Entangled N-photon states for fair and optimal social decision making
- URL: http://arxiv.org/abs/2007.09146v2
- Date: Mon, 27 Jul 2020 04:43:18 GMT
- Title: Entangled N-photon states for fair and optimal social decision making
- Authors: Nicolas Chauvet, Guillaume Bachelier, Serge Huant, Hayato Saigo,
Hirokazu Hori, Makoto Naruse
- Abstract summary: This paper presents the theoretical principles necessary to find polarization-entangled N-photon states that can optimize the total resource output while ensuring equality among players.
Although a general formula for the N-player case is not presented here, general derivation rules and a verification algorithm are proposed.
- Score: 0.0
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Situations involving competition for resources among entities can be modeled
by the competitive multi-armed bandit (CMAB) problem, which relates to social
issues such as maximizing the total outcome and achieving the fairest resource
repartition among individuals. In these respects, the intrinsic randomness and
global properties of quantum states provide ideal tools for obtaining optimal
solutions to this problem. Based on the previous study of the CMAB problem in
the two-arm, two-player case, this paper presents the theoretical principles
necessary to find polarization-entangled N-photon states that can optimize the
total resource output while ensuring equality among players. These principles
were applied to two-, three-, four-, and five-player cases by using numerical
simulations to reproduce realistic configurations and find the best strategies
to overcome potential misalignment between the polarization measurement systems
of the players. Although a general formula for the N-player case is not
presented here, general derivation rules and a verification algorithm are
proposed. This report demonstrates the potential usability of quantum states in
collective decision making with limited, probabilistic resources, which could
serve as a first step toward quantum-based resource allocation systems.
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