Quantifying the non-equilibrium activity of an active colloid

Abstract

Active matter systems exhibit rich emergent behavior due to constant injection and dissipation of energy at the level of individual agents. We characterize the dissipation of single active colloids.

Stochastic force dynamics of the model microswimmer Chlamydomonas reinhardtii: Active forces and energetics

“…6). Integrating the active energy spectrum provides an estimate for the energy dissipation rate, J , due to active processes [45,47]. Averaged over all swimmers and all time, we find J = 3.4 × 10 4 k B T /s (∼ 0.1 fW).…”

“…We use the force spectrum, a recently developed approach [36,47,[65][66][67], to quantify the non-equilibrium force dynamics of the swimmer as an active particle. The force spectrum is the power spectral density of the stochastic forces measured by the optical trap.…”

“…To isolate the non-equilibrium activity we calculate the average active energy spectrum, spectrum of the swimmer and | Fth | 2 is the spectrum of thermal forces, and ˜indicates the frequencydomain [47,69]. The active energy spectrum quantifies the energetic fluctuations due to non-thermal processes and thus characterizes the energy injected into the system by the swimmer (Fig.…”

“…This approach allows study of the stochasticity of forces given the high resolution in force and sampling rate (sub-pN and 50 kHz, respectively). By treating the swimmer as an "active particle" we quantify its non-equilibrium activity using tools from stochastic thermodynamics [44][45][46][47]. We find that Chlamydomonas exhibit complex oscillatory force dynamics with magnitude of tens of pNs, and rotational dynamics of 1-2 Hz, that can be characterized using a self-propelled particle model.…”

Fluctuation-Dissipation Relations in the absence of Detailed Balance: formalism and applications to Active Matter

“…In [48], response functions were obtained beyond such limit regimes, although they are not written in terms of NESS time-correlation functions, as one wills for establishing FDR, but as weighted averages (in the spirit of Malliavin weight sampling [49]). Another strategy consists in systematically quantifying the violations of the FDT through an effective temperature [50,51,27,52,53,54,55,56,57,58]. While this approach provides useful insights into the dynamics of NESS, it does not carry the same piece of information as a FDR, i.e.…”