Machine Learning the Cosmic Curvature in a Model-independent Way

Understand

In this work, we achieve the determination of the cosmic curvature $\Omega_K$ in a cosmological model-independent way, by using the Hubble parameter measurements $H(z)$ and type Ia supernovae (SNe Ia).

• In our analysis, two nonlinear interpolating tools are used to reconstruct the Hubble parameter, one is the Artificial Neural Network (ANN) method, and the other is the Gaussian process (GP) method.
• We find that $\Omega_K$ based on the GP method can be greatly influenced by the prior of $H_0$, while the ANN method can overcome this.
• Therefore, the ANN method may have more advantages than GP in the measurement of the cosmic curvature.