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researcher

Jun Takahashi

5 papers hereh-index 340 citations7 works total

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

author position
  • first author1
  • middle author1
  • last author3

Across the 5 of 5 papers where every author was matched, so the position is known.

fields
  • quant-ph4
  • cs.DS1
same name
  • Jun Takahashi — 6 papers
  • Jun Takahashi — 5 papers, h 2
  • Jun Takahashi — 4 papers, h 2
  • Jun Takahashi — 2 papers, h 1
  • Jun Takahashi — 1 paper
  • Jun Takahashi — 1 paper

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
20182026
most citedQuantum Phase Estimation by Compressed Sensing

4 citations · 4 across the 3 of their papers we have counts for

collaborators
Showing quant-phShow all

4 papers · 1 filter

quant-ph2026

Modular-Annihilator Parent Hamiltonians for Purified Gibbs States: Spectral Design and Controlled Approximation

Changhao Yi, Jun Takahashi, Cunlu Zhou

Purified Gibbs states provide a bridge between finite-temperature physics, dissipative dynamics, and ground-state methods. In this work, we study the exact finite sum-of-squares (S…

quant-ph2026

Spectral gap of Lee-Yang Hamiltonians

Chaithanya Rayudu, Jun Takahashi

The Lee-Yang theorem and its quantum extensions state that, for a broad class of Hamiltonians on any graph, the partition function's zeros in the complex magnetic field plane lie o…

quant-ph2023

An SU(2)-symmetric Semidefinite Programming Hierarchy for Quantum Max Cut

Jun Takahashi, Chaithanya Rayudu, Cunlu Zhou +3

Understanding and approximating extremal energy states of local Hamiltonians is a central problem in quantum physics and complexity theory. Recent work has focused on developing ap…

quant-ph2023★ 4 cited

Quantum Phase Estimation by Compressed Sensing

Changhao Yi, Cunlu Zhou, Jun Takahashi

As a signal recovery algorithm, compressed sensing is particularly useful when the data has low-complexity and samples are rare, which matches perfectly with the task of quantum ph…

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