Spin glass behavior in an interacting gamma-Fe2O3 nanoparticle system

In this paper we investigate the superspin glass behavior of a concentrated assembly of interacting maghemite nanoparticles and compare it to that of canonical atomic spin glass systems. ac versus temperature and frequency measurements show evidence of a superspin glass transition taking place at low temperature. In order to fully characterize the superspin glass phase, the aging behavior of both the thermo-remanent magnetization (TRM) and ac susceptibility has been investigated. It is shown that the scaling laws obeyed by superspin glasses and atomic spin glasses are essentially the same, after subtraction of a superparamagnetic contribution from the superspin glass response functions. Finally, we discuss a possible origin of this superparamagnetic contribution in terms of dilute spin glass models

FReD: The floral reflectance spectra database

Floral reflectance measurements are of great value to researchers who need consider the real colour of flowers, for example in the context of how the flowers appear to their pollinators. We have thus developed the Floral Reflectance Database (FReD) to assist these researchers, gathering together floral reflectance data in a publicly available, searchable online database. The first version of the database is now available online at "http://www.reflectance.co.uk":http://www.reflectance.co.uk. We anticipate that this resource will be of interest to researchers working on flower colour and animal vision

Aging, rejuvenation and memory effects in re-entrant ferromagnets

We have studied the slow dynamics of the ferromagnetic phases of the re-entrant CdCr_{2x}In_{2-2x}S_4 system for 0.85<x<=1 by means of low frequency ac susceptibility and magnetization measurements. Experimental procedures widely used in the investigation of the out-of-equilibrium dynamics of spin glasses (such as the x=0.85 compound) have been applied to search for aging, rejuvenation and memory effects, and to test their dependence on the disorder introduced by dilution of the magnetic ions. Whereas the rejuvenation effect is found in all studied samples, the memory effect is clearly enhanced for increasing dilutions. The results support a description of aging in both ferromagnetic and re-entrant spin-glass phases in terms of hierarchical reconformations of domain walls pinned by the disorder.Comment: Service de Physique de l'Etat Condense, DRECAM, DSM, CEA Saclay,91191 Gif sur Yvette Cedex, France, 9 pages, including 7 figures, To appear in Eur. Phys. J. B (2002

Memory interference effects in spin glasses

When a spin glass is cooled down, a memory of the cooling process is imprinted in the spin structure. This memory can be disclosed in a continuous heating measurement of the ac-susceptibility. E.g., if a continuous cooling process is intermittently halted during a certain aging time at one or two intermediate temperatures, the trace of the previous stop(s) is recovered when the sample is continuously re-heated [1]. However, heating the sample above the aging temperature, but keeping it below Tg, erases the memory of the thermal history at lower temperatures. We also show that a memory imprinted at a higher temperature can be erased by waiting a long enough time at a lower temperature. Predictions from two complementary spin glass descriptions, a hierarchical phase space model and a real space droplet picture are contested with these memory phenomena and interference effects. [1] K. Jonason, E. Vincent, J. Hammann, J. P. Bouchaud and P. Nordblad, Phys. Rev. Lett. 31, 3243 (1998).Comment: 7 pages, 1 LaTex file + 5 figures in EPS Revised version of June 17, 1999 (minor changes), to appear in EPJ B around November 9

Spin Anisotropy and Slow Dynamics in Spin Glasses

We report on an extensive study of the influence of spin anisotropy on spin glass aging dynamics. New temperature cycle experiments allow us to compare quantitatively the memory effect in four Heisenberg spin glasses with various degrees of random anisotropy and one Ising spin glass. The sharpness of the memory effect appears to decrease continuously with the spin anisotropy. Besides, the spin glass coherence length is determined by magnetic field change experiments for the first time in the Ising sample. For three representative samples, from Heisenberg to Ising spin glasses, we can consistently account for both sets of experiments (temperature cycle and magnetic field change) using a single expression for the growth of the coherence length with time.Comment: 4 pages and 4 figures - Service de Physique de l'Etat Condense CNRS URA 2464), DSM/DRECAM, CEA Saclay, Franc

Method of forming thin window drifted silicon charged particle detector Patent

Method of forming thin window drifted silicon charged particle detecto

Aging phenomena in spin glass and ferromagnetic phases: domain growth and wall dynamics

We compare aging in a disordered ferromagnet and in a spin glass, by studying the different phases of a reentrant system. We have measured the relaxation of the low-frequency ac susceptibility, in both the ferromagnetic and spin-glass phases of a CdCr_{1.9}In_{0.1}S_4 sample. A restart of aging processes when the temperature is lowered (`chaos-like' effect) is observed in both phases. The memory of previous aging at a higher temperature can be retrieved upon re-heating, but in the ferromagnetic phase it can rapidly be erased by the growth of ferromagnetic domains. We interpret the behaviour observed in the ferromagnetic phase in terms of a combination of domain growth and pinned wall reconformations, and suggest that aging in spin glasses is dominated by such wall reconformation processes.Comment: SPEC, CEA Saclay, 91191 Gif sur Yvette Cedex, France, to appear in Europhys. Lett. (2000

Development of advanced techniques for rotorcraft state estimation and parameter identification

An integrated methodology for rotorcraft system identification consists of rotorcraft mathematical modeling, three distinct data processing steps, and a technique for designing inputs to improve the identifiability of the data. These elements are as follows: (1) a Kalman filter smoother algorithm which estimates states and sensor errors from error corrupted data. Gust time histories and statistics may also be estimated; (2) a model structure estimation algorithm for isolating a model which adequately explains the data; (3) a maximum likelihood algorithm for estimating the parameters and estimates for the variance of these estimates; and (4) an input design algorithm, based on a maximum likelihood approach, which provides inputs to improve the accuracy of parameter estimates. Each step is discussed with examples to both flight and simulated data cases