Additive noise destroys the random attractor close to bifurcation

Additive noise destroys the random attractor close to bifurcation
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加性噪声破坏了接近分叉的随机吸引子

DOI:
10.1088/0951-7715/29/12/3934
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发表时间:
2016-03
期刊:
影响因子:
1.7
通讯作者:
Meihua Yang
Meihua Yang
中科院分区:
数学2区
文献类型:
--
作者:
Luigi Bianchi;Dirk Bloemker;Meihua Yang

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我们提供了一个例子稳定的噪声。由于高阶微分算子的存在,我们的方法不依赖于单调性参数,即解的保持阶。此外,由于噪声是高度简并的,系统的混合特性可能不可用。在我们的例子中,标量加性噪声已经破坏了无界域上PDE的高维确定性吸引子的复杂性。主要结果表明,通过加入一定量的噪声,所有的轨迹收敛到一个单一的平稳解。接近分叉处,这种稳定所需的噪声量有一个下限,这取决于到分叉处的距离,并且小(但不是任意小)噪声的存在已经足够了。我们专注于无界域上的随机偏微分方程,在无穷远点没有任何衰减条件。该设置允许任意周期的空间恒定或周期性解。但我们需要在加权空间中工作,并首先在该设置中建立随机吸引子的存在性。
We provide an example for stabilization by noise. Due to the presence of higher order differential operators our approach does not rely on monotonicity arguments, i.e. the preserved order of solutions. Moreover, as the noise is highly degenerate mixing properties of the system might not be available. In our examples already a scalar additive noise destroys the complexity of a high-dimensional deterministic attractor of a PDE on an unbounded domain. The main result shows that by adding a certain amount of noise all trajectories converge to a single stationary solution. Close to bifurcation there is a lower bound on the amount of noise necessary for this stabilization, which depends on the distance to bifurcation, and the presence of small (but not arbitrarily small) noise already suffices. We focus on stochastic PDEs posed on unbounded domains without any decay condition at infinity. This setting allows for spatially constant or periodic solutions of arbitrary period. But we need to work in weighted spaces and establish the existence of random attractors in that setting first.
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