Stabilizer redundancy from error-correcting codes reduces the choice of physical operators for a logical target to a least-squares problem with closed-form solution, allowing native hardware Hamiltonians to replace costly swaps.
2012 The Moore–Penrose Pseudoinverse: A Tutorial Review of the Theory.Brazilian Journal of Physics42, 146–165
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Extends linear response theory to nonautonomous systems and applies it to optimal fingerprinting for attributing changes to multiple forcings in time-dependent backgrounds, with numerical tests on a climate model.
Bayesian Tucker decomposition enables unsupervised feature selection via Gaussian residual modeling and performs well on synthetic, dynamical, and genomic datasets.
citing papers explorer
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Stabilizers for Compiling Logical Circuits under Hardware Constraints
Stabilizer redundancy from error-correcting codes reduces the choice of physical operators for a logical target to a least-squares problem with closed-form solution, allowing native hardware Hamiltonians to replace costly swaps.
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Linear Response and Optimal Fingerprinting for Nonautonomous Systems
Extends linear response theory to nonautonomous systems and applies it to optimal fingerprinting for attributing changes to multiple forcings in time-dependent backgrounds, with numerical tests on a climate model.
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Unsupervised feature selection using Bayesian Tucker decomposition
Bayesian Tucker decomposition enables unsupervised feature selection via Gaussian residual modeling and performs well on synthetic, dynamical, and genomic datasets.