Realization of finite-rate isothermal compression and expansion using optical feedback trap

Abstract

We experimentally realize the finite-rate isothermal process of a Brownian particle in a breathing harmonic potential. For the compression process, finite-rate equilibration can be achieved by increasing and then decreasing the stiffness of the potential to the final stiffness according to the shortcuts-to-isothermal (ScI) protocol. On the other hand, the realization of the ScI expansion is experimentally impossible with optical tweezers due to the requirement of a negative stiffness. Here, we propose a simple and elegant method to resolve this problem and demonstrate the ScI expansion by using the optical feedback trap capable of creating an arbitrary spatiotemporal potential even with a negative stiffness. In addition, we check the thermodynamic energetics such as work, heat, and internal energy, which indeed obey stochastic thermodynamics. Our method provides the possibility of a Brownian heat engine with maximum efficiency but non-vanishing power.

Engineered swift equilibration of brownian particles: consequences of hydrodynamic coupling

“…First, stiffnesses have to remain positive (ie attractive potentials), and second they cannot exceed maximum values above which the particles can be damaged. Actually it is possible to mimic repulsive potentials and go beyond the first constraint [12], but considering our basic optical tweezers set up, it is far more convenient to stick to positive stiffness. In the case of the Coupled ESE, assuming that k 2,i = 1 and k f > 1, these limitations translate into k 2 > 0 and k 1 < k max .…”

“…) we obtain the system to describe the dynamics of the moments given above in eqs. 11, (12) and (13).…”

Optimal Control of Uniformly Heated Granular Fluids in Linear Response

“…This might be surprising at first sight, since the control of physical systems has been considered for some time in different physical contexts, such as quantum mechanics [ 23 , 24 , 25 , 26 ] and statistical mechanics [ 27 , 28 , 29 , 30 , 31 , 32 ]. A paradigmatic case of control of a mesoscopic system is that of an optically trapped colloidal particle [ 27 , 28 , 31 , 33 , 34 , 35 , 36 , 37 , 38 , 39 ]. When the confining potential is harmonic, the time dependence of the stiffness of the trap can be externally controlled, and one aims at optimising the connection between two given equilibrium states, corresponding to different values of the stiffness of the trap—i.e., the colloidal particle is being confined or deconfined.…”

Reinforcement Learning Approach to Shortcuts between Thermodynamic States with Extra Constraints

“…Similarly, finding shortcuts in thermodynamic transformations is also a fundamental problem. The thermodynamic transformation here includes the thermalization to obtain an equilibrium distribution from an initial state [15][16][17][18], and the acceleration of isothermal processes [19][20][21], and so on. In the thermalization problem, Dann et al proposed a method to find a shortcut of the transitions between equilibrium states [17] in the quantum case.…”