Pyxel submission

[flemmel]

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 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.
One-Line Description of Package: Description here
Repository Link: https://gitlab.com/esa/pyxel
Version submitted: 2.12
EiC: TBD
Editor: TBD
Reviewer 1: TBD
Reviewer 2: TBD
Archive: TBD
JOSS DOI: TBD
Version accepted: TBD
Date accepted (month/day/year): TBD

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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):

  • Data retrieval
  • Data extraction
  • Data processing/munging
  • Data deposition
  • Data validation and testing
  • Data visualization¹
  • Workflow automation
  • Citation management and bibliometrics
  • Scientific software wrappers
  • Database interoperability

Domain Specific

• Geospatial
• Education

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• 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.

  • If you made a pre-submission enquiry, please paste the link to the corresponding issue, forum post, or other discussion, or @tag the 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

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Footnotes

1. Please fill out a pre-submission inquiry before submitting a data visualization package. ↩

[eliotwrobson]

@flemmel thanks for your submission! I'll be able to start on the pre-review-checks soon 👍🏽