6 papers · 1 filter
Gram-Certified Resource Continuation for Structured Quantum Representation Audits
Azadeh Alavi, Fatemeh Kouchmeshki, Hossein Akhoundi +1
Dense representation of an -qubit pure state requires complex amplitudes, precluding dense classical materialization at large . We develop Gram-certified resource conti…
Invariance Audits for Quantum Kernels and Variational Rewinding: A Real-to-Hermitian Taxonomy of Projector, Flag, Anchor, and Density Geometry
Azadeh Alavi, Fatemeh Kouchmeshki, Hossein Akhoundi
Machine-learning models often replace vectors by normalized directions, projectors, covariances, subspaces, ordered flags, quantum states, or density operators before any classifie…
HamQASBench: A Hamiltonian-Informed Diagnostic Benchmark for Evaluating Quantum Architecture Search
Jiayang Niu, Akib Karim, Yan Wang +5
Quantum Architecture Search (QAS) automates the design of parameterized quantum circuits for variational quantum algorithms, yet existing benchmarks organize instances by molecular…
Hybrid Action Reinforcement Learning for Quantum Architecture Search
Jiayang Niu, Yan Wang, Jie Li +4
Reinforcement learning-based Quantum Architecture Search (QAS) offers a promising avenue for automating the design of variational quantum circuits, but existing methods typically d…
Quantum Semi-Random Forests for Qubit-Efficient Recommender Systems
Azadeh Alavi, Fatemeh Kouchmeshki, Abdolrahman Alavi +2
Modern recommenders describe each item with hundreds of sparse semantic tags, yet most quantum pipelines still map one qubit per tag, demanding well beyond one hundred qubits, far…
A Geometric-Aware Perspective and Beyond: Hybrid Quantum-Classical Machine Learning Methods
Azadeh Alavia, Hossein Akhoundib, Fatemeh Kouchmeshkib +4
Geometric Machine Learning (GML) has shown that respecting non-Euclidean geometry in data spaces can significantly improve performance over naive Euclidean assumptions. In parallel…