Fermion exchange in ring polymer self-consistent field theory

A mapping is made between fermion exchange and excluded volume in the quantum-classical isomorphism using polymer self-consistent field theory. Apart from exchange, quantum particles are known to be exactly representable in classical statistical mechanics as ring polymers, with contours that are parametrized by the inverse thermal energy, often called the imaginary time. Evidence in support of a previously used approximation for fermion exchange in ring polymer self-consistent field theory is given, specifically, that the use of all-contour interactions in the mean field picture instead of equal imaginary time interactions is justified based on the symmetry of ring polymers. It is also shown that the removal of forbidden thermal trajectories, both those that violate excluded volume directly and those that represent topologically inaccessible microstates, is equivalent to antisymmetric exchange. The electron density of the beryllium atom is calculated with ring polymer self-consistent field theory ignoring classical correlations, and very good agreement is found with Hartree-Fock theory which also neglects Coulomb correlations. The total binding energies agree to within less than 6%, which while still far from chemical accuracy, is remarkable given that the field theory equations are derived from first principles with zero free parameters. The discrepancy between self-consistent field theory and Hartree-Fock theory is attributed to classical Coulomb self-interactions which are included in Hartree-Fock theory but not in self-consistent field theory. A potential method to improve the agreement by more accurately representing electron-electron self-interactions in self-consistent field theory is discussed, as are the implications for quantum foundations of the quantum-classical mapping between fermion exchange and thermal trajectory excluded volume.Comment: 17 pages, 2 figure

Intrinsic and extrinsic factors drive ontogeny of early-life at-sea behaviour in a marine top predator

Young animals must learn to forage effectively to survive the transition from parental provisioning to independent feeding. Rapid development of successful foraging strategies is particularly important for capital breeders that do not receive parental guidance after weaning. The intrinsic and extrinsic drivers of variation in ontogeny of foraging are poorly understood for many species. Grey seals (Halichoerus grypus) are typical capital breeders; pups are abandoned on the natal site after a brief suckling phase, and must develop foraging skills without external input. We collected location and dive data from recently-weaned grey seal pups from two regions of the United Kingdom (the North Sea and the Celtic and Irish Seas) using animal-borne telemetry devices during their first months of independence at sea. Dive duration, depth, bottom time, and benthic diving increased over the first 40 days. The shape and magnitude of changes differed between regions. Females consistently had longer bottom times, and in the Celtic and Irish Seas they used shallower water than males. Regional sex differences suggest that extrinsic factors, such as water depth, contribute to behavioural sexual segregation. We recommend that conservation strategies consider movements of young naïve animals in addition to those of adults to account for developmental behavioural changes

Does Infall End Before the Class I Stage?

We have observed HCO+ J=3-2 toward 16 Class I sources and 18 Class 0 sources, many of which were selected from Mardones et al. (1997). Eight sources have profiles significantly skewed to the blue relative to optically thin lines. We suggest six sources as new infall candidates. We find an equal "blue excess" among Class 0 and Class I sources after combining this sample with that of Gregersen et al. (1997). We used a Monte Carlo code to simulate the temporal evolution of line profiles of optically thick lines of HCO+, CS and H2CO in a collapsing cloud and found that HCO+ had the strongest asymmetry at late times. If a blue-peaked line profile implies infall, then the dividing line between the two classes does not trace the end of the infall stage.Comment: 21 pages, 8 figures, accepted by ApJ for April 20, 2000, added acknowledgmen

Inner Structure of Protostellar Collapse Candidate B335 Derived from Millimeter-Wave Interferometry

We present a study of the density structure of the protostellar collapse candidate B335 using continuum observations from the IRAM Plateau de Bure Interferometer made at wavelengths of 1.2mm and 3.0mm. We analyze these data, which probe spatial scales from 5000 AU to 500 AU, directly in the visibility domain by comparison to synthetic observations constructed from models that assume different physical conditions. This approach allows for much more stringent constraints to be derived from the data than from analysis of images. A single radial power law in density provides a good description of the data, with best fit power law index p=1.65+/-0.05. Through simulations, we quantify the sensitivity of this result to various model uncertainties, including assumptions of temperature distribution, outer boundary, dust opacity spectral index, and an unresolved central component. The largest uncertainty comes from the unknown presence of a centralized point source. A point source with 1.2mm flux of F=12+/-7 mJy reduces the density index to p=1.47+/-0.07. The remaining sources of systematic uncertainty, the most important of which is the temperature distribution, likely contribute a total uncertainty of < 0.2. We therefore find strong evidence that the power law index of the density distribution within 5000 AU is significantly less than the value at larger radii, close to 2.0 from previous studies of dust emission and extinction. These results conform well to the generic paradigm of isolated, low-mass star formation which predicts a power law density index close to p=1.5 for an inner region of gravitational free fall onto the protostar.Comment: Accepted to the Astrophysical Journal; 27 pages, 3 figure

A Mentoring Guide for Female Faculty in Engineering

One widely accepted method for increasing the chances of success of female engineering and science students and faculty alike is to provide access to female role models and mentors. In this article we offer to new female faculty, and to those who would mentor them, an annotated list of text and electronic resources that address most of the most important challenges facing new female faculty in science and engineering

Talking About Looking: Three Approaches to Interviewing Carers of People With Rheumatoid Arthritis About Information Seeking

