Thermal Expansion and Magnetostriction Studies of a Kondo Lattice Compound: Ceagsb2

We have investigated a single crystal of CeAgSb2 using low field ac-susceptibility, thermal expansion and magnetostriction measurements in the temperature range 1.5K to 90K. The ac-susceptibility exhibits a sharp peak at 9.7K for both B//c and B perp c due to the magnetic ordering of the Ce moment. The thermal expansion coefficient alpha, exhibits highly anisotropic behaviour between 3K and 80K : alpha is positive for dL/L perp c, but negative for dL/L // c. Furthermore, alpha (for dL/L) perp c (i.e. in ab-plane) exhibits a sharp peak at TN followed by a broad maximum at 20K, while a sharp negative peak at TN followed by a minimum at 20K has been observed for (dL/L //) the c direction. The observed maximum and minimum in alpha(T) at 20K have been attributed to the crystalline field effect on the J=5/2 state of the Ce3+ ion. The magnetostriction also exhibits anisotropic behaviour with a large magnetostriction along the c-axis. The ab-plane magnetostriction exhibits a peak at B=3.3T at 3K, which is consistent with the observed peak in the magnetoresistance measurements.Comment: 4 Pages (B5), 3 figures, submitted to SCES200

Cloud information content analysis of multi-angular measurements in the oxygen A-band: application to 3MI and MSPI

The vertical distribution of cloud cover has a significant impact on a large number of meteorological and climatic processes. Cloud top altitude and cloud geometrical thickness are then essential. Previous studies established the possibility of retrieving those parameters from multi-angular oxygen A-band measurements. Here we perform a study and comparison of the performances of future instruments. The 3MI (Multi-angle, Multi-channel and Multi-polarization Imager) instrument developed by EUMETSAT, which is an extension of the POLDER/PARASOL instrument, and MSPI (Multi-angles Spectro-Polarimetric Imager) develoloped by NASA's Jet Propulsion Laboratory will measure total and polarized light reflected by the Earth's atmosphere–surface system in several spectral bands (from UV to SWIR) and several viewing geometries. Those instruments should provide opportunities to observe the links between the cloud structures and the anisotropy of the reflected solar radiation into space. Specific algorithms will need be developed in order to take advantage of the new capabilities of this instrument. However, prior to this effort, we need to understand, through a theoretical Shannon information content analysis, the limits and advantages of these new instruments for retrieving liquid and ice cloud properties, and especially, in this study, the amount of information coming from the A-Band channel on the cloud top altitude (CTOP) and geometrical thickness (CGT). We compare the information content of 3MI A-Band in two configurations and that of MSPI. Quantitative information content estimates show that the retrieval of CTOP with a high accuracy is possible in almost all cases investigated. The retrieval of CGT seems less easy but possible for optically thick clouds above a black surface, at least when CGT > 1–2 km

Cloud thermodynamic phase inferred from merged POLDER and MODIS data

International audienceThe global spatial and diurnal distribution of cloud properties is a key issue for understanding the hydrological cycle, and critical for advancing efforts to improve numerical weather models and general circulation models. Satellite data provides the best way of gaining insight into global cloud properties. In particular, the determination of cloud thermodynamic phase is a critical first step in the process of inferring cloud optical and microphysical properties from satellite measurements. It is important that cloud phase be derived together with an estimate of the confidence of this determination, so that this information can be included with subsequent retrievals (optical thickness, effective particle radius, and ice/liquid water content). In this study, we combine three different and well documented approaches for inferring cloud phase into a single algorithm. The algorithm is applied to data obtained by the MODIS (MODerate resolution Imaging Spectroradiometer) and POLDER3 (Polarization and Directionality of the Earth Reflectance) instruments. It is shown that this synergistic algorithm can be used routinely to derive cloud phase along with an index that helps to discriminate ambiguous phase from confident phase cases. The resulting product provides a semi-continuous confidence index ranging from confident liquid to confident ice instead of the usual discrete classification of liquid phase, ice phase, mixed phase (potential combination of ice and liquid particles), or simply unknown phase clouds. This approach is expected to be useful for cloud assimilation and modeling efforts while providing more insight into the global cloud properties derived from satellite data

Ice particle habit and surface roughness derived from PARASOL polarization measurements

Ice clouds are an important element in the radiative balance of the earth's climate system, but their microphysical and optical properties still are not well constrained, especially ice particle habit and the degree of particle surface roughness. In situ observations have revealed common ice particle habits and evidence for surface roughness, but these observations are limited. An alternative is to infer the ice particle shape and surface roughness from satellite observations of polarized reflectivity since they are sensitive to both particle shape and degree of surface roughness. In this study an adding–doubling radiative transfer code is used to simulate polarized reflectivity for nine different ice habits and one habit mixture, along with 17 distinct levels of the surface roughness. A lookup table (LUT) is constructed from the simulation results and used to infer shape and surface roughness from PARASOL satellite polarized reflectivity data over the ocean. Globally, the retrievals yield a compact aggregate of columns as the most commonly retrieved ice habit. Analysis of PARASOL data from the tropics results in slightly more aggregates than in midlatitude or polar regions. Some level of surface roughness is inferred in nearly 70% of PARASOL data, with mean and median roughness near σ = 0.2 and 0.15, respectively. Tropical region analyses have 20% more pixels retrieved with particle surface roughness than in midlatitude or polar regions. The global asymmetry parameter inferred at a wavelength of 0.865 μm has a mean value of 0.77 and a median value of 0.75

