Enhancement of Tc in the Superconductor-Insulator Phase Transition on Scale-Free Networks

TL;DR

This paper investigates how heterogeneity in scale-free networks influences the critical temperature of superconducting phase transitions, revealing that increased cutoff values can enhance superconductivity.

Contribution

It provides a detailed phase diagram analysis of a Random Transverse Ising Model on scale-free networks using advanced mean-field and quantum cavity methods, highlighting the role of network heterogeneity.

Findings

Critical temperature increases linearly with the branching ratio.

Fractal disorder can enhance the superconducting critical temperature.

Different behaviors observed in annealed vs quenched networks at low temperature.

Abstract

A road map to understand the relation between the onset of the superconducting state with the particular optimum heterogeneity in granular superconductors is to study a Random Tranverse Ising Model on complex networks with a scale-free degree distribution regularized by and exponential cutoff p(k) \propto k^{-\gamma}\exp[-k/\xi]. In this paper we characterize in detail the phase diagram of this model and its critical indices both on annealed and quenched networks. To uncover the phase diagram of the model we use the tools of heterogeneous mean-field calculations for the annealed networks and the most advanced techniques of quantum cavity methods for the quenched networks. The phase diagram of the dynamical process depends on the temperature T, the coupling constant J and on the value of the branching ratio <k(k-1)>/<k> where k is the degree of the nodes in the network. For fixed value of the coupling the critical temperature increases linearly with the branching ration which diverges with the increasing cutoff value \xi or value of the \gamma exponent \gamma< 3. This result suggests that the fractal disorder of the superconducting material can be responsible for an enhancement of the superconducting critical temperature. At low temperature and low couplings T<<1 and J<<1, instead, we observe a different behavior for annealed and quenched networks. In the annealed networks there is no phase transition at zero temperature while on quenched network we observe a Griffith phase dominated by extremely rare events and a phase transition at zero temperature. The Griffiths critical region, nevertheless, is decreasing in size with increasing value of the cutoff \xi of the degree distribution for values of the \gamma exponents \gamma< 3.