scholarly journals Observer Effects on Quantum Randomness: Testing Micro-Psychokinetic Effects of Smokers on Addiction-Related Stimuli

2018 ◽  
Vol 32 (2) ◽  
pp. 265-297 ◽  
Author(s):  
Markus A. Maier ◽  
Moritz C. Dechamps
Keyword(s):  
Quantum Randomness ◽  
Observer Effects

Extraction of quantum randomness

2020 ◽  
Author(s):  
I.M. Arbekov ◽  
Sergei N. Molotkov
Keyword(s):  
Quantum Randomness

scholarly journals The Topological Origin of Quantum Randomness

Symmetry ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 581
Author(s):  
Stefan Heusler ◽  
Paul Schlummer ◽  
Malte S. Ubben
Keyword(s):  
High School ◽  
Hilbert Space ◽  
Group Theory ◽  
Lorentz Group ◽  
Quantum Physics ◽  
Time Development ◽  
Mathematical Structures ◽  
Stochastic Nature ◽  
Quantum Randomness ◽  
And Topology

What is the origin of quantum randomness? Why does the deterministic, unitary time development in Hilbert space (the ‘4π-realm’) lead to a probabilistic behaviour of observables in space-time (the ‘2π-realm’)? We propose a simple topological model for quantum randomness. Following Kauffmann, we elaborate the mathematical structures that follow from a distinction(A,B) using group theory and topology. Crucially, the 2:1-mapping from SL(2,C) to the Lorentz group SO(3,1) turns out to be responsible for the stochastic nature of observables in quantum physics, as this 2:1-mapping breaks down during interactions. Entanglement leads to a change of topology, such that a distinction between A and B becomes impossible. In this sense, entanglement is the counterpart of a distinction (A,B). While the mathematical formalism involved in our argument based on virtual Dehn twists and torus splitting is non-trivial, the resulting haptic model is so simple that we think it might be suitable for undergraduate courses and maybe even for High school classes.

scholarly journals The Daubert/Kumho Implications of Observer Effects in Forensic Science: Hidden Problems of Expectation and Suggestion

2002 ◽  
Vol 90 (1) ◽  
pp. 1 ◽  
Author(s):  
D. Michael Risinger ◽  
Michael J. Saks ◽  
William C. Thompson ◽  
Robert Rosenthal
Keyword(s):  
Forensic Science ◽  
Observer Effects

Observer Effects of Punishment in a Distribution Network

2013 ◽  
Vol 50 (5) ◽  
pp. 627-643 ◽  
Author(s):  
Danny T. Wang ◽  
Flora F. Gu ◽  
Maggie Chuoyan Dong
Keyword(s):  
Information Asymmetry ◽  
Information Flow ◽  
Distribution Network ◽  
Trust Building ◽  
Attitudes And Behaviors ◽  
Building Process ◽  
Relational Embeddedness ◽  
Managerial Implications ◽  
Deterrence Effect ◽  
Observer Effects

In a distribution network, a punishment event not only affects the disciplined distributor but also changes the attitudes and behaviors of others in the network (i.e., observers). By moving beyond a dyadic view of punishment, this article considers the effects of punishment on observers and integrates insights from social learning, fairness heuristic, and social network theories. The resulting framework of the observer effects of punishment in a distribution network, empirically tested with a survey in China, reveals two mechanisms through which punishment leads to reduced observer opportunism: (1) a direct deterrence effect and (2) a trust-building process. Moreover, two information-related constructs moderate the observer effects differently. The disciplined distributor's relational embeddedness, which motivates greater information flow to observers, aggravates the problem of information asymmetry against the manufacturer, making punishment less deterrent for observers. In contrast, the manufacturer's monitoring capability, which reduces information asymmetry, strengthens observer effects. The authors discuss both theoretical and managerial implications of using punishment to achieve collaboration from a wide network of channel members.

scholarly journals Testing the Waters: Behavior across Participant Pools

2021 ◽  
Vol 111 (2) ◽  
pp. 687-719
Author(s):  
Erik Snowberg ◽  
Leeat Yariv
Keyword(s):  
External Validity ◽  
Large Scale ◽  
Student Population ◽  
University Student ◽  
Mechanical Turk ◽  
Amazon Mechanical Turk ◽  
Lab Experiments ◽  
The Us ◽  
Small Set ◽  
Observer Effects

We leverage a large-scale incentivized survey eliciting behaviors from (almost) an entire undergraduate university student population, a representative sample of the US population, and Amazon Mechanical Turk (MTurk) to address concerns about the external validity of experiments with student participants. Behavior in the student population offers bounds on behaviors in other populations, and correlations between behaviors are similar across samples. Furthermore, non-student samples exhibit higher levels of noise. Adding historical lab participation data, we find a small set of attributes over which lab participants differ from non-lab participants. An additional set of lab experiments shows no evidence of observer effects. (JEL C83, D90, D91)

Observer effects and examiner bias

2007 ◽  
pp. 51-83
Author(s):  
Craig M. Cooley ◽  
Brent E. Turvey
Keyword(s):  
Observer Effects
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