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Related Concept Videos

Entropy02:39

Entropy

Salt particles that have dissolved in water never spontaneously come back together in solution to reform solid particles. Moreover, a gas that has expanded in a vacuum remains dispersed and never spontaneously reassembles. The unidirectional nature of these phenomena is the result of a thermodynamic state function called entropy (S). Entropy is the measure of the extent to which the energy is dispersed throughout a system, or in other words, it is proportional to the degree of disorder of a...
Entropy01:18

Entropy

The first law of thermodynamics is quantitatively formulated via an equation relating the internal energy of a system, the heat exchanged by it, and the work done on it. A quantitative formulation of the second law of thermodynamics leads to defining a state function, the entropy.
When an ideal gas expands isothermally, the disorder in the gas increases. From the molecular perspective, the gas molecules have more volume to move around in.
Consider an infinitesimal step in the expansion, which...
The Entropy as a State Function01:14

The Entropy as a State Function

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...
Entropy and the Second Law of Thermodynamics01:20

Entropy and the Second Law of Thermodynamics

The second law of thermodynamics can be stated quantitatively using the concept of entropy. Entropy is the measure of disorder of the system.
The relation  between entropy and disorder can be illustrated with the example of the phase change of ice to water. In ice, the molecules are located at specific sites giving a solid state, whereas, in a liquid form, these molecules are much freer to move. The molecular arrangement has therefore become more randomized. Although the change in average...
Entropy and the Second Law of Thermodynamics01:26

Entropy and the Second Law of Thermodynamics

Consider an isolated system in which a hot object is placed in contact with a cold one. This is an irreversible process that eventually leads both objects to reach the same equilibrium temperature. It is crucial to note that the constituents of any substance exhibit increased disorder at higher temperatures. As a cold substance absorbs heat, its constituents become more disordered. The energy transfer from a hotter object to a cooler one increases the system's disorder or randomness. This...
Absolute Entropies and the Third Law of Thermodynamics01:23

Absolute Entropies and the Third Law of Thermodynamics

Ludwig Edward Boltzmann developed a definition for entropy, which stated that absolute entropy is proportional to the natural logarithm of the number of possible combinations of particles. Entropy stands alone among state functions as the only one whose absolute values can be determined.Consider a gas sample confined to a container. As the container expands, the energy levels of gas molecules become more closely spaced. This increases the number of available energy states, thereby increasing...

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Related Experiment Video

Updated: May 14, 2026

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
05:30

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Published on: September 8, 2023

Post-Quantum Entropy as a Service for Embedded Systems.

Javier Blanco-Romero1, Yuri Melissa Garcia-Niño1,2, Florina Almenares Mendoza1

  • 1Department of Telematic Engineering, Universidad Carlos III de Madrid, 28911 Leganés, Spain.

Sensors (Basel, Switzerland)
|May 13, 2026
PubMed
Summary

This study introduces a Quantum Entropy as a Service (QEaaS) system for secure, post-quantum communication on small devices. The system offers faster key exchange and authentication than classical methods, enhancing embedded cryptography.

Keywords:
CoAPIoTPQCQEaaSQRNGsZephyrcryptographyentropymicrocontrollers

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A Photonic System for Generating Unconditional Polarization-Entangled Photons Based on Multiple Quantum Interference
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A Photonic System for Generating Unconditional Polarization-Entangled Photons Based on Multiple Quantum Interference

Published on: September 5, 2019

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Last Updated: May 14, 2026

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
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Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

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A Photonic System for Generating Unconditional Polarization-Entangled Photons Based on Multiple Quantum Interference
07:56

A Photonic System for Generating Unconditional Polarization-Entangled Photons Based on Multiple Quantum Interference

Published on: September 5, 2019

Area of Science:

  • Cryptography and Network Security
  • Quantum Technologies
  • Embedded Systems Engineering

Background:

  • Embedded systems require high-quality entropy for cryptography, but often lack sufficient sources and processing power for complex protocols.
  • Existing solutions struggle to balance security needs with the resource constraints of small devices.

Purpose of the Study:

  • To develop and evaluate a Quantum Entropy as a Service (QEaaS) system for resource-constrained embedded devices.
  • To enable post-quantum cryptography (PQC) for secure communication on ESP32-class clients using quantum-derived entropy.
  • To benchmark the performance of PQC key exchange and authentication against classical methods.

Main Methods:

  • Implemented a QEaaS system transmitting quantum random number generator (QRNG) entropy over post-quantum secured channels to ESP32 clients.
  • Integrated wolfSSL-based DTLS 1.3 into the CoAP stack on the client-side, incorporating a BLAKE2s entropy pool with an injection API.
  • Developed server-side entropy paths: direct quantum entropy via OpenSSL and mixed entropy via the Linux system pool.

Main Results:

  • The QEaaS system demonstrated faster DTLS 1.3 handshake times using ML-KEM-512 (313 ms) compared to ECDHE P-256 (35% slower).
  • A fully post-quantum configuration (ML-KEM-512 with ML-DSA-44) achieved a mean handshake time of 225 ms, remaining 63% faster than classical methods even with full verification.
  • Client-side BLAKE2s pool operations were minimal (<0.1 ms), indicating efficient entropy handling.

Conclusions:

  • Post-quantum key exchange and authentication are feasible and outperform classical baselines on ESP32-class embedded platforms.
  • The QEaaS system effectively provides high-quality entropy, overcoming limitations in resource-constrained devices.
  • This approach significantly enhances the security and performance of embedded cryptography.