Separating intrinsic alignment and galaxy-galaxy lensing

The coherent physical alignment of galaxies is an important systematic for gravitational lensing studies as well as a probe of the physical mechanisms involved in galaxy formation and evolution. We develop a formalism for treating this intrinsic alignment (IA) in the context of galaxy-galaxy lensing and present an improved method for measuring IA contamination, which can arise when sources physically associated with the lens are placed behind the lens due to photometric redshift scatter. We apply the technique to recent Sloan Digital Sky Survey (SDSS) measurements of Luminous Red Galaxy lenses and typical (L*) source galaxies with photometric redshifts selected from the SDSS imaging data. Compared to previous measurements, this method has the advantage of being fully self-consistent in its treatment of the IA and lensing signals, solving for the two simultaneously. We find an IA signal consistent with zero, placing tight constraints on both the magnitude of the IA effect and its potential contamination to the lensing signal. While these constraints depend on source selection and redshift quality, the method can be applied to any measurement that uses photometric redshifts. We obtain a model-independent upper-limit of roughly 10% IA contamination for projected separations of approximately 0.1-100 Mpc/h. With more stringent photo-z cuts and reasonable assumptions about the physics of intrinsic alignments, this upper limit is reduced to 1-2%. These limits are well below the statistical error of the current lensing measurements. Our results suggest that IA will not present intractable challenges to the next generation of galaxy-galaxy lensing experiments, and the methods presented here should continue to aid in our understanding of alignment processes and in the removal of IA from the lensing signal.Comment: 31 pages, 8 Figures. Minor changes to reflect published versio

Alternative Kullback-Leibler information entropy for enantiomers

In our series of studies on quantifying chirality, a new chirality measure is proposed in this work based on the Kullback-Leibler information entropy. The index computes the extra information that the shape function of one enantiomer carries over a normalized shape function of the racemate, while in our previous studies the shape functions of the R and S enantiomers were used considering one as reference for the other. Besides being mathematically more elegant (symmetric, positive definite, zero in the case of a nonchiral system), this new index bears a more direct relation with chirality oriented experimental measurements such as circular dichroism (CD) and optical rotation measurements, where the racemate is frequently used as a reference, The five chiral halomethanes holding one asymmetric carbon atom and H, F, Cl, Br, and I as substituents have been analyzed. A comparison with our calculated optical rotation and with Avnir's Continuous Chirality Measure (CCM) is computed. The results show that with this index the emphasis lies on the differences between the noncoinciding substituents

ConSole: using modularity of contact maps to locate solenoid domains in protein structures.

BackgroundPeriodic proteins, characterized by the presence of multiple repeats of short motifs, form an interesting and seldom-studied group. Due to often extreme divergence in sequence, detection and analysis of such motifs is performed more reliably on the structural level. Yet, few algorithms have been developed for the detection and analysis of structures of periodic proteins.ResultsConSole recognizes modularity in protein contact maps, allowing for precise identification of repeats in solenoid protein structures, an important subgroup of periodic proteins. Tests on benchmarks show that ConSole has higher recognition accuracy as compared to Raphael, the only other publicly available solenoid structure detection tool. As a next step of ConSole analysis, we show how detection of solenoid repeats in structures can be used to improve sequence recognition of these motifs and to detect subtle irregularities of repeat lengths in three solenoid protein families.ConclusionsThe ConSole algorithm provides a fast and accurate tool to recognize solenoid protein structures as a whole and to identify individual solenoid repeat units from a structure. ConSole is available as a web-based, interactive server and is available for download at http://console.sanfordburnham.org