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maximum entropy

Grammar usage guide and real-world examples

USAGE SUMMARY

The phrase "maximum entropy" is correct and usable in written English.
It is typically used in contexts related to information theory, statistics, and thermodynamics to describe a state of highest uncertainty or disorder. Example: "In the context of statistical mechanics, the system reaches maximum entropy when it is in thermodynamic equilibrium."

✓ Grammatically correct

Science

News & Media

Formal & Business

Human-verified examples from authoritative sources

Exact Expressions

59 human-written examples

Similarly, the one-way street to maximum entropy is just that, it has a beginning and an end.

News & Media

The New York Times

For the ultimate laptop, the maximum entropy corresponds to an information capacity of about 2.13 x 1031 bits -- a billion trillion times more than today's laptops.

Maximum Entropy.

bias-corrected maximum entropy.

MaxEnt ∙ (maximum entropy) [27].

This is thus the maximum entropy solution.

Equal probable quantization offers maximum entropy.

Based on copulas and univariate maximum entropy margins, multivariate maximum entropy distributions are constructed.

The second-stage algorithm uses a maximum entropy classifier.

A maximum entropy distribution signifies the decentralization of the network.

They tend to the state of thermodynamic equilibrium (maximum entropy).

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Expert writing Tips

Best practice

When discussing physical systems, clarify the context (e.g., thermodynamics, information theory) to ensure the meaning of "maximum entropy" is clear. For example: "The system reached its "maximum entropy" state at thermal equilibrium."

Common error

Avoid assuming that "maximum entropy" implies simplicity or ease of understanding. It often represents complex states with high uncertainty, not necessarily elementary arrangements.

Antonio Rotolo, PhD - Digital Humanist | Computational Linguist | CEO @Ludwig.guru

Antonio Rotolo, PhD

Digital Humanist | Computational Linguist | CEO @Ludwig.guru

Source & Trust

82%

Authority and reliability

4.5/5

Expert rating

Real-world application tested

Linguistic Context

The phrase "maximum entropy" functions primarily as a noun phrase. It typically acts as a subject or object in a sentence, denoting a specific state or condition in various scientific and technical contexts. Ludwig AI confirms its accurate usage.

Expression frequency: Very common

Frequent in

Science

77%

News & Media

13%

Formal & Business

10%

Less common in

Academia

0%

Encyclopedias

0%

Wiki

0%

Ludwig's WRAP-UP

In summary, "maximum entropy" is a noun phrase of high utility, primarily functioning to denote a state of maximum disorder or uncertainty in scientific contexts. Ludwig AI validates its grammatical correctness. It is frequently encountered in scientific publications and academic papers, while its presence in news media and business contexts, though notable, remains secondary. Alternative phrasing might involve terms like "peak entropy" or ""greatest uncertainty"", but it's important to consider that in some contexts there's no alternative.

FAQs

How is "maximum entropy" used in thermodynamics?

In thermodynamics, "maximum entropy" describes a state of equilibrium in a closed system, where energy is evenly distributed and no further work can be extracted. This state represents the highest degree of disorder.

What does "maximum entropy" mean in information theory?

In information theory, "maximum entropy" signifies the probability distribution that best represents the current state of knowledge about a system. It represents the highest uncertainty given the available constraints, similar to "greatest uncertainty".

Which fields commonly use the concept of "maximum entropy"?

The concept of "maximum entropy" is commonly applied in fields such as thermodynamics, information theory, statistical mechanics, machine learning, and ecology. Its broad applicability stems from its ability to model systems with limited information.

What are some practical applications of the "maximum entropy" principle?

Practical applications include species distribution modeling (using Maxent software), image reconstruction, and natural language processing. These models aim to make predictions based on incomplete data by maximizing entropy under given constraints.

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Source & Trust

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Authority and reliability

4.5/5

Expert rating

Real-world application tested

Most frequent sentences: