Bridging theoretical quantum physics and practical computational engineering across error correction, machine learning, and combinatorial solvers.
Noisy physical qubits cannot sustain coherence for deep quantum circuits without active error protection. Qube8 investigates rotated planar surface codes, syndrome extraction circuits, and ultra-fast decoding algorithms designed to operate within hardware coherence windows.
Minimum-Weight Perfect Matching (MWPM) and neural decoders capable of resolving Pauli-X and Pauli-Z errors in under 1 microsecond.
Compiling fault-tolerant Clifford+T gate sets onto planar lattice arrangements with minimal physical qubit overhead.
Monte Carlo simulations estimating fault-tolerance thresholds across depolarizing, amplitude damping, and correlated noise channels.
Quantum computers naturally execute transformations in exponential \(2^N\)-dimensional Hilbert spaces. We develop Parameterized Quantum Circuits (PQC) and Quantum Kernel estimators that discover non-linear patterns undetectable by classical Support Vector Machines or Deep Neural Networks.
Local cost function formulations and layer-by-layer training strategies to ensure non-vanishing gradients in deep ansatz circuits.
Design of entangled feature embedding circuits (ZZFeatureMap) that encode tabular and image features into non-separable quantum states.
QCNN architectures performing quantum pooling and translation-invariant classification on multi-qubit states.
Focusing on near-term variational algorithms. We specialize in mapping NP-hard enterprise routing, portfolio covariance selection, and molecular energy states to Quadratic Unconstrained Binary Optimization (QUBO) and Ising Hamiltonians.
Implementing multi-layer QAOA circuits with classical optimizer feedback (COBYLA, SPSA) for large-scale multi-vehicle route scheduling.
Unitary Coupled Cluster (UCCSD) ansatz simulations computing molecular ground-state energies for catalytic and pharmaceutical discovery.