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PreprintCC BY 4.0arXiv

Bias and Correlations in Quasiperiodicity: Impact on Localization in an Extended Aubry-André Model

Abstract

Unlike in Anderson localization - where any amount of uncorrelated disorder localizes all eigenstates in one dimension - a one-dimensional system with quasiperiodic potential supports a richer range of localization behavior. This paper investigates the fundamental question of which potential characteristics govern localization properties. We characterize quasiperiodic potentials using two independent parameters, correlation and bias, and demonstrate that bias, in addition to correlation, critically influences localization. Through the study of an extended Aubry-André model, in which a tunable parameter allows systematic control over both the bias and correlation of the potential, we show that bias is key in determining the fraction of delocalized states. An increase in the potential strength generally enhances the tendency toward localization, while simultaneously strengthening the correlations in the quasiperiodic potential. This apparent counterintuitive behavior can be understood in terms of the bias parameter: increasing the potential strength reduces the bias, which in turn favors localization. For the family of Hamiltonians considered, we identify two critical bias thresholds: below the lower threshold, the entire spectrum is localized, whereas below the higher threshold, at most a fraction of the states can be delocalized, precluding delocalization of the entire spectrum. To further test our framework, we examine a quasiperiodic model with zero bias and find that, despite its correlated nature, all states become localized even at very weak potential strengths - recovering the Anderson-like scenario.

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BibTeX
@misc{j2026bias,
  title = {{Bias and Correlations in Quasiperiodicity: Impact on Localization in an Extended Aubry-André Model}},
  author = {Adithya J D and Ranjan Modak and Shaon Sahoo},
  howpublished = {arXiv},
  year = {2026},
  month = sep,
  doi = {10.48550/arxiv.2609.15092},
  eprint = {2609.15092},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2609.15092},
  note = {CC BY 4.0},
}
RIS
TY  - UNPB
TI  - Bias and Correlations in Quasiperiodicity: Impact on Localization in an Extended Aubry-André Model
AU  - Adithya J D
AU  - Ranjan Modak
AU  - Shaon Sahoo
PY  - 2026
DA  - 2026/09/14
PB  - arXiv
DO  - 10.48550/arxiv.2609.15092
UR  - https://arxiv.org/abs/2609.15092
AB  - Unlike in Anderson localization - where any amount of uncorrelated disorder localizes all eigenstates in one dimension - a one-dimensional system with quasiperiodic potential supports a richer range of localization behavior. This paper investigates the fundamental question of which potential characteristics govern localization properties. We characterize quasiperiodic potentials using two independent parameters, correlation and bias, and demonstrate that bias, in addition to correlation, critically influences localization. Through the study of an extended Aubry-André model, in which a tunable parameter allows systematic control over both the bias and correlation of the potential, we show that bias is key in determining the fraction of delocalized states. An increase in the potential strength generally enhances the tendency toward localization, while simultaneously strengthening the correlations in the quasiperiodic potential. This apparent counterintuitive behavior can be understood in terms of the bias parameter: increasing the potential strength reduces the bias, which in turn favors localization. For the family of Hamiltonians considered, we identify two critical bias thresholds: below the lower threshold, the entire spectrum is localized, whereas below the higher threshold, at most a fraction of the states can be delocalized, precluding delocalization of the entire spectrum. To further test our framework, we examine a quasiperiodic model with zero bias and find that, despite its correlated nature, all states become localized even at very weak potential strengths - recovering the Anderson-like scenario.
ER  -