Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/45821
Title: Derivation of the deformed Heisenberg algebra from discrete spacetime
Authors: Shah, Naveed ahmad
Ashraf, S. s. zulqarnayn
Shaikh, Aasiya
Yamin, Yas
Sahoo, P. K.
Bhat, Aaqid
Lone, Suhail ahmad
MIR, Faizal 
Ahsan, M. A. H.
Issue Date: 2025
Publisher: IOP Publishing Ltd
Source: Epl, 149 (4) (Art N° 40001)
Abstract: - Although the deformation of the Heisenberg algebra by a minimal length has become a central tool in quantum gravity phenomenology, it has never been rigorously obtained and is often derived using heuristic reasoning. In this study, we move beyond the heuristic derivation of the deformed Heisenberg algebra and explicitly derive it using a model of discrete spacetime, which is motivated by quantum gravity. Initially, we investigate the effects of the leading order Planckian lattice corrections and demonstrate that they precisely match those suggested by the heuristic arguments commonly used in quantum gravity phenomenology. Furthermore, we rigorously obtain deformations from the higher-order Planckian lattice corrections. In contrast to the leading-order corrections, these higher-order corrections are model dependent. We select a specific model that breaks the rotational symmetry, as the importance of such rotational symmetry breaking lies in the relationship between CMB anisotropies and quantum gravitational effects. Based on the mathematical similarity of the Planckian lattice used here with the graphene lattice, we propose that graphene can serve as an analogue system for the study of quantum gravity. Finally, we examine the deformation of the covariant form of the Heisenberg algebra using a four-dimensional Euclidean lattice.
Notes: Shah, NA (corresponding author), Aligarh Muslim Univ, Dept Phys, Aligarh 202002, India.
shahnaveed75@gmail.com
Document URI: http://hdl.handle.net/1942/45821
ISSN: 0295-5075
e-ISSN: 1286-4854
DOI: 10.1209/0295-5075/ada79d
ISI #: 001451067100001
Rights: 2025 EPLA. All rights, including for text and data mining, AI training, and similar technologies, are reserved
Category: A1
Type: Journal Contribution
Appears in Collections:Research publications

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