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Neural Networks for Programming Quantum Annealers
Samuel Bosch, Bobak Kiani, Rui Yang +2
Quantum machine learning has the potential to enable advances in artificial intelligence, such as solving problems intractable on classical computers. Some fundamental ideas behind…
Improving the speed of variational quantum algorithms for quantum error correction
Fabio Zoratti, Giacomo De Palma, Bobak Kiani +4
We consider the problem of devising a suitable Quantum Error Correction (QEC) procedures for a generic quantum noise acting on a quantum circuit. In general, there is no analytic u…
Operational Quantum Mereology and Minimal Scrambling
Paolo Zanardi, Emanuel Dallas, Faidon Andreadakis +1
In this paper we will attempt to answer the following question: what are the natural quantum subsystems which emerge out of a system's dynamical laws? To answer this question we fi…
Learning efficient decoders for quasi-chaotic quantum scramblers
Lorenzo Leone, Salvatore F. E. Oliviero, Seth Lloyd +1
Scrambling of quantum information is an important feature at the root of randomization and benchmarking protocols, the onset of quantum chaos, and black-hole physics. Unscrambling…
Unscrambling Quantum Information with Clifford decoders
Salvatore F. E. Oliviero, Lorenzo Leone, Seth Lloyd +1
Quantum information scrambling is a unitary process that destroys local correlations and spreads information throughout the system, effectively hiding it in nonlocal degrees of fre…
Efficient classical algorithms for simulating symmetric quantum systems
Eric R. Anschuetz, Andreas Bauer, Bobak T. Kiani +1
In light of recently proposed quantum algorithms that incorporate symmetries in the hope of quantum advantage, we show that with symmetries that are restrictive enough, classical a…