Quantum K-Means Clustering and Its Speedup
Quantum versions of k-means clustering, how they compute distances between points, the claimed speedups and the data loading caveat.
Quantum versions of k-means clustering, how they compute distances between points, the claimed speedups and the data loading caveat.
Quantum Shannon theory extends Shannon’s information theory to quantum channels: compression, capacities, coding and entanglement.
Sampling problems such as boson sampling and random circuit sampling were used to demonstrate quantum advantage. Why they are hard classically.
Quantum embedding methods treat a small, important part of a system on a quantum computer and the rest classically. How they work and scale.
Quantum algorithms for linear systems, from HHL to later improvements: how they work, their caveats and applications in science and finance.
How state machine models are extended to quantum systems, how they compare with classical state machines, and possible applications.
Error mitigation techniques compared, including zero-noise extrapolation, probabilistic error cancellation and dynamical decoupling.
Hardware-software co-design tailors quantum algorithms to qubit connectivity and noise, and hardware to algorithms. Strategies and examples.
What quantum annealing can solve: how it works, how it compares with classical optimizers, its hardware and software, and applications.
Quantum counting complexity covers classes such as #P and their quantum analogues. Algorithms, speedups, oracle results and known bounds.
QIP is the class of problems with quantum interactive proofs. Its definition, protocols and the 2010 result that QIP equals PSPACE.
The rotated surface code achieves the same distance as the standard surface code with about half the qubits. Layout, features and experiments.