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V. Tsyganok

15 papers hereh-index 8187 citations24 works total

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

author position
  • first author3
  • middle author9

Across the 12 of 15 papers where every author was matched, so the position is known.

fields
  • physics.atom-ph11
  • cond-mat.quant-gas2
  • physics.atm-clus1
  • quant-ph1
same name
  • V. Tsyganok — 7 papers, h 10

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
20172026
most citedMachine Learning for Achieving Bose-Einstein Condensation of Thulium Atoms

61 citations · 192 across the 15 of their papers we have counts for

collaborators
Showing 2023Show all

3 papers · 1 filter

quant-ph2023★ 3 cited

Inspiration from machine learning on example of optimization of the Bose-Einstein condensate of thulium atoms in a 1064-nm trap

D. A. Kumpilov, D. A. Pershin, I. S. Cojocaru +10

The number of atoms in Bose-Einstein condensate determines the scale of experiments that can be performed, making it crucial for quantum simulations. Optimization of the number of…

physics.atom-ph2023★ 4 cited

Bose-Einstein condensate as a diagnostic tool for an optical lattice formed by 1064 nm laser light

V. V. Tsyganok, D. A. Pershin, V. A. Khlebnikov +10

Recently, the thulium atom has been cooled down to the temperature of Bose-Einstein condensation. While the condensate of the thulium atom has a lot of applications in quantum simu…

physics.atom-ph2023★ 8 cited

Losses of thulium atoms from optical dipole traps operating at 532 and 1064 nm

V. V. Tsyganok, D. A. Pershin, V. A. Khlebnikov +10

Recently thulium has been condensed to Bose-Einstein condensate. Machine learning was used to avoid a detailed study of all obstacles making cooling difficult. This paper analyses…

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