公开(公告)号：US20200175535A1

公开(公告)日：2020-06-04

申请号：US16629007

申请日：2017-07-07

Applicant: ALIBABA GROUP HOLDING LIMITED

Inventor： Hua XU ,  Guang YANG ,  Chi ZHANG ,  Jun YIN ,  Kaifan YANG ,  Chuang TIAN ,  Cheng YANG ,  Shenghuo ZHU ,  Rong JIN

IPC: G06Q30/02 ,  G06F16/957 ,  G06Q30/06

Abstract: Systems and methods are provided for online traffic dynamical adjustment and optimization. A such system may comprise one or more servers configured to monitor an incoming traffic volume for visiting an online platform, determine one or more unit traffic values of the monitored incoming traffic volume to the online platform, and monitor one or more subsets of the incoming traffic volume for respectively visiting one or more sub-platforms of the online platform.

公开(公告)号：US20190258517A1

公开(公告)日：2019-08-22

申请号：US16399621

申请日：2019-04-30

Applicant: Alibaba Group Holding Limited

Inventor： Yuqian LI ,  Hua XU ,  Yu Ding ,  Xingfei Yang ,  Tao Huang

IPC: G06F9/50 ,  G06F11/34 ,  G06F11/30

Abstract: Application link scaling method, apparatus and system are provided. The method includes obtaining an application link, the application link being a path formed by at least two associated applications for a service scenario; determining information of target resources required by capacity scaling for all applications in the application link; allocating respective resources to the applications according to the information of the target resources; and generating instances for the applications to according the respective resources. From the perspective of services, the method performs capacity assessment for related applications on a link as a whole, and capacity scaling of the entire link, thus fully utilizing resources, and preventing the applications from being called by other applications which results in insufficient resources. This ensures the applications not to become the vulnerability of a system, ensures the stability of the system, avoids allocating excessive resources to the applications, and reduces a waste of resources.

公开(公告)号：US20230253692A1

公开(公告)日：2023-08-10

申请号：US18299181

申请日：2023-04-12

Applicant: ALIBABA GROUP HOLDING LIMITED

Inventor： Hua XU ,  Jin QIN

IPC: H01P3/00 ,  H05K1/02

CPC classification number: H01P3/003 ,  H05K1/0237

Abstract: A waveguide includes: a substrate; a first ground wire; a second ground wire; a signal wire; and a compensation structure. The first ground wire, the second ground wire, and the signal wire are disposed on the substrate at intervals, and the signal wire is located between the first ground wire and the second ground wire. The compensation structure is configured to contact at least one of the substrate, the first ground wire, the second ground wire, or the signal wire; and the compensation structure comprises a superconducting material.

公开(公告)号：US20210359384A1

公开(公告)日：2021-11-18

申请号：US17319870

申请日：2021-05-13

Applicant: ALIBABA GROUP HOLDING LIMITED

Inventor： Hua XU ,  Jin QIN

IPC: H01P3/00 ,  H05K1/02

Abstract: A packaging structure, a method of manufacturing a packaging structure, and a quantum processor include a substrate; a coplanar waveguide including a first ground wire, a second ground wire, and a signal wire, wherein the first ground wire, the second ground wire, and the signal wire are disposed on a surface of the substrate at intervals, and the signal wire is located between the first ground wire and the second ground wire; an air bridge including a first end connected with the first ground wire and a second end connected with the second ground wire, wherein a gap exists between the air bridge and a surface of the signal wire away from the substrate; and a compensation structure located on the surface of the substrate.

公开(公告)号：US20210182727A1

公开(公告)日：2021-06-17

申请号：US17189719

申请日：2021-03-02

Applicant: ALIBABA GROUP HOLDING LIMITED

Inventor： Hua XU

IPC: G06N10/00 ,  G01N21/88 ,  G01N23/2251 ,  G01J4/00 ,  G06N3/08 ,  G06N3/04

Abstract: Methods for qubit detection include: imaging, via an imaging device, a qubit to obtain an image; inputting the image to a machine learning model; and outputting, by the machine learning model, prediction information based on the image. Systems for qubit detection include: a test module including an imaging device configured to provide an image of a qubit; and a prediction module communicatively coupled to the test module and including a machine learning model configured to output prediction information based on the image provided by the test module. Devices for qubit detection include: a non-transitory computer-readable storage medium storing an instruction set; and a processor configured to execute the instruction set to cause the device to perform controlling an imaging device to image a qubit to obtain an image; inputting the image to a machine learning model; and controlling the machine learning model to output prediction information based on the image.