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arXiv:2405.03657 · Physics Letters A

Quantum interpretations, causality and quantum computation

Vivek Kumar, M.P. Singh, R. Srikanth

Published Jan 29, 2026• 0 citations
arXivHTMLPDF
DOI
10.1016/j.physleta.2026.131422

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Process matrices are a framework to model causal relations in the absence of a well-defined acyclic causal order. The framework is very general and does not even assume the existence of a background spacetime. As a result, it is an open question how the framework should be interpreted physically and how and even if composition can be defined. On the other hand, so-called causal boxes define a framework that allows for arbitrary composition. In this work, we treat quantum circuits with quantum control of causal order (QC-QC), a subset of process matrices, which can be interpreted as generalized quantum circuits, and process box, a subset of causal boxes, which can be interpreted as processes. We analyze their state spaces and define a notion of operational equivalence between QC-QCs and process boxes based on this analysis. We then explicitly construct for each QC-QC an operationally equivalent process box. This allows us to define composition of QC-QCs in terms of composition of causal boxes which is well-defined. We further show that process boxes admit a unitary extension and conjecture that the background spacetime can be assumed to have a specific simple form. Based on this conjecture, we construct an operationally equivalent QC-QC for each process box. Our results indicate that the only class of processes that can be physically implemented in a fixed background spacetime are those that can be interpreted as quantum circuits with quantum controlled superpositions of orders. Further, they also reveal that the composability issue can be resolved by embedding processes in a spacetime structure. This in turn sheds light on the connection between physical realizability in a spacetime and composability.
We introduce Measure Reinforcement (MR), a computational framework for modeling quantum cognition and inference in a unified quantum mechanical framework.This framework bridges quantum cognition and emergent causality, modeling neural learning (STDP) within the relational interpretation of quantum mechanics where causality emerges from interactions.We model quantum cognition as a learning process where asymmetric entanglement-driven updates lead to the emergence of causal asymmetric neural patterns of activities.These updates are valid under quantum mechanics and resemble Hebbian learning.Classical causal graphs arise only when interpreted from the perspective of an observer enforcing a measurement basis.