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Erik Nielsen

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#machine learning Preprint Oct 2026

Evolutionary One-Step Generators: Fast and Diverse Sampling for Discrete Design

Several discrete design tasks, such as molecular discovery, require diverse collections of useful candidates at low computational cost. High validity alone does not guarantee a useful candidate library: repeatedly generating the same valid structures leaves few distinct alternatives. Training for both feasibility and d...

Marcus Vukojevic, Erik Nielsen, Veronica Lachi et al. · 0 citations

Preprint Aug 2026

A gauge-invariant theory of small Markovian errors in quantum gate sets

Noisy logic operations on a quantum computational register -- e.g., one or more qubits -- can be described by transfer matrices (a.k.a. CPTP maps or superoperators) that act linearly on the density matrix representing the register's quantum state. Collectively, these operations form a gate set. Gate sets have a gauge f...

J. D. de Mendoza, Corey I. Ostrove, T. Proctor et al. · 0 citations