公开(公告)号：US20160128103A1

公开(公告)日：2016-05-05

申请号：US14928473

申请日：2015-10-30

Applicant: Electronics and Telecommunications Research Institute ,  KOREA ADVANCED INSTITUTE OF SCIENCE AND TECHNOLOGY

Inventor： Byung-Jae KWAK ,  June-Koo RHEE ,  Junhyuk KIM ,  Kyounghye KIM

IPC: H04W74/08 ,  H04L12/26

CPC classification number: H04L43/10 ,  H04W74/0816

Abstract: Provided are a random access method and a terminal supporting the random access method. The terminal may monitor a state of a channel, when the state of the channel is idle, attempt a packet transmission at a first packet transmission probability, and transmit a packet including the first packet transmission probability.

Abstract translation: 提供了随机访问方法和支持随机访问方法的终端。 当信道的状态为空闲时，终端可以监视信道的状态，以第一分组传输概率尝试分组传输，并发送包括第一分组传输概率的分组。

公开(公告)号：US20220114047A1

公开(公告)日：2022-04-14

申请号：US17493091

申请日：2021-10-04

Applicant: Korea Advanced Institute of Science and Technology

Inventor： June-Koo RHEE ,  Changjun KIM ,  Kyungdeock PARK

IPC: G06F11/10 ,  G06N10/00 ,  G06N3/08

Abstract: The present disclosure relates to a method for mitigating an error of a quantum circuit in a quantum computer, the method including: detecting a quantum circuit to be mitigated among a plurality of quantum circuits forming the quantum computer; invoking a pre-trained deep learning model for mitigating an error of the plurality of quantum circuits; inferring an error correction value of the detected quantum circuit using the invoked deep learning model; and mitigating an error of the detected quantum circuit based on the inferred error correction value.

公开(公告)号：US20240311677A1

公开(公告)日：2024-09-19

申请号：US18575259

申请日：2022-06-27

Applicant: KOREA ADVANCED INSTITUTE OF SCIENCE AND TECHNOLOGY

Inventor： June-Koo RHEE ,  Siheon PARK ,  Kyungdeock PARK

IPC: G06N10/60 ,  G06N20/10

CPC classification number: G06N10/60 ,  G06N20/10

Abstract: The present invention relates to a data classification apparatus feasible on an NISQ computer, comprising: a weight calculation unit that calculates weight information that minimizes an objective function of a quantum approximation support vector machine (QASVM) algorithm; and a data classification unit that calculates a classification score of the QASVM algorithm using the weight information obtained from the weight calculation unit, and classifies a class of input data on the basis of the calculated classification score.