Entropy最新文献_第10页

Entropy Modifications of Charged Accelerating Anti-de Sitter Black Hole. 带电加速反德西特黑洞的熵修正。

IF 2 3区物理与天体物理

Entropy Pub Date : 2025-08-25 DOI: 10.3390/e27090900

Cong Wang, Jie Zhang, Shu-Zheng Yang

引用次数: 0

An Efficient Two-Stage Decoding Scheme for LDPC-CRC Concatenated Codes. 一种高效的LDPC-CRC级联码两阶段译码方案。

IF 2 3区物理与天体物理

Entropy Pub Date : 2025-08-25 DOI: 10.3390/e27090899

Lingjun Kong, Haiyang Liu, Yuezhuang Shi, Jiacheng Miao

{"title":"An Efficient Two-Stage Decoding Scheme for LDPC-CRC Concatenated Codes.","authors":"Lingjun Kong, Haiyang Liu, Yuezhuang Shi, Jiacheng Miao","doi":"10.3390/e27090899","DOIUrl":"10.3390/e27090899","url":null,"abstract":"In modern communication systems, the concatenation of a low-density parity-check (LDPC) code with a cyclic redundancy check (CRC) code is commonly used for error correction. In this paper, we propose a low-complexity two-stage scheme for decoding these codes using their concatenation structures. In the first stage, the traditional belief propagation (BP)-based iterative algorithm with a relative small maximum number of iterations is performed for decoding the LDPC code. If an LDPC codeword is obtained in this stage, the decoding process terminates. Otherwise, the second stage of the decoding process is performed, in which the guessing random additive noise decoding (GRAND) algorithm is applied to the CRC code. A list of information sequences satisfying the CRC check is obtained, each of which is then encoded to an LDPC codeword. The most likely codeword among them is the output of the decoding approach. The simulation results indicate that the proposed two-stage decoding approach can outperform the traditional BP-based iterative algorithm with a large maximum number of iterations. Moreover, the average complexity of the proposed approach is relatively low.","PeriodicalId":11694,"journal":{"name":"Entropy","volume":"27 9","pages":""},"PeriodicalIF":2.0,"publicationDate":"2025-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12468592/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145174145","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Bridging Intuition and Data: A Unified Bayesian Framework for Optimizing Unmanned Aerial Vehicle Swarm Performance. 桥接直觉与数据：优化无人机群性能的统一贝叶斯框架。

IF 2 3区物理与天体物理

Entropy Pub Date : 2025-08-25 DOI: 10.3390/e27090897

Ruiguo Zhong, Zidong Wang, Hao Wang, Yanghui Jin, Shuangxia Bai, Xiaoguang Gao

{"title":"Bridging Intuition and Data: A Unified Bayesian Framework for Optimizing Unmanned Aerial Vehicle Swarm Performance.","authors":"Ruiguo Zhong, Zidong Wang, Hao Wang, Yanghui Jin, Shuangxia Bai, Xiaoguang Gao","doi":"10.3390/e27090897","DOIUrl":"10.3390/e27090897","url":null,"abstract":"The swift growth of the low-altitude economic ecosystem and Unmanned Aerial Vehicle (UAV) swarm applications across diverse sectors presents significant challenges for engineering managers in terms of effective performance evaluation and operational optimization. Traditional evaluation methods often struggle with the inherent complexities, dynamic nature, and multi-faceted performance criteria of UAV swarms. This study introduces a novel Bayesian Network (BN)-based multicriteria decision-making framework that systematically integrates expert intuition with real-time data. By employing variance decomposition, the framework establishes theoretically grounded, bidirectional mapping between expert-assigned weights and the network's probabilistic parameters, creating a unified model of subjective expertise and objective data. Comprehensive validation demonstrates the framework's efficacy in identifying critical performance drivers, including environmental awareness, communication ability, and a collaborative decision. Ultimately, our work provides engineering managers with a transparent and adaptive tool, offering actionable insights to inform resource allocation, guide technology adoption, and enhance the overall operational effectiveness of complex UAV swarm systems.","PeriodicalId":11694,"journal":{"name":"Entropy","volume":"27 9","pages":""},"PeriodicalIF":2.0,"publicationDate":"2025-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12469126/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145174199","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

