15,274 research outputs found

### Simulation of a Brownian particle in an optical trap

Cataloged from PDF version of article.Unlike passive Brownian particles, active Brownian particles, also known as microswimmers, propel themselves with directed motion and thus drive themselves out of equilibrium. Understanding their motion can provide insight into out-of-equilibrium phenomena associated with biological examples such as bacteria, as well as with artificial microswimmers. We discuss how to mathematically model their motion using a set of stochastic differential equations and how to numerically simulate it using the corresponding set of finite difference equations both in homogenous and complex environments. In particular, we show how active Brownian particles do not follow the Maxwell-Boltzmann distribution-a clear signature of their out-of-equilibrium nature- and how, unlike passive Brownian particles, microswimmers can be funneled, trapped, and sorted. (C) 2014 American Association of Physics Teachers

### The analysis and design of transonic two-element airfoil systems

The multiphase effort in the development of tools for the analysis and design of two-element airfoil systems, that is, airfoils with a slat or a flap at transonic speeds is described. The first phase involved the development of a method to compute the inviscid flow over such configurations. In the second phase the inviscid code was coupled to a boundary layer calculation program in order to compute the loss in performance due to viscous effects. An inverse code that constructs the airfoil system corresponding to a desired pressure distribution is described

### Sun tracker with rotatable plane-parallel plate and two photocells Patent

Sun tracker with rotatable plane-parallel plate and two photocell

### Simulation of the active Brownian motion of a microswimmer

Cataloged from PDF version of article.Unlike passive Brownian particles, active Brownian particles, also known as microswimmers, propel themselves with directed motion and thus drive themselves out of equilibrium. Understanding their motion can provide insight into out-of-equilibrium phenomena associated with biological examples such as bacteria, as well as with artificial microswimmers. We discuss how to mathematically model their motion using a set of stochastic differential equations and how to numerically simulate it using the corresponding set of finite difference equations both in homogenous and complex environments. In particular, we show how active Brownian particles do not follow the Maxwell-Boltzmann distribution-a clear signature of their out-of-equilibrium nature- and how, unlike passive Brownian particles, microswimmers can be funneled, trapped, and sorted. (C) 2014 American Association of Physics Teachers

### Untangling supernova-neutrino oscillations with beta-beam data

Recently, we suggested that low-energy beta-beam neutrinos can be very useful
for the study of supernova neutrino interactions. In this paper, we examine the
use of a such experiment for the analysis of a supernova neutrino signal. Since
supernova neutrinos are oscillating, it is very likely that the terrestrial
spectrum of supernova neutrinos of a given flavor will not be the same as the
energy distribution with which these neutrinos were first emitted. We
demonstrate the efficacy of the proposed method for untangling multiple
neutrino spectra. This is an essential feature of any model aiming at gaining
information about the supernova mechanism, probing proto-neutron star physics,
and understanding supernova nucleosynthesis, such as the neutrino process and
the r-process. We also consider the efficacy of different experimental
approaches including measurements at multiple beam energies and detector
configurations.Comment: 13 pages, 11 figures, accepted for publication in Phys. Rev.

### Low energy neutrino scattering measurements at future Spallation Source facilities

In the future several Spallation Source facilities will be available
worldwide. Spallation Sources produce large amount of neutrinos from
decay-at-rest muons and thus can be well adapted to accommodate
state-of-the-art neutrino experiments. In this paper low energy neutrino
scattering experiments that can be performed at such facilities are reviewed.
Estimation of expected event rates are given for several nuclei, electrons and
protons at a detector located close to the source. A neutrino program at
Spallation Sources comprises neutrino-nucleus cross section measurements
relevant for neutrino and core-collapse supernova physics, electroweak tests
and lepton-flavor violation searches.Comment: 12 pages, 4 figures, 5 table

### Forma: Force reconstruction via maximum-likelihood-estimator analysis

We propose an algorithm to retrieve the conservative and non-conservative components of a force field acting on a Brownian particle from the analysis of its displacements with important advantages over established techniques

### Active Brownian Motion Tunable by Light

Active Brownian particles are capable of taking up energy from their
environment and converting it into directed motion; examples range from
chemotactic cells and bacteria to artificial micro-swimmers. We have recently
demonstrated that Janus particles, i.e. gold-capped colloidal spheres,
suspended in a critical binary liquid mixture perform active Brownian motion
when illuminated by light. In this article, we investigate in some more details
their swimming mechanism leading to active Brownian motion. We show that the
illumination-borne heating induces a local asymmetric demixing of the binary
mixture generating a spatial chemical concentration gradient, which is
responsible for the particle's self-diffusiophoretic motion. We study this
effect as a function of the functionalization of the gold cap, the particle
size and the illumination intensity: the functionalization determines what
component of the binary mixture is preferentially adsorbed at the cap and the
swimming direction (towards or away from the cap); the particle size determines
the rotational diffusion and, therefore, the random reorientation of the
particle; and the intensity tunes the strength of the heating and, therefore,
of the motion. Finally, we harness this dependence of the swimming strength on
the illumination intensity to investigate the behaviour of a micro-swimmer in a
spatial light gradient, where its swimming properties are space-dependent

### Neutrino-nucleus interaction rates at a low-energy beta-beam facility

We compute the neutrino detection rates to be expected at a low-energy
beta-beam facility. We consider various nuclei as neutrino detectors and
compare the case of a small versus large storage ring.Comment: 6 pages, 3 figure

### Characterization of anomalous diffusion classical statistics powered by deep learning (CONDOR)

Diffusion processes are important in several physical, chemical, biological and human phenomena. Examples include molecular encounters in reactions, cellular signalling, the foraging of animals, the spread of diseases, as well as trends in financial markets and climate records. Deviations from Brownian diffusion, known as anomalous diffusion (AnDi), can often be observed in these processes, when the growth of the mean square displacement in time is not linear. An ever-increasing number of methods has thus appeared to characterize anomalous diffusion trajectories based on classical statistics or machine learning approaches. Yet, characterization of anomalous diffusion remains challenging to date as testified by the launch of the AnDi challenge in March 2020 to assess and compare new and pre-existing methods on three different aspects of the problem: the inference of the anomalous diffusion exponent, the classification of the diffusion model, and the segmentation of trajectories. Here, we introduce a novel method (CONDOR) which combines feature engineering based on classical statistics with supervised deep learning to efficiently identify the underlying anomalous diffusion model with high accuracy and infer its exponent with a small mean absolute error in single 1D, 2D and 3D trajectories corrupted by localization noise. Finally, we extend our method to the segmentation of trajectories where the diffusion model and/or its anomalous exponent vary in time

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