Entropy最新文献

{"title":"On Meta-Geometric Gravity, Emergent Holography and Naturalness.","authors":"Andrea Addazi","doi":"10.3390/e28101095","DOIUrl":"https://doi.org/10.3390/e28101095","url":null,"abstract":"<p><p>We show that a discrete quantization law for cosmological entropy emerges naturally within a meta-geometric gauge theory of gravity, when the standard de Sitter entropy relation is combined with the topological structure of the theory. Our framework is based on a pre-metric action containing a MacDowell-Mansouri term with a spontaneously broken (A)dS gauge symmetry reduced to the Lorentz subgroup. We derive an inverse proportionality between the topological θ-angle and the cosmological constant, which enforces a topological quantization condition. As a consequence, the de Sitter entropy becomes quantized and scales linearly with a topological quantum number. This quantization provides a natural entropic stabilizer and a quantum topological protection for a large cosmological constant, thereby offering a microscopic gauge-theoretic realization of the holographic naturalness conjecture. We also discuss possible emergence of the N-portrait in cosmology and a dynamical relaxation of the vacuum energy.</p>","PeriodicalId":11694,"journal":{"name":"Entropy","volume":"28 10","pages":""},"PeriodicalIF":2.1,"publicationDate":"2026-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149264532","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exergoeconomic Analysis of Power Plants: Impact of Exergy Destruction Due to Entropy Generation on Unit Cost of Electricity.","authors":"Yungpil Yoo, Seok-Ho Seo, Si-Doek Oh, Ho-Young Kwak","doi":"10.3390/e28101097","DOIUrl":"https://doi.org/10.3390/e28101097","url":null,"abstract":"<p><p>Various exergy-based exergoeconomic methods have been developed to evaluate the production cost of electricity in power systems. One of the unresolved issues in the field of exergoeconomics is that different exergoeconomic analysis methods can yield different unit costs of power production. In this study, the unit cost of electricity generation is comprehensively analyzed using three representative approaches: the Moran method, the specific exergy costing (SPECO) method, and the Modified Productive Structure Analysis (MOPSA) method. The objective of this study is to identify a condition under which different exergoeconomic methods yield the same production cost for a power plant. The results show that power production costs are obtained using all three exergoeconomic methods when the costs associated with exergy destruction are appropriately incorporated in the cost-balance equation. In other words, under this condition, the cost-balance equations of SPECO and MOPSA for the entire power plant reduce to the Moran equation. These findings indicate that the critical issue in exergoeconomic analysis for determining the unit cost of products is whether the cost of exergy destruction is explicitly or implicitly accounted for. Furthermore, the numerical results demonstrate that all input cost rates, including equipment investment, operation and maintenance, and fuel costs, are fully recovered through the cost flow rates of the products. It is also shown that the cost flow associated with exergy destruction ultimately appears as the cost flow of waste streams.</p>","PeriodicalId":11694,"journal":{"name":"Entropy","volume":"28 10","pages":""},"PeriodicalIF":2.1,"publicationDate":"2026-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149264557","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Forecasting Explosive Bubble Regimes in Bitcoin Time Series with Multi-Step Ensemble Learning.","authors":"Jian-Rong Li, Guang-Yan Zhong, Jiang-Cheng Li","doi":"10.3390/e28101096","DOIUrl":"https://doi.org/10.3390/e28101096","url":null,"abstract":"<p><p>Bitcoin bubbles exhibit locally explosive dynamics, but identifying past episodes does not establish their predictability. We combine the generalized supremum augmented Dickey-Fuller test with nine probabilistic learners and three probability-output ensembles to forecast bubble states over one-, three-, and seven-day horizons. Using daily data from January 2016 to April 2026, we identify 30 maximal uninterrupted episodes comprising 455 bubble days. Development-period validation selects the lookback window and oversampling ratios before final-test evaluation; ensemble weights are estimated from development-period rolling forecasts. No model family dominates across horizons. The constrained least-squares ensemble has the lowest final-test mean squared error at one day, whereas logistic regression has the lowest error at three and seven days. The inverse-error-weighted ensemble has the highest average precision at seven days. Moving-block bootstrap intervals overlap substantially, and the 90% Model Confidence Set retains several models at every horizon. A cross-source robustness check yields 99.58% agreement in daily bubble-state classifications. These findings support horizon-dependent probabilistic risk monitoring, while the limited number of independent episodes and low recall at longer horizons constrain the practical interpretation of the forecasts.