Cooperative Physics of Fly Swarms: An Emergent Behavior

We have simulated the behavior of several artificial flies, interacting visually with each other. Each fly is described by a simple tracking system (Poggio and Reichardt, 1973; Land and Collett, 1974) which summarizes behavioral experiments in which individual flies fixate a target. Our main finding is that the interaction of theses implemodules gives rise to a variety of relatively complex behaviors. In particular, we observe a swarm-like behavior of a group of many artificial flies for certain reasonable ranges of our tracking system parameters

Vortex Lattice Melting of a NbSe2 single grain probed by Ultrasensitive Cantilever Magnetometry

Using dynamic cantilever magnetometry, we study the vortex lattice and its corresponding melting transition in a micrometer-size crystallite of superconducting NbSe2. Measurements of the cantilever resonance frequency as a function of magnetic field and temperature respond to the magnetization of the vortex-lattice. The cantilever dissipation depends on thermally activated vortex creep motion, whose pinning energy barrier is found to be in good agreement with transport measurements on bulk samples. This approach reveals the phase diagram of the crystallite, and is applicable to other micro- or nanometer-scale superconducting samples.Comment: 5 pages, 4 figure

A geometry for optimizing nanoscale magnetic resonance force microscopy

We implement magnetic resonance force microscopy (MRFM) in an experimental geometry, where the long axis of the cantilever is normal to both the external magnetic field and the RF microwire source. Measurements are made of the statistical polarization of $^1$H in polystyrene with negligible magnetic dissipation, gradients greater than $10^5$ T/m within 100 nm of the magnetic tip, and rotating RF magnetic fields over 12 mT at 115 MHz. This geometry could facilitate the application of nanometer-scale MRFM to nuclear species with low gyro-magnetic ratios and samples with broadened resonances, such as In spins in quantum dots.Comment: 4 pages, 5 figure

A Nonparametric Approach to Pricing and Hedging Derivative Securities Via Learning Networks

We propose a nonparametric method for estimating the pricing formula of a derivative asset using learning networks. Although not a substitute for the more traditional arbitrage-based pricing formulas, network pricing formulas may be more accurate and computationally more efficient alternatives when the underlying asset's price dynamics are unknown, or when the pricing equation associated with no-arbitrage condition cannot be solved analytically. To assess the potential value of network pricing formulas, we simulate Black-Scholes option prices and show that learning networks can recover the Black-Scholes formula from a two-year training set of daily options prices, and that the resulting network formula can be used successfully to both price and delta-hedge options out-of-sample. For comparison, we estimate models using four popular methods: ordinary least squares, radial basis function networks, multilayer perceptron networks, and projection pursuit. To illustrate the practical relevance of our network pricing approach, we apply it to the pricing and delta-hedging of S&P 500 futures options from 1987 to 1991.

Electric field sensing with a scanning fiber-coupled quantum dot

We demonstrate the application of a fiber-coupled quantum-dot-in-a-tip as a probe for scanning electric field microscopy. We map the out-of-plane component of the electric field induced by a pair of electrodes by measurement of the quantum-confined Stark effect induced on a quantum dot spectral line. Our results are in agreement with finite element simulations of the experiment. Furthermore, we present results from analytic calculations and simulations which are relevant to any electric field sensor embedded in a dielectric tip. In particular, we highlight the impact of the tip geometry on both the resolution and sensitivity.Comment: 10 pages, 4 figure

Boundary between the thermal and statistical polarization regimes in a nuclear spin ensemble

As the number of spins in an ensemble is reduced, the statistical uctuations in its polarization eventually exceed the mean thermal polarization. This transition has now been surpassed in a number of recent nuclear magnetic resonance experiments, which achieve nanometer-scale detection volumes. Here, we measure nanometer- scale ensembles of nuclear spins in a KPF6 sample using magnetic resonance force microscopy. In particular, we investigate the transition between regimes dominated by thermal and statistical nuclear polarization. The ratio between the two types of polarization provides a measure of the number of spins in the detected ensemble

Force sensing with nanowire cantilevers

Nanometer-scale structures with high aspect ratio such as nanowires and nanotubes combine low mechanical dissipation with high resonance frequencies, making them ideal force transducers and scanning probes in applications requiring the highest sensitivity. Such structures promise record force sensitivities combined with ease of use in scanning probe microscopes. A wide variety of possible material compositions and functionalizations is available, allowing for the sensing of various kinds of forces with optimized sensitivity. In addition, nanowires possess quasi-degenerate mechanical mode doublets, which has allowed the demonstration of sensitive vectorial force and mass detection. These developments have driven researchers to use nanowire cantilevers in various force sensing applications, which include imaging of sample surface topography, detection of optomechanical, electrical, and magnetic forces, and magnetic resonance force microscopy. In this review, we discuss the motivation behind using nanowires as force transducers, explain the methods of force sensing with nanowire cantilevers, and give an overview of the experimental progress and future prospects of the field