbon nanotubes in tension and compression are identical. The stress-strain response of SWNT’s can explain recent experimental data for carbon nanotube-composite systems

Tests of the random phase approximation for transition strengths

We investigate the reliability of transition strengths computed in the random-phase approximation (RPA), comparing with exact results from diagonalization in full $0\hbar\omega$ shell-model spaces. The RPA and shell-model results are in reasonable agreement for most transitions; however some very low-lying collective transitions, such as isoscalar quadrupole, are in serious disagreement. We suggest the failure lies with incomplete restoration of broken symmetries in the RPA. Furthermore we prove, analytically and numerically, that standard statements regarding the energy-weighted sum rule in the RPA do not hold if an exact symmetry is broken.Comment: 11 pages, 7 figures; Appendix added with new proof regarding violation of energy-weighted sum rul

A dementia classification framework using frequency and time-frequency features based on EEG signals.

Alzheimer's Disease (AD) accounts for 60-70% of all dementia cases, and clinical diagnosis at its early stage is extremely difficult. As several new drugs aiming to modify disease progression or alleviate symptoms are being developed, to assess their efficacy, novel robust biomarkers of brain function are urgently required. This study aims to explore a routine to gain such biomarkers using the quantitative analysis of Electroencephalography (QEEG). This paper proposes a supervised classification framework which uses EEG signals to classify healthy controls (HC) and AD participants. The framework consists of data augmentation, feature extraction, K-Nearest Neighbour (KNN) classification, quantitative evaluation and topographic visualisation. Considering the human brain either as a stationary or a dynamical system, both frequency-based and time-frequency-based features were tested in 40 participants. Results: a) The proposed method can achieve up to 99% classification accuracy on short (4s) eyes open EEG epochs, with the KNN algorithm that has best performance when compared to alternative machine learning approaches; b) The features extracted using the wavelet transform produced better classification performance in comparison to the features based on FFT; c) In the spatial domain, the temporal and parietal areas offer the best distinction between healthy controls and AD. The proposed framework can effectively classify HC and AD participants with high accuracy, meanwhile offering identification and localisation of significant QEEG features. These important findings and the proposed classification framework could be used for the development of a biomarker for the diagnosis and monitoring of disease progression in AD

Strain and temperature sensitivity of a singlemode polymer optical fibre

We report experimental measurements of the strain and temperature sensitivity of the optical phase in a singlemode polymer optical fibre. These values were obtained by measuring optical path length change using a Mach-Zender interferometer