Quantum deep learning
AssigneeMicrosoft Technology Licensing, LLC
InventorsNathan Wiebe, Krysta Svore, Ashish Kapoor
Life of this patent
Estimating the term…
Abstract
Boltzmann machines are trained using an objective function that is evaluated by sampling quantum states that approximate a Gibbs state. Classical processing is used to produce the objective function, and the approximate Gibbs state is based on weights and biases that are refined using the sample results. In some examples, amplitude estimation is used. A combined classical/quantum computer produces suitable weights and biases for classification of shapes and other applications.
Claims21
-15. (canceled)
A method of efficiently training a Boltzmann machine, comprising:
- with a classical computer, receiving a specification of a Boltzmann machine, an objective function, and associated training data, and
- in a quantum computer, determining at least one gradient of the objective function;
- based on the at least one gradient of the objective function, specifying at least one visible bias, at least one hidden bias or at least one weight of the Boltzmann machine so as to produce a trained Boltzmann machine.
A method, comprising:
- preparing at least one quantum state in a quantum computer to approximate a Gibbs state and sampling the at least one quantum state;
- and
- estimating in a classical computer, gradients of an objective function based on the sampling of the at least one quantum state.
A method, comprising:
- in a classical computer,
- receiving a training data set, a specification of a deep Boltzmann machine, and an objective function;
- in a quantum computer, establishing a mean-field state based on the mean-field approximation so as to approximate a Gibbs state;
- and
- in the classical computer,
- estimating a gradient of the objective function based on sampling the mean-field state, and determining hidden biases and weights of the deep Boltzmann machine;
- and
- processing an input data example associated with an image, a shape, speech data, a text, an audio recording, a video or a quantum state output by a quantum device such as a quantum computer or simulator based on the Boltzmann machine.
Dependencies are inferred from the claim text.