# Extracting Microlensing Signals from K2 Campaign 9

## TL;DR

This paper introduces a novel method for extracting microlensing signals from the challenging, crowded K2 Campaign 9 data by combining advanced photometry, systematic removal, and color-based modeling to improve parameter constraints.

## Contribution

The work presents the first method capable of extracting microlensing signals from K2C9 data, incorporating color-color relations to enhance microlensing parameter estimation.

## Key findings

- Successfully extracted signals from two example events.
- Improved microlensing parameter constraints using color-color relations.
- Demonstrated the method's effectiveness on crowded, unstable K2 data.

## Abstract

The reduction of the \emph{K2}'s Campaign 9 (K2C9) microlensing data is challenging mostly because of the very crowded field and the unstable pointing of the spacecraft. In this work, we present the first method that can extract microlensing signals from this K2C9 data product. The raw light curves and the astrometric solutions are first derived, using the techniques from Soares-Furtado et al. and Huang et al. for \emph{K2} dense field photometry. We then minimize and remove the systematic effect by performing simultaneous modeling with the microlensing signal. We also derive precise $(K_p-I)$ vs. $(V-I)$ color-color relations that can predict the microlensing source flux in the \emph{Kepler} bandpass. By implementing the color-color relation in the light curve modeling, we show that the microlensing parameters can be better constrained. In the end, we use two example microlensing events, OGLE-2016-BLG-0980 and OGLE-2016-BLG-0940, to test our method.