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Quantum Machine Learning

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As we move towards primitive-based algorithms we are going to discontinue the algorithms that are based on `QuantumInstance`. This issue is created to mark the `QuantumKernel` class as pending deprecation....

### Summary Enhancing the documentation of Tutorial "01_neural_networks" as a mentee for QAMP 2022. Mentor: @ElePT Mentee: @SanyaNanda ### Details and comments 1. Restructured the notebook (Objective, Introduction, Tutorial and...

QAMP

### Summary This PR introduce a new NeuralNetwork class, `EsitmatorQNN`, that uses the `Estimator` primitive inside. - [x] unittests close #401 ### Details and comments

### Summary This is a tutorial which goes through the theory of a Quantum Autoencoder, followed by several examples of compressing different quantum states.

### What should we add? This issue covers adding Effective Dimension class for all PyTorch models. This would help to compare effective dimensions between the classical and quantum/hybrid models.

priority: low
type: feature request 💡
Connector: PyTorch 🔦

### What is the expected enhancement? Review all docstrings in the package and update references to Terra's classes. For instance, in the `VQC` documentation we reference \`\`ZZFeatureMap\`\` that is in...

good first issue
type: enhancement
type: documentation

### What should we add? Create a security policy following GitHub's guidelines: > Help your community understand how to securely report security vulnerabilities for your project. This item can be...

type: feature request 💡

### What should we add? Restructure the Readme file with a more structured introduction. Proposal: > ## What is ? > > ## How do I install ? > >...

good first issue
documentation 📖

https://docs.quantum.ibm.com/announcements/product-updates/2024-02-14-qiskit-runtime-primitives-update > **beginning 1 March 2024**, Qiskit Runtime will require that circuits and observables are transformed to use only instructions supported by the system (referred to as instruction set architecture...

priority: high
type: design 📐
Hardware runtime 💻

### What should we add? `Thunder` could be integrated with upcoming versions of the Torch connector and speed up the PyTorch compilation. This `jit` compiler is newly released and has...

Performance ⚡
type: enhancement ✨
Connector: PyTorch 🔦