Charge ordered ferromagnetic phase in La0.5Ca0.5MnO3

Mixed valent manganites are noted for their unusual magnetic,electronic and structural phase transitions. The La1-xCaxMnO3 phase diagram shows that below transition temperatures in the range 100-260 K, compounds with 0.2 < x < 0.5 are ferromagnetic and metallic whereas those with 0.5 < x < 0.9 are antiferromagnetic and charge ordered. In a narrow region around x = 0.5, these totally dissimilar states are thought to coexist. Uehara et al. have shown that charge order and charge disorder can coexist in the related compound La0.25Pr0.375Ca0.375MnO3. Here, we present electron microscopy data for La0.5Ca0.5MnO3 that sheds light on the distribution of coexisting phases and uncovers a novel and unexpected phase. Using electron holography and Fresnel imaging, we find micron sized ferromagnetic regions spanning several grains coexisting with similar sized regions with no local magnetisation. Holography shows that the ferromagnetic regions have a local magnetisation of 3.4 +- 0.2 mB/Mn (the spin aligned value is 3.5 mB/Mn). We use electron diffraction and dark field imaging to show that charge order exists in regions with no net magnetisation and, surprisingly, can also occur in ferromagnetic regions.Comment: 5 pages of pdf with 2 figures include

Neural Network Parameterizations of Electromagnetic Nucleon Form Factors

The electromagnetic nucleon form-factors data are studied with artificial feed forward neural networks. As a result the unbiased model-independent form-factor parametrizations are evaluated together with uncertainties. The Bayesian approach for the neural networks is adapted for chi2 error-like function and applied to the data analysis. The sequence of the feed forward neural networks with one hidden layer of units is considered. The given neural network represents a particular form-factor parametrization. The so-called evidence (the measure of how much the data favor given statistical model) is computed with the Bayesian framework and it is used to determine the best form factor parametrization.Comment: The revised version is divided into 4 sections. The discussion of the prior assumptions is added. The manuscript contains 4 new figures and 2 new tables (32 pages, 15 figures, 2 tables

Type II Supernovae as a significant source of interstellar dust

Large amounts of dust (>108M) have recently been discovered in high-redshift quasars1, 2 and galaxies3, 4, 5 corresponding to a time when the Universe was less than one-tenth of its present age. The stellar winds produced by stars in the late stages of their evolution (on the asymptotic giant branch of the Hertzsprung–Russell diagram) are thought to be the main source of dust in galaxies, but they cannot produce that dust on a short enough timescale6 (<1 Gyr) to explain the results in the high-redshift galaxies. Supernova explosions of massive stars (type II) are also a potential source, with models predicting 0.2–4M of dust7, 8, 9, 10. As massive stars evolve rapidly, on timescales of a few Myr, these supernovae could be responsible for the high-redshift dust. Observations11, 12, 13 of supernova remnants in the Milky Way, however, have hitherto revealed only 10-7–10-3M each, which is insufficient to explain the high-redshift data. Here we report the detection of 2–4M of cold dust in the youngest known Galactic supernova remnant, Cassiopeia A. This observation implies that supernovae are at least as important as stellar winds in producing dust in our Galaxy and would have been the dominant source of dust at high redshifts