Microscopic origin of Boson peak in amorphous solids

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1. Verfasser: Jiang, Cunyuan
Format: Preprint
Veröffentlicht: 2026
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author Jiang, Cunyuan
author_facet Jiang, Cunyuan
contents We proposed a non-analytic model to explain the microscopic origin of the anomalous vibrational density of states (DOS), the Boson peak (BP), in amorphous solids based on the scalar dynamical matrix of a network with springs and nodes. We argue that disorder can be classified into two factors: fluctuation of spring strength and fluctuation of coordination numbers (the number of springs connected to a node). The results suggest that BP originates solely from fluctuation of coordination numbers, while the fluctuation of spring strength only contributes to the effect of damping and has very limited effect on low frequency DOS. This work converts complexity into simplicity and provides a direct answer to the puzzle of the microscopic origin of BP in amorphous solids.
format Preprint
id arxiv_https___arxiv_org_abs_2605_09436
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Microscopic origin of Boson peak in amorphous solids
Jiang, Cunyuan
Disordered Systems and Neural Networks
We proposed a non-analytic model to explain the microscopic origin of the anomalous vibrational density of states (DOS), the Boson peak (BP), in amorphous solids based on the scalar dynamical matrix of a network with springs and nodes. We argue that disorder can be classified into two factors: fluctuation of spring strength and fluctuation of coordination numbers (the number of springs connected to a node). The results suggest that BP originates solely from fluctuation of coordination numbers, while the fluctuation of spring strength only contributes to the effect of damping and has very limited effect on low frequency DOS. This work converts complexity into simplicity and provides a direct answer to the puzzle of the microscopic origin of BP in amorphous solids.
title Microscopic origin of Boson peak in amorphous solids
topic Disordered Systems and Neural Networks
url https://arxiv.org/abs/2605.09436