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researcher

K. Nakano

9 papers hereh-index 211.3k citations86 works total

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

author position
  • first author4
  • middle author4

Across the 8 of 9 papers where every author was matched, so the position is known.

fields
  • physics.comp-ph3
  • cond-mat.supr-con2
  • physics.chem-ph2
  • cond-mat.mtrl-sci1
  • quant-ph1
same name
  • K. Nakano — 34 papers, h 42
  • K. Nakano — 10 papers
  • K. Nakano — 3 papers, h 12
  • K. Nakano — 2 papers
  • K. Nakano — 1 paper
  • K. Nakano — 1 paper, h 21

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
20132021
most citedS wave superconductivity in newly discovered superconductor BaTi2​Sb2​O revealed by 121/123Sb-NMR/Nuclear Quadrupole Resonance measurements

46 citations · 76 across the 3 of their papers we have counts for

collaborators
Showing physics.comp-phShow all

3 papers · 1 filter

physics.comp-ph2020

TurboRVB: a many-body toolkit for {\it ab initio} electronic simulations by quantum Monte Carlo

Kousuke Nakano, Claudio Attaccalite, Matteo Barborini +9

TurboRVB is a computational package for {\it ab initio} Quantum Monte Carlo (QMC) simulations of both molecular and bulk electronic systems. The code implements two types of well e…

physics.comp-ph2019

Stochastic estimations of a total number of classes for the clusterings with too enormous samples to be accommodate into a clustering engine

Keishu Utimula, Genki I. Prayogo, Kousuke Nakano +2

We considered the problem how to handle the exploding number of possibilities to be sorted into irreducible classes by using a clustering tool when its input capacity cannot accomm…

physics.comp-ph2019

Speeding up the ab initio diffusion Monte Carlo by a smart lattice regularization

Kousuke Nakano, Ryo Maezono, Sandro Sorella

One of the most significant drawbacks of the all-electron ab initio diffusion Monte Carlo (DMC) is that its computational cost drastically increases with the atomic number (Z), w…

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