Hybrid Quantum-Classical Models
Quantum computers are promising but still in their early stages. Most current quantum devices (known as Noisy Intermediate-Scale Quantum or NISQ devices) cannot handle complex tasks alone due to limited….
Tag: quantum optimization
Quantum Boltzmann Machines
Quantum Boltzmann Machines are a quantum-enhanced version of classical Boltzmann Machines, which are a type of stochastic recurrent neural network used in unsupervised machine learning. The quantum twist allows them….
Amplitude Amplification
In simple terms, Amplitude Amplification is a technique used in quantum computing to increase the probability of finding the right answer. It’s like giving a louder voice to the correct….
Quantum Approximate Optimization Algorithm (QAOA)
What is Quantum Approximate Optimization Algorithm (QAOA)? The Quantum Approximate Optimization Algorithm, commonly called QAOA, is a quantum algorithm designed to solve optimization problems — especially combinatorial optimization tasks. These….
Variational Quantum Eigensolver (VQE)
What is the Variational Quantum Eigensolver (VQE)? The Variational Quantum Eigensolver (VQE) is a hybrid quantum-classical algorithm designed to solve one of the most important problems in quantum chemistry and….
Quantum Machine Learning
Here’s a comprehensive and detailed explanation of Quantum Machine Learning (QML) covering all the fundamental concepts, key steps, and its significance. Quantum Machine Learning (QML) Quantum Machine Learning (QML) is….
The potential of quantum AI in problem-solving
AI has already transformed industries by automating complex tasks and enabling intelligent decision-making. However, classical AI systems face limitations when tackling highly complex problems that require massive computational power. Enter….