YOLO-GRBI: An Enhanced Lightweight Detector for Non-Cooperative Spatial Target in Complex Orbital Environments. YOLO-GRBI：一种用于复杂轨道环境下非合作空间目标的增强型轻型探测器。

IF 2 3区物理与天体物理

Entropy Pub Date : 2025-08-25 DOI: 10.3390/e27090902

Zimo Zhou, Shuaiqun Wang, Xinyao Wang, Wen Zheng, Yanli Xu

{"title":"YOLO-GRBI: An Enhanced Lightweight Detector for Non-Cooperative Spatial Target in Complex Orbital Environments.","authors":"Zimo Zhou, Shuaiqun Wang, Xinyao Wang, Wen Zheng, Yanli Xu","doi":"10.3390/e27090902","DOIUrl":"10.3390/e27090902","url":null,"abstract":"Non-cooperative spatial target detection plays a vital role in enabling autonomous on-orbit servicing and maintaining space situational awareness (SSA). However, due to the limited computational resources of onboard embedded systems and the complexity of spaceborne imaging environments, where spacecraft images often contain small targets that are easily obscured by background noise and characterized by low local information entropy, many existing object detection frameworks struggle to achieve high accuracy with low computational cost. To address this challenge, we propose YOLO-GRBI, an enhanced detection network designed to balance accuracy and efficiency. A reparameterized ELAN backbone is adopted to improve feature reuse and facilitate gradient propagation. The BiFormer and C2f-iAFF modules are introduced to enhance attention to salient targets, reducing false positives and false negatives. GSConv and VoV-GSCSP modules are integrated into the neck to reduce convolution operations and computational redundancy while preserving information entropy. YOLO-GRBI employs the focal loss for classification and confidence prediction to address class imbalance. Experiments on a self-constructed spacecraft dataset show that YOLO-GRBI outperforms the baseline YOLOv8n, achieving a 4.9% increase in mAP@0.5 and a 6.0% boost in mAP@0.5:0.95, while further reducing model complexity and inference latency.","PeriodicalId":11694,"journal":{"name":"Entropy","volume":"27 9","pages":""},"PeriodicalIF":2.0,"publicationDate":"2025-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12469221/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145174302","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Born's Rule from Contextual Relative-Entropy Minimization. 上下文相对熵最小化的玻恩法则。

IF 2 3区物理与天体物理

Entropy Pub Date : 2025-08-25 DOI: 10.3390/e27090898

Arash Zaghi

{"title":"Born's Rule from Contextual Relative-Entropy Minimization.","authors":"Arash Zaghi","doi":"10.3390/e27090898","DOIUrl":"10.3390/e27090898","url":null,"abstract":"We give a variational characterization of the Born rule. For each measurement context, we project a quantum state ρ onto the corresponding abelian algebra by minimizing Umegaki relative entropy; Petz's Pythagorean identity makes the dephased state the unique local minimizer, so the Born weights pC(i)=Tr(ρPi) arise as a consequence, not an assumption. Globally, we measure contextuality by the minimum classical Kullback-Leibler distance from the bundle {pC(ρ)} to the noncontextual polytope, yielding a convex objective Φ(ρ). Thus, Φ(ρ)=0 exactly when a sheaf-theoretic global section exists (noncontextuality), and Φ(ρ)>0 otherwise; the closest noncontextual model is the classical I-projection of the Born bundle. Assuming finite dimension, full-rank states, and rank-1 projective contexts, the construction is unique and non-circular; it extends to degenerate PVMs and POVMs (via Naimark dilation) without change to the statements. Conceptually, the work unifies information-geometric projection, the presheaf view of contextuality, and categorical classical structure into a single optimization principle. Compared with Gleason-type, decision-theoretic, or envariance approaches, our scope is narrower but more explicit about contextuality and the relational, context-dependent status of quantum probabilities.","PeriodicalId":11694,"journal":{"name":"Entropy","volume":"27 9","pages":""},"PeriodicalIF":2.0,"publicationDate":"2025-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12468893/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145174220","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

