Entropy

Scope & Guideline

Bridging disciplines to tackle complex scientific challenges.

Introduction

Explore the comprehensive scope of Entropy through our detailed guidelines, including its aims and scope. Stay updated with trending and emerging topics, and delve into declining areas to understand shifts in academic interest. Our guidelines also showcase highly cited topics, featuring influential research making a significant impact. Additionally, discover the latest published papers and those with high citation counts, offering a snapshot of current scholarly conversations. Use these guidelines to explore Entropy in depth and align your research initiatives with current academic trends.
LanguageEnglish
ISSN-
PublisherMDPI
Support Open AccessNo
Country-
Type-
Converge-
AbbreviationENTROPY-SWITZ / Entropy
Frequency12 issues/year
Time To First Decision-
Time To Acceptance-
Acceptance Rate-
Home Page-
AddressST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND

Aims and Scopes

The journal 'Entropy' primarily focuses on the interdisciplinary study of entropy in various fields, including physics, information theory, and complex systems. It aims to advance the understanding of entropy's role in systems ranging from quantum mechanics to thermodynamics and information science.
  1. Theoretical and Applied Entropy:
    Research exploring the fundamental principles of entropy across disciplines, including thermodynamics, statistical mechanics, and information theory.
  2. Complex Systems and Dynamics:
    Studies focusing on the dynamics of complex systems, including biological, ecological, and socio-economic systems, emphasizing how entropy influences system behavior.
  3. Quantum Information and Computation:
    Investigations into the role of entropy in quantum systems, including quantum information theory, quantum computing, and the implications of quantum entanglement.
  4. Entropy in Data Science and Machine Learning:
    Applications of entropy in data analysis, machine learning, and artificial intelligence, including feature selection, model evaluation, and uncertainty quantification.
  5. Entropy and Network Theory:
    Research examining the role of entropy in network structures, dynamics, and information flow, particularly in social networks and biological networks.
  6. Entropy in Environmental and Ecological Studies:
    Studies that utilize entropy measures to assess ecological diversity, environmental changes, and resource management.
Recent publications in 'Entropy' indicate a shift toward more interdisciplinary and applied research themes. These emerging topics reflect the evolving landscape of scientific inquiry where entropy serves as a pivotal concept across various domains.
  1. Entropy in Machine Learning and AI:
    There is a growing interest in utilizing entropy as a measure in machine learning, particularly in feature selection, model evaluation, and improving the robustness of algorithms.
  2. Quantum Computing and Information Theory:
    Research exploring the intersection of quantum mechanics and information theory is rapidly expanding, particularly regarding entanglement, quantum states, and their implications for computational efficiency.
  3. Entropy in Health and Biological Systems:
    Emerging studies are applying entropy concepts to health sciences, particularly in understanding complex biological processes and the dynamics of health-related data.
  4. Environmental Applications of Entropy:
    Research on the application of entropy measures in environmental science and ecology is trending, particularly in assessing biodiversity, climate change impacts, and resource management.
  5. Complex Networks and Entropy:
    The exploration of entropy within complex networks, including social networks, biological systems, and financial markets, indicates a significant trend towards understanding the dynamics and structure of these networks.

Declining or Waning

While 'Entropy' continues to publish a broad range of topics, certain themes have shown signs of declining prominence in recent years. This may reflect shifts in research focus or emerging areas of interest that overshadow previous trends.
  1. Classical Thermodynamics:
    Research specifically focused on classical thermodynamic principles appears to be waning as the field shifts towards more complex systems and interdisciplinary approaches.
  2. Basic Information Theory:
    While information theory remains a core theme, the focus on foundational concepts without interdisciplinary applications has declined in favor of more applied and complex analyses.
  3. Traditional Statistical Mechanics:
    The application of traditional statistical mechanics concepts in isolation is less frequent, with a growing preference for integrating these ideas into broader frameworks involving complex systems or quantum mechanics.
  4. Entropy in Simple Systems:
    Research that deals with entropy in overly simplified systems or models is becoming less common, as there is a clear trend towards studying more complex, real-world systems.

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