qiskit-metal | Quantum Hardware Design. Open-source project for engineers and scientists to design superconducting

 by   Qiskit Python Version: 0.1.5 License: Apache-2.0

kandi X-RAY | qiskit-metal Summary

kandi X-RAY | qiskit-metal Summary

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

Qiskit Metal is an open-source framework for engineers and scientists to design superconducting quantum devices with ease.

            kandi-support Support

              qiskit-metal has a low active ecosystem.
              It has 235 star(s) with 163 fork(s). There are 22 watchers for this library.
              There were 1 major release(s) in the last 12 months.
              There are 111 open issues and 372 have been closed. On average issues are closed in 449 days. There are 6 open pull requests and 0 closed requests.
              It has a neutral sentiment in the developer community.
              The latest version of qiskit-metal is 0.1.5

            kandi-Quality Quality

              qiskit-metal has 0 bugs and 0 code smells.

            kandi-Security Security

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

            kandi-License License

              qiskit-metal 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-metal 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 96610 lines of code, 1426 functions and 212 files.
              It has high code complexity. Code complexity directly impacts maintainability of the code.

            Top functions reviewed by kandi - BETA

            kandi has reviewed qiskit-metal and discovered the below as its top functions. This is intended to give you an instant insight into qiskit-metal implemented functionality, and help decide if they suit your requirements.
            • Extracts the spectral frequencies of a given caprogram
            • Parses the trace .
            • Connect the meander to the given start_pt .
            • Checks if a shapely polygon is too long .
            • Gets the data for a single option .
            • Generate a script script .
            • Fits a spectrum for a given signal .
            • Connect two line segments .
            • Edit Q3D setup .
            • Render a design .
            Get all kandi verified functions for this library.

            qiskit-metal Key Features

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

            qiskit-metal Examples and Code Snippets

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

            Community Discussions


            Why Pauli Z can be used to measure a single qubit ?
            Asked 2022-Mar-30 at 09:21

            According to the Q# documentation, a single qubit can be measured by M.The method uses Pauli-Z. But why Pauli Z can be used to measure a single qubit? I have known the matrix of Pauli-Z like below:

            and the output result is given by the distribution:

            But what's the relationship between the matrix and the formula? What's happened with method M? I really need your help.



            Answered 2022-Mar-25 at 18:18

            Pauli Z matrix defines the basis in which the measurement is performed. A measurement in the Pauli Z basis is the same as the computational basis measurement, projecting the state onto one of the states |0⟩ or |1⟩ (the eigenstates of Pauli Z matrix).

            I'm not up for spelling the math here, since classical StackOverflow doesn't support LaTeX. You can find a good tutorial on single-qubit measurements in Q# in the Quantum Katas project.

            Source https://stackoverflow.com/questions/71617443


            where can I get the detailed tutorial or document for Q# machine learning
            Asked 2022-Mar-25 at 17:34

            Recently, I'm learning the Q# language for machine learning. The sample of half-moons has been run correctly. Now I want to learn the detail of the code. But there is too little explanation to find. There are too many methods I can't understand and there are no introductions in detail. For example, it only explains the name, parameters for the method, but no further information. I really can't understand it. So is there an exits detailed document for machine learning for beginners? Thank u very much.

            how to get the detained document



            Answered 2022-Mar-25 at 17:34

            Q# machine learning library implements one specific approach, circuit-centric quantum classifiers. You can find the documentation for this approach at https://docs.microsoft.com/en-us/azure/quantum/user-guide/libraries/machine-learning/intro and the subsequent pages in that section. The paper it's based on is 'Circuit-centric quantum classifiers', Maria Schuld, Alex Bocharov, Krysta Svore and Nathan Wiebe.

            Source https://stackoverflow.com/questions/71596588


            Accessing Qubit With DAGCircuit
            Asked 2022-Mar-22 at 11:46

            I'm currently trying to make my own TransformationPass to use when compiling a QuantumCircuit for specific hardware, but I'm struggling to get things to work with the DAGCircuit that gets passed to the run(self, dag) method that gets overridden. My main issue at the moment is trying to figure out which qubits each node in the graph actually operates on. I can access the wire for each node, but accessing the qubit index from there raises a DeprecationWarning.