ERLD-HC: Entropy-Regularized Latent Diffusion for Harmony-Constrained Symbolic Music Generation. 调和约束符号音乐生成的熵正则化潜扩散。

IF 2 3区物理与天体物理

Entropy Pub Date : 2025-08-25 DOI: 10.3390/e27090901

Yang Li

{"title":"ERLD-HC: Entropy-Regularized Latent Diffusion for Harmony-Constrained Symbolic Music Generation.","authors":"Yang Li","doi":"10.3390/e27090901","DOIUrl":"10.3390/e27090901","url":null,"abstract":"Recently, music generation models based on deep learning have made remarkable progress in the field of symbolic music generation. However, the existing methods often have problems of violating musical rules, especially since the control of harmonic structure is relatively weak. To address these limitations, this paper proposes a novel framework, the Entropy-Regularized Latent Diffusion for Harmony-Constrained (ERLD-HC), which combines a variational autoencoder (VAE) and latent diffusion models with an entropy-regularized conditional random field (CRF). Our model first encodes symbolic music into latent representations through VAE, and then introduces the entropy-based CRF module into the cross-attention layer of UNet during the diffusion process, achieving harmonic conditioning. The proposed model balances two key limitations in symbolic music generation: the lack of theoretical correctness of pure algorithm-driven methods and the lack of flexibility of rule-based methods. In particular, the CRF module learns classic harmony rules through learnable feature functions, significantly improving the harmony quality of the generated Musical Instrument Digital Interface (MIDI). Experiments on the Lakh MIDI dataset show that compared with the baseline VAE+Diffusion, the violation rates of harmony rules of the ERLD-HC model under self-generated and controlled inputs have decreased by 2.35% and 1.4% respectively. Meanwhile, the MIDI generated by the model maintains a high degree of melodic naturalness. Importantly, the harmonic guidance in ERLD-HC is derived from an internal CRF inference module, which enforces consistency with music-theoretic priors. While this does not yet provide direct external chord conditioning, it introduces a form of learned harmonic controllability that balances flexibility and theoretical rigor.","PeriodicalId":11694,"journal":{"name":"Entropy","volume":"27 9","pages":""},"PeriodicalIF":2.0,"publicationDate":"2025-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12468149/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145174450","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Two Dynamical Scenarios for Binned Master Sample Interpretation. 分类主样本解释的两种动态情景。

IF 2 3区物理与天体物理

Entropy Pub Date : 2025-08-24 DOI: 10.3390/e27090895

Giovanni Montani, Elisa Fazzari, Nakia Carlevaro, Maria Giovanna Dainotti

{"title":"Two Dynamical Scenarios for Binned Master Sample Interpretation.","authors":"Giovanni Montani, Elisa Fazzari, Nakia Carlevaro, Maria Giovanna Dainotti","doi":"10.3390/e27090895","DOIUrl":"10.3390/e27090895","url":null,"abstract":"We analyze two different scenarios for the late universe dynamics, resulting in Hubble parameters deviating from the ΛCDM, mainly for the presence of an additional free parameter, which is the dark energy parameter. The first model consists of a pure evolutionary dark energy paradigm as a result of its creation by the gravitational field of the expanding universe. The second model also considers an interaction of the evolutionary dark energy with the matter component, postulated via the conservation of the sum of their ideal energy-momentum tensors. These two models are then compared via the diagnostic tool of the effective running Hubble constant, with the binned data of the so-called \"Master sample\" for the Type Ia Supernovae. The comparison procedures, based on a standard MCMC analysis, lead to a clear preference of data for the dark energy-matter interaction model, which is associated with a phantom matter equation of state parameter (very close to -1) when, being left free by data (it has a flat posterior), it is fixed in order to reproduce the decreasing power-law behavior of the effective running Hubble constant, already discussed in the literature.","PeriodicalId":11694,"journal":{"name":"Entropy","volume":"27 9","pages":""},"PeriodicalIF":2.0,"publicationDate":"2025-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12469079/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145174275","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Circuit Design in Biology and Machine Learning. II. Anomaly Detection. 生物学和机器学习中的电路设计。2。异常检测。

