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TASEPy: a Python-based package to iteratively solve the inhomogeneous exclusion process
by Luca Ciandrini, Richmond L. Crisostomo, Juraj Szavits-Nossan
This Submission thread is now published as
Submission summary
| Authors (as registered SciPost users): | Luca Ciandrini |
| Submission information | |
|---|---|
| Preprint Link: | scipost_202310_00038v1 (pdf) |
| Code repository: | https://github.com/exclusionprocess-tools/tasepy |
| Date accepted: | 2023-11-27 |
| Date submitted: | 2023-10-31 09:05 |
| Submitted by: | Ciandrini, Luca |
| Submitted to: | SciPost Physics Codebases |
| Ontological classification | |
|---|---|
| Academic field: | Physics |
| Specialties: |
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| Approach: | Theoretical |
Abstract
The totally asymmetric simple exclusion process (TASEP) is a paradigmatic lattice model for one-dimensional particle transport subject to excluded-volume interactions. Solving the inhomogeneous TASEP in which particles' hopping rates vary across the lattice is a long-standing problem. In recent years, a power series approximation (PSA) has been developed to tackle this problem, however no computer algorithm currently exists that implements this approximation. This paper addresses this issue by providing a Python-based package TASEPy that finds the steady state solution of the inhomogeneous TASEP for any set of hopping rates using the PSA truncated at a user-defined order.
Author comments upon resubmission
We updated the preprint of our work, now available at arXiv:2308.00847v3 ( https://arxiv.org/abs/2308.00847v3 ).
Here we resubmit a new pdf version of the manuscript with the formatted answer to referees and changes coloured in red. For a better visualization, referees' comments are italicized and coloured in gray.
We have also made changes to the TASEPy package (now v1.1), and to the tutorial file.
List of changes
- We have now added a section in the Appendix to better introduce the reader to the $\ell$ TASEP.
- The particle-hole symmetry is discussed.
- We implemented a new function of `psa_compute' to save in a csv file all the PSA coefficients.
- We added an explanation of Eq.(3)
- We fixed references and typos.
Published as SciPost Phys. Codebases 22-r1.1 (2023) , SciPost Phys. Codebases 22 (2023)
Reports on this Submission
Strengths
The paper has gained significant impact compared to the previous version by allowing the computation of a general observable.
Weaknesses
The limit raised previously has been addressed.
Report
I am satisfied by the authors' revision of the manuscript. I feel that their python package can now be used by a much larger community.
Strengths
same as first report
Weaknesses
The weaknesses pointed out in the first report have been addressed satisfactorily.
Report
The authors have addressed my comments in a sensible way. The manuscript is now suitable for publication.
Requested changes
none.