Probabilistic Causality in Space and Time

Patrick Suppes

Patrick Suppes

Amy Malady

Quantum mechanics successfully predicts experimental outcomes, yet its geometric and causal interpretation remains an open area of foundational inquiry. Concepts such as superposition, interference, and decoherence are frequently described as intrinsically probabilistic or nonclassical, often leaving unresolved whether these behaviors reflect fundamental randomness or limitations of our representational framework. This paper proposes a geometric reinterpretation in which quantum phenomena arise from the projection of a deeper causal structure into observer-dependent frames. Through thought experiments only, this work explores the possible literal interpretation of an orthogonal space-causal frame of reference, associated with null propagation, within a physical tradition otherwise strongly rooted in time-causal description. In our familiar time-causal frame, time is treated as the ordered causal axis and space as a volumetric domain of alternatives. Introduced here is a complementary space-causal frame, in which space becomes the ordered causal axis while time forms a volumetric domain of alternatives. Within this framework, superposition, interference, and decoherence emerge as consequences of geometric constraint rather than physical collapse. This approach preserves relativistic causality, introduces no additional dimensions, and leaves experimental predictions unchanged while offering a unified conceptual account of quantum behavior.

Simon W. Saunders

Sonia Markes, Lucién Hardy

Any theory with definite causal structure has a defined past and future, be it defined by light cones or an absolute time scale. Entropy is a concept that has traditionally been reliant on a definite notion of causality. However, without a definite notion of causality, the concept of entropy is not all lost. Indefinite causal structure results from combining probabilistic predictions and dynamical space-time. The causaloid framework lays the mathematical groundwork to be able to treat indefinite causal structure. In this paper, we build on the causaloid mathematics and define a causally-unbiased entropy for an indefinite causal structure. In defining a causally-unbiased entropy, there comes about an emergent idea of causality in the form of a measure of causal connectedness, termed the Q factor.