Hot atomic vapors are widely used in non-linear and quantum optics due to their large Kerr non-linearity. While the linear refractive index and the transmission are precisely measured and well modeled theoretically, similar characterization remains partial for the
χ(3) non-linear part of the susceptibility. In this work, we present a set of tools to measure and estimate numerically the non-linear index of hot atomic vapors both in the steady state and during the transient response of the medium. We apply these techniques for the characterization of a hot vapor of rubidium and we evidence the critical role played by transit effects, due to finite beam sizes, in the measurement of the non-linear index.
The potential to precisely control both the linear and nonlinear index of refraction through optical manipulation of the atomic states has recently pushed warm alkali vapors to the forefront of research in the field of quantum sensors, quantum memories, and quantum fluids of light. Rubidium (Rb) vapor in centimeter-scale glass cells or millimeter-scale MEMS cells has proven to be a very promising platform for these applications, yet only a handful of research works have been dedicated to the investigation of the (non)linear refractive index of Rb vapor. We present results of theoretical calculations of the (non)linear refractive index of warm Rb vapor, based on the optical Bloch equations for 6-level Rb atoms interacting with a probe laser. They are compared to the experimental results obtained using an interferometric technique, showing excellent quantitative agreement. A Kerr nonlinear refractive index
n2 of up to
10−4 cm
2/W is obtained. Python scripts for all theoretical calculations presented in this work are provided, including the refractive index calculation, that can readily be used in practical implementations for simulating the (non)linear refractive index of Rb vapor including the effects of Doppler broadening, transit time broadening, pressure broadening, saturation, optical pumping, and spin-exchange collisions.