Related Experiment Video
Updated: Jul 16, 2025

All-electronic Nanosecond-resolved Scanning Tunneling Microscopy: Facilitating the Investigation of Single Dopant Charge Dynamics
Published on: January 19, 2018
Dynamic hysteresis at a noisy saddle node shows power-law scaling but nonuniversal exponent
Satyaki Kundu1, Ranjan Kumar Patel2, Srimanta Middey2
1Indian Institute of Science Education and Research Kolkata, Mohanpur, Nadia 741246, West Bengal, India.
Abstract:
Dynamic hysteresis, viz., delay in switching of a bistable system on account of the finite sweep rate of the drive, has been extensively studied in dynamical and thermodynamic systems. Dynamic hysteresis results from slowing of the response around a saddle-node bifurcation. As a consequence, the hysteresis area increases with the sweep rate. Mean-field theory, relevant for noise-free situations, predicts power-law scaling with the area scaling exponent of 2/3. We have experimentally investigated the dynamic hysteresis for a thermally driven metal-insulator transition in a high-quality NdNiO_{3} thin film and found the scaling exponent to be about 1/3, far less than the mean-field value. To understand this, we have numerically studied Langevin dynamics of the order parameter and found that noise, which can be thought to parallel finite temperature effects, influences the character of dynamic hysteresis by systematically lowering the dynamical exponent to as small as 0.2. The power-law scaling character, on the other hand, is unaffected in the range of chosen parameters. This work rationalizes the ubiquitous power-law scaling of the dynamic hysteresis as well as the wide variation in the scaling exponent between 0.66 and 0.2 observed in different systems over the last 30 years.
Related Concept Videos
Types of Damping
Damped Oscillations
Although friction and other non-conservative...
The Swing Equation
In a steady-state operation, the mechanical torque (Τm) supplied to the generator is balanced by the electrical torque...
Second Order systems II
Forced Oscillations
Exponential and Sinusoidal Signals