© 2016 The Author(s). Given the profusion of illness-related information, in this article, we consider how talking about information seeking - and in particular Internet use - is difficult, not because it is necessarily a highly sensitive topic (though it may be), but rather due to the unusual and unfamiliar situation of talking about information seeking. Drawing on interviews conducted as part of a study on the educational needs of carers of people with rheumatoid arthritis, we compare three types of interview for understanding online information seeking: interviews (recall), researcher-led observation (joining participant at the computer), and diaries. We discuss the strengths and weaknesses of each approach and discuss how changing interview questions and the form of interaction can help to produce different types of data, and potentially more meaningful insights. Of the three approaches, conducting interviews with participants while looking at a computer (talking while looking) offered the best opportunities to understand Internet-based information seeking

Developmental constraints enforce altruism and avert the tragedy of the commons in a social microbe

Organisms often cooperate through the production of freely available public goods. This can greatly benefit the group but is vulnerable to the “tragedy of the commons” if individuals lack the motivation to make the necessary investment into public goods production. Relatedness to groupmates can motivate individual investment because group success ultimately benefits their genes’ own self-interests. However, systems often lack mechanisms that can reliably ensure that relatedness is high enough to promote cooperation. Consequently, groups face a persistent threat from the tragedy unless they have a mechanism to enforce investment when relatedness fails to provide adequate motivation. To understand the real threat posed by the tragedy and whether groups can avert its impact, we determine how the social amoeba Dictyostelium discoideum responds as relatedness decreases to levels that should induce the tragedy. We find that, while investment in public goods declines as overall within-group relatedness declines, groups avert the expected catastrophic collapse of the commons by continuing to invest, even when relatedness should be too low to incentivize any contribution. We show that this is due to a developmental buffering system that generates enforcement because insufficient cooperation perturbs the balance of a negative feedback system controlling multicellular development. This developmental constraint enforces investment under the conditions expected to be most tragic, allowing groups to avert a collapse in cooperation. These results help explain how mechanisms that suppress selfishness and enforce cooperation can arise inadvertently as a by-product of constraints imposed by selection on different traits

Recognizing Structural Nonidentifiability: When Experiments Do Not Provide Information About Important Parameters and Misleading Models Can Still Have Great Fit

This is the peer reviewed version of the following article: Schmidt, P. J., Emelko, M. B., & Thompson, M. E. (2020). Recognizing Structural Nonidentifiability: When Experiments Do Not Provide Information About Important Parameters and Misleading Models Can Still Have Great Fit. Risk Analysis, 40(2), 352–369, which has been published in final form at https://doi.org/10.1111/risa.13386. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions.In the quest to model various phenomena, the foundational importance of parameter identifiability to sound statistical modeling may be less well appreciated than goodness of fit. Identifiability concerns the quality of objective information in data to facilitate estimation of a parameter, while nonidentifiability means there are parameters in a model about which the data provide little or no information. In purely empirical models where parsimonious good fit is the chief concern, nonidentifiability (or parameter redundancy) implies overparameterization of the model. In contrast, nonidentifiability implies underinformativeness of available data in mechanistically derived models where parameters are interpreted as having strong practical meaning. This study explores illustrative examples of structural nonidentifiability and its implications using mechanistically derived models (for repeated presence/absence analyses and dose–response of Escherichia coli O157:H7 and norovirus) drawn from quantitative microbial risk assessment. Following algebraic proof of nonidentifiability in these examples, profile likelihood analysis and Bayesian Markov Chain Monte Carlo with uniform priors are illustrated as tools to help detect model parameters that are not strongly identifiable. It is shown that identifiability should be considered during experimental design and ethics approval to ensure generated data can yield strong objective information about all mechanistic parameters of interest. When Bayesian methods are applied to a nonidentifiable model, the subjective prior effectively fabricates information about any parameters about which the data carry no objective information. Finally, structural nonidentifiability can lead to spurious models that fit data well but can yield severely flawed inferences and predictions when they are interpreted or used inappropriately.Natural Sciences and Engineering Research Council of Canada (NSERC), RGPIN-2016-04655 || Alberta Innovates, Grant 3360-E086

The Role of Galactic Winds on Molecular Gas Emission from Galaxy Mergers

We assess the impact of starburst and AGN feedback-driven winds on the CO emission from galaxy mergers, and, in particular, search for signatures of these winds in the simulated CO morphologies and emission line profiles. We do so by combining a 3D non-LTE molecular line radiative transfer code with smoothed particle hydrodynamics (SPH) simulations of galaxy mergers that include prescriptions for star formation, black hole growth, a multiphase interstellar medium (ISM), and the winds associated with star formation and black hole growth. Our main results are: (1) Galactic winds can drive outflows of masses ~10^8-10^9 Msun which may be imaged via CO emission line mapping. (2) AGN feedback-driven winds are able to drive imageable CO outflows for longer periods of time than starburst-driven winds owing to the greater amount of energy imparted to the ISM by AGN feedback compared to star formation. (3) Galactic winds can control the spatial extent of the CO emission in post-merger galaxies, and may serve as a physical motivation for the sub-kiloparsec scale CO emission radii observed in local advanced mergers. (4) Secondary emission peaks at velocities greater than the circular velocity are seen in the CO emission lines in all models. In models with winds, these high velocity peaks are seen to preferentially correspond to outflowing gas entrained in winds, which is not the case in the model without winds. The high velocity peaks seen in models without winds are typically confined to velocity offsets (from the systemic) < 1.7 times the circular velocity, whereas the models with AGN feedback-driven winds can drive high velocity peaks to ~2.5 times the circular velocity.Comment: Accepted by ApJ; Minor revisions; Resolution tests include

The specificity of pathogenic oxidative stress in schizophrenia

Abstract not available