arXiv subjects

Nahuel Freitas

Publications and source records attributed to Nahuel Freitas.

At least 19 recordsLinked to original sources

arXiv2026

Dissipation-Reliability Tradeoff for Stochastic CMOS Bits in Series

Physical instantiations of a bit of information are subject to thermal noise that can trigger unintended bit-flip errors. Bits implemented with CMOS technology typically operate in regimes that reliably suppress these errors with a large supply voltage, but miniaturization and circuit design for implantable biomedical devices motivate error suppression via alternative low-voltage strategies. We present and analyze an error-suppression technique that involves coupling multiple CMOS units into chains, introducing a natural error correction arising from inter-unit correlations. Using tensor networks to numerically solve a stochastic master equation for the CMOS chain, we quantify the dissipation-reliability tradeoff across system sizes that would be intractable with conventional sparse-matrix methods. The calculations show that the typical time for bit-flip errors grows exponentially in the square of the supply voltage but subexponentially with the chain length, a scaling we attribute to a spatially localized, domain-wall-mediated flip rather than a coherent one. While a CMOS chain adds stability compared to a single CMOS unit for a fixed low supply voltage, increasing the supply voltage is a lower-dissipation route to equivalent stability.

cond-mat.stat-mech↗

arXiv2026

Emergent Second Law for Time-Dependent Nonequilibrium States

For nonautonomous open systems described by macroscopic stochastic thermodynamics, we derive an emergent second law that constrains time-dependent macroscopic fluctuations by the entropy production along the most probable evolution under the time-reversed driving protocol. We show that this bound can be understood as a macroscopic consequence of the fluctuation theorem: the time reverse of this evolution provides a possible fluctuation path under the forward dynamics. In the linear-response and slow-driving regime, the bound becomes an equality to first order and generalizes the McLennan-Zubarev formula to the time-dependent probability density of nonautonomous systems with weak nonconservative affinities. We illustrate our results in a bistable system under sudden quenches and periodic driving.

cond-mat.stat-mech↗

arXiv2026

Taming non-equilibrium thermal fluctuations in subthreshold CMOS circuits

As CMOS technology scales down, thermal fluctuations increasingly impact circuit behavior, posing challenges to conventional circuit design. However, the inherent stochasticity introduced by thermal noise is now being explored as a potential resource in the emerging field of probabilistic computing. This work presents a fully CMOS experimental platform that enables direct control over its intrinsic thermal fluctuations. These devices function as programmable multivariate Gaussian samplers, offering a hardware primitive for energy-efficient stochastic computing and serving as an experimental platform for studies in electronic noise and stochastic thermodynamics.

cond-mat.stat-mech↗

arXiv2025

Improved diffusive approximation of Markov jump processes close to equilibrium

Diffusive approximations of Markov jump processes often fail to accurately capture large fluctuations. This is confounding, as the rare events triggered by these large fluctuations, such as the failure of electronic memories, are often the object of interest. In this paper we present an improved diffusive approximation, extending a method previously limited to equilibrium systems. Using new tools from stochastic thermodynamics, we prove its validity to linear order in departures from equilibrium and demonstrate its superior accuracy over the Kramers-Moyal expansion in predicting both steady-state and transient properties, including the error rate of a non-equilibrium electronic memory.

cond-mat.mes-hall↗

arXiv2025

Hypergraph-Based Models of Random Chemical Reaction Networks: Conservation Laws, Connectivity, and Percolation

Random graph models have been instrumental in characterizing complex networks, but chemical reaction networks (CRNs) are better represented as hypergraphs. Traditional models of random CRNs often reduce CRNs to bipartite graphs, representing species and reactions as distinct nodes, or simpler derived graphs, which can obscure the relationship between the statistical properties of these representations and the physical characteristics of the CRN. We introduce a straightforward model for generating random CRNs that preserves their hypergraph structure as well as atomic composition, enabling the direct study of chemically relevant features. Notably, our approach distinguishes two notions of connectivity that are equivalent in graphs but differ fundamentally in hypergraphs. These notions exhibit percolation-like phase transitions, which we analyze in detail. The first type of connectivity has relevance to steady-state synthesis and transduction, determining the effective reactions an open CRN can perform at steady state. The second type is suitable to identify which species can be produced from a given initial set of species in a closed CRN. Our findings highlight the importance of hypergraph-based modeling for uncovering the complex behaviors of CRNs.

