Toller matrices T^(±) in causal spinfoam amplitudes satisfy T^(+) + T^(-) = D and admit equivalent definitions via analyticity, iε prescription, and boost-eigenvalue integrals that reproduce the Euclidean-to-Lorentzian Wick rotation.
Oriti,Group field theory as the 2nd quantization of Loop Quantum Gravity,Class
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abstract
We construct a 2nd quantized reformulation of canonical Loop Quantum Gravity at both kinematical and dynamical level, in terms of a Fock space of spin networks, and show in full generality that it leads directly to the Group Field Theory formalism. In particular, we show the correspondence between canonical LQG dynamics and GFT dynamics leading to a specific GFT model from any definition of quantum canonical dynamics of spin networks. We exemplify the correspondence of dynamics in the specific example of 3d quantum gravity. The correspondence between canonical LQG and covariant spin foam models is obtained via the GFT definition of the latter.
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Collective excitations analogous to phonons are derived in quantum gravity condensates within a group field theory model, yielding leading beyond-mean-field corrections to emergent Friedmann dynamics.
Field leakage into ER=EPR wormholes modifies hydrogen hyperfine splitting and may induce net charge, yielding constraints from existing precision data.
citing papers explorer
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Toller matrices and the Feynman $i\varepsilon$ in spinfoams
Toller matrices T^(±) in causal spinfoam amplitudes satisfy T^(+) + T^(-) = D and admit equivalent definitions via analyticity, iε prescription, and boost-eigenvalue integrals that reproduce the Euclidean-to-Lorentzian Wick rotation.
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Collective excitations in quantum gravity condensates
Collective excitations analogous to phonons are derived in quantum gravity condensates within a group field theory model, yielding leading beyond-mean-field corrections to emergent Friedmann dynamics.
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Testing ER = EPR with Hydrogen
Field leakage into ER=EPR wormholes modifies hydrogen hyperfine splitting and may induce net charge, yielding constraints from existing precision data.