ProjectQ | open source software framework for quantum computing

by ProjectQ-Framework Python Version: 0.8.0 License: Apache-2.0

X-Ray Key Features Code Snippets Community Discussions(2)Vulnerabilities Install Support

kandi X-RAY | ProjectQ Summary

ProjectQ is a Python library typically used in Quantum Computing applications. ProjectQ has no vulnerabilities, it has build file available, it has a Permissive License and it has medium support. However ProjectQ has 4 bugs. You can install using 'pip install ProjectQ' or download it from GitHub, PyPI.

ProjectQ: An open source software framework for quantum computing

Support

Quality

Security

License

Reuse

Support

ProjectQ has a medium active ecosystem.

It has 814 star(s) with 263 fork(s). There are 70 watchers for this library.

It had no major release in the last 12 months.

There are 21 open issues and 122 have been closed. On average issues are closed in 289 days. There are 9 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of ProjectQ is 0.8.0

Quality

ProjectQ has 4 bugs (0 blocker, 0 critical, 4 major, 0 minor) and 329 code smells.

Security

ProjectQ has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

ProjectQ code analysis shows 0 unresolved vulnerabilities.

There are 12 security hotspots that need review.

License

ProjectQ is licensed under the Apache-2.0 License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

ProjectQ releases are available to install and integrate.

Deployable package is available in PyPI.

Build file is available. You can build the component from source.

ProjectQ saves you 8934 person hours of effort in developing the same functionality from scratch.

It has 18290 lines of code, 1431 functions and 199 files.

It has medium code complexity. Code complexity directly impacts maintainability of the code.

Top functions reviewed by kandi - BETA

kandi has reviewed ProjectQ and discovered the below as its top functions. This is intended to give you an instant insight into ProjectQ implemented functionality, and help decide if they suit your requirements.

Checks if the given gate is available
Return the reST representation of this module
Decompose the slave gate
Recognize a rotation matrix
Test if a matrix is equal to a given matrix
Resolve linkcode
Recursively get attr
Generate a zoo profile
Returns a LaTeX representation of the circuit
Allocate a new qubit
Check if a meta tag is supported
Allocate n_qubits
This function runs a teleport
Run the inverse qFT operator
Compute the histogram of the given qubits
Run Grover
Run the circuit
Get probabilities for a qubit
Return a LaTeX representation of the circuit
Build all the extensions
Get the probability of a qubit
Run the halfadder
Decompose a CnU
Gets the probability of a qubit
Allocate a new qubit
Run the entangle
Checks if the given command is available

Get all kandi verified functions for this library.

ProjectQ Key Features

No Key Features are available at this moment for ProjectQ.

ProjectQ Examples and Code Snippets

No Code Snippets are available at this moment for ProjectQ.

Community Discussions

Trending Discussions on ProjectQ

ProjectQ- In which part of the controlled gate object are the control bits scored

Why is conda build appending py27_0 to my package name if I'm building under python 3.6.1?

QUESTION

ProjectQ- In which part of the controlled gate object are the control bits scored

Asked 2019-Feb-26 at 08:24

I've been trying to decompose the projectQ objects and I could manage to decompose non controlled gates, and daggered gates. But I noticed that the object of a controlled version of a gate is the exact same as the object of that gate.

The code generating these objects:

...

ANSWER

Answered 2019-Feb-26 at 08:24

The control qubits are only added to the command after it is received by the ControlEngine further down the chain after the MainEngine. For implementation details see "3.2.1 Implementation of meta instructions" here.

To implement a testing engine such as this one, that can be used to check that indeed control qubits are added right after the MainEngine, you could do the following:

Source https://stackoverflow.com/questions/54665595

QUESTION

Why is conda build appending py27_0 to my package name if I'm building under python 3.6.1?

Asked 2017-May-09 at 15:43

I'm trying to make a conda recipe for ProjectQ. Something weird is going on during the build process under both linux and osx. I can build and install the package by hand (i.e. using 'python setup.py install' from the cloned git repo directory). However, when I make a recipe that does exactly the same thing, it fails. On both linux and osx.

My build recipe is here. What is particularly weird is that even though I specify python 3.6.* under the build requirements in the meta.yaml file, the conda-build procedure names the package "projectq-v0.3.0-py27_0", and when it installs the package, it tries to do so in one of the python 2.7 directories, which is what I assume makes it fail.

So clearly I'm doing something dumb, but I can't for the life of me figure out what. Can anyone see anything I've done wrong? Thanks in advance.

...

ANSWER

Answered 2017-May-09 at 15:43

I figured this out. Thanks to everyone who took the time to look over my question. There was truly no way that anyone could have figured this out for me, since it was rather specific to the package I was installing. I'm going to try to summarize what I've learned in case someone else runs into anything different.

First, as I noted in one of the comments, if you're specifying a specific version requirement under the build, you had better specify the same version requirement under run. Initially I had "python 3.6.*" specified under build, but just "python" under run. This caused the package to be named something ending with "-py27_0", since the package name, understandably, depends upon what's required to run it, not to build it.
The really tricky thing was to understand that there were additional requirements specified in the setup.py script that were being installed automatically when I ran "python setup.py install" by hand, but were not being run when I tried to build under conda. Once I added these requirements to the meta.yaml recipe, everything builds and tests fine.

So, the lessons are to be consistent with your conda requirements between build and run, and make sure you have all of the requirements listed, including bonus requirements that may be specified in the setup.py file.

Thanks again to all who looked at this.

Source https://stackoverflow.com/questions/43826263

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install ProjectQ

You can install using 'pip install ProjectQ' or download it from GitHub, PyPI.
You can use ProjectQ like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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