1,619 research outputs found
Hard-sphere limit of soft-sphere model for granular materials: Stiffness dependence of steady granular flow
Dynamical behavior of steady granular flow is investigated numerically in the
inelastic hard sphere limit of the soft sphere model. We find distinctively
different limiting behaviors for the two flow regimes, i.e., the collisional
flow and the frictional flow. In the collisional flow, the hard sphere limit is
straightforward; the number of collisions per particle per unit time converges
to a finite value and the total contact time fraction with other particles goes
to zero. For the frictional flow, however, we demonstrate that the collision
rate diverges as the power of the particle stiffness so that the time fraction
of the multiple contacts remains finite even in the hard sphere limit although
the contact time fraction for the binary collisions tends to zero.Comment: 10 figures. Typos removed. to appear in Phys. Rev.
Linear stability analysis of rapid granular flow on a slope and density wave formation
The linear stability of rapid granular flow on a slope under gravity against
the longitudinal perturbation is analyzed using hydrodynamic equations. It is
demonstrated that the steady flow uniform along the flow direction becomes
unstable against the long-wavelength perturbations longitudinal to the flow
direction for certain parameter ranges to form the density wave, in contrast
with the finite wavelength instability against the transverse perturbation
(Forterre & Pouliquen 2002). It is shown that the instability can be understood
as the the long-wave instability of the kinematic waves in a quasi-one
dimensional system. The results are compared with our previous molecular
dynamics simulations (Mitarai & Nakanishi 2001), where the spontaneous density
wave formation has been found.Comment: 25 pages, 15 figures, submitted to J. Fluid Mech.; larger parameter
range investigated, discussions revise
Spatio-temporal structure of traffic flow in a system with an open boundary
The spatio-temporal structure of traffic flow pattern is investigated under
the open boundary condition using the optimal velocity (OV) model. The
parameter region where the uniform solution is convectively unstable is
determined. It is found that a localized perturbation triggers a linearly
unstable oscillatory solution out of the linearly unstable uniform state, and
it is shown that the oscillatory solution is also convectively stabilized. It
is demonstrated that the observed traffic pattern near an on-ramp can be
interpreted as the noise sustained structure in the open flow system.Comment: 5 pages (RevTex), 3 figures (EPS). Submitted to Physical Review
Letter
Control of ribosome traffic by position-dependent choice of synonymous codons
Messenger RNA encodes a sequence of amino acids by using codons. For most
amino acids there are multiple synonymous codons that can encode the amino
acid. The translation speed can vary from one codon to another, thus there is
room for changing the ribosome speed while keeping the amino acid sequence and
hence the resulting protein. Recently, it has been noticed that the choice of
the synonymous codon, via the resulting distribution of slow- and
fast-translated codons, affects not only on the average speed of one ribosome
translating the messenger RNA (mRNA) but also might have an effect on nearby
ribosomes by affecting the appearance of "traffic jams" where multiple
ribosomes collide and form queues. To test this "context effect" further, we
here investigate the effect of the sequence of synonymous codons on the
ribosome traffic by using a ribosome traffic model with codon-dependent rates,
estimated from experiments. We compare the ribosome traffic on wild type
sequences and sequences where the synonymous codons were swapped randomly. By
simulating translation of 87 genes, we demonstrate that the wild type
sequences, especially those with a high bias in codon usage, tend to have the
ability to reduce ribosome collisions, hence optimizing the cellular investment
in the translation apparatus. The magnitude of such reduction of the
translation time might have a significant impact on the cellular growth rate
and thereby have importance for the survival of the species.Comment: 12 pages, 6 Figures. This is an author-created, un-copyedited version
of an article accepted for publication in Physical Biology. IOP Publishing
Ltd is not responsible for any errors or omissions in this version of the
manuscript or any version derived from i
Disturbance accelerates the transition from low- to high- diversity state in a model ecosystem
The effect of disturbance on a model ecosystem of sessile and mutually
competitive species [Mathiesen et al. Phys. Rev. Lett. 107, 188101 (2011);
Mitarai et al. Phys. Rev. E 86, 011929 (2012) ] is studied. The disturbance
stochastically removes individuals from the system, and the created empty sites
are re-colonized by neighbouring species. We show that the stable
high-diversity state, maintained by occasional cyclic species interactions that
create isolated patches of meta-populations, is robust against small
disturbance. We further demonstrate that finite disturbance can accelerate the
transition from the low- to high-diversity state by helping creation of small
patches through diffusion of boundaries between species with stand-off
relation.Comment: 8 pages, 8 figures. Typos correcte
Quantum Analog-Digital Conversion
Many quantum algorithms, such as Harrow-Hassidim-Lloyd (HHL) algorithm,
depend on oracles that efficiently encode classical data into a quantum state.
The encoding of the data can be categorized into two types; analog-encoding
where the data are stored as amplitudes of a state, and digital-encoding where
they are stored as qubit-strings. The former has been utilized to process
classical data in an exponentially large space of a quantum system, where as
the latter is required to perform arithmetics on a quantum computer. Quantum
algorithms like HHL achieve quantum speedups with a sophisticated use of these
two encodings. In this work, we present algorithms that converts these two
encodings to one another. While quantum digital-to-analog conversions have
implicitly been used in existing quantum algorithms, we reformulate it and give
a generalized protocol that works probabilistically. On the other hand, we
propose an deterministic algorithm that performs a quantum analog-to-digital
conversion. These algorithms can be utilized to realize high-level quantum
algorithms such as a nonlinear transformation of amplitude of a quantum state.
As an example, we construct a "quantum amplitude perceptron", a quantum version
of neural network, and hence has a possible application in the area of quantum
machine learning.Comment: 7 page
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