Perturbed graphs achieve unit transport efficiency without environmental noise

Abstract

Coherent transport of an excitation through a network corresponds to continuous-time quantum walk on a graph, and the transport properties of the system may be radically different depending on the graph and on the initial state. The transport efficiency, i.e., the integrated probability of trapping at a certain vertex, is a measure of the success rate of the transfer process. Purely coherent quantum transport is known to be less efficient than the observed excitation transport, e.g., in biological systems, and there is evidence that environmental noise is indeed crucial for excitation transport. At variance with this picture, we here address purely coherent transport on highly symmetric graphs, and show analytically that it is possible to enhance the transport efficiency without environmental noise, i.e., using only a minimal perturbation of the graph. In particular, we show that adding an extra weight to one or two edges, depending on whether the initial state is localized or in a superposition of two vertex states, breaks the inherent symmetries of the graph and may be sufficient to achieve unit transport efficiency. We also briefly discuss the conditions to obtain a null transport efficiency, i.e., to avoid trapping.

Non-equilibrium dynamics of spin-lattice coupling

“…The tr-XRD experiments were performed at the Bernina endstation [28,29] of the ARAMIS branch of SwissFEL at the Paul Scherrer Institute (Switzerland). The tr-RSXD experiments were performed at the Furka endstation, which is a new endstation for time-resolved studies in condensed matters at the Athos branch of SwissFEL at Paul Scherrer Institute [30,31].…”

Quantum transport efficiency in noisy random-removal and small-world networks

“…Using similar arguments, Bose et al [9] have shown that the single link removal also allows perfect state transfer between the two nodes. The mechanism behind this counter-intuitive result is the elimination of destructive interference by removal of the single interaction [8,9,12,15,20,40]. The problem could also be addressed by using graph spectral theoretical concepts in terms of the eigenvalues and eigenvectors of the adjacency matrix A of the network.…”

Multiparameter estimation of continuous-time quantum walk Hamiltonians through machine learning

“…CTQWs are especially useful to model physical phenomena such as quantum transport of energy in quantum biological systems, quantum routing, and quantum state transfer. [60][61][62][63][64][65][66] They have been both realized and simulated experimentally on different platforms, such as photons, [67][68][69] trapped atoms and ions, 70,71 waveguide arrays, [72][73][74][75] microwaves, 76 and nuclear magnetic resonance. 77 In all these tasks, fine tuning of the Hamiltonian parameters is required in order to achieve reliable and satisfactory results.…”