cond-mat.stat-mech↗

arXiv2024

Information thermodynamics for Markov jump processes coupled to underdamped diffusion: Application to nanoelectromechanics

We extend the principles of information thermodynamics to study energy and information exchanges between coupled systems composed of one part undergoing a Markov jump process and another underdamped diffusion. We derive integral fluctuation theorems for the partial entropy production of each subsystem and analyze two distinct regimes. First, when the inertial dynamics is slow compared to the discrete-state transitions, we show that the steady-state energy and information flows vanish at the leading order in an adiabatic approximation, if the underdamped subsystem is governed purely by conservative forces. To capture the non-zero contributions, we consistently derive dynamical equations valid to higher order. Second, in the limit of infinite mass, the underdamped dynamics becomes a deterministic Hamiltonian dynamics driving the jump processes, we capture the next-order correction beyond this limit. We apply our framework to study self-oscillations in the single-electron shuttle - a nanoelectromechanical system (NEMS) - from a measurement-feedback perspective. We find that energy flows dominate over information flows in the self-oscillating regime, and study the efficiency with which this NEMS converts electrical work into mechanical oscillations.

cond-mat.stat-mech↗

arXiv2024

Bridging Freidlin-Wentzell large deviations theory and stochastic thermodynamics

For overdamped Langevin systems subjected to weak thermal noise and nonconservative forces, we establish a connection between Freidlin-Wentzell large deviations theory and stochastic thermodynamics. First, we derive a series expansion of the quasipotential around the detailed-balance solution, i.e. the system's free energy, and identify the condition for the linear response regime to hold even far from equilibrium. Second, we prove that the escape rate from dissipative fixed points of the macroscopic dynamics is bounded by the entropy production of trajectories that relax into, and escape from the attractors. These results provide the foundation to study the nonequilibrium thermodynamics of dissipative metastable states.

cond-mat.stat-mech↗

arXiv2024

Is stochastic thermodynamics the key to understanding the energy costs of computation?

The relationship between the thermodynamic and computational characteristics of dynamical physical systems has been a major theoretical interest since at least the 19th century, and has been of increasing practical importance as the energetic cost of digital devices has exploded over the last half century. One of the most important thermodynamic features of real-world computers is that they operate very far from thermal equilibrium, in finite time, with many quickly (co-)evolving degrees of freedom. Such computers also must almost always obey multiple physical constraints on how they work. For example, all modern digital computers are periodic processes, governed by a global clock. Another example is that many computers are modular, hierarchical systems, with strong restrictions on the connectivity of their subsystems. This properties hold both for naturally occurring computers, like brains or Eukaryotic cells, as well as digital systems. These features of real-world computers are absent in 20th century analyses of the thermodynamics of computational processes, which focused on quasi-statically slow processes. However, the field of stochastic thermodynamics has been developed in the last few decades - and it provides the formal tools for analyzing systems that have exactly these features of real-world computers. We argue here that these tools, together with other tools currently being developed in stochastic thermodynamics, may help us understand at a far deeper level just how the fundamental physical properties of dynamic systems are related to the computation that they perform.

cond-mat.stat-mech↗

arXiv2024

Entropy production in communication channels

In many complex systems, whether biological or artificial, the thermodynamic costs of communication among their components are large. These systems also tend to split information transmitted between any two components across multiple channels. A common hypothesis is that such inverse multiplexing strategies reduce total thermodynamic costs. So far, however, there have been no physics-based results supporting this hypothesis. This gap existed partially because we have lacked a theoretical framework that addresses the interplay of thermodynamics and information in off-equilibrium systems. Here we present the first study that rigorously combines such a framework, stochastic thermodynamics, with Shannon information theory. We develop a minimal model that captures the fundamental features common to a wide variety of communication systems, and study the relationship between the entropy production of the communication process and the channel capacity, the canonical measure of the communication capability of a channel. In contrast to what is assumed in previous works not based on first principles, we show that the entropy production is not always a convex and monotonically increasing function of the channel capacity. However, those two properties are recovered for sufficiently high channel capacity. These results clarify when and how to split a single communication stream across multiple channels.

