arXiv subjects

Ben Ansbacher

Publications and source records attributed to Ben Ansbacher.

3 recordsLinked to original sources

arXiv2026

Strengthened second law for periodic processes

Many physical systems evolve under periodic driving: the same control protocol is applied again and again, even though the state of the system itself need not return to where it started after each cycle. We derive a physics-independent lower bound on the entropy production of \emph{any} periodic process modeled by the evolution of an initial distribution $p_0$ by a repeated application of the same map $G$. This is a strict strengthening of the second law of thermodynamics for periodic processes. It does not require that the single-period dynamics arise from a CTMC, satisfy (local) detailed balance, or be subject to other typical restrictions. We discuss its application to spins in the Curie-Weiss model and Deterministic Finite Automata, with possible extensions to other uniform computers.

cond-mat.stat-mech↗

arXiv2026

Finite relaxation protocols with minimal dissipation

Work extraction from nonequilibrium systems is a major challenge across biological, chemical, physical, and engineering systems. Idealized protocols generally require a quasistatic relaxation stage in which the Hamiltonian is gradually adjusted through a continuum of intermediaries. Here, we consider protocols restricted to a finite number $N$ of intermediary Hamiltonians, consisting of a sequence of quench-relax steps. We determine the sequence of quenches that minimizes the dissipated work, which can be expressed in terms of a recurrence involving the Lambert function. The optimal sequence converges to the Fisher-Rao geodesic, saturating known leading-order dissipation bounds at large $N$. We obtain lower bounds on work extraction from a nonequilibrium distribution as a function of its Fisher-Rao distance to equilibrium. We extend and apply the framework in two simple models: (i) an optical trap experiment, showing that the optimal intermediary distribution can be bimodal even for unimodal initial and final distributions, and (ii) an enzyme-catalyzed reaction, showing that that accounting for relaxation time in addition to dissipation can favor barrier-lowering.

cond-mat.stat-mech↗

arXiv2025

Mapping gene expression dynamics to developmental phenotypes with information entropy analysis

The development of multicellular organisms entails a deep connection between time-dependent biochemical processes taking place at the subcellular level, and the resulting macroscopic phenotypes that arise in populations of up to trillions of cells. A statistical mechanics of developmental processes would help to understand how microscopic genotypes map onto macroscopic phenotypes, a general goal across biology. Here we follow this approach, hypothesizing that development should be understood as a thermodynamic transition between non-equilibrium states. We test this hypothesis in the context of the fruit fly, Drosophila melanogaster, a model organism used widely in genetics and developmental biology for over a century. Applying a variety of information-theoretic measures to public transcriptomics datasets of whole fly embryos during development, we show that the global temporal dynamics of gene expression can be understood as a process that probabilistically guides embryonic dynamics across macroscopic phenotypic stages. In particular, we demonstrate signatures of irreversibility in the information complexity of transcriptomic dynamics, as measured mainly by the permutation entropy of indexed ensembles (PI entropy). Our results show that the dynamics of PI entropy correlate strongly with developmental stages. Overall, this is a test case in applying information complexity analysis to relate the statistical mechanics of biomarkers to macroscopic developmental dynamics.

physics.bio-ph↗