This work introduces optimization strategies to continuous variable measurement based quantum computation (MBQC) at different levels. We provide a recipe for mitigating the effects of finite squeezing, which affect the production of cluster states and the result of a traditional MBQC. These strategies are readily implementable by several experimental groups. Furthermore, a more general scheme for MBQC is introduced that does not necessarily rely on the use of ancillary cluster states to achieve its aim, but rather on the detection of a resource state in a suitable mode basis followed by digital post-processing. A recipe is provided to optimize the adjustable parameters that are employed within this framework.
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