A ghost-free polynomially bounded scalar theory with momentum-dependent interactions that cancels all loop divergences to all orders, with finite one-loop self-energy and beta function computed, plus a variant with zero mass renormalization.
Consistent Use of the Standard Model Effective Potential
4 Pith papers cite this work. Polarity classification is still indexing.
abstract
The stability of the Standard Model is determined by the true minimum of the effective Higgs potential. We show that the potential at its minimum when computed by the traditional method is strongly dependent on the gauge parameter. It moreover depends on the scale where the potential is calculated. We provide a consistent method for determining absolute stability independent of both gauge and calculation scale, order by order in perturbation theory. This leads to a revised stability bounds mH > (129.4 \pm 2.3) GeV and mt < (171.2 \pm 0.3)GeV. We also show how to evaluate the effect of new physics on the stability bound without resorting to unphysical field values.
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2026 4verdicts
UNVERDICTED 4roles
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background 2representative citing papers
PPO reinforcement learning accelerates identification of gravitational wave signals from supercooled phase transitions in a minimal dark U(1)_x sector compared to Monte Carlo sampling.
A heat kernel plus background field method computes gauge-invariant beta functions and anomalous dimensions without diagrams by treating open and closed derivatives consistently.
A minimal extension of the Standard Model with three heavy Majorana neutrinos simultaneously realizes fermionic dark matter, a strong first-order electroweak phase transition, and low-scale resonant leptogenesis consistent with neutrino data.
citing papers explorer
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An Ultraviolet Finite Theory of Scalars
A ghost-free polynomially bounded scalar theory with momentum-dependent interactions that cancels all loop divergences to all orders, with finite one-loop self-energy and beta function computed, plus a variant with zero mass renormalization.
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Supercool with PPO: Exploring Supercooled Phase Transitions via Reinforcement Learning
PPO reinforcement learning accelerates identification of gravitational wave signals from supercooled phase transitions in a minimal dark U(1)_x sector compared to Monte Carlo sampling.
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Background Fields Meet the Heat Kernel: Gauge Invariance and RGEs without diagrams
A heat kernel plus background field method computes gauge-invariant beta functions and anomalous dimensions without diagrams by treating open and closed derivatives consistently.
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Solving Cosmological Puzzles using Finite Temperature $\nu$SMEFT
A minimal extension of the Standard Model with three heavy Majorana neutrinos simultaneously realizes fermionic dark matter, a strong first-order electroweak phase transition, and low-scale resonant leptogenesis consistent with neutrino data.