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Motivated by the search for geometric observables in nonperturbative quantum gravity, we define a notion of coarse-grained Ricci curvature. It is based on a particular way of extracting the local Ricci curvature of a smooth Riemannian manifold by comparing the distance between pairs of spheres with that of their centres. The quantum Ricci curvature is designed for use on non-smooth and discrete metric spaces, and to satisfy the key criteria of scalability and computability. We test the prescription on a variety of regular and random piecewise flat spaces, mostly in two dimensions. This enables us to quantify its behaviour for short lattices distances and compare its large-scale behaviour with that of constantly curved model spaces. On the triangulated spaces considered, the quantum Ricci curvature has good averaging properties and reproduces classical characteristics on scales large compared to the discretization scale.
43 pages, 27 figures
High Energy Physics - Theory, High Energy Physics - Lattice, High Energy Physics - Theory (hep-th), Theoretical High Energy Physics, High Energy Physics - Lattice (hep-lat), FOS: Physical sciences, High Energy Physics, General Relativity and Quantum Cosmology (gr-qc), General Relativity and Quantum Cosmology
High Energy Physics - Theory, High Energy Physics - Lattice, High Energy Physics - Theory (hep-th), Theoretical High Energy Physics, High Energy Physics - Lattice (hep-lat), FOS: Physical sciences, High Energy Physics, General Relativity and Quantum Cosmology (gr-qc), General Relativity and Quantum Cosmology
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 31 | |
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influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |