公开(公告)号：IL286607D0

公开(公告)日：2021-10-31

申请号：IL28660721

申请日：2021-09-22

Applicant: IBM ,  GAMBETTA JAY MICHAEL ,  GLICK JENNIFER RANAE ,  TEMME PAUL KRISTAN ,  GUJARATI TANVI PRADEEP

Inventor： GAMBETTA JAY MICHAEL ,  GLICK JENNIFER RANAE ,  TEMME PAUL KRISTAN ,  GUJARATI TANVI PRADEEP

IPC: G06N3/08 ,  G06N10/00 ,  G06N20/10

Abstract: In an embodiment, the method includes applying, by a quantum processor, a set of quantum feature maps to the selected objects, the set of quantum maps corresponding to a set of quantum kernels. In an embodiment, the method includes evaluating, by a quantum processor, a set of parameters for a quantum feature map circuit corresponding to at least one of the set of quantum feature maps.

公开(公告)号：AU2020250811A1

公开(公告)日：2021-09-30

申请号：AU2020250811

申请日：2020-03-26

Applicant: IBM

Inventor： GAMBETTA JAY MICHAEL ,  GLICK JENNIFER RANAE ,  TEMME PAUL KRISTAN ,  GUJARATI TANVI PRADEEP

IPC: G06N3/08 ,  G06N5/00 ,  G06N10/00 ,  G06N20/10

Abstract: The illustrative embodiments provide a method, system, and computer program product for quantum feature kernel alignment using a hybrid classical-quantum computing system. An embodiment of a method for hybrid classical-quantum decision maker training includes receiving a training data set. In an embodiment, the method includes selecting, by a first processor, a sampling of objects from the training set, each object represented by at least one vector.In an embodiment, the method includes applying, by a quantum processor, a set of quantum feature maps to the selected objects, the set of quantum maps corresponding to a set of quantum kernels. In an embodiment, the method includes evaluating, by a quantum processor, a set of parameters for a quantum feature map circuit corresponding to at least one of the set of quantum feature maps.

公开(公告)号：CA3135537A1

公开(公告)日：2020-10-08

申请号：CA3135537

申请日：2020-03-26

Applicant: IBM

Inventor： GAMBETTA JAY MICHAEL ,  GLICK JENNIFER RANAE ,  TEMME PAUL KRISTAN ,  GUJARATI TANVI PRADEEP

IPC: G06N3/08 ,  G06N5/00 ,  G06N20/10

Abstract: The illustrative embodiments provide a method, system, and computer program product for quantum feature kernel alignment using a hybrid classical-quantum computing system. An embodiment of a method for hybrid classical-quantum decision maker training includes receiving a training data set. In an embodiment, the method includes selecting, by a first processor, a sampling of objects from the training set, each object represented by at least one vector.In an embodiment, the method includes applying, by a quantum processor, a set of quantum feature maps to the selected objects, the set of quantum maps corresponding to a set of quantum kernels. In an embodiment, the method includes evaluating, by a quantum processor, a set of parameters for a quantum feature map circuit corresponding to at least one of the set of quantum feature maps.