IF 2 3区物理与天体物理

Entropy Pub Date : 2025-08-24 DOI: 10.3390/e27090896

Steven A Frank

{"title":"Circuit Design in Biology and Machine Learning. II. Anomaly Detection.","authors":"Steven A Frank","doi":"10.3390/e27090896","DOIUrl":"10.3390/e27090896","url":null,"abstract":"Anomaly detection is a well-established field in machine learning, identifying observations that deviate from typical patterns. The principles of anomaly detection could enhance our understanding of how biological systems recognize and respond to atypical environmental inputs. However, this approach has received limited attention in analyses of cellular and physiological circuits. This study builds on machine learning techniques-such as dimensionality reduction, boosted decision trees, and anomaly classification-to develop a conceptual framework for biological circuits. One problem is that machine learning circuits tend to be unrealistically large for use by cellular and physiological systems. I therefore focus on minimal circuits inspired by machine learning concepts, reduced to the cellular scale. Through illustrative models, I demonstrate that small circuits can provide useful classification of anomalies. The analysis also shows how principles from machine learning-such as temporal and atemporal anomaly detection, multivariate signal integration, and hierarchical decision-making cascades-can inform hypotheses about the design and evolution of cellular circuits. This interdisciplinary approach enhances our understanding of cellular circuits and highlights the universal nature of computational strategies across biological and artificial systems.","PeriodicalId":11694,"journal":{"name":"Entropy","volume":"27 9","pages":""},"PeriodicalIF":2.0,"publicationDate":"2025-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12468569/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145174236","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Post-Quantum Security of COPA. COPA的后量子安全性。

IF 2 3区物理与天体物理

Entropy Pub Date : 2025-08-23 DOI: 10.3390/e27090890

Ping Zhang, Yutao Wang

引用次数: 0

Entropy, Fidelity, and Entanglement During Digitized Adiabatic Quantum Computing to Form a Greenberger-Horne-Zeilinger (GHZ) State. 在数字化绝热量子计算中形成格林伯格-霍恩-塞林格（GHZ）态的熵、保真度和纠缠。

IF 2 3区物理与天体物理

Entropy Pub Date : 2025-08-23 DOI: 10.3390/e27090891

Nathan D Jansen, Katharine L C Hunt

{"title":"Entropy, Fidelity, and Entanglement During Digitized Adiabatic Quantum Computing to Form a Greenberger-Horne-Zeilinger (GHZ) State.","authors":"Nathan D Jansen, Katharine L C Hunt","doi":"10.3390/e27090891","DOIUrl":"10.3390/e27090891","url":null,"abstract":"We analyzed the accuracy of digitized adiabatic quantum computing to form the entangled three-qubit Greenberger-Horne-Zeilinger (GHZ) state on two IBM quantum computers and four quantum simulators by comparison with direct calculations using a Python code (version 3.12). We initialized three-qubit systems in the ground state of the Hamiltonian for noninteracting spins in an applied magnetic field in the x direction. We then gradually varied the Hamiltonian to an Ising model form with nearest-neighbor zz spin coupling with an eight-step discretization. The von Neumann entropy provides an indicator of the accuracy of the discretized adiabatic evolution. The von Neumann entropy of the density matrix from the Python code remains very close to zero, while the von Neumann entropy of the density matrices on the quantum computers increases almost linearly with the step number in the process. The GHZ witness operator indicates that the quantum simulators incorporate a GHZ component in part. The states on the two quantum computers acquire partial GHZ character, even though the trace of the product of the GHZ witness operator with the density matrix not only remains positive but also rises monotonically from Step 5 to Step 8. Each of the qubits becomes entangled during the adiabatic evolution in all of the calculations, as shown by the single-qubit reduced density matrices.","PeriodicalId":11694,"journal":{"name":"Entropy","volume":"27 9","pages":""},"PeriodicalIF":2.0,"publicationDate":"2025-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12468138/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145174411","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0