cond-mat.stat-mech↗

arXiv2024

Thermodynamic cost of precise timekeeping in an electronic underdamped clock

Clocks are inherently out-of-equilibrium because, due to friction, they constantly consume free energy to keep track of time. The Thermodynamic Uncertainty Relation (TUR) quantifies the trade-off between the precision of any time-antisymmetric observable and entropy production. In the context of clocks, the TUR implies that a minimum entropy production is needed in order to achieve a certain level of precision in timekeeping. But the TUR has only been proven for overdamped systems. Recently, a toy model of a classical underdamped pendulum clock was proposed that violated this relation (Phys. Rev. Lett. 128, 130606), thus demonstrating that the TUR does not hold for underdamped dynamics. We propose an electronic implementation of such a clock, using a resistor-inductor-capacitor (RLC) circuit and a biased CMOS inverter (NOT gate), which can work at different scales. We find that in the nanoscopic single-electron regime of the circuit, we essentially recover the toy model violating the TUR bound. However, in different macroscopic regimes of the circuit, we show that the TUR bound is restored and analyze the thermodynamic efficiency of timekeeping.

cond-mat.stat-mech↗

arXiv2024

Methods and Conversations in (Post)Modern Thermodynamics

Lecture notes after the doctoral school (Post)Modern Thermodynamics held at the University of Luxembourg, December 2022, 5-7, covering and advancing continuous-time Markov chains, network theory, stochastic thermodynamics, large deviations, deterministic and stochastic chemical reaction networks, metastability, martingales, quantum thermodynamics, and foundational issues.

cond-mat.stat-mech↗

arXiv2023

A chemical reaction network implementation of a Maxwell demon

We study an autonomous model of a Maxwell demon that works by rectifying thermal fluctuations of chemical reactions. It constitutes the chemical analog of a recently studied electronic demon. We characterize its scaling behavior in the macroscopic limit, its performances, and the impact of potential internal delays. We obtain analytical expressions for all quantities of interest, namely, the generated reverse chemical current, the output power, the transduction efficiency, and the correlations between the numbers of molecules. Due to a bound on the nonequilibrium response of its chemical reaction network, we find that, contrary to the electronic case, there is no way for the Maxwell demon to generate a finite output in the macroscopic limit. Finally, we analyze the information thermodynamics of the Maxwell demon from a bipartite perspective. In the limit of a fast demon, the information flow is obtained, its pattern in the state space is discussed, and the behavior of the partial efficiencies related to the measurement and the feedback processes is examined.

cond-mat.stat-mech↗

arXiv2023

Circuit Theory for Chemical Reaction Networks

We lay the foundation of a circuit theory for chemical reaction networks. Chemical reactions are grouped into chemical modules solely characterized by their current-concentration characteristic, as electrical devices by their current-voltage (I-V) curve in electronic circuit theory. This, combined with the chemical analog of Kirchhoff's current and voltage laws, provides a powerful tool to predict reaction currents and dissipation across complex chemical networks. The theory can serve to build accurate reduced models of complex networks as well as to design networks performing desired tasks.

q-bio.MN↗

arXiv2022

Information flows in macroscopic Maxwell's demons

A CMOS-based implementation of an autonomous Maxwell's demon was recently proposed (Phys. Rev. Lett. 129, 120602) to demonstrate that a Maxwell demon can still work at macroscopic scales, provided that its power supply is scaled appropriately. Here, we first provide a full analytical characterization of the non-autonomous version of that model. We then study system-demon information flows within generic autonomous bipartite setups displaying a macroscopic limit. By doing so, we can study the thermodynamic efficiency of both the measurement and the feedback process performed by the demon. We find that the information flow is an intensive quantity and that, as a consequence, any Maxwell's demon is bound to stop working above a finite scale if all parameters but the scale are fixed. However, this can be prevented by appropriately scaling the thermodynamic forces. These general results are applied to the autonomous CMOS-based demon.

