Submitting Author: @flemmel or for Gitlab: https://gitlab.com/frederic.lemmel
All current maintainers: from Gitlab: https://gitlab.com/vinzaff and https://gitlab.com/benoit.serra
Package Name: pyxel
One-Line Description of Package: Pyxel is a easy-to-use general detector simulation framework that can simulate a variety of imaging detector effects combined on images (e.g. radiation and optical effects, noises) made by CCD or CMOS-based detectors.
Repository Link: https://gitlab.com/esa/pyxel
Version submitted: 2.12
EiC: @crhea93
Editor: @dhomeier
Reviewer 1: @hamogu
Reviewer 2: @crhea93
Archive: TBD
JOSS DOI: TBD
Version accepted: TBD
Date accepted (month/day/year): TBD
Code of Conduct & Commitment to Maintain Package
Description
Pyxel is an open-source, modular Python framework for simulating detector effects in imaging sensors such as CCDs, Monolithic CMOS, and Hybrid CMOS devices.
It allows users to input images, configure detector and model parameters through a simple interface, and simulate effects like cosmic rays, PSF, electronic noise, CTI, persistence, dark current, and charge diffusion.
The framework outputs images combining these effects and also provides image analysis tools, an image generator, parametric studies,
and model calibration capabilities.
Designed primarily for detector scientists and engineers in astronomy and Earth observation, Pyxel helps interpret laboratory data,
guide detector design, and predict instrument performance, while promoting reuse of models across projects to foster collaboration and
reduce duplication of effort
Scope
Domain Specific
Community Partnerships
If your package is associated with an
existing community please check below:
- For all submissions, explain how and why the package falls under the categories you indicated above. In your explanation, please address the following points (briefly, 1-2 sentences for each):
Pyxel falls under the category of “data processing/munging” because it applies a pipeline of physical models to CCD and CMOS detectors,
transforming input data into an output image that simulates what the detector would record in practice.
- Who is the target audience and what are scientific applications of this package?
The target audience of Pyxel is:
- Detector scientists and engineers: designing, calibrating, and testing CCD/CMOS detectors.
- Instrument teams: working on space- and ground-based telescopes, payload validation, and performance prediction.
- Astronomers & astrophysicists: who need to understand how detector effects influence scientific measurements.
- Mission designers & ESA/NASA instrument consortia: to validate detector performance before building hardware.
The scientific applications of Pyxel are:
-
Detector characterization: reproducing effects such as charge transfer inefficiency, inter-pixel capacitance, dark current, persistence,
or radiation damage to compare with laboratory measurements.
-
Performance prediction: forecasting how CCD and CMOS detectors behave under mission-specific conditions
(e.g., low flux, cosmic rays, varying temperatures, long exposures).
-
Instrument design & optimization: testing detector architectures, readout strategies, and noise budgets before building hardware.
-
Calibration & correction development: generating realistic synthetic datasets with known detector effects to design and validate data-reduction algorithms.
- Are there other Python packages that accomplish the same thing? If so, how does yours differ?
Yes, there are other simulation packages, for example:
-
PhoSim (Photon Simulator): Developed for the LSST (now Rubin Observatory).
It simulates the atmosphere, telescope optics, and CCD detector effects, but is highly specialized for that mission and less modular for general use.
-
Mirage: A NASA toolkit for simulating JWST’s NIRCam and NIRISS detectors.
It provides high-fidelity simulations but is tailored to specific instruments and data formats.
-
ScopeSim: A Python framework for simulating telescope instruments.
It models the atmosphere, telescope optics, and instrument throughput, with simplified detector modeling. However, it is less suited for detailed, pixel-level detector physics.
Technical checks
For details about the pyOpenSci packaging requirements, see our packaging guide. Confirm each of the following by checking the box. This package:
Publication Options
JOSS Checks
Note: JOSS accepts our review as theirs. You will NOT need to go through another full review. JOSS will only review your paper.md file. Be sure to link to this pyOpenSci issue when a JOSS issue is opened for your package. Also be sure to tell the JOSS editor that this is a pyOpenSci reviewed package once you reach this step.
Are you OK with Reviewers Submitting Issues and/or pull requests to your Repo Directly?
This option will allow reviewers to open smaller issues that can then be linked to PR's rather than submitting a more dense text based review. It will also allow you to demonstrate addressing the issue via PR links.
Confirm each of the following by checking the box.
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Editor and Review Templates
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The review template can be found here.
