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Scientific American

Inferring the Many Worlds.

Graham P. Collins

Published Jan 1, 2007• 0 citations
OpenAlex

Related papers

Locating the many worlds.

Joe Rosen

•Jan 1, 1991•0 citations

The Structure of a Quantum World*

Jill North

I argue that the fundamental space of a quantum mechanical world is the wavefunction's space. I argue for this using some very general principles that guide our inferences to the fundamental nature of a world, for any fundamental physical theory. I suggest that ordinary three-dimensional space exists in such a world, but is non-fundamental; it emerges from the fundamental space of the wavefunction.

Oxford University Press eBooks•Apr 8, 2013•121 citations

Many Worlds

Mariette DiChristina

Scientific American•Dec 16, 2014•0 citations

Distributing Fuzzy Inference Engines on Quantum Computers

Giovanni Acampora, Alfredo A. Massa, Roberto Schiattarella +1 more

Recently, a quantum algorithm called Quantum Fuzzy Inference Engine (QFIE) has been introduced with the main goal of providing exponential speedup in the execution of a Mamdani fuzzy inference engine. This quantum algorithm achieves this result by modeling a fuzzy rule base with a quantum oracle, a black box that is widely used to estimate functions using quantum mechanical principles. Although QFIE offers the possibility of performing efficient fuzzy computation on quantum computers, its real-world applicability is limited by the high levels of noise still present in current quantum computers. Consequently, it is necessary to introduce technological arrangements to make QFIE fully functional in practical cases until noise-free quantum computers are released. This paper addresses this issue by designing a distributed version of QFIE, based on the D-NISQ reference model, to distribute the computation of subsets of fuzzy rules across multiple quantum processors and minimize the negative impact of quantum noise. Experimental results prove that this distributed version of QFIE is able to significantly improve the accuracy of fuzzy computation on quantum devices, making QFIE applicable in real-world scenarios.

IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)•Aug 13, 2023•7 citations

Parallel Dialogues: What LLM Inference Can (and Cannot) Teach Us About the Many-Worlds Interpretation — A Companion Note

Earth Vitaly Shcherbak — Institution: Montenegro, San Francisco) Claude (Anthropic PBC

A companion note to "Evidence for the Many-Worlds Interpretation of Quantum Mechanics via Large Language Model Architecture" (10.5281/zenodo.20533902). Revisits the structural analogy between parallel LLM inference and Everettian branching honestly: identifies what the analogy illustrates well (shared origin, isolated states, irreversible branch selection) and where it breaks down as physics — chiefly, the analogy is externally observable in a way that MWI branches, by construction, cannot be.

•Sep 15, 2026•0 citations

Many Worlds

Benjamin Bähr, Boris Lemmer, Rina Piccolo

Springer eBooks•Jan 1, 2016•0 citations
Recently, a quantum algorithm called Quantum Fuzzy Inference Engine (QFIE) has been introduced with the main goal of providing exponential speedup in the execution of a Mamdani fuzzy inference engine. This quantum algorithm achieves this result by modeling a fuzzy rule base with a quantum oracle, a black box that is widely used to estimate functions using quantum mechanical principles. Although QFIE offers the possibility of performing efficient fuzzy computation on quantum computers, its real-world applicability is limited by the high levels of noise still present in current quantum computers. Consequently, it is necessary to introduce technological arrangements to make QFIE fully functional in practical cases until noise-free quantum computers are released. This paper addresses this issue by designing a distributed version of QFIE, based on the D-NISQ reference model, to distribute the computation of subsets of fuzzy rules across multiple quantum processors and minimize the negative impact of quantum noise. Experimental results prove that this distributed version of QFIE is able to significantly improve the accuracy of fuzzy computation on quantum devices, making QFIE applicable in real-world scenarios.
A companion note to "Evidence for the Many-Worlds Interpretation of Quantum Mechanics via Large Language Model Architecture" (10.5281/zenodo.20533902). Revisits the structural analogy between parallel LLM inference and Everettian branching honestly: identifies what the analogy illustrates well (shared origin, isolated states, irreversible branch selection) and where it breaks down as physics — chiefly, the analogy is externally observable in a way that MWI branches, by construction, cannot be.