论文标题
部分可观测时空混沌系统的无模型预测
Measuring neutron-star distances and properties with gravitational-wave parallax
论文作者
论文摘要
储层计算是预测湍流的有力工具,其简单的架构具有处理大型系统的计算效率。然而,其实现通常需要完整的状态向量测量和系统非线性知识。我们使用非线性投影函数将系统测量扩展到高维空间,然后将其输入到储层中以获得预测。我们展示了这种储层计算网络在时空混沌系统上的应用,该系统模拟了湍流的若干特征。我们表明,使用径向基函数作为非线性投影器,即使只有部分观测并且不知道控制方程,也能稳健地捕捉复杂的系统非线性。最后,我们表明,当测量稀疏、不完整且带有噪声,甚至控制方程变得不准确时,我们的网络仍然可以产生相当准确的预测,从而为实际湍流系统的无模型预测铺平了道路。
Gravitational-wave astronomy allows us to study objects and events invisible to electromagnetic waves. So far, only signals triggered by coalescing binaries have been detected. However, as the interferometers' sensitivities improve over time, we expect to observe weaker signals in the future, e.g. emission of continuous gravitational waves from spinning, isolated neutron stars. Parallax is a well-known method, widely used in electromagnetic astronomical observations, to estimate the distance to a source. In this work, we consider the application of the parallax method to gravitational-wave searches and explore possible distance estimation errors. We show that detection of parallax in the signal from a spinning down source can constrain the neutron star moment of inertia. For instance, we found that the relative error of the moment of inertia estimation is smaller than $10\%$ for all sources closer than 300 pc, for the assumed birth frequency of 700 Hz, ellipticity $\geq 10^{-7}$ and for two years of observations by the Einstein Telescope, assuming spin down due purely to quadrupolar gravitational radiation.