qiskit | source SDK for working with quantum computers

 by   Qiskit Python Version: 1.0.0rc1 License: Apache-2.0

kandi X-RAY | qiskit Summary

kandi X-RAY | qiskit Summary

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

The four elements of Qiskit are the essential parts that give Qiskit its power. and if you want to run your experiments on real systems you need the 5th element.

            kandi-support Support

              qiskit has a highly active ecosystem.
              It has 1496 star(s) with 515 fork(s). There are 80 watchers for this library.
              There were 10 major release(s) in the last 6 months.
              There are 57 open issues and 287 have been closed. On average issues are closed in 23 days. There are 8 open pull requests and 0 closed requests.
              It has a negative sentiment in the developer community.
              The latest version of qiskit is 1.0.0rc1

            kandi-Quality Quality

              qiskit has 0 bugs and 0 code smells.

            kandi-Security Security

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

            kandi-License License

              qiskit 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.

            kandi-Reuse Reuse

              qiskit releases are available to install and integrate.
              Deployable package is available in PyPI.
              Build file is available. You can build the component from source.
              Installation instructions, examples and code snippets are available.
              It has 2491 lines of code, 200 functions and 40 files.
              It has medium code complexity. Code complexity directly impacts maintainability of the code.

            Top functions reviewed by kandi - BETA

            kandi has reviewed qiskit and discovered the below as its top functions. This is intended to give you an instant insight into qiskit implemented functionality, and help decide if they suit your requirements.
            • Setup extension
            • Install api sources
            • Return a dictionary of the current version
            • Copies a package from a given package
            • Extend the html context
            • Return the language label
            • Retrieve the label of the current version
            • Get current translation
            • Build the table
            • Get the date of a given version
            • Extract the version information from git tags
            • Build table
            • Return the URL for a translation
            • Add content prefix
            • Gets the URL for a file
            • Run a shell command
            • Create a temporary directory
            Get all kandi verified functions for this library.

            qiskit Key Features

            No Key Features are available at this moment for qiskit.

            qiskit Examples and Code Snippets

            D-Wave Ocean plugin for IBM Qiskit,Examples
            Pythondot img1Lines of Code : 57dot img1License : Permissive (Apache-2.0)
            copy iconCopy
            >>> from qiskit.optimization import QuadraticProgram
            >>> from qiskit.optimization.algorithms import MinimumEigenOptimizer
            >>> from dwave.plugins.qiskit import DWaveMinimumEigensolver
            >>> # Construct a simple qu  
            Rigetti Provider for Qiskit,Advanced,Lifecycle Hooks
            Pythondot img2Lines of Code : 42dot img2License : Permissive (Apache-2.0)
            copy iconCopy
            def custom_hook_1(qasm: str) -> str:
               new_qasm = ...
               return new_qasm
            def custom_hook_2(qasm: str) -> str:
               new_qasm = ...
               return new_qasm
            job = execute(circuit, backend, shots=10, before_compile=[custom_hook_1, custom_hook_2])
            Rigetti Provider for Qiskit,Usage
            Pythondot img3Lines of Code : 24dot img3License : Permissive (Apache-2.0)
            copy iconCopy
            from qiskit import execute
            from qiskit_rigetti import RigettiQCSProvider, QuilCircuit
            # Get provider and backend
            p = RigettiQCSProvider()
            backend = p.get_simulator(num_qubits=2, noisy=True)  # or p.get_backend(name='Aspen-9')
            # Create a Bell state   
            copy iconCopy
            spsa = SPSA(maxiter=300)
            ry = TwoLocal(qubitOp.num_qubits, 'ry', 'cz', reps=7, entanglement='linear')
            vqe = VQE(qubitOp, ry, spsa, quantum_instance=quantum_instance)
            result = vqe.run(quantum_instance)
            Where was Qiskit-Textbook downloaded?
            Pythondot img5Lines of Code : 14dot img5License : Strong Copyleft (CC BY-SA 4.0)
            copy iconCopy
            pip show qiskit-textbook
            Name: qiskit-textbook
            Version: 0.1.0
            Summary: A collection of widgets, tools and games for using along
              the Qiskit Textbook. See the textbook and a list of contributors at qiskit.org/textb
            AttributeError: 'QuantumCircuit' object has no attribute 'config'
            Pythondot img6Lines of Code : 4dot img6License : Strong Copyleft (CC BY-SA 4.0)
            copy iconCopy
            from qiskit.compiler import assemble
            my_qobj = assemble(c)
            result = simulator.run(my_qobj).result()
            Can I have two iterables in the reduce function? (Python)
            Pythondot img7Lines of Code : 2dot img7License : Strong Copyleft (CC BY-SA 4.0)
            copy iconCopy
            a, x_sum = reduce(lambda x,y: (x[0].compose(y[0], y[1]), x[1][0]+y[1][0]), zip(circli, cs), (qcla, 0))
            ValueError: numpy.ndarray size changed on importing qiskit
            Pythondot img8Lines of Code : 2dot img8License : Strong Copyleft (CC BY-SA 4.0)
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            pip install --ignore-installed qiskit-terra qiskit-aer
            QisKit: Difference on Statevector / No Difference on Vizualization
            Pythondot img9Lines of Code : 20dot img9License : Strong Copyleft (CC BY-SA 4.0)
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            from qiskit import QuantumCircuit
            from qiskit.quantum_info import Statevector
            from kaleidoscope import qsphere
            circ = QuantumCircuit(1)
            state = Statevector.from_instruction(circ)
            Distance Estimation Using Quantum Computer
            Pythondot img10Lines of Code : 9dot img10License : Strong Copyleft (CC BY-SA 4.0)
            copy iconCopy
            # IBMQ Configure
            # IBMQ.save_account(os.environ.get('IBM'))
            # IBMQ.load_account()
            # provider = IBMQ.get_provider('ibm-q')
            # qcomp = provider.get_backend('ibmq_16_melbourne')
            # Get backend using the Aer provider

