You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
{{ message }}
This repository was archived by the owner on Mar 23, 2021. It is now read-only.
Idea: We classify regions of the Hilbert space, of quantum states of n qubits. There are 2 categories, Qat and DoQ. As an example, for n=1, one hemisphere of the Bloch sphere could be labelled Qat, the other hemisphere DoQ. The state vectors to classify are generated as the output of a sensor, which is then fed into a classifier circuit of M layers. Note that we are NOT classifying the classical params vector of the sensor, as we could use any other sensor with different parameterization as long as it's capable of producing Qat and DoQ states. Also, we take the sensor as is, we don't try to "optimize" it.
Team Name: Quant'ronauts
Project Description:
Idea: We classify regions of the Hilbert space, of quantum states of n qubits. There are 2 categories, Qat and DoQ. As an example, for n=1, one hemisphere of the Bloch sphere could be labelled Qat, the other hemisphere DoQ. The state vectors to classify are generated as the output of a sensor, which is then fed into a classifier circuit of M layers. Note that we are NOT classifying the classical params vector of the sensor, as we could use any other sensor with different parameterization as long as it's capable of producing Qat and DoQ states. Also, we take the sensor as is, we don't try to "optimize" it.
Presentation:
Link to the presentation poster
Source code:
GitHub
Jupyter notebook with 2 examples of classification, one classify
<0|1>and the other one<+|->