12,200 research outputs found
A Probabilistic Linear Genetic Programming with Stochastic Context-Free Grammar for solving Symbolic Regression problems
Traditional Linear Genetic Programming (LGP) algorithms are based only on the
selection mechanism to guide the search. Genetic operators combine or mutate
random portions of the individuals, without knowing if the result will lead to
a fitter individual. Probabilistic Model Building Genetic Programming (PMB-GP)
methods were proposed to overcome this issue through a probability model that
captures the structure of the fit individuals and use it to sample new
individuals. This work proposes the use of LGP with a Stochastic Context-Free
Grammar (SCFG), that has a probability distribution that is updated according
to selected individuals. We proposed a method for adapting the grammar into the
linear representation of LGP. Tests performed with the proposed probabilistic
method, and with two hybrid approaches, on several symbolic regression
benchmark problems show that the results are statistically better than the
obtained by the traditional LGP.Comment: Genetic and Evolutionary Computation Conference (GECCO) 2017, Berlin,
German
Entanglement and quantum phase transition in alternating XY spin chain with next-nearest neighbour interactions
By using the method of density-matrix renormalization-group to solve the
different spin-spin correlation functions, the nearest-neighbouring
entanglement(NNE) and next-nearest-neighbouring entanglement(NNNE) of
one-dimensional alternating Heisenberg XY spin chain is investigated in the
presence of alternating nearest neighbour interactions of exchange couplings,
external magnetic fields and next-nearest neighbouring interactions. For
dimerized ferromagnetic spin chain, NNNE appears only above the critical
dimerized interaction, meanwhile, the dimerized interaction effects quantum
phase transition point and improves NNNE to a large value. We also study the
effect of ferromagnetic or antiferromagnetic next-nearest neighboring (NNN)
interactions on the dynamics of NNE and NNNE. The ferromagnetic NNN interaction
increases and shrinks NNE below and above critical frustrated interaction
respectively, while the antiferromagnetic NNN interaction always decreases NNE.
The antiferromagnetic NNN interaction results to a larger value of NNNE in
comparison to the case when the NNN interaction is ferromagnetic.Comment: 13 pages, 4 figures,. accepted by Chinese Physics B 2008 11 (in
press
Diffusion in a multi-component Lattice Boltzmann Equation model
Diffusion phenomena in a multiple component lattice Boltzmann Equation (LBE)
model are discussed in detail. The mass fluxes associated with different
mechanical driving forces are obtained using a Chapman-Enskog analysis. This
model is found to have correct diffusion behavior and the multiple diffusion
coefficients are obtained analytically. The analytical results are further
confirmed by numerical simulations in a few solvable limiting cases. The LBE
model is established as a useful computational tool for the simulation of mass
transfer in fluid systems with external forces.Comment: To appear in Aug 1 issue of PR
Galilean invariance of lattice Boltzmann models
It is well-known that the original lattice Boltzmann (LB) equation deviates
from the Navier-Stokes equations due to an unphysical velocity dependent
viscosity. This unphysical dependency violates the Galilean invariance and
limits the validation domain of the LB method to near incompressible flows. As
previously shown, recovery of correct transport phenomena in kinetic equations
depends on the higher hydrodynamic moments. In this Letter, we give specific
criteria for recovery of various transport coefficients. The Galilean
invariance of a general class of LB models is demonstrated via numerical
experiments
Cardiovascular Risk in Patients with Psoriatic Arthritis
Psoriatic arthritis (PsA) is an inflammatory arthritis associated with psoriasis. In addition to skin and joint involvement, there is increasing evidence suggesting that patients with PsA also have an increase in risk of clinical and subclinical cardiovascular diseases, mostly due to accelerating atherosclerosis. Both conventional and nonconventional cardiovascular risk factors contribute to the increased cardiovascular risk in PsA. Chronic inflammation plays a pivotal role in the pathogenesis of atherosclerosis in PsA, acting independently and/or synergistically with the conventional risk factors. In this paper, we discuss the current literature indicating that patients with PsA are at risk of cardiovascular diseases
The entanglement in one-dimensional random XY spin chain with Dzyaloshinskii-Moriya interaction
The impurities of exchange couplings, external magnetic fields and
Dzyaloshinskii--Moriya (DM) interaction considered as Gaussian distribution,
the entanglement in one-dimensional random spin systems is investigated by
the method of solving the different spin-spin correlation functions and the
average magnetization per spin. The entanglement dynamics at central locations
of ferromagnetic and antiferromagnetic chains have been studied by varying the
three impurities and the strength of DM interaction. (i) For ferromagnetic spin
chain, the weak DM interaction can improve the amount of entanglement to a
large value, and the impurities have the opposite effect on the entanglement
below and above critical DM interaction. (ii) For antiferromagnetic spin chain,
DM interaction can enhance the entanglement to a steady value. Our results
imply that DM interaction strength, the impurity and exchange couplings (or
magnetic field) play competing roles in enhancing quantum entanglement.Comment: 12 pages, 3 figure
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