Quantum AI (2026) | Quantum Machine Learning, Variational Circuits, QAOA & VQE

Core Quantum AI Concepts

6 entries

Where quantum circuits act as ML models or accelerate pieces of classical AI pipelines.

01Variational Quantum CircuitsParameterised circuits trained like a neural network, with a classical optimiser tuning parameters between runs. 02Quantum KernelsMapping classical data into a quantum feature space and measuring similarity there for kernel methods such as SVMs. 03Quantum Neural NetworksLayered parameterised circuits mimicking neural network structure, still an active research area. 04Variational ClassifierHands-on tutorial building a quantum classifier with a variational circuit. 05QAOA – Quantum Approximate OptimizationIntroduction to the hybrid algorithm aimed at combinatorial optimisation. 06VQE – Variational Quantum EigensolverOverview of the hybrid algorithm used for molecular and materials simulation.

Quantum Pages on This Site

10 entries

Related quantum topics covered elsewhere on peterindia.net.

07Quantum ComputingHub for quantum computing hardware, software, cryptography and machine learning. 08Quantum Machine LearningExplainers, courses, frameworks and papers on QML. 09Top Quantum ML ProjectsTen hands-on quantum machine learning projects with datasets and algorithms. 10Quantum Computing LanguagesLanguages and SDKs for programming quantum computers. 11Quantum Computing VendorsDirectory of quantum hardware and cloud vendors. 12NISQ Computing ExplainedWhat noisy intermediate-scale quantum computing means for today's algorithms. 13Quantum Error CorrectionPath from noisy physical qubits to fault-tolerant logical qubits. 14Quantum Software Start-UpsCompanies building the quantum software stack. 15Artificial IntelligenceHub for artificial intelligence resources. 16Machine LearningMachine learning resources and tools.

Frameworks & Learning

9 entries

Libraries and courses for building quantum AI models.

17PennyLane LearnTutorials and demos on quantum programming and quantum machine learning. 18PennyLane DemonstrationsHands-on demos for quantum machine learning and optimisation. 19IBM Quantum Learning – Quantum Machine LearningIBM's course on quantum machine learning with Qiskit. 20IBM Quantum Learning – Variational Algorithm DesignCourse on designing variational algorithms such as VQE and QAOA. 21Qiskit Machine LearningQiskit module for quantum neural networks and kernels. 22Qiskit OptimizationQiskit module for quantum optimisation problems. 23TensorFlow QuantumGoogle's library for hybrid quantum-classical machine learning. 24NVIDIA CUDA-QPlatform for hybrid quantum-classical programs on GPUs. 25Cirq (Google Quantum AI)Python framework for writing and simulating quantum circuits.

Foundational Papers

10 entries

Original and survey papers behind quantum AI methods.

26Quantum Machine Learning (Biamonte et al.)Widely cited review of quantum machine learning. 27A Quantum Approximate Optimization Algorithm (Farhi et al.)The original QAOA paper. 28A Variational Eigenvalue Solver on a Quantum Processor (Peruzzo et al.)The original VQE paper. 29Variational Quantum Algorithms (Cerezo et al.)Review of variational quantum algorithms. 30Supervised Learning with Quantum-Enhanced Feature Spaces (Havlicek et al.)Quantum kernel and variational classifiers demonstrated on hardware. 31Quantum Machine Learning in Feature Hilbert Spaces (Schuld and Killoran)Connects quantum computing and kernel methods. 32Quantum Circuit Learning (Mitarai et al.)Framework for training parameterised quantum circuits. 33Classification with Quantum Neural Networks on Near-Term Processors (Farhi and Neven)Quantum classifiers for near-term devices. 34Supervised Quantum Machine Learning Models Are Kernel Methods (Schuld)Kernel-method view of quantum models. 35Power of Data in Quantum Machine Learning (Huang et al.)When data lets classical models match quantum ones.

Platforms & News

10 entries

Cloud access to quantum hardware and where to follow progress.

36IBM QuantumIBM's quantum hardware, cloud access and Qiskit. 37Google Quantum AIGoogle's quantum hardware and research programme. 38Amazon BraketManaged access to several quantum hardware types. 39Azure QuantumMicrosoft's quantum cloud platform. 40NVIDIA Quantum ComputingNVIDIA's accelerated computing for quantum research. 41XanaduPhotonic quantum computing company and creator of PennyLane. 42PasqalNeutral-atom quantum computing company. 43The Quantum InsiderQuantum computing news and market intelligence. 44Quantum (open journal)Open-access journal for quantum science. 45National Quantum Mission (India)India's mission on quantum computing, communication and sensing.

Frequently Asked Questions

What is quantum AI?

Quantum AI combines quantum computing and AI in two ways: using quantum circuits as machine-learning models, and using quantum processors to accelerate hard subroutines such as optimisation inside classical AI pipelines.

Is quantum AI practical today?

Mostly experimental. Current noisy devices run small hybrid circuits, and there is no proven advantage over classical AI on practical workloads yet.

What are variational quantum circuits?

Parameterised circuits whose parameters are tuned by a classical optimiser to minimise a loss, forming the basis of many near-term quantum machine learning models.

What are QAOA and VQE?

QAOA tackles combinatorial optimisation and VQE estimates ground-state energies of molecules and materials, both as hybrid quantum-classical algorithms.

Where do I start?

Try PennyLane or IBM Quantum Learning tutorials, then read the Quantum Machine Learning and Top Quantum ML Projects pages on this site.