Machine learning unveils multiple Pauli blockades in the transport spectroscopy of bilayer graphene double-quantum dots

TL;DR

This paper develops a theoretical and machine learning framework to identify multiple Pauli blockades in bilayer graphene double quantum dots, advancing understanding of spin-valley qubits in 2-D materials.

Contribution

It introduces a comprehensive model combining transport theory and machine learning to detect multiple Pauli blockades in 2-D material quantum-dot systems, a novel approach in the field.

Findings

Multiple resonances within a bias triangle were identified.

Multiple Pauli blockades can occur simultaneously in the system.

Machine learning effectively detects blockade regimes in real-time.

Abstract

Recent breakthroughs in the transport spectroscopy of 2-D material quantum-dot platforms have engendered a fervent interest in spin-valley qubits. In this context, Pauli blockades in double quantum dot structures form an important basis for multi-qubit initialization and manipulation. Focusing on double quantum dot structures, and the experimental results, we first build theoretical models to capture the intricate interplay between externally fed gate voltages and the physical properties of the 2-D system in such an architecture, allowing us to effectively simulate Pauli blockades. Employing the master equations for transport and considering extrinsic factors such as electron-photon interactions, we thoroughly investigate all potential occurrences of Pauli blockades. Notably, our research reveals two remarkable phenomena: (i) the existence of multiple resonances within a bias triangle, and (ii) the occurrence of multiple Pauli blockades. Leveraging our model to train a machine learning algorithm, we successfully develop an automated method for real-time detection of multiple Pauli blockade regimes. Through numerical predictions and validations against test data, we identify where and how many Pauli blockades are likely to occur. We propose that our model can effectively detect the generic class of Pauli blockades in practical experimental setups and hence serves as the foundation for future experiments on qubits that utilize 2-D material platforms.