Overview of Computational Simulations in Quantum Dots

Abstract

Quantum dots (QDs) are semiconductor nanocrystals that exhibit exceptional properties not found in their bulk counterparts. They have attracted extensive academic and industrial attentions due to their quantum confinement effects and unique photophysical properties. Computational approaches such as first principles and classical molecular dynamics simulations are indispensable tools in both scientific studies and industrial applications of QDs. In this review, the state‐of‐the‐art progress in computational simulations of optical, electronic and thermal properties of QDs is summarized and discussed. First, the physics of QDs in low dimensional materials are comprehensively reviewed. Then, the theoretical basis and practical applications of two main computational methods are presented. Properties of QDs revealed by computational studies are summarized respectively. Finally, the paper was concluded with comments on future directions in computational modeling of QDs.

Nature of electronic excitations in small non-stoichiometric quantum dots

“…Several simulation techniques, ranging from the adiabatic ground state to non-adiabatic excited-state calculations, have been applied to understand the photo-chemo-physical properties of QDs in detail. 25–28 However, most of these attempts 29–37 have focused on stoichiometric QDs (with an equal number of cation and anion atoms) that are less frequently obtained from the conventional synthesis. The more common non-stoichiometric QDs, with cation-to-anion ratios deviating from one, that are critical to many optical and photocatalytic applications, remain largely unexplored.…”

Emerging quantum computing algorithms for quantum chemistry

“…For many problems, it is necessary to simulate d-level particles with d > 2, including bosonic elementary particles, 138 spin-s particles, 139 vibrational modes, 140 and electronic energy levels in molecules and quantum dots. 141,142 Accordingly, several qubit-based quantum algorithms were recently developed for efficiently studying some of these systems, including nuclear degrees of freedom in molecules, [143][144][145][146][147] the Holstein model, 148,149 and quantum optics. 150,151 Mapping a d-level system to a set of qubits can be done in a variety of ways, and determining which encodings is optimal for a given problem has important practical implications.…”

Resource-efficient digital quantum simulation of d-level systems for photonic, vibrational, and spin-s Hamiltonians

“…However, for a large subset of quantum physics problems, important roles are played by components that are d-level particles (qudits) with d > 2, including bosonic fundamental particles 9 , vibrational modes 10 , spin-s particles 11 , or electronic energy levels in molecules 12 and quantum dots 13 . Accordingly, several qubit-based quantum algorithms were recently developed for efficiently studying some such processes, including nuclear degrees of freedom in molecules [14][15][16][17][18] , the Holstein model 19,20 , and quantum optics 21,22 .…”