Fluctuation Effects in High Sheet Resistance Superconducting Films

As the normal state sheet resistance, $R_n$, of a thin film superconductor increases, its superconducting properties degrade. For $R_n\simeq h/4e^2$ superconductivity disappears and a transition to a nonsuperconducting state occurs. We present electron tunneling and transport measurements on ultrathin, homogeneously disordered superconducting films in the vicinity of this transition. The data provide strong evidence that fluctuations in the amplitude of the superconducting order parameter dominate the tunneling density of states and the resistive transitions in this regime. We briefly discuss possible sources of these amplitude fluctuation effects. We also describe how the data suggest a novel picture of the superconductor to nonsuperconductor transition in homogeneous 2D systems.Comment: 11 pages, 5 figure

Early stage morphology of quench condensed Ag, Pb and Pb/Ag hybrid films

Scanning Tunneling Microscopy (STM) has been used to study the morphology of Ag, Pb and Pb/Ag bilayer films fabricated by quench condensation of the elements onto cold (T=77K), inert and atomically flat Highly Oriented Pyrolytic Graphite (HOPG) substrates. All films are thinner than 10 nm and show a granular structure that is consistent with earlier studies of QC films. The average lateral diameter, $\bar {2r}$, of the Ag grains, however, depends on whether the Ag is deposited directly on HOPG ($\bar {2r}$ = 13 nm) or on a Pb film consisting of a single layer of Pb grains ($\bar {2r}$ = 26.8 nm). In addition, the critical thickness for electrical conduction ($d_{G}$) of Pb/Ag films on inert glass substrates is substantially larger than for pure Ag films. These results are evidence that the structure of the underlying substrate exerts an influence on the size of the grains in QC films. We propose a qualitative explanation for this previously unencountered phenomenon.Comment: 11 pages, 3 figures and one tabl

Coherent, mechanical control of a single electronic spin

The ability to control and manipulate spins via electrical, magnetic and optical means has generated numerous applications in metrology and quantum information science in recent years. A promising alternative method for spin manipulation is the use of mechanical motion, where the oscillation of a mechanical resonator can be magnetically coupled to a spins magnetic dipole, which could enable scalable quantum information architectures9 and sensitive nanoscale magnetometry. To date, however, only population control of spins has been realized via classical motion of a mechanical resonator. Here, we demonstrate coherent mechanical control of an individual spin under ambient conditions using the driven motion of a mechanical resonator that is magnetically coupled to the electronic spin of a single nitrogen-vacancy (NV) color center in diamond. Coherent control of this hybrid mechanical/spin system is achieved by synchronizing pulsed spin-addressing protocols (involving optical and radiofrequency fields) to the motion of the driven oscillator, which allows coherent mechanical manipulation of both the population and phase of the spin via motion-induced Zeeman shifts of the NV spins energy. We demonstrate applications of this coherent mechanical spin-control technique to sensitive nanoscale scanning magnetometry.Comment: 6 pages, 4 figure

Approaching Zero-Temperature Metallic States in Mesoscopic Superconductor-Normal-Superconductor Arrays

Systems of superconducting islands placed on normal metal films offer tunable realizations of two-dimensional (2D) superconductivity; they can thus elucidate open questions regarding the nature of 2D superconductors and competing states. In particular, island systems have been predicted to exhibit zero-temperature metallic states. Although evidence exists for such metallic states in some 2D systems, their character is not well understood: the conventional theory of metals cannot explain them, and their properties are difficult to tune. Here, we characterize the superconducting transitions in mesoscopic island-array systems as a function of island thickness and spacing. We observe two transitions in the progression to superconductivity; both transition temperatures exhibit unexpectedly strong depression for widely spaced islands. These depressions are consistent with the system approaching zero-temperature metallic states. The nature of the transitions and the state between them is explained using a phenomenological model involving the stabilization of superconductivity on each island via a weak coupling to and feedback from its neighbors.Comment: 15 pages, 5 figure

Deviations from mean-field behavior in disordered nanoscale superconductor-normal-metal-superconductor arrays

We have fabricated quasi-two-dimensional arrays of nano-scale Pb grains coupled by an overlayer of Ag grains. Their temperature dependent resistive transitions follow predictions for an array of mesoscopic superconductor-normal-superconductor junctions. The decrease of their transition temperatures with Ag overlayer thickness systematically deviates from the Cooper limit theory of the proximity effect as the Pb grain size decreases. The deviations occur when the estimated number of Cooper pairs per grain is less than or equal to 1 and suggest the approach to a superconductor to metal transition.Comment: 11 pages, Pdf only, Revisions include text and figure

A Generalized Linear Model for Estimating Spectrotemporal Receptive Fields from Responses to Natural Sounds

In the auditory system, the stimulus-response properties of single neurons are often described in terms of the spectrotemporal receptive field (STRF), a linear kernel relating the spectrogram of the sound stimulus to the instantaneous firing rate of the neuron. Several algorithms have been used to estimate STRFs from responses to natural stimuli; these algorithms differ in their functional models, cost functions, and regularization methods. Here, we characterize the stimulus-response function of auditory neurons using a generalized linear model (GLM). In this model, each cell's input is described by: 1) a stimulus filter (STRF); and 2) a post-spike filter, which captures dependencies on the neuron's spiking history. The output of the model is given by a series of spike trains rather than instantaneous firing rate, allowing the prediction of spike train responses to novel stimuli. We fit the model by maximum penalized likelihood to the spiking activity of zebra finch auditory midbrain neurons in response to conspecific vocalizations (songs) and modulation limited (ml) noise. We compare this model to normalized reverse correlation (NRC), the traditional method for STRF estimation, in terms of predictive power and the basic tuning properties of the estimated STRFs. We find that a GLM with a sparse prior predicts novel responses to both stimulus classes significantly better than NRC. Importantly, we find that STRFs from the two models derived from the same responses can differ substantially and that GLM STRFs are more consistent between stimulus classes than NRC STRFs. These results suggest that a GLM with a sparse prior provides a more accurate characterization of spectrotemporal tuning than does the NRC method when responses to complex sounds are studied in these neurons

Cortical Surround Interactions and Perceptual Salience via Natural Scene Statistics

Spatial context in images induces perceptual phenomena associated with salience and modulates the responses of neurons in primary visual cortex (V1). However, the computational and ecological principles underlying contextual effects are incompletely understood. We introduce a model of natural images that includes grouping and segmentation of neighboring features based on their joint statistics, and we interpret the firing rates of V1 neurons as performing optimal recognition in this model. We show that this leads to a substantial generalization of divisive normalization, a computation that is ubiquitous in many neural areas and systems. A main novelty in our model is that the influence of the context on a target stimulus is determined by their degree of statistical dependence. We optimized the parameters of the model on natural image patches, and then simulated neural and perceptual responses on stimuli used in classical experiments. The model reproduces some rich and complex response patterns observed in V1, such as the contrast dependence, orientation tuning and spatial asymmetry of surround suppression, while also allowing for surround facilitation under conditions of weak stimulation. It also mimics the perceptual salience produced by simple displays, and leads to readily testable predictions. Our results provide a principled account of orientation-based contextual modulation in early vision and its sensitivity to the homogeneity and spatial arrangement of inputs, and lends statistical support to the theory that V1 computes visual salience