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  • Letter
  • Open Access

Resonating valence bond pairing energy in graphene by quantum Monte Carlo

S. Azadi1,*, A. Principi1, T. D. Kühne2,3,4, and M. S. Bahramy1

  • *Contact author: sam.azadi@manchester.ac.uk
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Phys. Rev. B 113, L121101 – Published 2 March, 2026

DOI: https://doi.org/10.1103/hmmc-nhdl

Abstract

Whether short-range electron pairing can be stabilized in graphene remains a central question because pristine graphene is a semimetal with vanishing density of states at the Dirac point. We show that geometry alone can enhance short-range pairing correlations in confined graphene. Using real-space quantum Monte Carlo with correlated trial wavefunctions, we control a simple geometric knob, the commensurability of the simulation cell with the Dirac points, which creates or removes a small, single-particle gap in finite graphene samples. Diffusion quantum Monte Carlo reveals a clear dichotomy, when this geometry-induced gap is present, a resonance-valence-bond(RVB)-like state is energetically favored. Whereas when the spectrum is gapless and cell includes the Dirac points, no RVB energy gain is found. The effect persists in large cells at fixed geometry, establishing that confinement and commensurability can tip the energetic balance toward singlet pairing, while pristine bulk graphene shows no intrinsic RVB instability. These results identify a practical, geometry-controlled route to amplify pairing tendencies in nanoscale graphene devices and provide many-body benchmarks for interpreting finite-cell ab initio calculations. Our results also suggest design principles, via shape, aspect ratio, or mild superlattice modulations, to engineer stronger electronic correlations in carbon-based nanoelectronics.

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Phys. Rev. B 113, L121101– Published 2 March, 2026
  • Received 23 October 2025
  • Revised 12 December 2025
  • Accepted 13 February 2026
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Published by the American Physical Society under the terms of the Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to the author(s) and the published article's title, journal citation, and DOI.

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