Correlation of optical conductivity and ARPES spectra of strong-coupling large polarons and its display in cuprates

Common approach is used to calculate band due to strong-coupling large polaron (SCLP) photodissociation in ARPES and in optical conductivity (OC) spectra. It is based on using the coherent-states representation for the phonon field in SCLP. The calculated positions of both band maximums are universal functions of one parameter - the SCLP binding energy Ep: ARPES band maximum lies at binding energy about 3.2Ep; the OC band maximum is at the photon energy about 4.2Ep. The half-widths of the bands are mainly determined by Ep and slightly depend on Frohlich electron-phonon coupling constant: for its value 6-8 the ARPES band half-width is 1.7-1.3Ep and the OC band half-width is 2.8-2.2Ep. Using these results one can predict approximate position of ARPES band maximum and half-width from the maximum of mid-IR OC band and vice versa. Comparison of the results with experiments leads to a conclusion that underdoped cuprates contain SCLPs with Ep=0.1-0.2 eV that is in good conformity with the medium parameters in cuprates. The values of the polaron binding energy determined from experimental ARPES and OC spectra of the same material are in good conformity too: the difference between them is within 10 percent.Comment: 17 pages, 6 figure

FlyEx, the quantitative atlas on segmentation gene expression at cellular resolution

The datasets on gene expression are the valuable source of information about the functional state of an organism. Recently, we have acquired the large dataset on expression of segmentation genes in the Drosophila blastoderm. To provide efficient access to the data, we have developed the FlyEx database (http://urchin.spbcas.ru/flyex). FlyEx contains 4716 images of 14 segmentation gene expression patterns obtained from 1579 embryos and 9 500 000 quantitative data records. Reference data are available for all segmentation genes in cycles 11–13 and all temporal classes of cycle 14A. FlyEx supports operations on images of gene expression patterns. The database can be used to examine the quality of data, analyze the dynamics of formation of segmentation gene expression domains, as well as to estimate the variability of gene expression patterns. Currently, a user is able to monitor and analyze the dynamics of formation of segmentation gene expression domains over the whole period of segment determination, that amounts to 1.5 h of development. FlyEx supports the data downloads and construction of personal reference datasets, that makes it possible to more effectively use and analyze data