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Entropy Change in Reversible Processes01:10

Entropy Change in Reversible Processes

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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.
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Standard Entropy Change for a Reaction03:00

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Entropy is a state function, so the standard entropy change for a chemical reaction (ΔS°rxn) can be calculated from the difference in standard entropy between the products and the reactants.
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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...
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The Entropy as a State Function01:14

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Consider an arbitrary process that moves between two specific states (A and B) in a cyclic manner. This process is reversible and broken down into smaller parts that each follow a Carnot cycle. A Carnot cycle has two isothermal (constant temperature) processes. During these processes, the ratio of the amount of heat transferred to their respective temperature remains constant. The other two processes in the Carnot cycle are also reversible but adiabatic, which means they occur without any heat...
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Relative Risk01:12

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Relative risk (RR) is a statistical measure commonly used in epidemiology to compare the likelihood of a particular event occurring between two groups. This metric is important for evaluating the relationship between exposure to a specific risk factor and the probability of a particular outcome. It plays a crucial role in medical research, public health studies, and risk assessment. Relative risk quantifies how much more (or less) likely an event is to occur in an exposed group compared to an...
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Entropy and the Second Law of Thermodynamics01:20

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The second law of thermodynamics can be stated quantitatively using the concept of entropy. Entropy is the measure of disorder of the system.
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Related Experiment Video

Updated: Feb 28, 2026

An R-Based Landscape Validation of a Competing Risk Model
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An R-Based Landscape Validation of a Competing Risk Model

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Crofton Risk and Relative Transactional Entropy.

Marcin Makowski1, Edward W Piotrowski2

  • 1Faculty of Physics, Department of Mathematical Methods in Physics, University of Białystok, ul. Ciołkowskiego 1L, 15-245 Białystok, Poland.

Entropy (Basel, Switzerland)
|February 27, 2026
PubMed
Summary
This summary is machine-generated.

This study introduces a geometric approach to financial risk, defining risk as exchange dilemmas from instrument trajectory intersections. This method yields a novel risk measure based on trajectory length, offering new market complexity insights.

Keywords:
Radon transformannual percentage rate (APR)complex systementropyfinancial instrumentmarketrisktrajectory temperature

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Area of Science:

  • Quantitative Finance
  • Geometric Measure Theory
  • Financial Mathematics

Background:

  • Traditional financial risk models often lack geometric intuition.
  • The annual percentage rate (APR) provides a simple model for financial instruments.
  • Understanding market complexity requires novel analytical tools.

Purpose of the Study:

  • To develop a novel geometric framework for quantifying financial risk.
  • To introduce new concepts for analyzing market dynamics and complexity.
  • To explore analogies between financial risk and thermodynamics.

Main Methods:

  • Utilizing Crofton's geometric approach and the Radon transform.
  • Defining financial instrument trajectories within a reference frame (money, benchmark).
  • Interpreting risk as the density of intersection dilemmas with simple instruments (APR-based).

Main Results:

  • A new risk measure derived from trajectory length in the Crofton-Steinhaus sense.
  • Introduction of geometric volatility, transactional entropy, and trajectory temperature.
  • Demonstration of thermodynamic analogies for describing market behavior.

Conclusions:

  • Geometric methods offer a new perspective on financial risk assessment.
  • The proposed framework enhances the understanding of market complexity.
  • Thermodynamic analogies can be fruitfully applied to financial market analysis.