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Found 9 papers, 4 papers with code
Measurement-based quantum computation from Clifford quantum cellular automata
Measurement-based quantum computation (MBQC) is a paradigm for quantum computation where computation is driven by local measurements on a suitably entangled resource state.
Variational measurement-based quantum computation for generative modeling
Measurement-based quantum computation (MBQC) offers a fundamentally unique paradigm to design quantum algorithms.
Automated Gadget Discovery in Science
This process of gadget discovery develops in three stages: First, we use an RL agent to generate data, then, we employ a mining algorithm to extract gadgets and finally, the obtained gadgets are grouped by a density-based clustering algorithm.
Quantum machine learning beyond kernel methods
In this work, we identify a constructive framework that captures all standard models based on parametrized quantum circuits: that of linear quantum models.
Operationally meaningful representations of physical systems in neural networks
To make progress in science, we often build abstract representations of physical systems that meaningfully encode information about the systems.
Quantum enhancements for deep reinforcement learning in large spaces
In the past decade, the field of quantum machine learning has drawn significant attention due to the prospect of bringing genuine computational advantages to now widespread algorithmic methods.
Photonic architecture for reinforcement learning
The last decade has seen an unprecedented growth in artificial intelligence and photonic technologies, both of which drive the limits of modern-day computing devices.
Optimizing Quantum Error Correction Codes with Reinforcement Learning
Using efficient simulations with about 70 data qubits with arbitrary connectivity, we demonstrate that such a reinforcement learning agent can determine near-optimal solutions, in terms of the number of data qubits, for various error models of interest.
Active learning machine learns to create new quantum experiments
We investigate this question by using the projective simulation model, a physics-oriented approach to artificial intelligence.
