Data analysis methods for testing alternative theories of gravity with LISA Pathfinder
Data analysis methods for testing alternative theories of gravity with LISA Pathfinder
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DOI：
10.1103/physrevd.89.123511
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发表时间：
2014-04
影响因子：
5
通讯作者：
N. Korsakova;C. Messenger;F. Pannarale;M. Hewitson;M. Armano
中科院分区：
文献类型：
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作者：
N. Korsakova;C. Messenger;F. Pannarale;M. Hewitson;M. Armano
本文提出了一种适用于丽莎探路者（LPF）潜在鞍点飞越使命扩展的数据分析方法。在其灵敏度的峰值时，LPF将以大约1 mHz的频率以几个fm/s2/Hz的精度对我们太阳系中的引力场进行采样。这样一个精确的加速度计将使我们能够测试替代理论的重力预测偏离牛顿动力学在非相对论性的限制。作为一个例子，我们考虑的情况下，张量矢量标量（TeVeS）理论的重力和计算，在非相对论性的限制，这一理论，异常潮汐应力产生的LPF的信号。我们研究了这些信号的参数空间，并将其分为两个子组，一个与使命参数相关，另一个与引力模型确定的理论参数相关。我们调查的使命参数如何影响信号的可探测性，得出结论，这些参数可以确定足够的精度从航天器的导航和固定在我们的分析。此外，我们应用贝叶斯参数估计，并确定重力理论参数可以推断的准确性。我们评估的参数空间的一部分，可以消除在没有信号检测的情况下，估计作为参数空间位置的函数的信号的可检测性。我们还进行了第一次调查的非高斯“噪声毛刺”，可能会发生在数据中。我们开发的分析是通用的，可以应用到任何重力理论预测的异常潮汐应力引起的信号。
In this paper we present a data analysis approach applicable to the potential saddle-point fly-by mission extension of LISA Pathfinder (LPF). At the peak of its sensitivity, LPF will sample the gravitational field in our Solar System with a precision of several fm/s2/Hz at frequencies around 1 mHz. Such an accurate accelerometer will allow us to test alternative theories of gravity that predict deviations from Newtonian dynamics in the nonrelativistic limit. As an example, we consider the case of the Tensor-Vector-Scalar (TeVeS) theory of gravity and calculate, within the nonrelativistic limit of this theory, the signals that anomalous tidal stresses generate in LPF. We study the parameter space of these signals and divide it into two subgroups, one related to the mission parameters and the other to the theory parameters that are determined by the gravity model. We investigate how the mission parameters affect the signal detectability concluding that these parameters can be determined with the sufficient precision from the navigation of the spacecraft and fixed during our analysis. Further, we apply Bayesian parameter estimation and determine the accuracy to which the gravity theory parameters may be inferred. We evaluate the portion of parameter space that may be eliminated in case of no signal detection and estimate the detectability of signals as a function of parameter space location. We also perform a first investigation of non-Gaussian “noise glitches” that may occur in the data. The analysis we develop is universal and may be applied to anomalous tidal stress induced signals predicted by any theory of gravity.