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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

Submission summary

Authors (as registered SciPost users): Luca Ciandrini
Submission information
Preprint Link: scipost_202310_00038v1  (pdf)
Code repository:
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
  • Statistical and Soft Matter Physics
Approach: Theoretical


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.

Published as SciPost Phys. Codebases 22-r1.1 (2023) , SciPost Phys. Codebases 22 (2023)

Author comments upon resubmission

We would like to thank the Reviewers for their insightful comments, to which we have responded in full.

We updated the preprint of our work, now available at arXiv: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.

Reports on this Submission

Anonymous Report 2 on 2023-11-21 (Invited Report)


The paper has gained significant impact compared to the previous version by allowing the computation of a general observable.


The limit raised previously has been addressed.


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.

  • validity: top
  • significance: high
  • originality: high
  • clarity: top
  • formatting: excellent
  • grammar: excellent

Anonymous Report 1 on 2023-11-12 (Invited Report)


same as first report


The weaknesses pointed out in the first report have been addressed satisfactorily.


The authors have addressed my comments in a sensible way. The manuscript is now suitable for publication.

Requested changes


  • validity: top
  • significance: top
  • originality: high
  • clarity: high
  • formatting: excellent
  • grammar: excellent

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