Ice particle habit and surface roughness derived from PARASOL polarization measurements

Ice clouds are an important element in the radiative balance of the earth's climate system, but their microphysical and optical properties still are not well constrained, especially ice particle habit and the degree of particle surface roughness. In situ observations have revealed common ice particle habits and evidence for surface roughness, but these observations are limited. An alternative is to infer the ice particle shape and surface roughness from satellite observations of polarized reflectivity since they are sensitive to both particle shape and degree of surface roughness. In this study an adding–doubling radiative transfer code is used to simulate polarized reflectivity for nine different ice habits and one habit mixture, along with 17 distinct levels of the surface roughness. A lookup table (LUT) is constructed from the simulation results and used to infer shape and surface roughness from PARASOL satellite polarized reflectivity data over the ocean. Globally, the retrievals yield a compact aggregate of columns as the most commonly retrieved ice habit. Analysis of PARASOL data from the tropics results in slightly more aggregates than in midlatitude or polar regions. Some level of surface roughness is inferred in nearly 70% of PARASOL data, with mean and median roughness near σ = 0.2 and 0.15, respectively. Tropical region analyses have 20% more pixels retrieved with particle surface roughness than in midlatitude or polar regions. The global asymmetry parameter inferred at a wavelength of 0.865 μm has a mean value of 0.77 and a median value of 0.75

Calculating and visualizing the density of states for simple quantum mechanical systems

We present a graphical approach to understanding the degeneracy, density of states, and cumulative state number for some simple quantum systems. By taking advantage of basic computing operations, we define a straightforward procedure for determining the relationship between discrete quantum energy levels and the corresponding density of states and cumulative level number. The density of states for a particle in a rigid box of various shapes and dimensions is examined and graphed. It is seen that the dimension of the box, rather than its shape, is the most important feature. In addition, we look at the density of states for a multi-particle system of identical bosons built on the single-particle spectra of those boxes. A simple model is used to explain how the N-particle density of states arises from the single particle system it is based on

Observation of band structure and density of states effects in Co-based magnetic tunnel junctions

Utilizing Co/Al$_2$O$_3$/Co magnetic tunnel junctions (MTJs) with Co electrodes of different crystalline phases, a clear relationship between electrode structure and junction transport properties is presented. For junctions with one fcc(111) textured and one polycrystalline (poly-phase and poly-directional) Co electrode, a strong asymmetry is observed in the magnetotransport properties, while when both electrodes are polycrystalline the magnetotransport is essentially symmetric. These observations are successfully explained within a model based on ballistic tunneling between the calculated band structures (DOS) of fcc-Co and hcp-Co.Comment: 4 pages, 3 figures, submitted to Phys. Rev. Let

Field-induced segregation of ferromagnetic nano-domains in Pr0.5_{0.5}Sr0.5_{0.5}MnO3_3, detected by 55^{55}Mn NMR

The antiferromagnetic manganite Pr$_{0.5}$Sr$_{0.5}$MnO$_3$ was investigated at low temperature by means of magnetometry and $^{55}$Mn NMR. A field-induced transition to a ferromagnetic state is detected by magnetization measurements at a threshold field of a few tesla. NMR shows that the ferromagnetic phase develops from zero field by the nucleation of microscopic ferromagnetic domains, consisting of an inhomogeneous mixture of tilted and fully aligned parts. At the threshold the NMR spectrum changes discontinuously into that of a homogeneous, fully aligned, ferromagnetic state, suggesting a percolative origin for the ferromagnetic transition.Comment: Latex 2.09 language. 4 pages, 3 figures, 23 references. Submitted to physical Review

Influence of ice particle model on satellite ice cloud retrieval: lessons learned from MODIS and POLDER cloud product comparison

The influence is investigated of the assumed ice particle microphysical and optical model on inferring ice cloud optical thickness (τ) from satellite measurements of the Earth's reflected shortwave radiance. Ice cloud τ are inferred, and subsequently compared, using products from MODIS (MODerate resolution Imaging Spectroradiometer) and POLDER (POLarization and Directionality of the Earth's Reflectances). POLDER τ values are found to be substantially smaller than those from collocated MODIS data. It is shown that this difference is caused primarily by the use of different ice particle bulk scattering models in the two retrievals, and more specifically, the scattering phase function. Furthermore, the influence of the ice particle model on the derivation of ice cloud radiative forcing (CRF) from satellite retrievals is studied. Three sets of shortwave CRF are calculated using different combinations of the retrieval and associated ice particle models. It is shown that the uncertainty associated with an ice particle model may lead to two types of errors in estimating CRF from satellite retrievals. One stems from the retrieval itself and the other is due to the optical properties, such as the asymmetry factor, used for CRF calculations. Although a comparison of the CRFs reveals that these two types of errors tend to cancel each other, significant differences are still found between the three CRFs, which indicates that the ice particle model affects not only optical thickness retrievals but also CRF calculations. In addition to CRF, the effect of the ice particle model on the derivation of seasonal variation of τ from satellite measurements is discussed. It is shown that optical thickness retrievals based on the same MODIS observations, but derived using different assumptions of the ice particle model, can be substantially different. These differences can be divided into two parts. The first-order difference is mainly caused by the differences in the asymmetry factor. The second-order difference is related to seasonal changes in the sampled scattering angles and therefore dependent on the sun-satellite viewing geometry. Because of this second-order difference, the use of different ice particle models may lead to a different understanding of the seasonal variation of τ