Flicker and random telegraph noise between gyrotropic and dynamic C-state of a vortex based spin torque nano oscillator

  1. Wittrock, Steffen 3
  2. Talatchian, Philippe 3
  3. Romera, Miguel 3
  4. Garcia, Mafalda Jotta 3
  5. Cyrille, Marie-Claire 1
  6. Ferreira, Ricardo 2
  7. Lebrun, Romain 3
  8. Bortolotti, Paolo 3
  9. Ebels, Ursula 4
  10. Grollier, Julie 3
  11. Cros, Vincent 3
  1. 1 University Grenoble Alpes, CEA-LETI, MINATEC-Campus 2 , 38000 Grenoble, France
  2. 2 International Iberian Nanotechnology Laboratory (INL) 3 , 471531 Braga, Portugal
  3. 3 Unité Mixte de Physique CNRS, Thales, University Paris-Saclay 1 , 1 Avenue Augustin Fresnel, 91767 Palaiseau, France
  4. 4 University Grenoble Alpes, CEA, INAC-SPINTEC, CNRS, SPINTEC 4 , 38000 Grenoble, France
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Revista:
AIP Advances

ISSN: 2158-3226

Año de publicación: 2021

Volumen: 11

Número: 3

Páginas: 035042-1-035042-6

Tipo: Artículo

DOI: 10.1063/9.0000197 GOOGLE SCHOLAR lock_openAcceso abierto editor

Otras publicaciones en: AIP Advances

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Resumen

Vortex based spin torque nano oscillators (STVOs) can present more complex dynamics than the spin torque induced gyrotropic (G) motion of the vortex core. The respective dynamic modes and the transition between them can be controlled by experimental parameters such as the applied dc current. An interesting behavior is the stochastic transition from the G-to a dynamic C-state occurring for large current densities. Moreover, the C-state oscillations exhibit a constant active magnetic volume. We present noise measurements in the different dynamic states that allow accessing specific properties of the stochastic transition, such as the characteristic state transition frequency. Furthermore, we confirm, as theoretically predicted, an increase of flicker noise with when the oscillation volume remains constant with the current. These results bring insight into the potential optimization of noise properties sought for many potential rf applications with spin torque oscillators. Furthermore, the investigated stochastic characteristics open up new potentialities, for instance in the emerging field of neuromorphic computing schemes.

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