Measurements of the absolute value of the penetration depth in high-Tc T_c superconductors using a tunnel diode resonator

A method is presented to measure the absolute value of the London penetration depth, $\lambda$, from the frequency shift of a resonator. The technique involves coating a high-$T_c$ superconductor (HTSC) with film of low - Tc material of known thickness and penetration depth. The method is applied to measure London penetration depth in YBa2Cu3O{7-\delta} (YBCO) Bi2Sr2CaCu2O{8+\delta} (BSCCO) and Pr{1.85}Ce{0.15}CuO{4-\delta}$(PCCO). For YBCO and BSCCO, the values of$\lambda (0)$are in agreement with the literature values. For PCCO$\lambda \approx 2790$ \AA, reported for the first time.Comment: RevTex 4 (beta 4). 4 pages, 4 EPS figures. Submitted to Appl. Phys. Let

Low temperature vortex phase diagram of Bi2Sr2CaCu2O8 : a magnetic penetration depth study

We report measurements of the magnetic penetration depth \lambda_m(T) in the presence of a DC magnetic field in optimally doped BSCCO-2212 single crystals. Warming, after magnetic field is applied to a zero-field cooled sample, results in a non-monotonic \lambda_m(T), which does not coincide with a curve obtained upon field cooling, thus exhibiting a hysteretic behaviour. We discuss the possible relation of our results to the vortex decoupling, unbinding, and dimensional crossover.Comment: M2S-HTSC-V

Evolution of Magnetic and Superconducting Fluctuations with Doping of High-Tc Superconductors (An electronic Raman scattering study)

For YBa_2Cu_3O_{6+\delta} and Bi_2Sr_2CaCu_2O_8 superconductors, electronic Raman scattering from high- and low-energy excitations has been studied in relation to the hole doping level, temperature, and energy of the incident photons. For underdoped superconductors, it is concluded that short range antiferromagnetic (AF) correlations persist with hole doping and doped single holes are incoherent in the AF environment. Above the superconducting (SC) transition temperature T_c the system exhibits a sharp Raman resonance of B_1g symmetry and about 75 meV energy and a pseudogap for electron-hole excitations below 75 meV, a manifestation of a partially coherent state forming from doped incoherent quasi-particles. The occupancy of the coherent state increases with cooling until phase ordering at T_c produces a global SC state.Comment: 5 pages, 4 EPS figures; SNS'97 Proceedings to appear in J. Phys. Chem. Solid

Electronic Spectra and Their Relation to the (pi,pi) Collective Mode in High-Tc Superconductors

Photoemission spectra of Bi2Sr2CaCu2O8 reveal that the high energy feature near (pi,0), the "hump", scales with the superconducting gap and persists above Tc in the pseudogap phase. As the doping decreases, the dispersion of the hump increasingly reflects the wavevector (pi,pi) characteristic of the undoped insulator, despite the presence of a large Fermi surface. This can be understood from the interaction of the electrons with a collective mode, supported by our observation that the doping dependence of the resonance observed by neutron scattering is the same as that inferred from our data.Comment: 4 pages (revtex), 5 figures (eps

Predominantly Superconducting Origin of Large Energy Gaps in Underdoped Bi2Sr2CaCu2O8-d from Tunneling Spectroscopy

New tunneling data are reported in underdoped Bi2Sr2CaCu2O8-d using superconductor-insulator-superconductor break junctions. Energy gaps, Delta, of 51+2, 54+2 and 57+3 meV are observed for three crystals with Tc=77, 74, and 70 K respectively. These energy gaps are nearly three times larger than for overdoped crystals with similar Tc. Detailed examination of tunneling spectra over a wide doping range from underdoped to overdoped, including the Josephson IcRn product, indicate that these energy gaps are predominantly of superconducting origin.Comment: 10 pages, 4 figures, 1 tabl

Two-dimensional Vortices in Superconductors

Superconductors have two key characteristics. They expel magnetic field and they conduct electrical current with zero resistance. However, both properties are compromised in high magnetic fields which can penetrate the material and create a mixed state of quantized vortices. The vortices move in response to an electrical current dissipating energy which destroys the zero resistance state\cite{And64}. One of the central problems for applications of high temperature superconductivity is the stabilization of vortices to ensure zero electrical resistance. We find that vortices in the anisotropic superconductor Bi$_{2}$Sr$_{2}$CaCu$_{2}$O$_{8+\delta}$ (Bi-2212) have a phase transition from a liquid state, which is inherently unstable, to a two-dimensional vortex solid. We show that at high field the transition temperature is independent of magnetic field, as was predicted theoretically for the melting of an ideal two-dimensional vortex lattice\cite{Fis80,Gla91}. Our results indicate that the stable solid phase can be reached at any field as may be necessary for applications involving superconducting magnets\cite{Has04,Sca04,COHMAG}. The vortex solid is disordered, as suggested by previous studies at lower fields\cite{Lee93,Cub93}. But its evolution with increasing magnetic field displays unexpected threshold behavior that needs further investigation.Comment: 5 pages and 4 figures. submitted to Nature Physic

Bayesian inference of biochemical kinetic parameters using the linear noise approximation

Background Fluorescent and luminescent gene reporters allow us to dynamically quantify changes in molecular species concentration over time on the single cell level. The mathematical modeling of their interaction through multivariate dynamical models requires the deveopment of effective statistical methods to calibrate such models against available data. Given the prevalence of stochasticity and noise in biochemical systems inference for stochastic models is of special interest. In this paper we present a simple and computationally efficient algorithm for the estimation of biochemical kinetic parameters from gene reporter data. Results We use the linear noise approximation to model biochemical reactions through a stochastic dynamic model which essentially approximates a diffusion model by an ordinary differential equation model with an appropriately defined noise process. An explicit formula for the likelihood function can be derived allowing for computationally efficient parameter estimation. The proposed algorithm is embedded in a Bayesian framework and inference is performed using Markov chain Monte Carlo. Conclusion The major advantage of the method is that in contrast to the more established diffusion approximation based methods the computationally costly methods of data augmentation are not necessary. Our approach also allows for unobserved variables and measurement error. The application of the method to both simulated and experimental data shows that the proposed methodology provides a useful alternative to diffusion approximation based methods