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Effective dimension of machine learning models
Amira Abbas, David Sutter, Alessio Figalli +1
Making statements about the performance of trained models on tasks involving new data is one of the primary goals of machine learning, i.e., to understand the generalization power…
Error Bounds for Variational Quantum Time Evolution
Christa Zoufal, David Sutter, Stefan Woerner
Variational quantum time evolution allows us to simulate the time dynamics of quantum systems with near-term compatible quantum circuits. Due to the variational nature of this meth…
Error mitigation for universal gates on encoded qubits
Christophe Piveteau, David Sutter, Sergey Bravyi +2
The Eastin-Knill theorem states that no quantum error correcting code can have a universal set of transversal gates. For CSS codes that can implement Clifford gates transversally i…
Quasiprobability decompositions with reduced sampling overhead
Christophe Piveteau, David Sutter, Stefan Woerner
Quantum error mitigation techniques can reduce noise on current quantum hardware without the need for fault-tolerant quantum error correction. For instance, the quasiprobability me…