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Found 5 papers, 2 papers with code
A Cryogenic Memristive Neural Decoder for Fault-tolerant Quantum Error Correction
Neural decoders for quantum error correction (QEC) rely on neural networks to classify syndromes extracted from error correction codes and find appropriate recovery operators to protect logical information against errors.
Neural Error Mitigation of Near-Term Quantum Simulations
Near-term quantum computers provide a promising platform for finding ground states of quantum systems, which is an essential task in physics, chemistry, and materials science.
Generative models for sampling of lattice field theories
We explore a self-learning Markov chain Monte Carlo method based on the Adversarial Non-linear Independent Components Estimation Monte Carlo, which utilizes generative models and artificial neural networks.
Disordered Systems and Neural Networks Statistical Mechanics Computational Physics
QuCumber: wavefunction reconstruction with neural networks
As we enter a new era of quantum technology, it is increasingly important to develop methods to aid in the accurate preparation of quantum states for a variety of materials, matter, and devices.
Quantum Physics Strongly Correlated Electrons
Quantum Boltzmann Machine
Inspired by the success of Boltzmann Machines based on classical Boltzmann distribution, we propose a new machine learning approach based on quantum Boltzmann distribution of a transverse-field Ising Hamiltonian.
Quantum Physics