            Community Discussions


            How to add a dropout layer in LSTM to avoid overfitting
            Asked 2021-Oct-17 at 12:46

            While implementing a hybrid quantum LSTM model, the model is overfitting and thus giving low accuracy. I tried setting dropout = 1 in nn.LSTM but no improvement. I have used a single hidden layer. How do I add the dropout layer to reduce overfitting?

            Model parameters:



            Answered 2021-Oct-17 at 12:46

            Pytorch's LSTM layer takes the dropout parameter as the probability of the layer having its nodes zeroed out. When you pass 1, it will zero out the whole layer. I assume you meant to make it a conventional value such as 0.3 or 0.5.

            As @ayandas says above, too, it applies dropout to each layer except the last (see the link above), so it won't work for a single-layer LSTM. You can always apply your own dropout using nn.dropout at the output of your LSTM layers if you wish.

            Source https://stackoverflow.com/questions/69594311


            Quantum Neural Networks - Noise Models
            Asked 2021-Aug-09 at 12:35

            Surveying the QML module in Qiskit for a quantum neural network project and wondering if there is support to add noise models and run noisy simulations?

            Going through this tutorial and wondering how one would define a noise model in the argument of qnn.forward when doing a batched forward pass.



            Answered 2021-Aug-09 at 11:40

            You can create a noisy simulator like in the snippet below and then use it when you create a QuantumInstance:

            Source https://stackoverflow.com/questions/68709800


            Deutsch algorithm with NOT gate as oracle
            Asked 2021-Aug-01 at 05:36

            I tried to implement Deutsch algorithm using qiskit. The following is a code.



            Answered 2021-Aug-01 at 05:36

            Deutsch algorithm applies the X gate to the qubit you use for phase kickback trick, to prepare it in the |-⟩ state before applying the oracle. Your implementation applies it to the "data" qubit instead, so that the combined effect of the algorithm (after H gates cancel out) is just preparing the data qubit in |1⟩ state.

            Source https://stackoverflow.com/questions/68600069


            Why does drawing a qiskit quantum circuit look different when I run a jupyter notebook locally
            Asked 2021-Jun-05 at 17:40

            I'm using the qiskit textbook, and it creates a QuantumCircuit and then draws the circuit, and it looks like this:

            I see the same result when running the textbook as a jupyter notebook in IBM's quantum lab.

            However, when I download the textbook as a jupyter notebook and run it myself locally, it looks like this:

            I don't like this very much, and I think I am missing something simple. The code that is running is exactly the same. I am using MacOS 11.4 (Big Sur). The following code is sufficient to show a difference when I run it online vs. locally:



            Answered 2021-Jun-05 at 17:40

            Because Qiskit has multiple drawers. Those are:

            • text
            • mpl
            • latex
            • latex_source.

            The drawer you see in the IBM Quantum Lab is the one based on Matplotlib. You can get the same output by qc.draw('mpl').

