Hello Devel Mailing List,

I have requested 4 ITPs to WNPP.  Below is following a concluded
summary.

Greets,
Dirk =)


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Bug#1101791: ITP: python-qutip-qip -- QuTiP package - Quantum Information Processing

Package: wnpp
Severity: wishlist
Owner: Dirk Lehmann <deb...@dj-l.de>
X-Debbugs-Cc: debian-scie...@lists.debian.org

* Package name    : python-qutip-qip
  Version         : 0.4.0
  Upstream Contact: https://github.com/qutip/qutip-qip/discussions
* URL             : https://github.com/qutip/qutip-qip
* License         : BSD-3-Clause
  Programming Lang: Python
  Description     : QuTiP package - Quantum Information Processing

 The qutip-qip package, QuTiP quantum information processing, aims at
 providing basic tools for quantum computing simulation both for
 simple quantum algorithm design and for experimental
 realization. Compared to other libraries for quantum information
 processing, qutip-qip puts additional emphasis on the physics layer
 and the interaction with the QuTiP core package `python3-qutip`. The
 package offers two different approaches for simulating quantum
 circuits, one with `QubitCircuit` calculating unitary evolution under
 quantum gates by matrix product, another called `Processor` using
 open system solvers in QuTiP to simulate noisy quantum device.

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Bug#1101792: ITP: python-qutip-qtrl -- QuTiP package - Quantum Optimal Control

Package: wnpp
Severity: wishlist
Owner: Dirk Lehmann <deb...@dj-l.de>
X-Debbugs-Cc: debian-scie...@lists.debian.org

* Package name    : python-qutip-qtrl
  Version         : 0.1.5
  Upstream Contact: https://github.com/qutip/qutip-qtrl/issues
* URL             : https://github.com/qutip/qutip-qtrl
* License         : BSD-3-Clause
  Programming Lang: Python
  Description     : QuTiP package - Quantum Optimal Control

 The qutip-qtrl package, QuTiP quantum optimal control, aims at
 providing advanced tools for the optimal control of quantum
 devices. Compared to other libraries for quantum optimal control,
 qutip-qtrl puts additional emphasis on the physics layer and the
 interaction with the QuTiP core package `python3-qutip`. The package
 offers support for both the CRAB and GRAPE methods.

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Bug#1101793: ITP: python-qutip-qoc -- QuTiP package - Advanced Quantum Optimal Control

Package: wnpp
Severity: wishlist
Owner: Dirk Lehmann <deb...@dj-l.de>
X-Debbugs-Cc: debian-scie...@lists.debian.org

* Package name    : python-qutip-qoc
  Version         : 0.1.1
  Upstream Contact: https://github.com/qutip/qutip-qoc/issues
* URL             : https://github.com/qutip/qutip-qoc
* License         : BSD-3-Clause
  Programming Lang: Python
  Description     : QuTiP package - Advanced Quantum Optimal Control

 The qutip-qoc package builds up on the `python3-qutip-qtrl` package.
 .
 It enhances it by providing two additional algorithms to optimize
 analytically defined control functions. The first one is an extension
 of Gradient Optimization of Analytic conTrols (GOAT). The second one
 (JOPT) leverages QuTiPs version 5 new diffrax abilities to directly
 calculate gradients of JAX defined control functions using automatic
 differentiation.
 .
 The package also aims for a more general way of defining control
 problems with QuTiP and makes switching between the four control
 algorithms (GOAT, JOPT, and GRAPE and CRAB implemented in qutip-qtrl)
 very easy.

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Bug#1101794: ITP: python-qutip -- QuTiP: Quantum Toolbox in Python

Package: wnpp
Severity: wishlist
Owner: Dirk Lehmann <deb...@dj-l.de>
X-Debbugs-Cc: debian-scie...@lists.debian.org

* Package name    : python-qutip
  Version         : 5.1.1
  Upstream Contact: https://github.com/qutip/qutip/discussions
* URL             : https://github.com/qutip/qutip
* License         : BSD-3-Clause
  Programming Lang: Python
  Description     : QuTiP: Quantum Toolbox in Python

 QuTiP is open-source software for simulating the dynamics of open
 quantum systems. The QuTiP library depends on the excellent Numpy,
 Scipy, and Cython numerical packages. In addition, graphical output
 is provided by Matplotlib. QuTiP aims to provide user-friendly and
 efficient numerical simulations of a wide variety of Hamiltonians,
 including those with arbitrary time-dependence, commonly found in a
 wide range of physics applications such as quantum optics, trapped
 ions, superconducting circuits, and quantum nanomechanical
 resonators.

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