Modeling multivariate distributions for bayesian optimal inference

Your model doesn’t correspond to your data generating process. Summing pdfs is not the same as summing two RVs. For instance the sampler can easily propose a prior>1 which could explain the divergences you see.

I think the equivalent would be a Mixture of Betas (with 0.5 weight, but you can also try to infer that from the data).