PATENT CLAIM ANALYSIS

Application Number: 15900983
Application Type: Utility
Filing Date: 2018-02
Publication Date: 2019-03
Patent Classification: ["370", "252000"]

Abstract:
Disclosed herein is a method of performing quantum channel estimation. The method is performed by a first device of a transmission device, and may include a first quantum state transmission step of transmitting a first quantum state ρ including an N-qubit sequence to a second device of a reception device through a quantum channel, a second quantum state information reception step of receiving information about a second quantum state Φ(ρ) received by the second device through the quantum channel from the second device, and a quantum channel estimation step of estimating the quantum channel based on the received information about the second quantum state Φ(ρ).

Claim (Index 13):
A quantum transmission device performing quantum channel estimation, comprising:\n a transceiver configured to transmit a first quantum state \u03c1 comprising an N-qubit sequence to a second device of a reception device through a quantum channel and receive information about a second quantum state \u03a6(\u03c1) received by the second device through the quantum channel from the second device; and a controller configured to estimate the quantum channel based on the received information about the second quantum state \u03a6(\u03c1).

Metadata:
- Claim Count in Document: 50.0
- Percentile: 88.0
- Lexical Diversity: 2.57778
- Patent Class: 370.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: True
- Related Applications: ['13127317', '12925867', '16062260', '15624145', '14324127']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.5392084050606786
- 35 USC 102 Novelty (BERT): 0.485956987137641
- Combined Prediction Score: 0.5338832632683749
- Mean Citation Score: 192.86339
- Max Citation Score: 206.29593
- Similarity Product: 145.81591137746568

Labels:
- Claim Label 101: 0
- Claim Label 102: 1
- Claim Label 103: 1
- Claim Label 112: 1
- Combined Label: 0
- Label 101 Adjusted: 0

Dataset: test