IBM Introduces IBM Quantum Prototypes for Users to Try Out New Cutting Edge Quantum Algorithms

IBM has created a new capability called IBM Quantum prototypes that allows users to beta test new quantum algorithms being developed by IBM Research that aren't ready yet to be integrated into a Qiskit library release. This capability provides a user with early access to the algorithms but can also help IBM gather early feedback on the new algorithms. IBM has released two algorithms to IBM Quantum prototypes called Entanglement Forging and Quantum Kernel Training.

Entanglement Forging is a technique that involves taking a large quantum circuit, splitting it into pieces, running the pieces separately, and then having the classical computer combine the pieces together to get the answer. Although this may not work for all quantum circuits, this method may be able to allow a user to reduce either the number of qubits needed, or the levels needed to run their program and it may allow the user to fit a larger problem into a smaller machine.

Quantum Kernel Training is used in machine learning applications. In classification problems one can use a quantum kernel to determine the best way to group together similar objects but finding these is not always straightforward. The Quantum Kernel Training prototype allows one to experiment with different families of quantum kernels, test out classical optimizers, and even define new loss functions for learning problems.

These two algorithms are the first of two algorithms that will utilize this IBM Quantum prototype capability. But IBM plans on adding additional algorithms as they develop them. The next one planned is a Clifford Optimizer which will be a module for finding the optimal gate configuration of a Clifford circuit.

To find out more about IBM's new Quantum prototype capability, you can view a blog that has been posted on Medium here and also go to a GitHub page to find the repositories for the two algorithms here. You can also see a YouTube demonstration of the Entanglement Forging module here and another YouTube demonstration of Quantum Kernel Training here.

March 1, 2022