A Possible Nanometer-scale Computing Device Based on an Adding Cellular Automaton

We present a simple one-dimensional Cellular Automaton (CA) which has the property that an initial state composed of two binary numbers evolves quickly into a final state which is their sum. We call this CA the Adding Cellular Automaton (ACA). The ACA requires only 2N two-state cells in order to add any two N-1 bit binary numbers. The ACA could be directly realized as a wireless nanometer-scale computing device - a possible implementation using coupled quantum dots is outlined.Comment: 8 pages, RevTex, 3 Postscript figures. This version to appear in App. Phys. Let

Evolutionary quantum game

We present the first study of a dynamical quantum game. Each agent has a `memory' of her performance over the previous m timesteps, and her strategy can evolve in time. The game exhibits distinct regimes of optimality. For small m the classical game performs better, while for intermediate m the relative performance depends on whether the source of qubits is `corrupt'. For large m, the quantum players dramatically outperform the classical players by `freezing' the game into high-performing attractors in which evolution ceases.Comment: 4 pages in two-column format. 4 figure

Exact dynamical response of an N-electron quantum dot subject to a time-dependent potential

We calculate analytically the exact dynamical response of a droplet of N interacting electrons in a quantum dot with an arbitrarily time-dependent parabolic confinement potential \omega(t) and a perpendicular magnetic field. We find that, for certain frequency ranges, a sinusoidal perturbation acts like an attractive effective interaction between electrons. In the absence of a time-averaged confinement potential, the N electrons can bind together to form a stable, free-standing droplet.Comment: 10 pages, RevTex, 3 Postscript figures. This version to appear as a Rapid Communication in PR

Cellular automata models of traffic flow along a highway containing a junction

We examine various realistic generalizations of the basic cellular automaton model describing traffic flow along a highway. In particular, we introduce a {\em slow-to-start} rule which simulates a possible delay before a car pulls away from being stationary. Having discussed the case of a bare highway, we then consider the presence of a junction. We study the effects of acceleration, disorderness, and slow-to-start behavior on the queue length at the entrance to the highway. Interestingly, the junction's efficiency is {\it improved} by introducing disorderness along the highway, and by imposing a speed limit.Comment: to appear in J. Phys. A:Math.& General. 15 pages, RevTeX, 3 Postscript figure

MEDUSA: A Low-Cost, 16-Channel Neuromodulation Platform with Arbitrary Waveform Generation

Neural stimulation systems are used to modulate electrically excitable tissue to interrogate neural circuit function or provide therapeutic benefit. Conventional stimulation systems are expensive and limited in functionality to standard stimulation waveforms, and they are bad for high frequency stimulation. We present MEDUSA, a system that enables new research applications that can leverage multi-channel, arbitrary stimulation waveforms. MEDUSA is low cost and uses commercially available components for widespread adoption. MEDUSA is comprised of a PC interface, an FPGA for precise timing control, and eight bipolar current sources that can each address up to 16 electrodes. The current sources have a resolution of 15.3 nA and can provide ±5 mA with ±5 V compliance. We demonstrate charge-balancing techniques in vitro using a custom microelectrode. An in vivo strength-duration curve for earthworm nerve activation is also constructed using MEDUSA. MEDUSA is a multi-functional neuroscience research tool for electroplating microelectrodes, performing electrical impedance spectroscopy, and examining novel neural stimulation protocols

Measuring Galaxy Star Formation Rates From Integrated Photometry: Insights from Color-Magnitude Diagrams of Resolved Stars

We use empirical star formation histories (SFHs), measured from HST-based resolved star color-magnitude diagrams, as input into population synthesis codes to model the broadband spectral energy distributions (SEDs) of ~50 nearby dwarf galaxies (6.5 < log M/M_* < 8.5, with metallicities ~10% solar). In the presence of realistic SFHs, we compare the modeled and observed SEDs from the ultraviolet (UV) through near-infrared (NIR) and assess the reliability of widely used UV-based star formation rate (SFR) indicators. In the FUV through i bands, we find that the observed and modeled SEDs are in excellent agreement. In the Spitzer 3.6micron and 4.5micron bands, we find that modeled SEDs systematically over-predict observed luminosities by up to ~0.2 dex, depending on treatment of the TP-AGB stars in the synthesis models. We assess the reliability of UV luminosity as a SFR indicator, in light of independently constrained SFHs. We find that fluctuations in the SFHs alone can cause factor of ~2 variations in the UV luminosities relative to the assumption of a constant SFH over the past 100 Myr. These variations are not strongly correlated with UV-optical colors, implying that correcting UV-based SFRs for the effects of realistic SFHs is difficult using only the broadband SED. Additionally, for this diverse sample of galaxies, we find that stars older than 100 Myr can contribute from <5% to100% of the present day UV luminosity, highlighting the challenges in defining a characteristic star formation timescale associated with UV emission. We do find a relationship between UV emission timescale and broadband UV-optical color, though it is different than predictions based on exponentially declining SFH models. Our findings have significant implications for the comparison of UV-based SFRs across low-metallicity populations with diverse SFHs.Comment: 22 pages, 15 figures, ApJ accepte