</p>","PeriodicalId":11694,"journal":{"name":"Entropy","volume":"28 10","pages":""},"PeriodicalIF":2.1,"publicationDate":"2026-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149264569","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Generalized Weighted Ordinal Pattern Descriptors for the Characterization of Adventitious Respiratory Sounds.","authors":"Jorge I Lopez Perez, Cristina D Duarte, Claudio A Delrieux","doi":"10.3390/e28101092","DOIUrl":"https://doi.org/10.3390/e28101092","url":null,"abstract":"<p><p>Automatic characterization of adventitious respiratory sounds is essential for developing computer-aided systems that support respiratory disease diagnosis. Commonly used acoustic descriptors, such as Mel frequency cepstral coefficients (MFCCs), primarily characterize spectral information and may not fully capture the nonlinear temporal dynamics of respiratory signals. In this work, we investigate the discriminative capability of Generalized Weighted Ordinal Pattern (GWOP) descriptors for representing adventitious respiratory sounds. Using respiratory recordings from the publicly available SPRSound pediatric database, GWOP descriptors were computed over multiple embedding dimensions, weighting factors, and time delays. An XGBoost classifier was employed exclusively as a supervised validation model to assess the discriminative information contained in the proposed feature representation, while the XGBoost Gain criterion was used to analyze the contribution of individual descriptor components. The proposed representation achieved stable performance across cross-validation folds, outperformed a conventional MFCC representation under the same evaluation protocol, and demonstrated that a reduced subset of Gain selected features preserved, and slightly improved, the classification performance while substantially reducing the dimensionality of the original feature space. These findings indicate that GWOP provides a lighter yet more informative and interpretable representation of adventitious respiratory sounds, capturing nonlinear ordinal dynamics that complement conventional spectral descriptors and offering a promising alternative for respiratory sound characterization.</p>","PeriodicalId":11694,"journal":{"name":"Entropy","volume":"28 10","pages":""},"PeriodicalIF":2.1,"publicationDate":"2026-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149264141","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Shared Functional Representation and Genomic Region Association Analysis of Longitudinal Phenotypes in Rice.","authors":"Yuejiao Ji, Xiaoping Chen","doi":"10.3390/e28101091","DOIUrl":"https://doi.org/10.3390/e28101091","url":null,"abstract":"<p><p>High-throughput phenotyping technologies enable plant growth to be measured repeatedly at high temporal resolution, providing rich information for studying the dynamic genetic basis of longitudinal traits. However, growth trajectories from repeated experiments contain both reproducible variation among lines and experiment-specific variation. In this study, we analyzed projected shoot area data from 356 rice lines measured in three independent experiments using an integrated genomic region association framework based on shared functional representation. We extracted the major longitudinal variation shared across experiments and characterized the covariance eigenspectra using spectral entropy and entropy-based effective rank. The first shared functional principal component explained 96.069% of shared variation, while the shared component had a normalized spectral entropy of 0.101 and an effective rank of 1.198. Regional association analysis using 200 kb genomic windows, with adjustment for population structure and leave-one-chromosome-out genetic relatedness, identified a region at 14.2-14.4 Mb on chromosome 10 that remained significant after false discovery rate correction (q=0.004). Further analyses showed time-varying regional effects and differences in association evidence across experiments, while the chromosome 10 signal was attenuated in an endpoint benchmark. Our analysis provides a method for linking longitudinal phenotypic variation shared across repeated experiments with localized genomic variation.