International Journal of Theoretical Physics (2023) 62:149
https://doi.org/10.1007/s10773-023-05394-w
RESEARCH
Quantum Entanglement and Encoding Algorithm
Cesarino Bertini
1
· Roberto Leporini
2
· Sergio Moriani
2
Received: 25 April 2023 / Accepted: 23 May 2023
© The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2023
Abstract
Entanglement is a resource for quantum computation and information tasks. It has increas-
ingly become clear that entanglement may be brought forth in combination of concepts as
“(the) Animal Acts” or “Animal (eats) Food” rather than being unique to micro-physical sys-
tems like photons or electrons. We extend the approach to the combination of three concepts
which determine non-classical statistical correlations. Moreover, we introduce a new vector
encoding algorithm that takes entanglement into account.
Keywords Entanglement · Encoding
1 Introduction
How can a mathematical model based on quantum theory capture the meaning of sentences
that depend on the whole context and not just on their parts? Quantum computational seman-
tics is an approach that uses quantum theory to model the semantic function of language. It
assumes that meanings are represented by quantum information quantities, such as states of
qudit systems represented by density operators of a Hilbert space. Quantum theory allows for
holistic and contextual features, such as superposition, entanglement and uncertainty, which
can account for how sentences can have different meanings depending on the situation.
Human perception and thought appear to be primarily synthetic, as is well known. We imme-
diately create a Gestalt, or a broad conception of an object. The main foundation of rational
activity appears to be Gestaltic patterns as well. The analytical and compositional framework
of classical semantics, which essentially determines the meaning of a compound expression
All authors contributed equally to this work.
B Roberto Leporini
roberto.leporini@unibg.it
Cesarino Bertini
cesarino.bertini@unibg.it
Sergio Moriani
sergio.moriani@guest.unibg.it
1
Department of Management, University of Bergamo, via dei Caniana 2, Bergamo I-24127,
BG, Italy
2
Department of Economics, University of Bergamo, via dei Caniana 2, Bergamo I-24127, BG, Italy
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