Collapse Models: a theoretical, experimental and philosophical review

• URL: http://arxiv.org/abs/2310.14969v1
• Date: Mon, 23 Oct 2023 14:13:41 GMT
• Title: Collapse Models: a theoretical, experimental and philosophical review
• Authors: Angelo Bassi, Mauro Dorato and Hendrik Ulbricht
• Abstract summary: We show that a clarification of the ontological intimations of collapse models is needed for at least three reasons. We show that a clarification of the ontological intimations of collapse models is needed for at least three reasons.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: n this paper, we review and connect the three essential conditions needed by the collapse model to achieve a complete and exact formulation, namely the theoretical, the experimental, and the ontological ones. These features correspond to the three parts of the paper. In any empirical science, the first two features are obviously connected but, as is well known, among the different formulations and interpretations of non-relativistic quantum mechanics, only collapse models, as the paper well illustrates with a richness of details, have experimental consequences. Finally, we show that a clarification of the ontological intimations of collapse models is needed for at least three reasons: (1) to respond to the indispensable task of answering the question `what are collapse models (and in general any physical theory) about?'; (2) to achieve a deeper understanding of their different formulations; (3) to enlarge the panorama of possible readings of a theory, which historically has often played a fundamental heuristic role.

Related papers

• Learning Discrete Concepts in Latent Hierarchical Models [73.01229236386148]
  Learning concepts from natural high-dimensional data holds potential in building human-aligned and interpretable machine learning models. We formalize concepts as discrete latent causal variables that are related via a hierarchical causal model. We substantiate our theoretical claims with synthetic data experiments.
  arXiv  Detail & Related papers  (2024-06-01T18:01:03Z)
• What makes Models Compositional? A Theoretical View: With Supplement [60.284698521569936]
  We propose a general neuro-symbolic definition of compositional functions and their compositional complexity. We show how various existing general and special purpose sequence processing models fit this definition and use it to analyze their compositional complexity.
  arXiv  Detail & Related papers  (2024-05-02T20:10:27Z)
• Neural Causal Abstractions [63.21695740637627]
  We develop a new family of causal abstractions by clustering variables and their domains. We show that such abstractions are learnable in practical settings through Neural Causal Models. Our experiments support the theory and illustrate how to scale causal inferences to high-dimensional settings involving image data.
  arXiv  Detail & Related papers  (2024-01-05T02:00:27Z)
• Quantum Theory Needs (And Probably Has) Real Reduction [0.0]
  It appears that for quantum theory to be viable in a realist sense, it must possess genuine, physical non-unitarity. Penrose's theory of gravitation-induced collapse and the Transactional Interpretation are discussed.
  arXiv  Detail & Related papers  (2023-04-20T21:25:23Z)
• MetaLogic: Logical Reasoning Explanations with Fine-Grained Structure [129.8481568648651]
  We propose a benchmark to investigate models' logical reasoning capabilities in complex real-life scenarios. Based on the multi-hop chain of reasoning, the explanation form includes three main components. We evaluate the current best models' performance on this new explanation form.
  arXiv  Detail & Related papers  (2022-10-22T16:01:13Z)
• Generalized possibilistic Theories: the multipartite experiments problem [0.0]
  The complete axiomatic of Generalized possibilistic Theories is generalized and clarified in the present paper. The problem of bipartite experiments is then addressed as the main skill of this paper.
  arXiv  Detail & Related papers  (2022-07-19T06:34:40Z)
• Scientific Explanation and Natural Language: A Unified Epistemological-Linguistic Perspective for Explainable AI [2.7920304852537536]
  This paper focuses on the scientific domain, aiming to bridge the gap between theory and practice on the notion of a scientific explanation. Through a mixture of quantitative and qualitative methodologies, the presented study allows deriving the following main conclusions.
  arXiv  Detail & Related papers  (2022-05-03T22:31:42Z)
• Quantum realism: axiomatization and quantification [77.34726150561087]
  We build an axiomatization for quantum realism -- a notion of realism compatible with quantum theory. We explicitly construct some classes of entropic quantifiers that are shown to satisfy almost all of the proposed axioms.
  arXiv  Detail & Related papers  (2021-10-10T18:08:42Z)
• The Struggles of Feature-Based Explanations: Shapley Values vs. Minimal Sufficient Subsets [61.66584140190247]
  We show that feature-based explanations pose problems even for explaining trivial models. We show that two popular classes of explainers, Shapley explainers and minimal sufficient subsets explainers, target fundamentally different types of ground-truth explanations.
  arXiv  Detail & Related papers  (2020-09-23T09:45:23Z)
• Unscrambling the omelette of causation and inference: The framework of causal-inferential theories [0.0]
  We introduce the notion of a causal-inferential theory using a process-theoretic formalism. Recasting the notions of operational and realist theories in this mold clarifies what a realist account of an experiment offers beyond an operational account. We argue that if one can identify axioms for a realist causal-inferential theory such that the notions of causation and inference can differ from their conventional (classical) interpretations, then one has the means of defining an intrinsically quantum notion of realism.
  arXiv  Detail & Related papers  (2020-09-07T17:58:22Z)
• A structure theorem for generalized-noncontextual ontological models [0.0]
  We use a process-theoretic framework to prove that every generalized-noncontextual ontological model of a tomographically local operational theory has a surprisingly rigid and simple mathematical structure. We extend known results concerning the equivalence of different notions of classicality from prepare-measure scenarios to arbitrary compositional scenarios.
  arXiv  Detail & Related papers  (2020-05-14T17:28:19Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.