Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Random Variables01:09

Random Variables

A random variable is a single numerical value that indicates the outcome of a procedure. The concept of random variables is fundamental to the probability theory and was introduced by a Russian mathematician, Pafnuty Chebyshev, in the mid-nineteenth century.
Uppercase letters such as X or Y denote a random variable. Lowercase letters like x or y denote the value of a random variable. If X is a random variable, then X is written in words, and x is given as a number.
For example, let X = the...
Entropy Change in Reversible Processes01:10

Entropy Change in Reversible Processes

In the Carnot engine, which achieves the maximum efficiency between two reservoirs of fixed temperatures, the total change in entropy is zero. The observation can be generalized by considering any reversible cyclic process consisting of many Carnot cycles. Thus, it can be stated that the total entropy change of any ideal reversible cycle is zero.
The statement can be further generalized to prove that entropy is a state function. Take a cyclic process between any two points on a p-V diagram.
Censoring Survival Data01:09

Censoring Survival Data

Survival analysis is a statistical method used to analyze time-to-event data, often employed in fields such as medicine, engineering, and social sciences. One of the key challenges in survival analysis is dealing with incomplete data, a phenomenon known as "censoring." Censoring occurs when the event of interest (such as death, relapse, or system failure) has not occurred for some individuals by the end of the study period or is otherwise unobservable, and it might have many different reasons...
Propagation of Uncertainty from Random Error00:59

Propagation of Uncertainty from Random Error

An experiment often consists of more than a single step. In this case, measurements at each step give rise to uncertainty. Because the measurements occur in successive steps, the uncertainty in one step necessarily contributes to that in the subsequent step. As we perform statistical analysis on these types of experiments, we must learn to account for the propagation of uncertainty from one step to the next. The propagation of uncertainty depends on the type of arithmetic operation performed on...
Randomized Experiments01:13

Randomized Experiments

The randomization process involves assigning study participants randomly to experimental or control groups based on their probability of being equally assigned. Randomization is meant to eliminate selection bias and balance known and unknown confounding factors so that the control group is similar to the treatment group as much as possible. A computer program and a random number generator can be used to assign participants to groups in a way that minimizes bias.
Simple randomization
Simple...
Entropy Changes Accompanying Specific Processes01:21

Entropy Changes Accompanying Specific Processes

Entropy, a measure of disorder in a system, changes during phase transitions like freezing or boiling. At the transition temperature Ttrs, where two phases are in equilibrium, the phase transition is a reversible process. The entropy change can be calculated from a substance's enthalpy of transition using the equation ΔStrs = ΔtrsH /Ttrs.When a perfect gas expands isothermally from one volume to another, entropy increases logarithmically with volume. Conversely, isothermal compression results...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Pedestrian's approach to large deviations in semi-Markov processes with an application to entropy production.

Physical review. E·2026
Same author

General theory for localizing the where and when of entropy production meets single-molecule experiments.

Proceedings of the National Academy of Sciences of the United States of America·2024
Same author

Estimator of entropy production for partially accessible Markov networks based on the observation of blurred transitions.

Physical review. E·2024
Same author

Nonequilibrium fluctuations of chemical reaction networks at criticality: The Schlögl model as paradigmatic case.

The Journal of chemical physics·2024
Same author

Time-Resolved Statistics of Snippets as General Framework for Model-Free Entropy Estimators.

Physical review letters·2023
Same author

Waiting Time Distributions in Hybrid Models of Motor-Bead Assays: A Concept and Tool for Inference.

International journal of molecular sciences·2023
Same journal

Erratum: Spectroscopy and Ground-State Transfer of Ultracold Bosonic ^{39}K^{133}Cs Molecules [Phys. Rev. Lett. 135, 203401 (2025)].

Physical review letters·2026
Same journal

Erratum: Lifetime of the ^{2}F_{7/2} Level in Yb^{+} for Spontaneous Emission of Electric Octupole Radiation [Phys. Rev. Lett. 127, 213001 (2021)].

Physical review letters·2026
Same journal

Laser-Plasma Based Seeded Free Electron Laser in the High-Gain Regime.

Physical review letters·2026
Same journal

Parent Hamiltonians for Stabilizer Quantum Many-Body Scars.

Physical review letters·2026
Same journal

Properties of Heavy Cosmic Nuclei Phosphorus, Chlorine, Argon, Potassium, and Calcium: Results from the Alpha Magnetic Spectrometer.

Physical review letters·2026
Same journal

Role of Spin-Isospin Symmetries in Nuclear β-Decays.

Physical review letters·2026
See all related articles

Related Experiment Videos

Compensating Random Transition-Detection Blackouts in Markov Networks.

Alexander M Maier1, Benjamin Häsler1, Udo Seifert1

  • 1Universität Stuttgart, II. Institut für Theoretische Physik, 70550 Stuttgart, Germany.

Physical Review Letters
|July 7, 2026
PubMed
Summary
This summary is machine-generated.

Measurement blackouts in Markov networks disrupt thermodynamic inference. This study introduces a method to correct observed data, enabling reliable estimation of entropy production even with unknown blackout frequencies.

Related Experiment Videos

Area of Science:

  • Statistical physics
  • Non-equilibrium thermodynamics
  • Stochastic processes

Background:

  • Measurement blackouts in Markov networks obscure thermodynamic quantities.
  • Observed currents fail to distinguish equilibrium from non-equilibrium states.
  • Existing entropy production estimators are compromised by data gaps.

Purpose of the Study:

  • To develop a strategy for reliable thermodynamic inference despite measurement blackouts.
  • To recover accurate estimations of entropy production.
  • To address limitations in current data analysis methods for stochastic systems.

Main Methods:

  • Modeling blackouts as a secondary channel in Markov networks.
  • Analyzing the short-time limit of waiting-time distributions to determine blackout frequency and transition rates.
  • Post-modifying observed trajectory data to create virtual effective dynamics.

Main Results:

  • A method to determine unknown blackout frequencies and true transition rates is established.
  • Post-modification of data allows full recovery of the lower bound on entropy production using thermodynamic uncertainty relations.
  • The corrected data integrates with waiting-time based estimators for entropy production.

Conclusions:

  • The proposed strategy effectively corrects for measurement blackouts in Markov networks.
  • Reliable inference of thermodynamic quantities, including entropy production, is achievable.
  • The method is robust, not requiring homogeneous or time-reversal symmetric blackout occurrences.