            To set a default, you can change (or create if does not exist) the file ~/.qiskit/settings.conf) with the entry circuit_drawer = mpl.

            Source https://stackoverflow.com/questions/67852048


            How to solve TSP problem with more than 3 nodes in the tutorial of Max-Cut and Traveling Salesman Problem Qiskit 0.24.0?
            Asked 2021-Jun-05 at 12:02

            I had to try the example of qiskit’s Traveling Salesman Problem with 3 nodes and executing it at IBM backend called simulator_statevector.Can execute and get the result normally.

            But when trying to solve the TSP problem with more than 3 nodes,I changed n = 3 to n = 4.



            Answered 2021-Jun-05 at 12:02

            I found the answer, my method is to increase the Ansat number of reps from 5 to 7.

            from solving TSP 4 node problem

            Source https://stackoverflow.com/questions/66920772


            Qiskit and IPython conf files do not exist
            Asked 2021-May-27 at 14:53

            I had installed the qiskit-textbook distribution of Qiskit using this command : pip install git+https://github.com/qiskit-community/qiskit-textbook.git#subdirectory=qiskit-textbook-src

            The tutorial then said to change the contents of the configuration file located at ~/.qiskit/settings.conf but I can't find the folder at ~/. I can't find the iPython configuration file either at ~/.ipython/profile_default/ipython_kernel_config.py for some reason.

            How do I fix this?



            Answered 2021-May-27 at 14:53
            • If you don't have the ~/.qiskit/settings.conf you can create that yourself at that location (see this answer here and the docs here).

            • If you don't have ~/.ipython/profile_default/ipython_kernel_config.py, try running ipython profile create and see if it then appears.

            Source https://stackoverflow.com/questions/67718967


            Where was Qiskit-Textbook downloaded?
            Asked 2021-May-11 at 12:41

            I've installed Qiskit-textbook by pip install git+https://github.com/qiskit-community/qiskit-textbook.git#subdirectory=qiskit-textbook-src. But I don't know where is it downloaded



            Answered 2021-May-11 at 12:41

            That command installs the Qiskit Textbook package, which is a Python package containing some of the problems and widgets used in the textbook. You can see the location of an installed package using pip show :

            Source https://stackoverflow.com/questions/67448011


            AttributeError: 'QuantumCircuit' object has no attribute 'config'
            Asked 2021-May-03 at 12:24

            I am working on a program for Qiskit, but I am getting a strange error (one that I have not gotten in the past) when I try to simulate a circuit. Here is a minimal example producing the error:



            Answered 2021-May-03 at 12:24

            I believe you need to assemble the transpiled circuit in a qobj before running it :

            Source https://stackoverflow.com/questions/67362847


            TypeError: conv2d(): argument 'input' (position 1) must be Tensor, not str
            Asked 2021-Apr-16 at 07:30

            When I try to train the model I get the following error:

            TypeError: conv2d(): argument 'input' (position 1) must be Tensor, not str

            The code I'm using is:



            Answered 2021-Apr-16 at 07:27

            The problem is that data is a dictionary and when you unpack it the way you did (X_train, Y_train = data) you unpack the keys while you are interested in the values.

            refer to this simple example:

            Source https://stackoverflow.com/questions/67120788


            How to get a default EquivalenceLibrary?
            Asked 2021-Mar-31 at 10:46

            I want to use the BasisTranslator in Qiskit to process my circuit to base gates.

            One of the constructor parameters for BasisTranslator is EquivalenceLibrary. I attempted creating a parameter-less EquivalenceLibrary() and pass it to a BasisTranslator, but the code fails, saying it cannot translate gates like MCT or CCX into the default basis.



            Answered 2021-Mar-31 at 10:46

            The easiest way is to leverage the session equivalence library that is included with qiskit (at qiskit.circuit.equivalence_library.SessionEquivalenceLibrary) which is a prebuilt equivalence library which includes all the standard library gates. You can use it with something like:

            Source https://stackoverflow.com/questions/66881062

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


            No vulnerabilities reported

            Install qiskit

            The best way of installing qiskit is by using pip:. See install Qiskit for detailed instructions, how to use virtual environments, and build from source standalone versions of the individual Qiskit elements and components.


            If you'd like to contribute to Qiskit, please take a look at our contribution guidelines. This project adheres to Qiskit's code of conduct. By participating, you are expected to uphold this code. We use GitHub issues for tracking requests and bugs. Please use our Slack for discussion and simple questions. For questions that are more suited for a forum we use the Qiskit tag in the Stack Exchange.
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