12,346 research outputs found
Mapping of dissipative particle dynamics in fluctuating hydrodynamics simulations
Dissipative particle dynamics (DPD) is a novel particle method for mesoscale
modeling of complex fluids. DPD particles are often thought to represent
packets of real atoms, and the physical scale probed in DPD models are
determined by the mapping of DPD variables to the corresponding physical
quantities. However, the non-uniqueness of such mapping has led to difficulties
in setting up simulations to mimic real systems and in interpreting results.
For modeling transport phenomena where thermal fluctuations are important
(e.g., fluctuating hydrodynamics), an area particularly suited for DPD method,
we propose that DPD fluid particles should be viewed as only 1) to provide a
medium in which the momentum and energy are transferred according to the
hydrodynamic laws and 2) to provide objects immersed in the DPD fluids the
proper random "kicks" such that these objects exhibit correct fluctuation
behaviors at the macroscopic scale. We show that, in such a case, the choice of
system temperature and mapping of DPD scales to physical scales are uniquely
determined by the level of coarse-graining and properties of DPD fluids. We
also verified that DPD simulation can reproduce the macroscopic effects of
thermal fluctuation in particulate suspension by showing that the Brownian
diffusion of solid particles can be computed in DPD simulations with good
accuracy
Single-particle machine for quantum thermalization
The long time accumulation of the \textit{random} actions of a single
particle "reservoir" on its coupled system can transfer some temperature
information of its initial state to the coupled system. This dynamic process
can be referred to as a quantum thermalization in the sense that the coupled
system can reach a stable thermal equilibrium with a temperature equal to that
of the reservoir. We illustrate this idea based on the usual micromaser model,
in which a series of initially prepared two-level atoms randomly pass through
an electromagnetic cavity. It is found that, when the randomly injected atoms
are initially prepared in a thermal equilibrium state with a given temperature,
the cavity field will reach a thermal equilibrium state with the same
temperature as that of the injected atoms. As in two limit cases, the cavity
field can be cooled and "coherently heated" as a maser process, respectively,
when the injected atoms are initially prepared in ground and excited states.
Especially, when the atoms in equilibrium are driven to possess some coherence,
the cavity field may reach a higher temperature in comparison with the injected
atoms. We also point out a possible experimental test for our theoretical
prediction based on a superconducting circuit QED system.Comment: 9 pages,4 figures
Accelerating charging dynamics in sub-nanometer pores
Having smaller energy density than batteries, supercapacitors have
exceptional power density and cyclability. Their energy density can be
increased using ionic liquids and electrodes with sub-nanometer pores, but this
tends to reduce their power density and compromise the key advantage of
supercapacitors. To help address this issue through material optimization, here
we unravel the mechanisms of charging sub-nanometer pores with ionic liquids
using molecular simulations, navigated by a phenomenological model. We show
that charging of ionophilic pores is a diffusive process, often accompanied by
overfilling followed by de-filling. In sharp contrast to conventional
expectations, charging is fast because ion diffusion during charging can be an
order of magnitude faster than in bulk, and charging itself is accelerated by
the onset of collective modes. Further acceleration can be achieved using
ionophobic pores by eliminating overfilling/de-filling and thus leading to
charging behavior qualitatively different from that in conventional, ionophilic
pores
Asymmetry in Photoproduction
By adopting two models of strange and antistrange quark distributions inside
nucleon, the light-cone meson-baryon fluctuation model and the effective chiral
quark model, we calculate the asymmetry in photoproduction in
the framework of heavy-quark recombination mechanism. We find that the effect
of asymmetry of strange sea to the asymmetry is considerable and
depending on the different models. Therefore, we expect that with the further
study in electroproduction, e.g. at HERA and CEBAF, the experimental
measurements on the asymmetry may impose a strong restriction
on the strange-antistrange distribution asymmetry models.Comment: 4 pages, talk presented by I. Caprini at the International Conference
on QCD and Hadronic Physics, June 16-20 2005, Beijin
Adaptive motor control and learning in a spiking neural network realised on a mixed-signal neuromorphic processor
Neuromorphic computing is a new paradigm for design of both the computing
hardware and algorithms inspired by biological neural networks. The event-based
nature and the inherent parallelism make neuromorphic computing a promising
paradigm for building efficient neural network based architectures for control
of fast and agile robots. In this paper, we present a spiking neural network
architecture that uses sensory feedback to control rotational velocity of a
robotic vehicle. When the velocity reaches the target value, the mapping from
the target velocity of the vehicle to the correct motor command, both
represented in the spiking neural network on the neuromorphic device, is
autonomously stored on the device using on-chip plastic synaptic weights. We
validate the controller using a wheel motor of a miniature mobile vehicle and
inertia measurement unit as the sensory feedback and demonstrate online
learning of a simple 'inverse model' in a two-layer spiking neural network on
the neuromorphic chip. The prototype neuromorphic device that features 256
spiking neurons allows us to realise a simple proof of concept architecture for
the purely neuromorphic motor control and learning. The architecture can be
easily scaled-up if a larger neuromorphic device is available.Comment: 6+1 pages, 4 figures, will appear in one of the Robotics conference
Electrical properties of breast cancer cells from impedance measurement of cell suspensions
Impedance spectroscopy of biological cells has been used to monitor cell status, e.g. cell proliferation, viability, etc. It is also a fundamental method for the study of the electrical properties of cells which has been utilised for cell identification in investigations of cell behaviour in the presence of an applied electric field, e.g. electroporation. There are two standard methods for impedance measurement on cells. The use of microelectrodes for single cell impedance measurement is one method to realise the measurement, but the variations between individual cells introduce significant measurement errors. Another method to measure electrical properties is by the measurement of cell suspensions, i.e. a group of cells within a culture medium or buffer. This paper presents an investigation of the impedance of normal and cancerous breast cells in suspension using the Maxwell-Wagner mixture theory to analyse the results and extract the electrical parameters of a single cell. The results show that normal and different stages of cancer breast cells can be distinguished by the conductivity presented by each cell. © 2010 IOP Publishing Ltd
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