Causal Order Multicast Protocol Using Minimal Message History Information

Author(s):  
Chayoung Kim ◽  
Jinho Ahn
Author(s):  
David K. Skelly

This chapter presents two examples to demonstrate that natural history is the necessary basis of any reliable understanding of the world. More than a half century ago, Rachel Carson revolutionized the public’s view of pesticides. The foundation of her success was the careful use of natural history data, collated from across North America. The examples she assembled left little doubt that DDT and other pesticides were causing a widespread decline in birds. More recently, the case for the impact of atrazine on wildlife was based on laboratory experiments, without the advantage of natural history observations. For atrazine, natural history observations now suggest that other chemical agents are more likely to be responsible for feminization of wildlife populations. Developing expectations for scientists to collect natural history information can help to avoid over-extrapolating lab results to wild populations, a tendency often seen when those lab results conform to preconceptions about chemicals in the environment.


2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Jonathan Barrett ◽  
Robin Lorenz ◽  
Ognyan Oreshkov

AbstractCausal reasoning is essential to science, yet quantum theory challenges it. Quantum correlations violating Bell inequalities defy satisfactory causal explanations within the framework of classical causal models. What is more, a theory encompassing quantum systems and gravity is expected to allow causally nonseparable processes featuring operations in indefinite causal order, defying that events be causally ordered at all. The first challenge has been addressed through the recent development of intrinsically quantum causal models, allowing causal explanations of quantum processes – provided they admit a definite causal order, i.e. have an acyclic causal structure. This work addresses causally nonseparable processes and offers a causal perspective on them through extending quantum causal models to cyclic causal structures. Among other applications of the approach, it is shown that all unitarily extendible bipartite processes are causally separable and that for unitary processes, causal nonseparability and cyclicity of their causal structure are equivalent.


Author(s):  
Kohei Ogura ◽  
Hideaki Imaizumi ◽  
Masaki Minami ◽  
Osamu Nakamura ◽  
Jun Murai

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