Environmental Memory and the Entropy Bathtub of Living Systems

Original: "Non-Markovian Entropy Dynamics in Living Systems from the Keldysh Formalism"
· Feiyi Liu, Min Guo, Hongwei Tan, Yang Wang
arXiv:2603.12184 · 2026-03-12 · CC BY 4.0 · 3 min
An organism's life cycle traces a bathtub-shaped entropy curve, and environmental memory governs how we age.

A bathtub full of water is a simple thing. You fill it, the level holds, and then it slowly drains away. Entropy, the measure of disorder, behaves much the same way in a living organism over the course of a lifetime. First, in childhood and youth, the body puts things in order: cells divide, organs grow, entropy falls. In maturity, order holds on a plateau, like water sitting in the tub. With old age, disorder accumulates and entropy climbs until the system exhausts itself.

But this bathtub has a feature that is often overlooked. The water in it does not just sit there; it remembers what came before. The environment the organism trades with leaves traces: epigenetic marks on DNA, accumulated damage, changes in proteins. These traces do not vanish instantly; they shape what comes next. Physicists call this kind of memory "colored noise," as opposed to "white noise," which forgets the past right away. In a new theoretical paper, the authors built this memory into the mathematical description of the life cycle and looked at what changes.

The main tool is the Keldysh formalism. It is a way of describing nonequilibrium systems in which system and environment are treated as equals rather than as figure and background. Out of it comes the memory kernel, a mathematical object that says how strongly the past influences the present.

The result turned out to be vivid. Without memory, the entropy curve is a smooth bathtub: a descent, a flat bottom, a rise. With memory, oscillations appear on the way down: the organism seems to try out different versions of order before settling on one. On the plateau of maturity, a slow drift sets in along with enhanced correlated fluctuations, small disturbances that trail one another. And during aging, the rise becomes steeper and acquires a long tail: traces of past orderliness persist longer than one would expect.

These changes can be measured through one subtle signature. At equilibrium, the link between spontaneous fluctuations and the response to an external push is strictly defined: this is the fluctuation-dissipation theorem. In living systems it breaks down, and the degree of violation depends on frequency. In youth, low-frequency fluctuations are suppressed: the organism actively damps random disturbances. In maturity, behavior is nearly equilibrium-like. With old age, low-frequency noise grows stronger, and the system loses its ability to resist slow failures.

One more detail: the authors introduced a "damage variable," an abstract counter of accumulated breakdowns. Its dynamics reveal critical slowing down: the time to return to normal grows, and near the critical point the system seems to freeze. This is the thermodynamic sign that death is approaching.

So the entropy bathtub stops being just a metaphor. It becomes a precise curve you can calculate if you know how the environment talks to the organism. The work offers no recipe for eternal life, but it does propose a language for talking about aging as a loss of dynamical stability, not merely as an accumulation of breakdowns. And in that language, environmental memory is not a nuisance but a key player.

In the model, the entropy bathtub is not universal: as the memory time increases, the aging curve acquires a long tail, which means the organism retains traces of its past order for longer after decay sets in.

X_{AB}(\omega) = \frac{S_{AB}(\omega)}{\coth(\omega/2T_{\mathrm{ref}})\chi''_{AB}(\omega)}
The ratio of the fluctuation spectrum to the dissipative part of the response, normalized to a reference temperature; deviation from unity signals nonequilibrium behavior.
\langle \dot{S}_{\mathrm{tot}} \rangle = \int_{-\infty}^{\infty} \frac{d\omega}{2\pi} \frac{\omega^2}{T} |\chi(\omega)|^2 [S_\xi(\omega) - 2T\,\mathrm{Re}\,\tilde{\gamma}(\omega)]
Entropy production is proportional to the violation of the fluctuation-dissipation theorem, weighted by the square of the susceptibility.
\tau_{\mathrm{rel}} \sim |\mu - \mu_c|^{-\nu}
Near the critical point, the relaxation time diverges as a power law, reflecting the slowing of dynamics during aging.
Scientists
Ludwig BoltzmannRudolf ClausiusJacob BekensteinStephen HawkingJames Clerk MaxwellEdward Witten
Concepts
boltzmann entropy ecosystem Dynamical Systems biological rhythm modeling natural variability enthalpy stochastic differential equations microorganism swimming dynamics Boltzmann equation biological stochastic dynamics entropy non equilibrium state thermal equilibrium fluctuation-dissipation theorem thermodynamics second law of thermodynamics Markov chain action lagrangian ecological resilience