2,690 research outputs found
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 H in polystyrene with negligible magnetic
dissipation, gradients greater than 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
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