Superconducting transport through a vibrating molecule

Nonequilibrium electronic transport through a molecular level weakly coupled to a single coherent phonon/vibration mode has been studied for superconducting leads. The Keldysh Green function formalism is used to compute the current for the entire bias voltage range. In the subgap regime, Multiple Andreev Reflection (MAR) processes accompanied by phonon emission cause rich structure near the onset of MAR channels, including an even-odd parity effect that can be interpreted in terms of an inelastic MAR ladder picture. Thereby we establish a connection between the Keldysh formalism and the Landauer scattering approach for inelastic MAR.Comment: 5 pages, 5 figures, version contains now more details, accepted by PR

Intrinsic limitations of inverse inference in the pairwise Ising spin glass

We analyze the limits inherent to the inverse reconstruction of a pairwise Ising spin glass based on susceptibility propagation. We establish the conditions under which the susceptibility propagation algorithm is able to reconstruct the characteristics of the network given first- and second-order local observables, evaluate eventual errors due to various types of noise in the originally observed data, and discuss the scaling of the problem with the number of degrees of freedom

Buchberger-Zacharias Theory of multivariate Ore extensions

Following the recent survey on Buchberger-Zacharias Theory for monoid rings R[S] over a unitary effective ring R and an effective monoid S, we propose here a presentation of Buchberger Zacharias Theory and related Grobner basis computation algorithms for multivariate Ore extensions of rings presented as modules over a principal ideal domain, using Moller-Pritchard lifting theorem

Improving Performance of Iterative Methods by Lossy Checkponting

Iterative methods are commonly used approaches to solve large, sparse linear systems, which are fundamental operations for many modern scientific simulations. When the large-scale iterative methods are running with a large number of ranks in parallel, they have to checkpoint the dynamic variables periodically in case of unavoidable fail-stop errors, requiring fast I/O systems and large storage space. To this end, significantly reducing the checkpointing overhead is critical to improving the overall performance of iterative methods. Our contribution is fourfold. (1) We propose a novel lossy checkpointing scheme that can significantly improve the checkpointing performance of iterative methods by leveraging lossy compressors. (2) We formulate a lossy checkpointing performance model and derive theoretically an upper bound for the extra number of iterations caused by the distortion of data in lossy checkpoints, in order to guarantee the performance improvement under the lossy checkpointing scheme. (3) We analyze the impact of lossy checkpointing (i.e., extra number of iterations caused by lossy checkpointing files) for multiple types of iterative methods. (4)We evaluate the lossy checkpointing scheme with optimal checkpointing intervals on a high-performance computing environment with 2,048 cores, using a well-known scientific computation package PETSc and a state-of-the-art checkpoint/restart toolkit. Experiments show that our optimized lossy checkpointing scheme can significantly reduce the fault tolerance overhead for iterative methods by 23%~70% compared with traditional checkpointing and 20%~58% compared with lossless-compressed checkpointing, in the presence of system failures.Comment: 14 pages, 10 figures, HPDC'1

Statistical distributions in the folding of elastic structures

The behaviour of elastic structures undergoing large deformations is the result of the competition between confining conditions, self-avoidance and elasticity. This combination of multiple phenomena creates a geometrical frustration that leads to complex fold patterns. By studying the case of a rod confined isotropically into a disk, we show that the emergence of the complexity is associated with a well defined underlying statistical measure that determines the energy distribution of sub-elements,``branches'', of the rod. This result suggests that branches act as the ``microscopic'' degrees of freedom laying the foundations for a statistical mechanical theory of this athermal and amorphous system

Stellar Populations and Star Cluster Formation in Interacting Galaxies with the Advanced Camera for Surveys

Pixel-by-pixel colour-magnitude and colour-colour diagrams - based on a subset of the Hubble Space Telescope Advanced Camera for Surveys Early Release Observations - provide a powerful technique to explore and deduce the star and star cluster formation histories of the Mice and the Tadpole interacting galaxies. In each interacting system we find some 40 bright young star clusters (20 <= F606W (mag) <= 25, with a characteristic mass of ~3 x 10^6 Msun), which are spatially coincident with blue regions of active star formation in their tidal tails and spiral arms. We estimate that the main events triggering the formation of these clusters occurred ~(1.5-2.0) x 10^8 yr ago. We show that star cluster formation is a major mode of star formation in galaxy interactions, with >= 35% of the active star formation in encounters occurring in star clusters. This is the first time that young star clusters have been detected along the tidal tails in interacting galaxies. The tidal tail of the Tadpole system is dominated by blue star forming regions, which occupy some 60% of the total area covered by the tail and contribute ~70% of the total flux in the F475W filter (decreasing to ~40% in F814W). The remaining pixels in the tail have colours consistent with those of the main disk. The tidally triggered burst of star formation in the Mice is of similar strength in both interacting galaxies, but it has affected only relatively small, spatially coherent areas.Comment: 23 pages in preprint form, 6 (encapsulated) postscript figures; accepted for publication in New Astronomy; ALL figures (even the grey-scale ones) need to be printed on a colour printer style files included; for full-resolution paper, see http://www.ast.cam.ac.uk/STELLARPOPS/ACSpaper

Clustering of solutions in the random satisfiability problem

Using elementary rigorous methods we prove the existence of a clustered phase in the random $K$-SAT problem, for $K\geq 8$. In this phase the solutions are grouped into clusters which are far away from each other. The results are in agreement with previous predictions of the cavity method and give a rigorous confirmation to one of its main building blocks. It can be generalized to other systems of both physical and computational interest.Comment: 4 pages, 1 figur

Measuring the sequence-affinity landscape of antibodies with massively parallel titration curves

Despite the central role that antibodies play in the adaptive immune system and in biotechnology, much remains unknown about the quantitative relationship between an antibody's amino acid sequence and its antigen binding affinity. Here we describe a new experimental approach, called Tite-Seq, that is capable of measuring binding titration curves and corresponding affinities for thousands of variant antibodies in parallel. The measurement of titration curves eliminates the confounding effects of antibody expression and stability that arise in standard deep mutational scanning assays. We demonstrate Tite-Seq on the CDR1H and CDR3H regions of a well-studied scFv antibody. Our data shed light on the structural basis for antigen binding affinity and suggests a role for secondary CDR loops in establishing antibody stability. Tite-Seq fills a large gap in the ability to measure critical aspects of the adaptive immune system, and can be readily used for studying sequence-affinity landscapes in other protein systems

On the criticality of inferred models

Advanced inference techniques allow one to reconstruct the pattern of interaction from high dimensional data sets. We focus here on the statistical properties of inferred models and argue that inference procedures are likely to yield models which are close to a phase transition. On one side, we show that the reparameterization invariant metrics in the space of probability distributions of these models (the Fisher Information) is directly related to the model's susceptibility. As a result, distinguishable models tend to accumulate close to critical points, where the susceptibility diverges in infinite systems. On the other, this region is the one where the estimate of inferred parameters is most stable. In order to illustrate these points, we discuss inference of interacting point processes with application to financial data and show that sensible choices of observation time-scales naturally yield models which are close to criticality.Comment: 6 pages, 2 figures, version to appear in JSTA