Simple model of the static exchange-correlation kernel of a uniform electron gas with long-range electron-electron interaction

A simple approximate expression in real and reciprocal spaces is given for the static exchange-correlation kernel of a uniform electron gas interacting with the long-range part only of the Coulomb interaction. This expression interpolates between the exact asymptotic behaviors of this kernel at small and large wave vectors which in turn requires, among other thing, information from the momentum distribution of the uniform electron gas with the same interaction that have been calculated in the G0W0 approximation. This exchange-correlation kernel as well as its complement analogue associated to the short-range part of the Coulomb interaction are more local than the Coulombic exchange-correlation kernel and constitute potential ingredients in approximations for recent adiabatic connection fluctuation-dissipation and/or density functional theory approaches of the electronic correlation problem based on a separate treatment of long-range and short-range interaction effects.Comment: 14 pages, 14 figures, to be published in Phys. Rev.

Analytical pair correlations in ideal quantum gases: Temperature-dependent bunching and antibunching

The fluctuation-dissipation theorem together with the exact density response spectrum for ideal quantum gases has been utilized to yield a new expression for the static structure factor, which we use to derive exact analytical expressions for the temperature{dependent pair distribution function g(r) of the ideal gases. The plots of bosonic and fermionic g(r) display "Bose pile" and "Fermi hole" typically akin to bunching and antibunching as observed experimentally for ultracold atomic gases. The behavior of spin-scaled pair correlation for fermions is almost featureless but bosons show a rich structure including long-range correlations near T_c. The coherent state at T=0 shows no correlation at all, just like single-mode lasers. The depicted decreasing trend in correlation with decrease in temperature for T < T_c should be observable in accurate experiments.Comment: 8 pages, 1 figure, minor revisio

Radar Cross Section Studies/Compact Range Research

A summary is given of the achievements of NASA Grant NsG-1613 by Ohio State University from May 1, 1987 to April 30, 1988. The major topics covered are as follows: (1) electromagnetic scattering analysis; (2) indoor scattering measurement systems; (3) RCS control; (4) waveform processing techniques; (5) material scattering and design studies; (6) design and evaluation of design studies; and (7) antenna studies. Major progress has been made in each of these areas as verified by the numerous publications produced

Radar cross section studies

The ultimate goal is to generate experimental techniques and computer codes of rather general capability that would enable the aerospace industry to evaluate the scattering properties of aerodynamic shapes. Another goal involves developing an understanding of scattering mechanisms so that modification of the vehicular structure could be introduced within constraints set by aerodynamics. The development of indoor scattering measurement systems with special attention given to the compact range is another goal. There has been considerable progress in advancing state-of-the-art scattering measurements and control and analysis of the electromagnetic scattering from general targets

Opportunities for integrated pest management to control the poultry red mite, Dermanyssus gallinae

Dermanyssus gallinae is the most economically important ectoparasite of laying hens in Europe. Control of D. gallinae is already hampered by issues of pesticide resistance and product withdrawal and, with the prohibition of conventional cages in 2012 and the resulting switch to more structurally complex housing which favours red mite, the importance of managing this pest will increase. Integrated Pest Management (IPM), as often employed in agricultural pest control, may be a way to address these issues where a combination of different novel control methods could be used with/without conventional management techniques to provide a synergistic and more efficacious effect. Work at in our laboratory has shown that essential oils including thyme and garlic may act as effective D. gallinae repellents and acaricides, whilst preliminary vaccine studies have demonstrated a significant increase in mite mortality in vitro using concealed antigens. Work elsewhere 27 has considered predators and fungi for D. gallinae control and other husbandry techniques such as manipulating temperature and lighting regimes in poultry units. This paper will review the available and emerging techniques for D. gallinae control and discuss which techniques might be suitable for inclusion in an integrated management programme (e.g. synthetic acaricides and diatomaceous earths)

Oscillation frequency of B and B mesons in a QCD potential model with relativistic effect

Wavefunction at the origin with the incorporation of relativistic effect leads to singularity in a specific potential model. To regularise the wavefunction, we introduce a short distance scale here and use it to estimate masses and decay constants of Bd and Bs mesons within the QCD potential model.These values are then used to compute the oscillation frequency \Delta mB of Bd and Bs mesons. The values are found to be in good agreement with experiment and other theoretical values.Comment: 10 page

Role of the van Hove Singularity in the Quantum Criticality of the Hubbard Model

A quantum critical point (QCP), separating the non-Fermi liquid region from the Fermi liquid, exists in the phase diagram of the 2D Hubbard model [Vidhyadhiraja et. al, Phys. Rev. Lett. 102, 206407 (2009)]. Due to the vanishing of the critical temperature associated with a phase separation transition, the QCP is characterized by a vanishing quasiparticle weight. Near the QCP, the pairing is enhanced since the real part of the bare d-wave p-p susceptibility exhibits algebraic divergence with decreasing temperature, replacing the logarithmic divergence found in a Fermi liquid [Yang et. al, Phys. Rev. Lett. 106, 047004 (2011)]. In this paper we explore the single-particle and transport properties near the QCP. We focus mainly on a van Hove singularity (vHS) coming from the relatively flat dispersion that crosses the Fermi level near the quantum critical filling. The flat part of the dispersion orthogonal to the antinodal direction remains pinned near the Fermi level for a range of doping that increases when we include a negative next-near-neighbor hopping t' in the model. For comparison, we calculate the bare d-wave pairing susceptibility for non-interacting models with the usual two-dimensional tight binding dispersion and a hypothetical quartic dispersion. We find that neither model yields a vHS that completely describes the critical algebraic behavior of the bare d-wave pairing susceptibility. The resistivity, thermal conductivity, thermopower, and the Wiedemann-Franz Law are examined in the Fermi liquid, marginal Fermi liquid, and pseudo-gap doping regions. A negative next-near-neighbor hopping t' increases the doping region with marginal Fermi liquid character. Both T and negative t' are relevant variables for the QCP, and both the transport and the motion of the vHS with filling suggest that they are qualitatively similar in their effect.Comment: 15 pages, 17 figure

Physics-Informed Echo State Networks for Chaotic Systems Forecasting

We propose a physics-informed Echo State Network (ESN) to predict the evolution of chaotic systems. Compared to conventional ESNs, the physics-informed ESNs are trained to solve supervised learning tasks while ensuring that their predictions do not violate physical laws. This is achieved by introducing an additional loss function during the training of the ESNs, which penalizes non-physical predictions without the need of any additional training data. This approach is demonstrated on a chaotic Lorenz system, where the physics-informed ESNs improve the predictability horizon by about two Lyapunov times as compared to conventional ESNs. The proposed framework shows the potential of using machine learning combined with prior physical knowledge to improve the time-accurate prediction of chaotic dynamical systems.Comment: 7 pages, 3 figure