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arXiv 2409.14749math.AP
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Noisy integrate-and-fire equation:blow-up后的延拓

Noisy integrate-and-fire equation: continuation after blow-up

Xu'An Dou, Benoît Perthame, Delphine Salort, Zhennan Zhou

AI总结:

研究神经集群integrate and fire equation在blow-up后如何延拓解,通过随机放电模型与时间变换建立全局解,并利用两个新估计处理非线性项,揭示blow-up后的动力学。

摘要:

integrate and fire equation是神经集群的经典模型,可能出现有限时间blow-up。一个主要的开放性问题是理解如何在blow-up后延拓解。这里我们研究一种基于随机放电模型和时间变换的方法,该方法以强吸收率1/$ε$为代价生成经典全局解。我们证明在极限$ε$ $\ ightarrow$ 0 + 下,恢复了全局解,其中integrate and fire equation用奇异测度重新表述。这描述了blow-up后的动力学,并给出了blow-up现象本身的信息。主要困难在于处理非线性项。为规避此问题,我们建立了两个新估计:放电测度的一种等度可积性和密度的L 2估计。新时间尺度的使用对这些估计至关重要。

英文摘要:

The integrate and fire equation is a classical model for neural assemblies which can exhibit finite time blow-up. A major open problem is to understand how to continue solutions after blow-up. Here we study an approach based on random discharge models and a change of time which generates a classical global solution to the expense of a strong absorption rate 1/$ε$. We prove that in the limit $ε$ $\rightarrow$ 0 + , a global solution is recovered where the integrate and fire equation is reformulated with a singular measure. This describes the dynamics after blow-up and also gives information on the blow-up phenomena itself.The major difficulty is to handle nonlinear terms. To circumvent it, we establish two new estimates, a kind of equi-integrability of the discharge measure and a L 2 estimate of the density. The use of the new timescale turns out to be fundamental for those estimates.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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