AI summary · arXiv: 1409.1439v1 · cond-mat.stat-mech

System size expansion using Feynman rules and diagrams

Philipp Thomas, Christian Fleck, Ramon Grima, Nikola Popović
Original paper · DOI 10.1088/1751-8113/47/45/455007 Submitted to arXiv on 04 Sep. 2014 25 pages, 5 figures, under review, Journal of Physics A License: NONEXCLUSIVE-DISTRIB 1.0

How to read this summary? Illustrated guide

The essentials

  • The authors address the challenge of studying large fluctuations in stochastic systems
  • They develop a simple diagrammatic approach to the Chemical Master Equation
  • The approach allows for the calculation of multi-time correlation functions with high accuracy using van Kampen's system size expansion
  • The authors present a set of Feynman rules for constructing a diagrammatic perturbation expansion algorithmically
  • These rules enable calculations up to any desired order in the system size expansion, providing a powerful tool for quantitative studies of stochastic systems
  • The methodology is applied to biochemical reaction networks and closed-form expressions for leading order corrections to the linear noise approximation are derived
  • The corrections reveal noise-induced oscillations in the Brusselator reaction scheme that are not captured by commonly used approximations like the linear noise approximation
  • The diagrammatic approach offers insights into complex dynamics and fluctuations in stochastic systems that would otherwise be missed

Key points written by AI: they may contain errors, check them against the paper.

AI-generated keywords: Stochastic systems

Read further

  • Comprehensive Summary
  • Layman's Summary
  • Blog article
  • Original abstract
, , , , In this article, the authors address the challenge of studying large fluctuations in stochastic systems by developing a simple diagrammatic approach to the Chemical Master Equation. This approach allows for the calculation of multi-time correlation functions with high accuracy using van Kampen's system size expansion. The authors present a set of Feynman rules that can be used to construct a diagrammatic perturbation expansion algorithmically. These rules enable the calculation of correlation functions to any desired order in the system size expansion, providing a powerful tool for quantitative studies of stochastic systems. pose challenges for accurate analysis due to their inherent randomness and fluctuations. To overcome this, the authors propose a novel approach based on . By utilizing van Kampen's system size expansion, they are able to calculate multi-time correlation functions with high precision. The key contribution of this work is the development of , which provide a systematic way to construct diagrammatic perturbation expansions. These rules allow for calculations up to any desired order in the system size expansion, making it a valuable tool for studying complex dynamics and fluctuations in stochastic systems. To demonstrate its effectiveness, the authors apply their methodology to biochemical reaction networks and derive closed-form expressions for leading order corrections to the linear noise approximation. This enables them to capture more accurately the behavior and fluctuations in such networks. By considering these corrections, they are able to reveal noise-induced oscillations in the Brusselator reaction scheme that are not captured by commonly used approximations like the linear noise approximation. This highlights how their diagrammatic approach can provide insights into complex dynamics and fluctuations that would otherwise be missed. In summary, this article presents a valuable contribution to analytical methods for studying large fluctuations in stochastic systems. The and developed here offer a systematic way to calculate correlation functions and improve upon existing approximations like the linear noise approximation. Its application to demonstrates its potential for understanding real-world systems with inherent stochasticity.

Was this synthesis useful?

Score: 0

Why do we need votes?

Votes are used to determine whether we need to re-run our summarizing tools. If the count reaches -10, our tools can be restarted.

Figures and plots

Ask about a figure by number or use its question button to request visual analysis. Up to two figures and four image panels per question. Values read from plots are approximate; check the original data.

AI assistant instructions?

Tools for this paper

Explain it differently 3 free rewrites left today
Save to a collection Group papers in collections to compare them, chat with them and export them. Create a free account Log in

Advanced tools Premium

For researchers who follow a field closely: citation alerts, journal-club slides, version comparison and Zotero export. Discover Premium

Zotero
Citation alerts Citation alerts guide
Journal club Premium+ Slides to present it

Papers around this one

See them on a map

Ranked by how close their title and abstract are to this paper’s. Select some to read them together.

Closest papers

  1. Related
    Finite-Size Scaling of Charge Carrier Mobility in Disordered Organic Semiconductors
    Pascal Kordt, Thomas Speck, Denis Andrienko · 2015 · Phys. Rev. B 94, 014208 (2016) · Not summarized yet
    Abstract

    Simulations of charge transport in amorphous semiconductors are often performed in microscopically sized systems. As a result, charge carrier mobilities become system-size dependent. We propose a simple method for extrapolating a macroscopic, nondispersive mobility from the system-size dependence of a microscopic one. The method is validated against a temperature-based extrapolation [Phys. Rev. B 82, 193202 (2010)]. In addition, we provide an analytic estimate of system sizes required to perform nondispersive charge transport simulations in systems with finite charge carrier density, derived from a truncated Gaussian distribution. This estimate is not limited to lattice models or specific ra…

  2. Related
    Classical limit of measurement-induced transition in many-body chaos in integrable and non-integrable oscillator chains
    Sibaram Ruidas, Sumilan Banerjee · 2022 · Statistical Mechanics · AI summary available
    Abstract

    We discuss the dynamics of integrable and non-integrable chains of coupled oscillators under continuous weak position measurements in the semiclassical limit. We show that, in this limit, the dynamics is described by a standard stochastic Langevin equation, and a measurement-induced transition appears as a noise- and dissipation-induced chaotic-to-non-chaotic transition akin to stochastic synchronization. In the non-integrable chain of anharmonically coupled oscillators, we show that the temporal growth and the ballistic light-cone spread of a classical out-of-time correlator characterized by the Lyapunov exponent and the butterfly velocity, are halted above a noise or below an interaction s…

