Life in terms of alternative scenarios instead of parallel worlds

Arbaaz Patel

This paper examines if the worlds depicted in anime series with their physics-defying events can exist in parallel worlds. Considering the Copenhagen Interpretation adopts the notion of wavefunction collapse, it is incompatible with the possibility of alternate universes existing. Thus, the Many Worlds Interpretation, which denies the possibility of this collapse and therefore allows other worlds to exist beyond ours, is adopted to argue that worlds parallel to ours with significantly different physical laws are highly unlikely to exist.

Paul Brenner

Jerome Romagosa

Do the worlds described by the Many Worlds Interpretation (MWI)—the most prominent Everettian interpretation of quantum mechanics—genuinely ‘branch’? According to the overlap view, the relationship between branching worlds is described in terms of mereological overlap: worlds share parts with one another through some temporal intervals. In recent years, an alternative known as the divergence view has gained prominence. The divergence view eschews ‘splitting’ and instead holds that Everettian worlds are mereologically disjoint parallel worlds whose histories diverge. I introduce a dilemma for the divergence view to demonstrate that it is metaphysically unsuitable for the MWI.

Mark Buchanan

Catarina Moreira, Emmanuel E. Haven, Sandro Sozzo +1 more

In this work, we analyse and model a real life financial loan application belonging to a sample bank in the Netherlands. The log is robust in terms of data, containing a total of 262 200 event logs, belonging to 13 087 different credit applications. The dataset is heterogeneous and consists of a mixture of computer generated automatic processes and manual human tasks. The goal is to work out a decision model, which represents the underlying tasks that make up the loan application service, and to assess potential areas of improvement of the institution's internal processes. To this end we study the impact of incomplete event logs for the extraction and analysis of business processes. It is quite common that event logs are incomplete with several amounts of missing information (for instance, workers forget to register their tasks). Absence of data is translated into a drastic decrease of precision and compromises the decision models, leading to biased and unrepresentative results. We investigate how classical probabilistic models are affected by incomplete event logs and we explore quantum-like probabilistic inferences as an alternative mathematical model to classical probability. This work represents a first step towards systematic investigation of the impact of quantum interference in a real life large scale decision scenario. The results obtained in this study indicate that, under high levels of uncertainty, the quantum-like models generate quantum interference terms, which allow an additional non-linear parameterisation of the data. Experimental results attest the efficiency of the quantum-like Bayesian networks, since the application of interference terms is able to reduce the error percentage of inferences performed over quantum-like models when compared to inferences produced by classical models.