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arXiv · 1706.08503

Fast optimization algorithms and the cosmological constant

Ning Bao·Raphael Bousso·Stephen Jordan·Brad Lackey
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Abstract

Denef and Douglas have observed that in certain landscape models the problem of finding small values of the cosmological constant is a large instance of an NP-hard problem. The number of elementary operations (quantum gates) needed to solve this problem by brute force search exceeds the estimated computational capacity of the observable universe. Here we describe a way out of this puzzling circumstance: despite being NP-hard, the problem of finding a small cosmological constant can be attacked by more sophisticated algorithms whose performance vastly exceeds brute force search. In fact, in some parameter regimes the average-case complexity is polynomial. We demonstrate this by explicitly finding a cosmological constant of order $10^{-120}$ in a randomly generated $10^9$-dimensional ADK landscape.

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Ning Bao, Raphael Bousso, Stephen Jordan, Brad Lackey. 2017-06-26. Fast optimization algorithms and the cosmological constant. https://doi.org/10.1103/physrevd.96.103512

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