Emergent Gravity from Quantum Information Flow: A Modified Dirac- Equation Perspective
Abstract
We present a unified thermodynamic framework in which the flow of quantum information -- described covariantly by the emergent entropy current vector s^μ-- couples to fermionic matter and suggests a possible effective origin for spacetime geometry within a low-energy effective field theory. The Dirac equation is modified as (iℏγμ ∂μ-mc+λγμ sμ)ψ=0, where dimensional analysis identifies λ as a coupling constant of mass dimension [λ]=-2, naturally placing the theory as a low-energy effective field theory. The modified dispersion relation E=-λs0 c±c√(p2+m2 c2 ) shows that uniform entropy flow produces only an overall energy shift, while non-uniform flows induce a complete gauge-like structure in the non-relativistic limit: the spatial entropy current s acts as a vector potential, and its curl generates an effective Zeeman-type field Beff=(λ/m)∇×s, driving spin precession via ωentropy=(λ/m)∇×s. Extending the Proca-type dynamics of sμ to curved spacetime with non-minimal curvature coupling, we quantize the entropy flow field and integrate out its quantum fluctuations. In this framework, the Einstein-Hilbert action emerges as the low-energy effective action, with Newton's constant G determined by the entropy field's vacuum expectation value. The linearized theory yields a massive spin-2 excitation -- the emergent graviton -- with dispersion E2=p2+ms2, where the entropy field mass ms is constrained by LIGO/Virgo gravitational-wave observations to ms≲10-20eV. Using STAR data on Λ…
Read the paper
Related studies
- Chaos and quantum thermalization
- The Dalton quantum chemistry program system
- Cord Blood Leptin and Adiponectin as Predictors of Adiposity in Children at 3 Years of Age: A Prospective Cohort Study
- Quantitative metabolomics by H-NMR and LC-MS/MS confirms altered metabolic pathways in diabetes
- Stable adiabatic quantum batteries
- A novel self-lipid antigen targets human T cells against CD1c(+) leukemias
Go deeper in Evidence Hub
Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.