A topological field-effect memristor

TL;DR

This paper introduces a topological field-effect memristor based on quantum wells that combines coherent topological transport with memristive behavior, enabling reconfigurable, low-power, and robust electronic devices for quantum-neuromorphic computing.

Contribution

It demonstrates a novel topological memristor integrating coherent and incoherent transport with memory, advancing the development of hybrid quantum-neuromorphic architectures.

Findings

Achieves reconfigurable memristive states via topological edge channels.

Demonstrates dissipationless transport in one resistance state.

Provides a platform for robust, low-power quantum-neuromorphic devices.

Abstract

Overcoming the limitations of the von Neumann architecture requires new computational paradigms capable of solving complex problems efficiently. Quantum and neuromorphic computing rely on unconventional materials and device functionalities, yet achieving resilience to imperfections and reliable operation remains a major challenge. This has motivated growing interest in topological materials that provide robust and low-power operation while preserving coherence. However, integrating coherent topological transport with non-volatile memory functionality in a single reconfigurable device has remained challenging. In this work, we demonstrate a topological field-effect memristor based on inverted InAs/GaInSb/InAs trilayer quantum wells operating in the quantum spin Hall regime. The intrinsic floating-gate behavior allows one to reconfigure the transistor functionality into memristive functionality with broad electric-field tunability. Unlike other memristor implementations, one resistance state is governed entirely by dissipationless, coherent transport through helical edge channels, while the other arises from incoherent bulk conduction. By combining electrically tunable coherent and incoherent transport with memory functionality, our device realizes a prototypical topological electronic element that integrates coherent transport and adaptive memristive behavior, paving the way for hybrid quantum-neuromorphic architectures.