English

Relativistic particles in super-periodic potentials: exploring graphene and fractal systems

Mesoscale and Nanoscale Physics 2026-04-06 v1 Quantum Physics

Abstract

In this article, we employ the transfer matrix method to investigate relativistic particles in super-periodic potentials (SPPs) of arbitrary order nI+n \in I^{+}. We calculate the reflection and transmission probabilities for spinless Klein particles encountering rectangular potential barriers with super-periodic repetition. It is found that spinless relativistic particles exhibit Klein tunneling and a significantly higher degree of reflection compared to their non-relativistic counterparts. Additionally, we analytically explore the behavior of experimentally realizable massless Dirac electrons as they encounter rectangular potential barriers with a super-periodic pattern in a monolayer of graphene. In this system, the transmission probability, conductance, and Fano factor are evaluated as functions of the number of barriers, the order of super-periodicity, and the angle of incidence. Our findings reveal that the transmission probability shows a series of resonances that depend on the number of barriers and the order of super-periodicity. We extend our analysis to specific cases within the Unified Cantor Potentials (UCPs)-γ\gamma system (γ\gamma is a scaling parameter greater than 11), focusing on the General Cantor fractal system and the General Smith-Volterra-Cantor (GSVC) system. For the General Cantor fractal system, we calculate the tunneling probability, which reveals sharp transmission peaks and progressively thinner unit cell potentials as GG increases. In the GSVC system, we analyze the potential segment length and tunneling probability, observing nearly unity tunneling coefficients when γ1\gamma \approx 1, as well as saturation behavior in transmission coefficients at higher stages GG.

Keywords

Cite

@article{arxiv.2412.13220,
  title  = {Relativistic particles in super-periodic potentials: exploring graphene and fractal systems},
  author = {Sudhanshu Shekhar and Bhabani Prasad Mandal and Anirban Dutta},
  journal= {arXiv preprint arXiv:2412.13220},
  year   = {2026}
}

Comments

15 pages, 13 figures