Quantum Symmetric States and Permutation Invariance
Symmetric states are unchanged when their particles are permuted. Their structure, entanglement properties and uses in computing and cryptography.
BasicsAlgorithmsHardwareError CorrectionCryptographyMachine LearningInformation TheoryPhysics & SimulationApplicationsIndustry & Careers
Tagged: Superposition
333 articles
The No-Cloning Theorem: The Proof in Three Lines
The no-cloning theorem forbids copying an unknown quantum state, and its proof takes only a few lines of linear algebra. Proof and consequences.
Quantum Decoherence: Why Quantum States Break Down
Decoherence is the loss of quantum behavior through interaction with the environment. Causes, time scales, experiments and mitigation.
Quantum Concept Learning and Hypothesis Classes
Concept learning asks how a learner identifies a rule from examples. How quantum learning theory treats hypothesis classes and sample complexity.
Quantum Anomaly Detection in Noisy Data
How quantum algorithms such as quantum SVMs and Grover-based methods are proposed for anomaly detection in security and finance, and their limits.
Quantum Decision Forests and Ensemble Trees
Decision forests combine many decision trees. How quantum versions have been proposed, how they compare with random forests and possible uses.
Quantum Boosting Algorithms and Weak Learners
Boosting combines weak learners into a strong one. How quantum boosting algorithms work, their claimed speedups and possible applications.
The Quantum Expectation-Maximization Algorithm
The expectation-maximization algorithm fits models with hidden variables. How a quantum version works and what speedup it could offer.
Quantum Probabilistic Models and Inference
Quantum probabilistic models describe uncertainty with quantum states. Their structure, algorithms and uses in data analysis and machine learning.
Quantum Generative Models and What They Sample
Quantum generative models such as quantum circuit Born machines learn to sample from probability distributions. How they work and their uses.
Quantum Incremental Learning From Streaming Data
Incremental learning updates a model as new data arrives. How quantum machine learning models might do this and the current challenges.
Quantum Ensemble Learning and Model Averaging
Ensemble methods combine several models to improve predictions. How quantum ensembles and model averaging work and what they could offer.
