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Why does Monte Carlo fail to work properly in high-dimensional optimization problems?

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arxiv 1603.00311 v2 pith:LY2XFKTR submitted 2016-03-01 math.OC

Why does Monte Carlo fail to work properly in high-dimensional optimization problems?

classification math.OC
keywords answercarlofailformulatedhigh-dimensionalmonteoptimizationproblems
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. Spontaneous Symmetry Breaking and the Vacuum Displacement Principle: From Galactic Scales to Cosmic Fine-Tuning

    gr-qc 2026-04 conditional novelty 6.0

    A Higgs-type scalar vacuum field displaced by baryonic matter yields a Yukawa-corrected gravitational potential that replaces dark matter and dynamically relaxes the cosmological constant.

  2. Spontaneous Symmetry Breaking and the Vacuum Displacement Principle: From Galactic Scales to Cosmic Fine-Tuning

    gr-qc 2026-04 unverdicted novelty 4.0

    A vacuum scalar field with spontaneous symmetry breaking and matter coupling generates Yukawa-corrected gravity that accounts for flat galactic rotation curves and dynamically tracks the cosmological constant.