arXiv subjects

Susan Coppersmith

Publications and source records attributed to Susan Coppersmith.

3 recordsLinked to original sources

arXiv2026

Structural disorder and critical voltage scaling in Al/AlOx/Al Josephson junction arrays

The insulating state of one-dimensional Josephson junction (JJ) arrays is governed by collective charge dynamics and disorder-induced pinning, resulting in a finite critical voltage under dc bias. Here, we investigate the influence of fabrication-induced structural defects on the critical-voltage scaling of small-capacitance Aluminium-Aluminium oxide-Aluminium (Al/AlOx/Al) JJ arrays. Controlled variation of the aluminium evaporation rate produces pronounced changes in grain morphology and room-temperature junction resistance. Despite these substantial structural modifications, the normalised critical-voltage scaling is preserved, demonstrating that the collective transport behaviour is remarkably robust against this class of fabrication-induced defects. In contrast, the deliberate introduction of nanoscale gaps into the junctions introduces additional junction-to-junction structural variations that systematically modify the normalised scaling behaviour. Likewise, in situ postfabrication oxidation alters the scaling coefficient while preserving the functional form of the scaling law, indicating that the collective transport is sensitive to specific classes of structural modifications. These results establish which fabrication-induced structural defects influence the collective transport in insulating Al/AlOx/Al Josephson junction arrays, providing new insight into the role of fabrication-induced structural disorder and practical guidance for the design of future Quantum Phase Slip (QPS) devices.

cond-mat.supr-con↗

arXiv2002

One-dimensional quantum walks with absorbing boundaries

In this paper we analyze the behavior of quantum random walks. In particular we present several new results for the absorption probabilities in systems with both one and two absorbing walls for the one-dimensional case. We compute these probabilites both by employing generating functions and by use of an eigenfunction approach. The generating function method is used to determine some simple properties of the walks we consider, but appears to have limitations. The eigenfunction approach works by relating the problem of absorption to a unitary problem that has identical dynamics inside a certain domain, and can be used to compute several additional interesting properties, such as the time dependence of absorption. The eigenfunction method has the distinct advantage that it can be extended to arbitrary dimensionality. We outline the solution of the absorption probability problem of a (d-1)-dimensional wall in a d-dimensional space.

quant-ph↗

arXiv2002

Boolean Dynamics with Random Couplings

This paper reviews a class of generic dissipative dynamical systems called N-K models. In these models, the dynamics of N elements, defined as Boolean variables, develop step by step, clocked by a discrete time variable. Each of the N Boolean elements at a given time is given a value which depends upon K elements in the previous time step. We review the work of many authors on the behavior of the models, looking particularly at the structure and lengths of their cycles, the sizes of their basins of attraction, and the flow of information through the systems. In the limit of infinite N, there is a phase transition between a chaotic and an ordered phase, with a critical phase in between. We argue that the behavior of this system depends significantly on the topology of the network connections. If the elements are placed upon a lattice with dimension d, the system shows correlations related to the standard percolation or directed percolation phase transition on such a lattice. On the other hand, a very different behavior is seen in the Kauffman net in which all spins are equally likely to be coupled to a given spin. In this situation, coupling loops are mostly suppressed, and the behavior of the system is much more like that of a mean field theory. We also describe possible applications of the models to, for example, genetic networks, cell differentiation, evolution, democracy in social systems and neural networks.

nlin.AO↗