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Jie Lin

Institute for Quantum Computing

14 papers hereh-index 12632 citations19 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author4
  • middle author9
  • last author1

Across the 14 of 14 papers where every author was matched, so the position is known.

fields
  • quant-ph14
affiliations
  • Institute for Quantum Computing
same name
  • Jie Lin — 20 papers, h 27
  • Jie Lin — 20 papers, h 6
  • Jie Lin — 16 papers, h 13
  • Jie Lin — 10 papers, h 25
  • Jie Lin — 9 papers, h 7
  • Jie Lin — 8 papers, h 2

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20172024
most citedSimple security analysis of phase-matching measurement-device-independent quantum key distribution

168 citations · 656 across the 14 of their papers we have counts for

collaborators
Showing 2019Show all

3 papers · 1 filter

quant-ph2019★ 8 cited

Quantum search for unknown number of target items hybridizing the fixed-point method with the trail-and-error method

Tan Li, Shuo Zhang, Xiang-Qun Fu +4

For the unsorted database quantum search with the unknown fraction λ of target items, there are mainly two kinds of methods, i.e., fixed-point or trail-and-error. (i) In terms of…

quant-ph2019★ 17 cited

Quantum-enhanced least-square support vector machine: simplified quantum algorithm and sparse solutions

Jie Lin, Dan-Bo Zhang, Shuo Zhang +3

Quantum algorithms can enhance machine learning in different aspects. Here, we study quantum-enhanced least-square support vector machine (LS-SVM). Firstly, a novel quantum algorit…

quant-ph2019★ 134 cited

Asymptotic security analysis of discrete-modulated continuous-variable quantum key distribution

Jie Lin, Twesh Upadhyaya, Norbert Lütkenhaus

Continuous-variable quantum key distribution (CV QKD) protocols with discrete modulation are interesting due to their experimental simplicity and their great potential for massive…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.