</p>","PeriodicalId":11694,"journal":{"name":"Entropy","volume":"28 10","pages":""},"PeriodicalIF":2.1,"publicationDate":"2026-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149264528","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"From \"More Is Different\" to Algorithmic Emergence: Regularity, Compression, and the Limits of Discovery.","authors":"Giulio Ruffini, Francesca Castaldo","doi":"10.3390/e28101090","DOIUrl":"https://doi.org/10.3390/e28101090","url":null,"abstract":"<p><p>Scientific discovery seeks regularities that support explanation and prediction. Compression makes their reuse explicit: shared structure is described once, while parameters specify individual cases. A model can, therefore, pay for itself through repeated use even when its description is not minimal, provided it captures reusable structure in the data. Because regularities are often easier to identify in simpler systems, a reductionist approach is often employed: discover the laws of the parts and treat them as fundamental. Yet knowing those laws does not by itself provide useful coarse-grained models of the larger systems they compose. Here we formulate Anderson's distinction between reduction and construction for finite algorithmic observers and prove three barriers to such construction. First, an observer's coarse-grained record may retain so much information about initial or boundary conditions that no substantially shorter description exists, even when the underlying laws are simple and known. Second, when a shorter description does exist, open-ended search can eventually find one, but there is no computable bound on how long this may take, and no algorithm that always halts with a valid description can succeed in every case. Third, every such algorithm has blind spots at all sufficiently large lengths: records it leaves unshortened even though they admit descriptions of only logarithmic length. Yet observers do discover useful models. We call the event in which an observer acquires a representation relevant to its objective and a reusable model that reveals previously unavailable regularity <i>algorithmic emergence</i>. We give a sufficient certificate in explicit code lengths: the pair passes when, with its own description cost included, it compresses the retained data relative to an agreed baseline and yields further savings on later observations. Even for a stream that repeats one block, no computable procedure that always halts with valid codes can guarantee finding a passing pair with the observations available whenever one exists, nor remain within a fixed number of bits of the best qualifying complete code. Favorable structure, including symmetry and restricted model classes, can nevertheless make discovery feasible.</p>","PeriodicalId":11694,"journal":{"name":"Entropy","volume":"28 10","pages":""},"PeriodicalIF":2.1,"publicationDate":"2026-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149264499","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"HQMSGAN: Enhancing Adversarial Robustness Using Hybrid Quantum-Classical Multi-Scale Generative Adversarial Network.","authors":"Hamil Stanly, Mercy Shalinie Selvaraj, Riji Paul","doi":"10.3390/e28101089","DOIUrl":"https://doi.org/10.3390/e28101089","url":null,"abstract":"<p><p>The growing vulnerability of computer vision models to adversarial attacks has raised great concerns about the reliability of generative models in security-sensitive applications. Quantum generative models show strong potential for learning complex data distributions. However, the robustness of quantum generative models to adversarial perturbations and the effectiveness of adversarial training using quantum-classical generative architectures remain less explored. In this work, we evaluate quantum and classical generative network-inspired adversarial training to analyse whether quantum state-space representations can enhance adversarial robustness compared with their classical counterparts. We propose HQMSGAN, a novel hybrid quantum-classical generative adversarial network with multiscaling discriminators that denoise the adversarial attacks through adversarial training. During adversarial training, the proposed model performs quantum projections to learn rich nonlinear feature representations using quantum state encoding and performs feature coupling using quantum entanglement in the quantum state space. Thus, it learns the probability distribution of both the clean and adversarially perturbed data and tries to generate pure samples by reducing the loss over iterations in the quantum realm. The experiment is carried out by inducing four different adversarial attacks and defending them by adversarial training using the resources provided by AWS Braket's quantum simulators in the Noisy Intermediate Scale Quantum (NISQ) era. The results provide favorable performance on metrics such as Structural Similarity Index Measure (SSIM), Peak Signal-to-Noise Ratio (PSNR), Fréchet Inception Distance (FID) score, Learned Perceptual Image Patch Similarity (LPIPS), and classification accuracy after performing adversarial training.