SciPost Submission Page
Quasi-particle functional Renormalisation Group calculations in the two-dimensional t-t'-Hubbard model
by Daniel Rohe
This Submission thread is now published as
Submission summary
Authors (as registered SciPost users): | Daniel Rohe |
Submission information | |
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Preprint Link: | https://arxiv.org/abs/2304.09001v2 (pdf) |
Date accepted: | 2023-08-28 |
Date submitted: | 2023-07-31 07:55 |
Submitted by: | Rohe, Daniel |
Submitted to: | SciPost Physics |
Ontological classification | |
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Academic field: | Physics |
Specialties: |
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Approaches: | Theoretical, Computational |
Abstract
We extend and apply a recently introduced quasi-particle functional renormalisation group scheme to the two-dimensional Hubbard model with next-nearest-neighbour hopping and away from half filling. We confirm the generation of superconducting correlations in some regions of the phase diagram, but also find that the inclusion of self-energy feedback by means of a decreasing quasi-particle weight can suppress superconducting tendencies more than anti-ferromagnetic correlations by which they are generated. As a supplement, we provide sample results for the self-energy in second-order perturbation theory and address some conceptual matters.
List of changes
Addressed comments by referees, including:
- added a new section 3 on remarks and limitations
- added section 5.2 on caveats
- rearranged former appendix A.3 into main body
- various smaller updates
Published as SciPost Phys. 15, 192 (2023)
Reports on this Submission
Report #2 by Andrey Katanin (Referee 2) on 2023-8-15 (Invited Report)
Strengths
In the revised paper the author has introduced the changes according to the Referees' suggestions. The revised paper can be therefore published .
Weaknesses
-
Report
The revised paper meets acceptance criteria.
Requested changes
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Report #1 by Anonymous (Referee 3) on 2023-8-9 (Invited Report)
- Cite as: Anonymous, Report on arXiv:2304.09001v2, delivered 2023-08-09, doi: 10.21468/SciPost.Report.7629
Report
I thank the authors for adequate clarification of my comments and for improved discussion of the rationale for the chosen model and the underlying approximations in the manuscript.
The drastic differences that result from the inclusion of self-energy feedback is an interesting observation. I hope this can be explored further, although I agree with the author that identifying a fully rigorous benchmarking model is a challenge in itself.
Since the changes made in the resubmission address my concerns to my satisfaction, I recommend publication of the manuscript.