A quantum geometric model of similarity

No other study has had as great an impact on the development of the similarity literature as that of Tversky (1977), which provided compelling demonstrations against all the fundamental assumptions of the popular, and extensively employed, geometric similarity models. Notably, similarity judgments were shown to violate symmetry and the triangle inequality, and also be subject to context effects, so that the same pair of items would be rated differently, depending on the presence of other items. Quantum theory provides a generalized geometric approach to similarity and can address several of Tversky’s (1997) main findings. Similarity is modeled as quantum probability, so that asymmetries emerge as order effects, and the triangle equality violations and the diagnosticity effect can be related to the context-dependent properties of quantum probability. We so demonstrate the promise of the quantum approach for similarity and discuss the implications for representation theory in general

Quantum cognition and decision theories: A tutorial

Models of cognition and decision making based on quantum theory have been the subject of much interest recently. Quantum theory provides an alternative probabilistic framework for modelling decision making compared with classical probability theory, and has been successfully used to address behaviour considered paradoxical or irrational from a classical point of view. The purpose of this tutorial is to give an introduction to quantum models, with a particular emphasis on how to build these models in practice. Examples are provided by the study of order effects on judgements, and we will show how order effects arise from the structure of the theory. In particular, we show how to derive the recent discovery of a particular constraint on order effects implied by quantum models, called the Quantum Question (QQ) Equality, which does not appear to be derivable from alternative accounts, and which has been experimentally verified to high precision. However the general theory and methods of model construction we will describe are applicable to any quantum cognitive model. Our hope is that this tutorial will give researchers the confidence to construct simple quantum models of their own, particularly with a view to testing these against existing cognitive theories

A quantum theoretical explanation for probability judgment errors

A quantum probability model is introduced and used to explain human probability judgment errors including the conjunction, disjunction, inverse, and conditional fallacies, as well as unpacking effects and partitioning effects. Quantum probability theory is a general and coherent theory based on a set of (von Neumann) axioms which relax some of the constraints underlying classic (Kolmogorov) probability theory. The quantum model is compared and contrasted with other competing explanations for these judgment errors including the representativeness heuristic, the averaging model, and a memory retrieval model for probability judgments. The quantum model also provides ways to extend Bayesian, fuzzy set, and fuzzy trace theories. We conclude that quantum information processing principles provide a viable and promising new way to understand human judgment and reasoning

From real materials to model Hamiltonians with density matrix downfolding

Due to advances in computer hardware and new algorithms, it is now possible to perform highly accurate many-body simulations of realistic materials with all their intrinsic complications. The success of these simulations leaves us with a conundrum: how do we extract useful physical models and insight from these simulations? In this article, we present a formal theory of downfolding--extracting an effective Hamiltonian from first-principles calculations. The theory maps the downfolding problem into fitting information derived from wave functions sampled from a low-energy subspace of the full Hilbert space. Since this fitting process most commonly uses reduced density matrices, we term it density matrix downfolding (DMD).Comment: 24 pages, 12 figures; Huihuo Zheng and Hitesh J. Changlani contributed equally to this wor

Public Opinion towards Welfare State Reform: The Role of Political Trust and Government Satisfaction

The traditional welfare state, which emerged as a response to industrialization, is not well equipped toaddress the challenges of today’s post-industrial knowledge economies. Experts and policymakers have thereforecalled for welfare state readjustment towards a ‘social investment’ model (focusing on human skills and capabilities).Under what conditions are citizens willing to accept such future-oriented reforms? We point at the crucialbut hitherto neglected role of citizens’ trust in and satisfaction with government. Trust and satisfaction matterbecause future-oriented reforms generate uncertainties, risks and costs, which trust and government satisfactioncan attenuate. We offer micro-level causal evidence using experiments in a representative survey covering eightEuropean countries and confirm these findings with European Social Survey data for 22 countries. We find thattrust and government satisfaction increase reform support and moderate the effects of self-interest and ideologicalstandpoints. These findings have crucial implications not least because they help explain why some countriesmanage – but others fail – to enact important reforms.Introduction Under what conditions do citizens accept reforms? Why governmental trust and satisfaction affect support for future-oriented welfare state reforms Research design Study 1: Three survey experiments in eight countries Findings Study 2: ESS survey Findings Concluding discussion Acknowledgements Supporting information Reference

Modeling Concept Combinations in a Quantum-theoretic Framework

We present modeling for conceptual combinations which uses the mathematical formalism of quantum theory. Our model faithfully describes a large amount of experimental data collected by different scholars on concept conjunctions and disjunctions. Furthermore, our approach sheds a new light on long standing drawbacks connected with vagueness, or fuzziness, of concepts, and puts forward a completely novel possible solution to the 'combination problem' in concept theory. Additionally, we introduce an explanation for the occurrence of quantum structures in the mechanisms and dynamics of concepts and, more generally, in cognitive and decision processes, according to which human thought is a well structured superposition of a 'logical thought' and a 'conceptual thought', and the latter usually prevails over the former, at variance with some widespread beliefsComment: 5 pages. arXiv admin note: substantial text overlap with arXiv:1311.605

Forestiera acuminata (Michx.) Poir.

https://thekeep.eiu.edu/herbarium_specimens_byname/21061/thumbnail.jp

TI-games I: An Exploration of Type Indeterminacy In Strategic Decision-Making

The Type Indeterminacy model is a theoretical framework that formalizes the constructive preference perspective suggested by Kahneman and Tversky. In this paper we explore an extention of the TI-model from simple to strategic decision-making. A 2X2 game is investigated. We first show that in a one-shot simultaneaous move setting the TI-model is equivalent to a standard incomplete information model. We then let the game be preceded by a cheap-talk promise exchange game. We show in an example that in the TI-model the promise stage can have impact on next following behavior when the standard classical model predicts no impact whatsoever. The TI approach differs from other behavioral approaches in identifying the source of the effect of cheap-talk promises in the intrinsic indeterminacy of the players' type.Comment: 18