The Measurement Problem Is a Feature, Not a Bug-Schematising the Observer and the Concept of an Open System on an Informational, or (Neo-)Bohrian, Approach

Entropy (Basel). 2023 Oct 2;25(10):1410. doi: 10.3390/e25101410.


I flesh out the sense in which the informational approach to interpreting quantum mechanics, as defended by Pitowsky and Bub and lately by a number of other authors, is (neo-)Bohrian. I argue that on this approach, quantum mechanics represents what Bohr called a "natural generalisation of the ordinary causal description" in the sense that the idea (which philosophers of science like Stein have argued for on the grounds of practical and epistemic necessity) that understanding a theory as a theory of physics requires that one be able to "schematise the observer" within it is elevated in quantum mechanics to the level of a postulate in the sense that interpreting the outcome of a measurement interaction, as providing us with information about the world, requires as a matter of principle, the specification of a schematic representation of an observer in the form of a 'Boolean frame'-the Boolean algebra representing the yes-or-no questions associated with a given observable representative of a given experimental context. I argue that the approach's central concern is with the methodological question of how to assign physical properties to what one takes to be a system in a given experimental context, rather than the metaphysical question of what a given state vector represents independently of any context, and I show how the quantum generalisation of the concept of an open system may be used to assuage Einstein's complaint that the orthodox approach to quantum mechanics runs afoul of the supposedly fundamental methodological requirement to the effect that one must always be able, according to Einstein, to treat spatially separated systems as isolated from one another.

Keywords: Bohrian; informational interpretation; measurement problem; neo-Bohrian; quantum mechanics.

Grants and funding

This research was funded by the Alexander von Humboldt Foundation and by the German Research Council (DFG) through grant number 468374455.