Unifying recent experiments on spin-valley locking in TMDC quantum dots

TL;DR

This paper presents a unified theoretical framework using quantum transport theory to simulate and understand spin-valley locking phenomena in TMDC quantum dots, connecting material properties with experimental observations.

Contribution

It introduces a comprehensive simulation approach to analyze spin-valley locking in TMDC quantum dots, aiding interpretation of experimental data and guiding future experiments.

Findings

Identifies conditions for spin-valley locking in TMDC quantum dots

Provides a predictive model linking material parameters to experimental signatures

Suggests methods for experimentally measuring valley-relaxation times

Abstract

The spin-valley or Kramers qubit promises significantly enhanced spin-valley lifetimes due to strong coupling of the electrons' spin to their momentum (valley) degrees of freedom. In transition metal dichalcogenides (TMDCs) such spin-valley locking is expected to be particularly strong owing to the significant intrinsic spin-orbit coupling strength. Very recently, a small number of experiments on TMDC quantum dots have put forth evidence for spin-valley locking for the first time at the few-electron limit. Employing quantum transport theory, here we numerically simulate their ground- and excited-state transport spectroscopy signatures in a unified theoretical framework. In doing so, we reveal the operating conditions under which spin-valley locking occurs in TMDC quantum dots, thereby weaving the connection between intrinsic material properties and the experimental data under diverse conditions. Our simulations thus provide a predictive modeling tool for TMDC quantum dots at the few-electron limit allowing us to deduce from experiments the degree of spin-valley locking based on the SOC strength, inter-valley mixing, and the spin and valley $g$-factors. Our theoretical analysis provides an important milestone towards the next challenge of experimentally confirming valley-relaxation times using single-shot projective measurements