4.7 Article

Stochastic properties of ultralight scalar field gradients

Journal

PHYSICAL REVIEW D
Volume 104, Issue 5, Pages -

Publisher

AMER PHYSICAL SOC
DOI: 10.1103/PhysRevD.104.055037

Keywords

-

Funding

  1. DOE [DESC0007968]
  2. Simons Foundation
  3. Princeton University Dicke Fellowship
  4. Princeton Institute for Computational Science and Engineering (PICSciE)
  5. Office of Information Technology's High Performance Computing Center at Princeton University
  6. Visualization Laboratory at Princeton University

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Ultralight axionlike particles are well-studied dark matter candidates that can be treated as oscillating scalar fields near the Solar System with a coherence time of about 10^6 oscillations. It is crucial to consider the stochastic behavior of the axion field gradient when analyzing data from axion direct detection experiments, as failing to do so may lead to missing a true axion signal. The first complete stochastic treatment for the gradient of the axion field has been presented, along with efficient methods for likelihood-based data analysis that can be applied to any axion signal regardless of coherence time.
Ultralight axionlike particles are well-motivated dark matter candidates that are the target of numerous direct detection efforts. In the vicinity of the Solar System, such particles can be treated as oscillating scalar fields. The velocity dispersion of the Milky Way determines a coherence time of about 10(6) oscillations, beyond which the amplitude of the axion field fluctuates stochastically. Any analysis of data from an axion direct detection experiment must carefully account for this stochastic behavior to properly interpret the results. This is especially true for experiments sensitive to the gradient of the axion field that are unable to collect data for many coherence times. Indeed, the direction, in addition to the amplitude, of the axion field gradient fluctuates stochastically. We present the first complete stochastic treatment for the gradient of the axion field, including multiple computationally efficient methods for performing likelihood-based data analysis, which can be applied to any axion signal, regardless of coherence time. Additionally, we demonstrate that ignoring the stochastic behavior of the gradient of the axion field can potentially result in failure to discover a true axion signal.

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