July 1736

Average mutual information for random fermionic Gaussian quantum states

Studying the typical entanglement entropy of a bipartite system when averaging over different ensembles of pure quantum states has been instrumental in different areas of physics, ranging from many-body quantum chaos to black hole evaporation. We extend such analysis to open quantum systems and mixed states, where we compute the typical mutual information in a bipartite system averaged over the ensemble of mixed Gaussian states with a fixed spectrum. Tools from random matrix theory and determinantal point processes allow us to compute arbitrary k-point correlation functions of the singular values of the corresponding complex structure in a subsystem for a given spectrum in the full system. In particular, we evaluate the average von Neumann entropy in a subsystem based on the level density and the average mutual information. Those results are given for finite system size as well as in the thermodynamic limit.

Taming Thiemann’s Hamiltonian constraint in canonical loop quantum gravity: reversibility, eigenstates and graph-change analysis

The Hamiltonian constraint remains an elusive object in loop quantum gravity because its action on spinnetworks leads to changes in their corresponding graphs. As a result, calculations in loop quantum gravity are often considered unpractical, and neither the eigenstates of the Hamiltonian constraint, which form the physical space of states, nor the concrete effect of its graph-changing character on observables are entirely known. Much worse, there is no reference value to judge whether the commonly adopted graph-preserving approximations lead to results anywhere close to the non-approximated dynamics. Our work sheds light on many of these issues, by devising a new numerical tool that allows us to implement the action of the Hamiltonian constraint without the need for approximations and to calculate expectation values for geometric observables. To achieve that, we fill the theoretical gap left in the derivations of the action of the Hamiltonian constraint on spinnetworks: we provide the first complete derivation of such action for the case of 4-valent spinnetworks, while updating the corresponding derivation for 3-valent spinnetworks. Our derivations also include the action of the volume operator. By proposing a new approach to encode spinnetworks into functions of lists and the derived formulas into functionals, we implement both the Hamiltonian constraint and the volume operator numerically. We are able to transform spinnetworks with graph-changing dynamics perturbatively and verify that volume expectation values have rather different behavior from the approximated, graph-preserving results. Furthermore, using our tool we find a family of potentially relevant solutions of the Hamiltonian constraint. Our work paves the way to a new generation of calculations in loop quantum gravity, in which graph-changing results and their phenomenology can finally be accounted for and understood.

Computing the graph-changing dynamics of loop quantum gravity

In loop quantum gravity (LQG), quantum states of the gravitational field are represented by labelled graphs called spinnetworks. Their dynamics can be described by a Hamiltonian constraint, which modifies the spinnetwork graphs. Fixed graph approximations of the dynamics have been extensively studied, but its full graph-changing action so far remains elusive. The latter, alongside the solutions of its constraint, are arguably the missing features to access physically correct quantum-relativistic phenomenology from canonical LQG. Here, we introduce the first numerical tool that implements graph-changing dynamics via the Hamiltonian constraint. We find new solutions to this constraint and show that some quantum-geometrical observables behave differently than in the graph-preserving truncation. This work aims at fostering a new era of numerical simulations in canonical LQG that, crucially, embrace the graph-changing aspects of its dynamics, laying aside debated approximations.