Measuring autonomy and emergence via Granger causality

Concepts of emergence and autonomy are central to artificial life and related cognitive and behavioral sciences. However, quantitative and easy-to-apply measures of these phenomena are mostly lacking. Here, I describe quantitative and practicable measures for both autonomy and emergence, based on the framework of multivariate autoregression and specifically Granger causality. G-autonomy measures the extent to which the knowing the past of a variable helps predict its future, as compared to predictions based on past states of external (environmental) variables. G-emergence measures the extent to which a process is both dependent upon and autonomous from its underlying causal factors. These measures are validated by application to agent-based models of predation (for autonomy) and flocking (for emergence). In the former, evolutionary adaptation enhances autonomy; the latter model illustrates not only emergence but also downward causation. I end with a discussion of relations among autonomy, emergence, and consciousness

Ultralong-range polyatomic Rydberg molecules formed by a polar perturber

The internal electric field of a Rydberg atom electron can bind a polar molecule to form a giant ultralong-range stable polyatomic molecule. Such molecules not only share their properties with Rydberg atoms, they possess huge permanent electric dipole moments and in addition allow for coherent control of the polar molecule orientation. In this work, we include additional Rydberg manifolds which couple to the nearly degenerate set of Rydberg states employed in [S. T. Rittenhouse and H. R. Sadeghpour, Phys. Rev. Lett. 104, 243002 (2010)]. The coupling of a set of $(n+3)s$ Rydberg states with the $n(l>2)$ nearly degenerate Rydberg manifolds in alkali metal atoms leads to pronounced avoided crossings in the Born-Oppenheimer potentials. Ultimately, these avoided crossings enable the formation of the giant polyatomic Rydberg molecules with standard two-photon laser photoassociation techniques.Comment: 7 pages, 4 figure

Drell-Yan, ZZ, W+W- production in SM & ADD model to NLO+PS accuracy at the LHC

In this paper, we present the next-to-leading order QCD corrections for di-lepton, di-electroweak boson (ZZ, W+W-) production in both the SM and the ADD model, matched to the HERWIG parton-shower using the aMC@NLO framework. A selection of results at the 8 TeV LHC, which exhibits deviation from the SM as a result of the large extra-dimension scenario are presented.Comment: 12 pages, 10 figures, search sensitivity for the 14 TeV LHC discussed, version to appear in Eur. Phys. J.

Causal connectivity of evolved neural networks during behavior

To show how causal interactions in neural dynamics are modulated by behavior, it is valuable to analyze these interactions without perturbing or lesioning the neural mechanism. This paper proposes a method, based on a graph-theoretic extension of vector autoregressive modeling and 'Granger causality,' for characterizing causal interactions generated within intact neural mechanisms. This method, called 'causal connectivity analysis' is illustrated via model neural networks optimized for controlling target fixation in a simulated head-eye system, in which the structure of the environment can be experimentally varied. Causal connectivity analysis of this model yields novel insights into neural mechanisms underlying sensorimotor coordination. In contrast to networks supporting comparatively simple behavior, networks supporting rich adaptive behavior show a higher density of causal interactions, as well as a stronger causal flow from sensory inputs to motor outputs. They also show different arrangements of 'causal sources' and 'causal sinks': nodes that differentially affect, or are affected by, the remainder of the network. Finally, analysis of causal connectivity can predict the functional consequences of network lesions. These results suggest that causal connectivity analysis may have useful applications in the analysis of neural dynamics

Surface Phonons and Other Localized Excitations

The diatomic linear chain of masses coupled by harmonic springs is a textboook model for vibrational normal modes (phonons) in crystals. In addition to propagating acoustic and optic branches, this model is known to support a ``gap mode'' localized at the surface, provided the atom at the surface has light rather than heavy mass. An elementary argument is given which explains this mode and provides values for the frequency and localization length. By reinterpreting this mode in different ways, we obtain the frequency and localization lengths for three other interesting modes: (1) the surface vibrational mode of a light mass impurity at the surface of a monatomic chain; (2) the localized vibrational mode of a stacking fault in a diatomic chain; and (3) the localized vibrational mode of a light mass impurity in a monatomic chain.Comment: 5 pages with 4 embedded postscript figures. This paper will appear in the American Journal of Physic

New directions in EEG measurement: an investigation into the fidelity of electrical potential sensor signals

Low frequency noise performance is the key indicator in determining the signal to noise ratio of a capacitively coupled sensor when used to acquire electroencephalogram signals. For this reason, a prototype Electric Potential Sensor device based on an auto-zero operational amplifier has been developed and evaluated. The absence of 1/f noise in these devices makes them ideal for use with signal frequencies ~10 Hz or less. The active electrodes are designed to be physically and electrically robust and chemically and biochemically inert. They are electrically insulated (anodized) and have diameters of 12 mm or 18 mm. In both cases, the sensors are housed in inert stainless steel machined housings with the electronics fabricated in surface mount components on a printed circuit board compatible with epoxy potting compounds. Potted sensors are designed to be immersed in alcohol for sterilization purposes. A comparative study was conducted with a commercial wet gel electrode system. These studies comprised measurements of both free running electroencephalogram and Event Related Potentials. Quality of the recorded electroencephalogram was assessed using three methods of inspection of raw signal, comparing signal to noise ratios, and Event Related Potentials noise analysis. A strictly comparable signal to noise ratio was observed and the overall conclusion from these comparative studies is that the noise performance of the new sensor is appropriate

Discovering hidden sectors with mono-photon Z' searches

In many theories of physics beyond the Standard Model, from extra dimensions to Hidden Valleys and models of dark matter, Z' bosons mediate between Standard Model particles and hidden sector states. We study the feasibility of observing such hidden states through an invisibly decaying Z' at the LHC. We focus on the process pp -> \gamma Z' -> \gamma X X*, where X is any neutral, (quasi-) stable particle, whether a Standard Model (SM) neutrino or a new state. This complements a previous study using pp -> Z Z' -> l+ l- X X*. Only the Z' mass and two effective charges are needed to describe this process. If the Z' decays invisibly only to Standard Model neutrinos, then these charges are predicted by observation of the Z' through the Drell-Yan process, allowing discrimination between Z' decays to SM neutrinos and invisible decays to new states. We carefully discuss all backgrounds and systematic errors that affect this search. We find that hidden sector decays of a 1 TeV Z' can be observed at 5 sigma significance with 50 fb^{-1} at the LHC. Observation of a 1.5 TeV state requires super-LHC statistics of 1 ab^{-1}. Control of the systematic errors, in particular the parton distribution function uncertainty of the dominant Z \gamma background, is crucial to maximize the LHC searchComment: 13 pages, 4 figure

Finite strain in Elastic problems. II

This article does not have an abstract

Catalytic hollow fiber membranes prepared using layer-by-layer adsorption of polyelectrolytes and metal nanoparticles

Immobilization of metalnanoparticles in hollowfibermembranes via alternating adsorption of polyelectrolytes and negatively charged Au nanoparticles yields catalytic reactors with high surface areas. SEM images show that this technique deposits a high density of unaggregated metalnanoparticles both on the surfaces and in the pores of the hollowfibers. Catalytic reduction of 4-nitrophenol with NaBH4, which can be easily monitored by UV–vis spectrophotometry, demonstrates that the nanoparticles in the hollowfibermembrane are highly catalytically active. In a single pass through the membrane, >99% of the 4-nitrophenol is reduced to 4-aminophenol, but this conversion decreases over time. The conversion decline may stem from catalyst fouling caused by by-products of 4-aminophenol oxidation