Machine learning constrains non-commutative black hole parameters and reports consistency with Sgr A* Keck observations.
Explicit Derivation of Yang-Mills Self-Dual Solutions on non-Commutative Harmonic Space
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abstract
We develop the noncommutative harmonic space (NHS) analysis to study the problem of solving the non-linear constraint eqs of noncommutative Yang-Mills self-duality in four-dimensions. We show that this space, denoted also as NHS($\eta,\theta$), has two SU(2) isovector deformations $\eta^{(ij)}$ and $\theta^{(ij)}$ parametrising respectively two noncommutative harmonic subspaces NHS($\eta,0$) and NHS($0,\theta$) used to study the self-dual and anti self-dual noncommutative Yang-Mills solutions. We formulate the Yang-Mills self-dual constraint eqs on NHS($\eta,0$) by extending the idea of harmonic analyticity to linearize them. Then we give a perturbative self-dual solution recovering the ordinary one. Finally we present the explicit computation of an exact self-dual solution.
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gr-qc 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
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Constraining Black Hole Parameters in Non-Commutative Geometry using Machine Learning
Machine learning constrains non-commutative black hole parameters and reports consistency with Sgr A* Keck observations.