Pressure shift of the superconducting T_c of LiFeAs

The effect of hydrostatic pressure on the superconductivity in LiFeAs is investigated up to 1.8 GPa. The superconducting transition temperature, T_c, decreases linearly with pressure at a rate of 1.5 K/GPa. The negative pressure coefficient of T_c and the high ambient pressure T_c indicate that LiFeAs is the high-pressure analogue of the isoelectronic SrFe_2As_2 and BaFe_2As_2.Comment: 3 pages, 2 figure

Towers of Gravitational Theories

In this essay we introduce a theoretical framework designed to describe black hole dynamics. The difficulties in understanding such dynamics stems from the proliferation of scales involved when one attempts to simultaneously describe all of the relevant dynamical degrees of freedom. These range from the modes that describe the black hole horizon, which are responsible for dissipative effects, to the long wavelength gravitational radiation that drains mechanical energy from macroscopic black hole bound states. We approach the problem from a Wilsonian point of view, by building a tower of theories of gravity each of which is valid at different scales. The methodology leads to multiple new results in diverse topics including phase transitions of Kaluza-Klein black holes and the interactions of spinning black hole in non-relativistic orbits. Moreover, our methods tie together speculative ideas regarding dualities for black hole horizons to real physical measurements in gravitational wave detectors.Comment: Awarded second prize for 2006 Gravity Research Foundation essay contes

Epilogue: Superconducting Materials Past, Present and Future

Experimental contributors to the field of Superconducting Materials share their informal views on the subject.Comment: Epilogue to Physica C Special Issue on Superconducting Materials, Volume 514 (2015

Estimation of Time-varying Frequency and its Rate of Change in Low-inertia Power Systems

In this paper, a hierarchical estimation scheme is designed to track the frequency and its rate of change of non-stationary power signals. The frequency is retrieved by a kernel-based parameter estimator in the first step. Subsequently, the frequency estimates are injected into a kernel-based numerical differentiator to extract its changing rate. Thanks to the deployed Volterra integral operator and suitably designed kernel-functions, the proposed estimator can achieve very fast convergence speed without compromising the robustness against noise. Therefore, the real-time estimates are able to follow the time-varying frequency and its rate of change with satisfactory accuracy. The effectiveness and robustness of the proposed method are verified by numerical experiments considering typical practical scenarios under the disturbance of noise. The results of the proposed method are compared with a highly-concerned quadrature phase-locked-loop (QPLL) method