Rare B-meson decays such as the B0 → Ksπ0 which proceed without a charm quark provide a probe for physics beyond the standard model. This decay proceeds mainly via the b → s penguin transition, with the b → u transition being colour suppressed, allowing CP-violating effects to be observable.
The asymmetric e+e− KEKB collider and the Belle detector provide the large luminosity and data collection required to observe these rare B decays.
Methods to reduce the large qq backgrounds are investigated. The use of optimised neural networks using TensorFlow shows a significant improvement compared to the commonly used NeuroBayes software. Techniques for reducing correlations between variables introduced by TensorFlow are also investigated, proving that the use of adversarial neural networks can provide an improved background suppression as compared to NeuroBayes, whilst minimising correlations introduced by the neural network.
An improved method of measuring the direct CP violation is introduced. Using Monte Carlo data with sample sizes corresponding to the full Belle datatset of (771.581 ± 10.566) × 106 BB events, the statistical uncertainty in ACP using this method is reduced from the latest Belle result of 0.13 to 0.1035 ± 0.0032. This method would also provide an up to date measurement on B(B0 → K0π0).