Submitting Author: @flemmel or for Gitlab: https://gitlab.com/frederic.lemmel
All current maintainers: from Gitlab: https://gitlab.com/vinzaff and https://gitlab.com/benoit.serra
Package Name: pyxel
One-Line Description of Package: Pyxel is a easy-to-use general detector simulation framework that can simulate a variety of imaging detector effects combined on images (e.g. radiation and optical effects, noises) made by CCD or CMOS-based detectors.
Repository Link: https://gitlab.com/esa/pyxel
Version submitted: 2.12
EiC: @crhea93
Editor: @dhomeier
Reviewer 1: @hamogu
Reviewer 2: @crhea93
Archive: TBD
JOSS DOI: TBD
Version accepted: TBD
Date accepted (month/day/year): TBD
Code of Conduct & Commitment to Maintain Package
Description
Pyxel is an open-source, modular Python framework for simulating detector effects in imaging sensors such as CCDs, Monolithic CMOS, and Hybrid CMOS devices.
It allows users to input images, configure detector and model parameters through a simple interface, and simulate effects like cosmic rays, PSF, electronic noise, CTI, persistence, dark current, and charge diffusion.
The framework outputs images combining these effects and also provides image analysis tools, an image generator, parametric studies,
and model calibration capabilities.
Designed primarily for detector scientists and engineers in astronomy and Earth observation, Pyxel helps interpret laboratory data,
guide detector design, and predict instrument performance, while promoting reuse of models across projects to foster collaboration and
reduce duplication of effort
Scope
Please indicate which category or categories.
Check out our package scope page to learn more about our
scope. (If you are unsure of which category you fit, we suggest you make a pre-submission inquiry):
Domain Specific
Community Partnerships
If your package is associated with an
existing community please check below:
Pyxel falls under the category of “data processing/munging” because it applies a pipeline of physical models to CCD and CMOS detectors,
transforming input data into an output image that simulates what the detector would record in practice.
The target audience of Pyxel is:
The scientific applications of Pyxel are:
Detector characterization: reproducing effects such as charge transfer inefficiency, inter-pixel capacitance, dark current, persistence,
or radiation damage to compare with laboratory measurements.
Performance prediction: forecasting how CCD and CMOS detectors behave under mission-specific conditions
(e.g., low flux, cosmic rays, varying temperatures, long exposures).
Instrument design & optimization: testing detector architectures, readout strategies, and noise budgets before building hardware.
Calibration & correction development: generating realistic synthetic datasets with known detector effects to design and validate data-reduction algorithms.
Yes, there are other simulation packages, for example:
PhoSim (Photon Simulator): Developed for the LSST (now Rubin Observatory).
It simulates the atmosphere, telescope optics, and CCD detector effects, but is highly specialized for that mission and less modular for general use.
Mirage: A NASA toolkit for simulating JWST’s NIRCam and NIRISS detectors.
It provides high-fidelity simulations but is tailored to specific instruments and data formats.
ScopeSim: A Python framework for simulating telescope instruments.
It models the atmosphere, telescope optics, and instrument throughput, with simplified detector modeling. However, it is less suited for detailed, pixel-level detector physics.
@tagthe editor you contacted:APE 22 follow-up: Candidates for pyOpenSci trial review period astropy/astropy.github.com#571 and Pyxel affiliated package: Pyxel astropy/astropy.github.com#516
Technical checks
For details about the pyOpenSci packaging requirements, see our packaging guide. Confirm each of the following by checking the box. This package:
Publication Options
JOSS Checks
paper.mdmatching JOSS's requirements with a high-level description in the package root or ininst/.Note: JOSS accepts our review as theirs. You will NOT need to go through another full review. JOSS will only review your paper.md file. Be sure to link to this pyOpenSci issue when a JOSS issue is opened for your package. Also be sure to tell the JOSS editor that this is a pyOpenSci reviewed package once you reach this step.
Are you OK with Reviewers Submitting Issues and/or pull requests to your Repo Directly?
This option will allow reviewers to open smaller issues that can then be linked to PR's rather than submitting a more dense text based review. It will also allow you to demonstrate addressing the issue via PR links.
Confirm each of the following by checking the box.
Please fill out our survey
submission and improve our peer review process. We will also ask our reviewers
and editors to fill this out.
P.S. Have feedback/comments about our review process? Leave a comment here
Editor and Review Templates
The editor template can be found here.
The review template can be found here.
Footnotes
Please fill out a pre-submission inquiry before submitting a data visualization package. ↩