Extracting Spatial Information from Noise Measurements of Multi-Spatial-Mode Quantum States

We show that it is possible to use the spatial quantum correlations present in twin beams to extract information about the shape of a mask in the path of one of the beams. The scheme, based on noise measurements through homodyne detection, is useful in the regime where the number of photons is low enough that direct detection with a photodiode is difficult but high enough that photon counting is not an option. We find that under some conditions the use of quantum states of light leads to an enhancement of the sensitivity in the estimation of the shape of the mask over what can be achieved with a classical state with equivalent properties (mean photon flux and noise properties). In addition, we show that the level of enhancement that is obtained is a result of the quantum correlations and cannot be explained with only classical correlations

Homogenized dynamics of stochastic partial differential equations with dynamical boundary conditions

A microscopic heterogeneous system under random influence is considered. The randomness enters the system at physical boundary of small scale obstacles as well as at the interior of the physical medium. This system is modeled by a stochastic partial differential equation defined on a domain perforated with small holes (obstacles or heterogeneities), together with random dynamical boundary conditions on the boundaries of these small holes. A homogenized macroscopic model for this microscopic heterogeneous stochastic system is derived. This homogenized effective model is a new stochastic partial differential equation defined on a unified domain without small holes, with static boundary condition only. In fact, the random dynamical boundary conditions are homogenized out, but the impact of random forces on the small holes' boundaries is quantified as an extra stochastic term in the homogenized stochastic partial differential equation. Moreover, the validity of the homogenized model is justified by showing that the solutions of the microscopic model converge to those of the effective macroscopic model in probability distribution, as the size of small holes diminishes to zero.Comment: Communications in Mathematical Physics, to appear, 200

Large-scale pharmacogenomic study of sulfonylureas and the QT, JT and QRS intervals: CHARGE Pharmacogenomics Working Group

Sulfonylureas, a commonly used class of medication used to treat type 2 diabetes, have been associated with an increased risk of cardiovascular disease. Their effects on QT interval duration and related electrocardiographic phenotypes are potential mechanisms for this adverse effect. In 11 ethnically diverse cohorts that included 71 857 European, African-American and Hispanic/Latino ancestry individuals with repeated measures of medication use and electrocardiogram (ECG) measurements, we conducted a pharmacogenomic genome-wide association study of sulfonylurea use and three ECG phenotypes: QT, JT and QRS intervals. In ancestry-specific meta-analyses, eight novel pharmacogenomic loci met the threshold for genome-wide significance (P<5 × 10−8), and a pharmacokinetic variant in CYP2C9 (rs1057910) that has been associated with sulfonylurea-related treatment effects and other adverse drug reactions in previous studies was replicated. Additional research is needed to replicate the novel findings and to understand their biological basis

Tree species diversity increases soil microbial carbon use efficiency in a subtropical forest

Plant communities strongly influence soil microbial communities and, in turn, soil carbon (C) cycling. Microbial carbon use efficiency (CUE) is an important parameter for predicting soil C accumulation, yet how plant and soil microbial community traits influence microbial CUE remains poorly understood. Here, we determined how soil microbial CUE is influenced by plant and soil microbial community traits, by studying a natural gradient of plant species diversity in a subtropical forest. Our results showed that microbial CUE increased with increasing tree species diversity, suggesting a correlation between plant community traits and soil C storage. The specific soil properties that explained the greatest variation in microbial CUE were associated with microbial communities (biomass, enzyme activities and the ratio of oligotrophic to copiotrophic taxa); there were weaker correlations with plant-input properties, soil chemistry and soil organic C quality and its mineral protection. Overall, high microbial CUE was associated with soil properties correlated with increased tree species diversity: higher substrate availability (simple SOM chemical structures and weak mineral organic associations) and high microbial growth rates despite increased community dominance by oligotrophic strategists. Our results point to a mechanism by which increased tree species diversity may increase the forest C sink by affecting carbon use with the soil microbial community

Coordinated cadherin functions sculpt respiratory motor circuit connectivity

Breathing, and the motor circuits that control it, are essential for life. At the core of respiratory circuits are Dbx1-derived interneurons, which generate the rhythm and pattern of breathing, and phrenic motor neurons (MNs), which provide the final motor output that drives diaphragm muscle contractions during inspiration. Despite their critical function, the principles that dictate how respiratory circuits assemble are unknown. Here we show that coordinated activity of a type I cadherin (N-cadherin) and type II cadherins (Cadherin-6, -9, and -10) is required in both MNs and Dbx1-derived neurons to generate robust respiratory motor output. Both MN- and Dbx1-specific cadherin inactivation in mice during a critical developmental window results in perinatal lethality due to respiratory failure and a striking reduction in phrenic MN bursting activity. This combinatorial cadherin code is required to establish phrenic MN cell body and dendritic topography; surprisingly, however, cell body position appears to be dispensable for the targeting of phrenic MNs by descending respiratory inputs. Our findings demonstrate that type I and type II cadherins function cooperatively throughout the respiratory circuit to generate a robust breathing output and reveal novel strategies that drive the assembly of motor circuits

Quantitative Treatment of Decoherence

We outline different approaches to define and quantify decoherence. We argue that a measure based on a properly defined norm of deviation of the density matrix is appropriate for quantifying decoherence in quantum registers. For a semiconductor double quantum dot qubit, evaluation of this measure is reviewed. For a general class of decoherence processes, including those occurring in semiconductor qubits, we argue that this measure is additive: It scales linearly with the number of qubits.Comment: Revised version, 26 pages, in LaTeX, 3 EPS figure

Driving non-Gaussian to Gaussian states with linear optics

Published versio

Knowledge-based energy functions for computational studies of proteins

This chapter discusses theoretical framework and methods for developing knowledge-based potential functions essential for protein structure prediction, protein-protein interaction, and protein sequence design. We discuss in some details about the Miyazawa-Jernigan contact statistical potential, distance-dependent statistical potentials, as well as geometric statistical potentials. We also describe a geometric model for developing both linear and non-linear potential functions by optimization. Applications of knowledge-based potential functions in protein-decoy discrimination, in protein-protein interactions, and in protein design are then described. Several issues of knowledge-based potential functions are finally discussed.Comment: 57 pages, 6 figures. To be published in a book by Springe