            I can simply ignore the warning, but it gives me the impression that I should be going about this another way.

            Is there a formal method for accessing the qubit (either object or simply its index) given the DAG?



            Answered 2022-Mar-22 at 11:46

            For DAGCircuit right now there isn't a great answer for this. The .index attribute is deprecated as in the case of standalone bit objects on the circuit if they're in a register it might not yield the result you expect (it'll be the register index not the index on the circuit necessarily).

            I typically do this by having something like:

            Source https://stackoverflow.com/questions/71571268


            Missing types, namespaces, directives, and assembly references
            Asked 2022-Feb-27 at 10:24

            I use VS Code for C# and Unity3D and TypeScript and Angular and Python programming, so I have pretty much every required extension, including the .NET Framework and Core as well as the Quantum Development Kit (QDK) plus the Q# Interoperability Tools and also C# and Python extensions for VS Code.

            I have devised the following steps to create my first quantum Hello World based on a few tutorials:



            Answered 2022-Feb-27 at 10:24

            With help from a user on another forum, it turns out the problem was the command:

            Source https://stackoverflow.com/questions/71100198


            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


            How to decide bias in Hamiltonian Ising model? python
            Asked 2021-May-12 at 03:26

            I am trying to code finance portfolio optimisation problem into a quantum annealer, using the Hamiltonian Ising model. I am using the dwave module



            Answered 2021-May-12 at 03:26

            If you are familiar with the physics of the Ising model (e.g. just look it up on wikipedia), you will find out that the term "linear bias" h is used instead of the physics term external constant magnetic field and the term "quadratic bias" J is used instead of the physics term of interaction between a pair of (neighbouring in the case of the Ising model) spins. My guess is that the h and J coefficients must be learned from some given data. Your job is to cast (interpret) the data available to you into an Ising model configuration (state) and then use some sort of optimization with unknown h and J that minimizes the difference between the model's solutions (theoretical Ising model configuration) and the observed data.

            Source https://stackoverflow.com/questions/67462360


            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


            Quantum computing vs traditional base10 systems
            Asked 2021-Feb-24 at 18:40

            This may show my naiveté but it is my understanding that quantum computing's obstacle is stabilizing the qbits. I also understand that standard computers use binary (on/off); but it seems like it may be easier with today's tech to read electric states between 0 and 9. Binary was the answer because it was very hard to read the varying amounts of electricity, components degrade over time, and maybe maintaining a clean electrical "signal" was challenging.

            But wouldn't it be easier to try to solve the problem of reading varying levels of electricity so we can go from 2 inputs to 10 and thereby increasing the smallest unit of storage and exponentially increasing the number of paths through the logic gates? I know I am missing quite a bit (sorry the puns were painful) so I would love to hear why or why not. Thank you



            Answered 2021-Feb-24 at 18:40

            "Exponentially increasing the number of paths through the logic gates" is exactly the problem. More possible states for each n-ary digit means more transistors, larger gates and more complex CPUs. That's not to say no one is working on ternary and similar systems, but the reason binary is ubiquitous is its simplicity. For storage, more possible states also means we need more sensitive electronics for reading and writing, and a much higher error frequency during these operations. There's a lot of hype around using DNA (base-4) for storage, but this is more on account of the density and durability of the substrate.

            You're correct, though that your question is missing quite a bit - qubits are entirely different from classical information, whether we use bits or digits. Classical bits and trits respectively correspond to vectors like

            Source https://stackoverflow.com/questions/66148518

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


            No vulnerabilities reported

            Install qiskit-metal

            If you are interested in customizing your experience, or if you are unable to install qiskit-metal using the pip install instructions below, consider installing directly the source code, following the instructions in the documentation and/or the installation instructions for developers. For normal use, please continue reading.


            The streaming will also be recorded and made available here for offline review. Through June 2021 we are offering live tutorials and Q&A. Sign up to receive an invite to the upcoming sessions. The streaming will also be recorded and made available for offline review. Find here more details on schedule and use the Slack channel to give us feedback and to request the most relevant content to you. Use the slack channel. Join qiskit slack and then join the #metal channel to communicate with the developers and other participants. You may also use this channel to inquire about collaborations.
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