Toward explaining why events occur

Jeffrey Bub

Paolo Faglia

Relational quantum mechanics (RQM) explains the world in terms of an ontology of systems and events, where an event consists of a variable of a system taking a value relative to another system. Two strands of RQM may be distinguished depending on whether events are taken to be absolute or relative. The arguments in this paper apply to both, although I assume that the relativity is not infinitely iterated. I argue that, to solve the problem of measurement, RQM needs to offer a specification of the circumstances in which events occur. Current formulations of RQM claim that events occur whenever interactions occur, without further defining what is meant by “interaction”. I develop plausible ways of understanding the notion of interaction, but I show that they fail to provide a satisfactory specification for the occurrence of events. RQM thus leaves the measurement problem unresolved and, in light of these failed constructive efforts, I conclude that developing a solution consistent with the aims of RQM is a formidable challenge.

Lachlan Mackinnon

Jerome R. Busemeyer, Peter Bruza

One of the goals of quantum Cognition and decision is to explain findings that seem paradoxical from a classic probability point of view. This is important to justify the introduction of this new theory. So far we have used the theory to explain paradoxical findings from research on human probability judgments and conceptual combinations. These are both considered higher level cognitive functions that involve more complex reasoning. What about more primitive cognitive functions such as memory recognition? Do paradoxical findings with respect to classic probability theory occur in this basic area of cognition? If so, how can a quantum model help to explain these findings over and above current explanations? This chapter presents a new application of quantum theory to a puzzling phenomenon observed in human memory recognition called the episodic overdistribution (EOD) effect (Brainerd & Reyna, 2008). First we describe the phenomena and explain why it is a puzzle, and then we present a quantum solution to the puzzle and compare it with previous memory recognition models. Episodic overdistribution effect In the conjoint–recognition paradigm, participants are rehearsed on a single set T of memory targets (e.g., each member is a short description of an event). After a delay, a recognition test phase occurs, during which they are presented with a series of test probes that consist of trained targets from T , related non-targets from a different set R of distracting events (e.g., each member is a new event that has some meaningful relation to a target event), and an unrelated set U of non-target items (e.g., each member is completely unrelated to the targets).

Richard Healey

We can use quantum theory to explain an enormous variety of phenomena by showing why they were to be expected and what they depend on. These explanations of probabilistic phenomena involve applications of the Born rule: to accept quantum theory is to let relevant Born probabilities guide one’s credences about presently inaccessible events. We use quantum theory to explain a probabilistic phenomenon by showing how its probabilities follow from a correct application of the Born rule, thereby exhibiting the phenomenon’s dependence on the quantum state to be assigned in circumstances of that type. This is not a causal explanation since a probabilistic phenomenon is not constituted by events that may manifest it: but each of those events does depend causally on events that actually occur in those circumstances. Born probabilities are objective and sui generis, but not all Born probabilities are chances.

Michaël Esfeld