qiskit-aer | high performance simulator for quantum circuits

 by   Qiskit C++ Version: 0.14.1 License: Apache-2.0

kandi X-RAY | qiskit-aer Summary

kandi X-RAY | qiskit-aer Summary

qiskit-aer is a C++ library typically used in Quantum Computing applications. qiskit-aer has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. You can download it from GitHub.

Qiskit is an open-source framework for working with noisy quantum computers at the level of pulses, circuits, and algorithms. Qiskit is made up of elements that each work together to enable quantum computing. This element is Aer, which provides high-performance quantum computing simulators with realistic noise models.
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              qiskit-aer has a low active ecosystem.
              It has 362 star(s) with 314 fork(s). There are 29 watchers for this library.
              There were 5 major release(s) in the last 6 months.
              There are 35 open issues and 623 have been closed. On average issues are closed in 188 days. There are 16 open pull requests and 0 closed requests.
              It has a neutral sentiment in the developer community.
              The latest version of qiskit-aer is 0.14.1

            kandi-Quality Quality

              qiskit-aer has 0 bugs and 0 code smells.

            kandi-Security Security

              qiskit-aer has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
              qiskit-aer code analysis shows 0 unresolved vulnerabilities.
              There are 0 security hotspots that need review.

            kandi-License License

              qiskit-aer 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.

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              qiskit-aer releases are available to install and integrate.
              Installation instructions, examples and code snippets are available.
              It has 24247 lines of code, 1590 functions and 206 files.
              It has high code complexity. Code complexity directly impacts maintainability of the code.

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            qiskit-aer Key Features

            No Key Features are available at this moment for qiskit-aer.

            qiskit-aer Examples and Code Snippets

            No Code Snippets are available at this moment for qiskit-aer.

            Community Discussions

            QUESTION

            My qiskit code's output differ from the Lecturer: Ryan O’Donnell
            Asked 2020-Aug-10 at 14:42

            My qiskit code's output differ from the Lecturer: Ryan O’Donnell

            I am testing the table shown in attached image by using qiskit in python3.8.5 and qiskit version {'qiskit-terra': '0.14.2', 'qiskit-aer': '0.5.2', 'qiskit-ignis': '0.3.3', 'qiskit-ibmq-provider': '0.7.2', 'qiskit-aqua': '0.7.3', 'qiskit': '0.19.6'}

            my code is :

            ...

            ANSWER

            Answered 2020-Aug-10 at 14:42

            Ahh, I think I see the issue. In the table from lecturer Ryan O'Donnell, the state is read from the first qubit to the last qubit. For example, the state |110> means that the qubit labelled q_0 is in state |1>, q_1 is in state |1> and q_2 is in state |0>. In Qiskit, the label convention is reversed. So, in Qiskit, |110> would actually be read as |011>, since the state is read from the last to the first qubit. So, your code and output is correct, since in Ryan O'Donnell's table, your state |011> is |110>. If this doesn't make sense, let me know.

            As to your new code, the reason why you are getting different results than expected is that as you run your for loop, instead of creating new circuits, you are consistently adding to an existing circuit. For example, when applying the first function, bit_000, you apply to ccx gate, barrier, and measure. Then calling bit_001, you add an x gate to q_0 and do the same thing. So far everything is good. Then you add an x gate to q_1 and do the same procedure, but you get the resulting state vector '111'. That is because in qiskit, it thinks there is an x gate on the first and second qubit, so when you apply the ccx gate, you get the result you get. So really, by applying all of those circuit operations, you've made one big circuit instead of 8 isolated circuits. I would initialize all the qubits to the state |0> after each time you measure, which will give you a clean slate to work off for the next circuit. With that edit, you should get the results that are written in Ryan O'Donnell's lecture. Hope this helps!

            Source https://stackoverflow.com/questions/63283443

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

            Vulnerabilities

            No vulnerabilities reported

            Install qiskit-aer

            We encourage installing Qiskit via the pip tool (a python package manager). The following command installs the core Qiskit components, including Aer. Pip will handle all dependencies automatically for us and you will always install the latest (and well-tested) version. To install from source, follow the instructions in the contribution guidelines.

            Support

            In order to install and run the GPU supported simulators on Linux, you need CUDA® 10.1 or newer previously installed. CUDA® itself would require a set of specific GPU drivers. Please follow CUDA® installation procedure in the NVIDIA® web.
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            Install
          • PyPI

            pip install qiskit-aer

          • CLONE
          • HTTPS

            https://github.com/Qiskit/qiskit-aer.git

          • CLI

            gh repo clone Qiskit/qiskit-aer

          • sshUrl

            git@github.com:Qiskit/qiskit-aer.git

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