Efficiently and Reliably Measuring Information Processing Capacity in Dynamical Systems via Kernels
quant-ph, cs.IT, math.DS, math.IT
Submitted: 2026-10-02
Updated: 2026-10-02
Code: https://github.com/benavoli/KernelIPC
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Sources
- Innovation Capacity of Dynamical Learning Systems
- Storage, Scrambling, and Loss of Information in Quantum Reservoir Computing
Related papers
- Reconquering Bell sampling on qudits: stabilizer learning and testing, quantum pseudorandomness bounds, and more
- Encrypted clones can leak: Classification of informative subsets in Quantum Encrypted Cloning
- Polynomial-time classical and quantum simulation of quantum impurity models
- A quasiparticle-protected superconducting qubit
- Theory of quantum-enhanced interferometry with general Markovian light sources
- A convergent hierarchy of spectral gap certificates for qubit Hamiltonians