cond-mat.stat-mech↗

arXiv2022

Emergent second law for non-equilibrium steady states

The Gibbs distribution universally characterizes states of thermal equilibrium. In order to extend the Gibbs distribution to non-equilibrium steady states, one must relate the self-information $\mathcal{I}(x) = -\log(P_\text{ss}(x))$ of microstate $x$ to measurable physical quantities. This is a central problem in non-equilibrium statistical physics. By considering open systems described by stochastic dynamics which become deterministic in the macroscopic limit, we show that changes $Δ\mathcal{I} = \mathcal{I}(x_t) - \mathcal{I}(x_0)$ in steady state self-information along deterministic trajectories can be bounded by the macroscopic entropy production $Σ$. This bound takes the form of an emergent second law $Σ+ k_b Δ\mathcal{I}\geq 0$, which contains the usual second law $Σ\geq 0$ as a corollary, and is saturated in the linear regime close to equilibrium. We thus obtain a tighter version of the second law of thermodynamics that provides a link between the deterministic relaxation of a system and the non-equilibrium fluctuations at steady state. In addition to its fundamental value, our result leads to novel methods for computing non-equilibrium distributions, providing a deterministic alternative to Gillespie simulations or spectral methods.

cond-mat.stat-mech↗

arXiv2022

Large deviations theory for noisy non-linear electronics: CMOS inverter as a case study

The latest generation of transistors are nanoscale devices whose performance and reliability are limited by thermal noise in low-power applications. Therefore developing efficient methods to compute the voltage and current fluctuations in such non-linear electronic circuits is essential. Traditional approaches commonly rely on adding Gaussian white noise to the macroscopic dynamical circuit laws, but do not capture rare fluctuations and lead to thermodynamic inconsistencies. A correct and thermodynamically consistent approach can be achieved by describing single-electron transfers as Poisson jump processes accounting for charging effects. But such descriptions can be computationally demanding. To address this issue, we consider the macroscopic limit which corresponds to scaling up the physical dimensions of the transistor and resulting in an increase of the number of electrons on the conductors. In this limit, the thermal fluctuations satisfy a Large Deviations Principle which we show is also remarkably precise in settings involving only a few tens of electrons, by comparing our results with Gillespie simulations and spectral methods. Traditional approaches are recovered by resorting to an ad hoc diffusive approximation introducing inconsistencies. To illustrate these findings, we consider a low-power CMOS inverter, or NOT gate, which is a basic primitive in electronic design. Voltage (resp. current) fluctuations are obtained analytically (semi-analytically) and reveal interesting features.

cond-mat.stat-mech↗

arXiv2022

A Maxwell demon that can work at macroscopic scales

Maxwell's demons work by rectifying thermal fluctuations. They are not expected to function at macroscopic scales where fluctuations become negligible and dynamics become deterministic. We propose an electronic implementation of an autonomous Maxwell's demon that indeed stops working in the regular macroscopic limit as the dynamics becomes deterministic. However, we find that if the power supplied to the demon is scaled up appropriately, the deterministic limit is avoided and the demon continues to work. The price to pay is a decreasing thermodynamic efficiency. Our work suggests that novel strategies may be found in nonequilibrium settings to bring to the macroscale non-trivial effects so far only observed at microscopic scales.

cond-mat.stat-mech↗

arXiv2021

Reliability and entropy production in non-equilibrium electronic memories

We find the relation between reliability and entropy production in a realistic model of electronic memory (low-power MOS-based SRAM) where logical values are encoded as metastable non-equilibrium states. We employ large deviations techniques to obtain an analytical expression for the bistable quasipotential describing the non-equilibrium steady state and use it to derive an explicit expression bounding the error rate of the memory. Our results go beyond the dominant contribution given by classical instanton theory and provide accurate estimates of the error rate as confirmed by comparison with stochastic simulations. The methods developed can be adapted to study the reliability of broad classes of nonlinear devices subjected to thermal noise.

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