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QUANTUM MACHINE LEARNING - Coggle Diagram
QUANTUM MACHINE LEARNING
SCALABILITY CHALLANGES
Hardware limitations
Algorithmic complexity
Complexity of Quantum Algorithms
Data size and dimensionality
Complex Data Structures
Large-scale Dataset Handling
Resource constraints
COMPLEX SIMULATION
Molecular dynamics
chemistry calculations
Materials science simulations
High-energy physics simulations
QUANTUM COMPUTING ARCHITECTURES
Gate-based quantum computers
Superconducting Qubit Architectures
Quantum Dot Qubit Architectures
Annealing-based quantum computers
Photonic quantum computers
QUANTUM MACHINE LEARNING ALGORITHIM
Variational quantum algorithms
Quantum Variational Algorithms
Quantum neural networks
Quantum Circuit Architectures
Quantum Feature Encoding
Quantum Gradient Descent
Quantum kernel methods
Quantum circuit learning
QUANTUM FRONTIER
Pushing the Limits of Quantum Computing
Quantum Error Correction Breakthroughs
Novel Quantum Computing Technologies
Overcoming Quantum Decoherence
Quantum Error Suppression Techniques
Quantum Error Detection and Correction Innovations
CONCEPTULA EFFICIENCY
Circuit depth reduction techniques
Error mitigation strategies
Quantum compilation methods
Quantum error correction codes
IMPACT ON SCIENTIFIC RESEARCH
Accelerating discovery in materials science
Improving understanding of quantum systems
Enabling new avenues in fundamental physics
APPLICATION IN PHYSICS AND CHEMESTRY
Quantum molecular modeling
Quantum chemical reaction prediction
Quantum materials design
Materials Property Prediction
Quantum Materials Discovery
QUANTUM CLASSICAL HYBRID APPROACHES
Variational quantum-classical algorithms
Quantum-classical data preprocessing techniques
Quantum-enhanced classical machine learning models
ERROR CORRECTION TECHNIQUES
Error mitigation methods
Error Characterization and Calibration
Error Suppression Techniques
Noise-resilient algorithms
quantum error correction code
Steane Code
Shor Code
Surface Code