  3. Related
    Large deviation full counting statistics in adiabatic open quantum dynamics
    Paulo J. Paulino, Igor Lesanovsky, Federico Carollo · 2024 · Statistical Mechanics · AI summary available
    Abstract

    The state of an open quantum system undergoing an adiabatic process evolves by following the instantaneous stationary state of its time-dependent generator. This observation allows one to characterize, for a generic adiabatic evolution, the average dynamics of the open system. However, information about fluctuations of dynamical observables, such as the number of photons emitted or the time-integrated stochastic entropy production in single experimental runs, requires controlling the whole spectrum of the generator and not only the stationary state. Here, we show how such information can be obtained in adiabatic open quantum dynamics by exploiting tools from large deviation theory. We prove …

  4. Related
    Field Theory of Birhythmicity
    Sergei Shmakov, Peter B. Littlewood · 2025 · Statistical Mechanics · AI summary available
    Abstract

    Non-equilibrium dynamics are present in many aspects of our lives, ranging from microscopic physical systems to the functioning of the brain. What characterizes stochastic models of non-equilibrium processes is the breaking of the fluctuation-dissipation relations as well as the existence of non-static stable states, or phases. A prototypical example is a dynamical phase characterized by a limit cycle - the order parameter of finite magnitude rotating or oscillating at a fixed frequency. Consequently, birhythmicity, where two stable limit cycles coexist, is a natural extension of the simpler single limit cycle phase. Both the abundance of real systems exhibiting such states as well as their …

  5. Related
    Topology protects chiral edge currents in stochastic systems
    Evelyn Tang, Jaime Agudo-Canalejo, Ramin Golestanian · 2020 · Phys. Rev. X 11, 031015 (2021) · AI summary available
    Abstract

    Constructing systems that exhibit time-scales much longer than those of the underlying components, as well as emergent dynamical and collective behavior, is a key goal in fields such as synthetic biology and materials self-assembly. Inspiration often comes from living systems, in which robust global behavior prevails despite the stochasticity of the underlying processes. Here, we present two-dimensional stochastic networks that consist of minimal motifs representing out-of-equilibrium cycles at the molecular scale and support chiral edge currents in configuration space. These currents arise in the topological phase due to the bulk-boundary correspondence and dominate the system dynamics in t…

  6. Related
    Dissipation in Hydrodynamics from Micro- to Macroscale: Wisdom from Boltzmann and Stochastic Thermodynamics
    Danilo Forastiere, Francesco Avanzini, Massimiliano Esposito · 2023 · Statistical Mechanics · AI summary available
    Abstract

    We show that macroscopic irreversible thermodynamics for viscous fluids can be derived from exact information-theoretic thermodynamic identities valid at the microscale. Entropy production in particular is a measure of the loss of many-particle correlations in the same way in which it measures the loss of system-reservoirs correlations in stochastic thermodynamics (ST). More specifically, we first show that boundary conditions at the macroscopic level define a natural decomposition of the entropy production rate (EPR) in terms of thermodynamic forces multiplying their conjugated currents, as well as a change in suitable nonequilibrium potential that acts as a Lyapunov function in absence of …

  7. Related
    Maximum Kolmogorov-Sinai entropy vs minimum mixing time in Markov chains
    Martin Mihelich, Berengere Dubrulle, Didier Paillard et al. · 2015 · Statistical Mechanics · AI summary available
    Abstract

    Many modern techniques employed in physics, such a computation of path integrals, rely on random walks on graphs that can be represented as Markov chains. Traditionally, estimates of running times of such sampling algorithms are computed using the number of steps in the chain needed to reach the stationary distribution. This quantity is generally defined as mixing time and is often difficult to compute. In this paper, we suggest an alternative estimate based on the Kolmogorov-Sinai entropy, by establishing a link between the maximization of KSE and the minimization of the mixing time. Since KSE are easier to compute in general than mixing time, this link provides a new faster method to appro…

  8. Related
    Nonperturbative Effects on the Ferromagnetic Transition in Repulsive Fermi Gases
    Lianyi He, Xu-Guang Huang · 2011 · Phys. Rev. A 85, 043624 (2012) · AI summary available
    Abstract

    It is generally believed that a dilute spin-1/2 Fermi gas with repulsive interactions can undergo a ferromagnetic phase transition to a spin-polarized state at a critical gas parameter $(k_{\rm F}a)_c$. Previous theoretical predictions of the ferromagnetic phase transition have been based on the perturbation theory, which treats the gas parameter as a small number. On the other hand, Belitz, Kirkpatrick, and Vojta (BKV) have argued that the phase transition in clean itinerant ferromagnets is generically of first order at low temperatures, due to the correlation effects that lead to a nonanalytic term in the free energy. The second-order perturbation theory predicts a first-order phase transi…

How are these papers found?

We compare the title and abstract of this paper with those of every paper summarized on this site, and with the papers Semantic Scholar recommends, those it cites and those citing it (for a much-cited paper, its most recent citations and, from OpenAlex, the most cited ones). Among the prior work and the follow-ups, the papers that use each other in depth, a method it uses and the much-cited follow-ups come a little higher. The levels (very close, close, related) come from the similarity of the texts, not from a judgment of quality; * marks a paper without an abstract, compared by its title. The sentence under a paper is written by an AI from the two abstracts: check it in the papers. A paper marked not relevant by three readers leaves the list.

For now only among the papers summarized on this site: search again to add the prior work, the follow-ups and Semantic Scholar’s recommendations.

The previous summary was created more than a year ago and can be re-run (if necessary) by clicking on the Run button below.

Disclaimer: The AI-based summarization tool and virtual assistant provided on this website may not always provide accurate and complete summaries or responses. We encourage you to carefully review and evaluate the generated content to ensure its quality and relevance to your needs.