Strategies for quantum races
Troy Lee, Maharshi Ray, Miklos Santha

TL;DR
This paper introduces a game-theoretic framework for quantum races, analyzing strategic behavior and equilibrium strategies in quantum competitions, with applications to quantum Bitcoin mining and blockchain stability.
Contribution
It develops a novel model of multiplayer quantum races, characterizes Nash equilibria, and applies findings to quantum Bitcoin mining strategies and collision probabilities.
Findings
Identifies approximate symmetric Nash equilibria in quantum races.
Characterizes equilibria in no-tie quantum race variants.
Suggests quantum mining strategies reduce collision risks in Bitcoin.
Abstract
We initiate the study of quantum races, games where two or more quantum computers compete to solve a computational problem. While the problem of dueling algorithms has been studied for classical deterministic algorithms, the quantum case presents additional sources of uncertainty for the players. The foremost among these is that players do not know if they have solved the problem until they measure their quantum state. This question of `when to measure?' presents a very interesting strategic problem. We develop a game-theoretic model of a multiplayer quantum race, and find an approximate Nash equilibrium where all players play the same strategy. In the two-party case, we further show that this strategy is nearly optimal in terms of payoff among all symmetric Nash equilibria. A key role in our analysis of quantum races is played by a more tractable version of the game where there is no…
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