Quantum Noise Simulation: Modelling Real Hardware
How noise in real quantum hardware is modeled and simulated, from noise channels to device-specific models, and how this guides error correction.
How noise in real quantum hardware is modeled and simulated, from noise channels to device-specific models, and how this guides error correction.
The depolarizing channel replaces a state with the maximally mixed state with some probability. Its representation, properties and uses as a noise model.
Google’s quantum program: the 2019 Sycamore supremacy result, later processors, error correction milestones and what the claims mean.
Zero-error capacity asks how much information a channel can send with no errors at all. How quantum effects and entanglement change the answer.
The quantum Hamming bound limits the parameters of non-degenerate quantum codes. Its derivation, examples and implications for code design.
Quantum error correction from an information theory perspective: codes, detection and correction, limits and the road to fault tolerance.
How error-correcting codes are used in quantum cryptography, from reconciliation in QKD to codes that protect quantum states.
A catalogue of quantum error-correcting codes: principles, types, detection and correction mechanisms, implementation challenges and uses.
The main models of quantum computation compared: circuits, adiabatic, measurement-based and topological, with their hardware and limits.
The threshold theorem shows that error correction beats error accumulation below a certain physical error rate. Codes, estimates and experiments.
Topological quantum computing would perform gates by braiding anyons. The theory, error resistance, challenges and state of the experiments.
Measurement-based quantum computing performs computation through measurements on an entangled cluster state. How it compares with gate models.