Designing pretty good state transfer via isospectral reductions
M. R\"ontgen, N. E. Palaiodimopoulos, C. V. Morfonios, I. Brouzos, M., Pyzh, F. K. Diakonos, P. Schmelcher

TL;DR
This paper introduces a novel method combining isospectral reductions and eigenvector conditions to design networks capable of high-fidelity quantum state transfer, with applications in quantum information storage.
Contribution
It develops a new approach to engineer networks with pretty good state transfer using isospectral reductions and eigenvector properties, enabling robust quantum information storage.
Findings
Networks with PGST can be systematically designed using the proposed method.
Networks can be manipulated to enable robust qubit storage.
The approach allows for the creation of Hamiltonians with localized states for quantum memory.
Abstract
We present an algorithm to design networks that feature pretty good state transfer (PGST), which is of interest for high-fidelity transfer of information in quantum computing. Realizations of PGST networks have so far mostly relied either on very special network geometries or imposed conditions such as transcendental on-site potentials. However, it was recently shown [Eisenberg et al., arXiv:1804.01645] that PGST generally arises when a network's eigenvectors and the factors of its characteristic polynomial fulfill certain conditions, where correspond to eigenvectors which have parity on the input and target sites. We combine this result with the so-called isospectral reduction of a network to obtain from a dimensionally reduced form of the Hamiltonian. Equipped with the knowledge of the factors , we show how a variety of setups can be…
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