Superconducting Networks Achieve Abrupt Phase Transitions with Critical Scaling Behavior

The emergence of abrupt phase transitions in complex systems often requires intricate interdependencies between multiple networks, but new research demonstrates that such behaviour can also arise within a single physical system. Yuval Sallem, Nahala Yadid, and colleagues at Bar-Ilan University, alongside Xi Wang, Irina Volotsenko, and Bnaya Gross from Northeastern University, reveal that a single-layer superconducting network exhibiting both electrical connectivity and long-range thermal dependency undergoes a dramatic phase transition when heat dissipates within it. The team’s experimental and simulation work establishes that this transition, characterised by a sudden change in resistance and critical scaling, originates from heat flow and exhibits dynamics reminiscent of interdependent network theory. This discovery broadens understanding of phase transitions and suggests innovative approaches to controlling such changes in diverse fields, from materials science to biological systems, where dual interactions play a crucial role.

By carefully controlling heat dissipation within this system, scientists observed a mixed-order phase transition characterised by a discontinuous change in resistance and critical scaling behaviour, mirroring results obtained from interdependent network systems., This work broadens understanding of phase transitions and suggests that the presence of dual interactions, rather than multiple networks, is sufficient to generate complex critical phenomena. The system, featuring both electrical connectivity and long-range thermal dependency, offers a simpler platform for studying and controlling phase changes compared to interdependent networks which require separate physical layers. Researchers acknowledge that further investigation is needed to fully characterise the spatial extent and interplay of these interactions, with implications for diverse fields including information networks, traffic flow, neural networks, and the behaviour of solid materials.

Phase Transitions in Josephson Junction Networks

Supplementary information supports research on superconducting networks, demonstrating and characterising normal-to-superconducting and vice versa phase transitions. Researchers investigated how these transitions manifest in current flow patterns and are affected by the substrate material, exploring both continuous and abrupt phase transitions. Key concepts include Josephson junctions, which are the building blocks of the networks, and phase transitions themselves, representing the change in state from normal to superconducting.

Analysis of current flow mapping, substrate dependence, and resistance versus current curves reveals insights into the behaviour of the networks. Figures demonstrate continuous transitions characterised by gradual changes in current flow and smooth decreases in resistance, while abrupt transitions are marked by sudden changes in current flow and sharp drops in resistance. The substrate material influences the phase transition characteristics, as demonstrated by differences in resistance curves between silicon and glass substrates. This research provides insights into the mechanisms governing phase transitions in superconducting networks and highlights the importance of the substrate material in controlling network properties, with potential applications in sensors, detectors, and quantum computing.

Heat Drives Hysteretic Superconducting Transitions

This research demonstrates that abrupt, hysteretic normal-to-superconducting phase transitions, previously thought to require interconnected networks, can also occur within a single layer superconducting system featuring both electrical connectivity and long-range thermal dependency. By carefully controlling heat dissipation within this “Two Interactions Superconducting System”, scientists observed a mixed-order phase transition characterised by a discontinuous change in resistance and critical scaling behaviour, mirroring results obtained from interdependent network systems.

The findings establish heat flow as a key driver of these unique transitions and reveal the presence of long-lived transient states and scaling dynamics near the critical point. This work broadens understanding of phase transitions and suggests that the presence of dual interactions, rather than multiple networks, is sufficient to generate complex critical phenomena. Unlike interdependent networks which require separate physical layers, this single-layer system offers a simpler and more readily implementable platform for studying and controlling phase changes. The authors acknowledge that further investigation is needed to fully characterise the spatial extent and interplay of these interactions. This research has implications for diverse fields including information networks, traffic flow, neural networks, and even the behaviour of solid materials, suggesting new avenues for designing and controlling complex systems where multiple interactions are present.