An improved Monte Carlo method for direct calculation of the density of states

We present an efficient Monte Carlo algorithm for determining the density of states which is based on the statistics of transition probabilities between states. By measuring the infinite temperature transition probabilities--that is, the probabilities associated with move proposal only--we are able to extract excellent estimates of the density of states. When this estimator is used in conjunction with a Wang-Landau sampling scheme [F. Wang and D. P. Landau, Phys. Rev. Lett. 86, 2050 (2001)], we quickly achieve uniform sampling of macrostates (e.g., energies) and systematically refine the calculated density of states. This approach requires only potential energy evaluations, continues to improve the statistical quality of its results as the simulation time is extended, and is applicable to both lattice and continuum systems. We test the algorithm on the Lennard-Jones liquid and demonstrate good statistical convergence properties.Comment: 7 pages, 4 figures. to appear in Journal of Chemical Physic

Development of Multiple Polymorphic Microsatellite Markers for Ceratina calcarata (Hymenoptera: Apidae) Using Genome-Wide Analysis

The small carpenter bee, Ceratina calcarata (Robertson), is a widespread native pollinator across eastern North America. The behavioral ecology and nesting biology of C. calcarata has been relatively well-studied and the species is emerging as a model organism for both native pollinator and social evolution research. C. calcarata is subsocial: reproductively mature females provide extended maternal care to their brood. As such, studies of C. calcarata may also reveal patterns of relatedness and demography unique to primitively social Hymenoptera. Here, we present 21 microsatellite loci, isolated from the recently completed C. calcarata genome. Screening in 39 individuals across their distribution revealed that no loci were in linkage disequilibrium, nor did any deviate significantly from Hardy-Weinberg following sequential Bonferroni correction. Allele count ranged from 2 to 14, and observed and expected heterozygosities ranged from 0.08 to 0.82 (mean 0.47) and 0.26 to 0.88 (mean 0.56), respectively. These markers will enable studies of population-wide genetic structuring across C. calcarata’s distribution. Such tools will also allow for exploration of between and within-colony relatedness in this subsocial native pollinator

Reality as a simulation of reality: robot illusions, fundamental limits, and a physical demonstration

We consider problems in which robots conspire to present a view of the world that differs from reality. The inquiry is motivated by the problem of validating robot behavior physically despite there being a discrepancy between the robots we have at hand and those we wish to study, or the environment for testing that is available versus that which is desired, or other potential mismatches in this vein. After formulating the concept of a convincing illusion, essentially a notion of system simulation that takes place in the real world, we examine the implications of this type of simulability in terms of infrastructure requirements. Time is one important resource: some robots may be able to simulate some others but, perhaps, only at a rate that is slower than real-time. This difference gives a way of relating the simulating and the simulated systems in a form that is relative. We establish some theorems, including one with the flavor of an impossibility result, and providing several examples throughout. Finally, we present data from a simple multi-robot experiment based on this theory, with a robot navigating amid an unbounded field of obstacles

Predicting Peptide Structures in Native Proteins from Physical Simulations of Fragments

It has long been proposed that much of the information encoding how a protein folds is contained locally in the peptide chain. Here we present a large-scale simulation study designed to examine the extent to which conformations of peptide fragments in water predict native conformations in proteins. We perform replica exchange molecular dynamics (REMD) simulations of 872 8-mer, 12-mer, and 16-mer peptide fragments from 13 proteins using the AMBER 96 force field and the OBC implicit solvent model. To analyze the simulations, we compute various contact-based metrics, such as contact probability, and then apply Bayesian classifier methods to infer which metastable contacts are likely to be native vs. non-native. We find that a simple measure, the observed contact probability, is largely more predictive of a peptide's native structure in the protein than combinations of metrics or multi-body components. Our best classification model is a logistic regression model that can achieve up to 63% correct classifications for 8-mers, 71% for 12-mers, and 76% for 16-mers. We validate these results on fragments of a protein outside our training set. We conclude that local structure provides information to solve some but not all of the conformational search problem. These results help improve our understanding of folding mechanisms, and have implications for improving physics-based conformational sampling and structure prediction using all-atom molecular simulations

Saddles in the energy landscape: extensivity and thermodynamic formalism

We formally extend the energy landscape approach for the thermodynamics of liquids to account for saddle points. By considering the extensive nature of macroscopic potential energies, we derive the scaling behavior of saddles with system size, as well as several approximations for the properties of low-order saddles (i.e., those with only a few unstable directions). We then cast the canonical partition function in a saddle-explicit form and develop, for the first time, a rigorous energy landscape approach capable of reproducing trends observed in simulations, in particular the temperature dependence of the energy and fractional order of sampled saddles.Comment: 4 pages, 1 figur