</p>","PeriodicalId":11694,"journal":{"name":"Entropy","volume":"28 10","pages":""},"PeriodicalIF":2.1,"publicationDate":"2026-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149264102","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Continuous Transmission of Delayed Bit-Interleaved Coded Modulation with Capacity-Preserving Boundary Pilot Design.","authors":"Gou Hosoya","doi":"10.3390/e28101087","DOIUrl":"https://doi.org/10.3390/e28101087","url":null,"abstract":"<p><p>Bit-interleaved coded modulation (BICM) with Gray labeling is widely used, yet its mismatched decoding metric keeps achievable rates below the coded modulation (CM) capacity, which multilevel coding attains only with multiple component codes. Delayed BICM (DBICM) bridges this gap with a single encoder and decoder by delaying coded bit subsequences so that already-decoded bits act as side information; for staircase delay vectors, its middle-region rate provably equals the CM capacity for any labeling. Under continuous transmission, however, initial and final codewords share symbols with pilot bits, and these boundary rates depend strongly on the pilot values. For pulse amplitude modulation, we design delay vectors and boundary pilots that keep every boundary rate at or above the middle-region capacity. For set-partitioning (SP) labeling, a closed-form minimum-shift pilot rule provably guarantees this condition for every staircase vector and SNR, whereas Gray labeling admits capacity-preserving pilots found by numerical search up to 32-PAM. Density evolution predicts gains approaching 1 dB over rate-matched BICM baselines for both labelings. Long continuous simulations, however, reveal severe inter-codeword error propagation under SP labeling, establishing Gray labeling as the practical choice. With per-level irregular LDPC codes, DBICM retains consistent threshold and waterfall gains at identical effective rates.</p>","PeriodicalId":11694,"journal":{"name":"Entropy","volume":"28 10","pages":""},"PeriodicalIF":2.1,"publicationDate":"2026-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149264390","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Information-Theoretic Limits and One-Bit Estimation of Sparse Relation Matrices Under Personalized Local Differential Privacy and Byzantine Contamination.","authors":"Jia Ouyang, Jinze Liu","doi":"10.3390/e28101088","DOIUrl":"https://doi.org/10.3390/e28101088","url":null,"abstract":"<p><p>We study estimation of globally sparse relation probability matrices from capped binary relation sets under personalized user-level local differential privacy and Byzantine response replacement. A cardinality-calibrated joint personalized relation sketch (JPRS) releases one bit per user. The decoder combines public channel-amplitude weighting with exact sparse feasible projection. We distinguish trimmed honest information, adversarial leverage, and a response-contamination indistinguishability radius. An explicit capped binary block construction yields a sampling lower bound with an explicit low-information truncation. A separate contamination construction gives a finite-sample error floor. For precommitted corrupted identities, the global decoder admits a uniform bound against adaptive valid-output attacks. In the strong-privacy, sufficiently informative regime, sampling and contamination bounds match up to logarithms on bounded-ratio budget classes, subject to the stated sample regularity and corruption-count conditions. The theory uses global sparsity rather than low-rank structure. Across six synthetic families, the global decoder has lower mean loss than the three tested private global baselines, but improves on zero only in the Zipf setting. Three public-data benchmarks further show that low aggregate error can be driven by a merged tail category. These results delimit practical utility; finite-budget attack searches do not certify worst-case performance.</p>","PeriodicalId":11694,"journal":{"name":"Entropy","volume":"28 10","pages":""},"PeriodicalIF":2.1,"publicationDate":"2026-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149264129","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"No-Signaling-in-Time Condition for Three-Flavor Neutrino Oscillations.","authors":"Massimo Blasone, Fabrizio Illuminati, Luciano Petruzziello, Kyrylo Simonov, Luca Smaldone","doi":"10.3390/e28101086","DOIUrl":"https://doi.org/10.3390/e28101086","url":null,"abstract":"<p><p>Macrorealism is a fundamental concept in quantum foundations, capturing basic features of our everyday experience. Among the main tools introduced to test violations of macrorealism are the Leggett-Garg inequalities. These inequalities provide necessary and sufficient conditions for a certain data set including the correlators measured in a number of different experimental runs (weak version of macrorealism). Leggett-Garg inequalities have proved useful for detecting violations of macrorealism in neutrino oscillation experiments. However, it is interesting to investigate a set of necessary and sufficient conditions for strong macrorealism-no-signaling-in-time and arrow-of-time conditions-in order to obtain a more complete characterization of macrorealism in the context of neutrino oscillations. In particular, here we extend a previous study of the no-signaling-in-time condition to the case of three-flavor neutrino oscillations, including the CP-violating phase of the Pontecorvo-Maki-Nakagawa-Sakata matrix.</p>","PeriodicalId":11694,"journal":{"name":"Entropy","volume":"28 10","pages":""},"PeriodicalIF":2.1,"publicationDate":"2026-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149264521","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}