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Fractional Calculus and the Future of Science

A special issue of Entropy (ISSN 1099-4300). This special issue belongs to the section "Complexity".

Deadline for manuscript submissions: closed (31 December 2020) | Viewed by 41249

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Guest Editor
Office of the Director, Army Research Office, Research Triangle Park, Durham, NC 27709, USA
Interests: nonlinear dynamics; network science; fractal physiology; fractional calculus

Special Issue Information

Dear Colleagues,

Three centuries ago, Newton transformed Natural Philosophy into today’s Science by focusing on change and quantification, and he did so in a way that resonated with the scientific community of his day. His arguments appeared to be geometric in character, and nowhere in the Principia do you find explicit reference to fluxions or to differentials. What Newton did was reveal the entailments of the calculus and convince generations of scientists of the value of their focusing on how physical objects change in space and time. Some contemporary mathematicians of his generation recognized what he had done, but their number could be counted on one hand, and their comments are primarily of historical interest only.

Fast-forward to today and Modern Science, from Anatomy to Zoology, is seen to have absorbed the transformational effect of Newton’s contribution to how we quantitatively and qualitatively understand the world, the fundamental importance of motion. However, it has occurred to a number of the more philosophically attuned contemporary scientists that we are now at another point of transition, where the implications of complexity, memory, and uncertainty have revealed themselves to be barriers to our future understanding of our technological society. Fractional calculus (FC) has emerged from the shadows as a way of taming the three horsemen in the figure with a methodology capable of analytically outdistancing these imposters.

We are looking for imaginative articles that implement FC and reveal its transformational nature, including but not limited to such things as: how a fractional derivative in time incorporates memory into the solution of the dynamic description of an earthquake, a brain quake or a crash in the stock market; how the fractional derivative in space incorporates spatial nonlocality into the solution of the complex dynamical descriptions of a riot, the collective intelligence of social groups, or the neuronal activity of the brain; or how the combined fractional derivatives in both time and space of measures of uncertainty incorporate both memory and nonlocality into the phase space solution to capture the limited uncertainty of an ensemble of fractal trajectories, or the scaling behavior of complex dynamical networks.

In short, we are seeking submissions in which the authors look behind the mathematics and examine what must be true about the phenomenon in order to justify the replacement of an ordinary derivative with a fractional derivative before they solve the new equations. For example, an insightful and extended explanatory description as to why one ought to expect the flow equations for honey and water to be different followed with a comparison of the solutions to the ordinary and fractional equations with data would constitute a paradigm for a submission. The desired articles are intended to provide the reader with a window into the future of a specific piece of science through the lens of FC and how that lens will make you think differently about that area of science. Thus, a perfect submission will be more about the intellectual implications and utility of the FC than it is about its formal structure in chemistry, epidemiology, sociology, psychology, physics, or any other scientific discipline.  

Prof. Dr. Bruce J. West
Guest Editor

Manuscript Submission Information

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Entropy is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Published Papers (13 papers)

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Editorial

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5 pages, 186 KiB  
Editorial
Fractional Calculus and the Future of Science
by Bruce J. West
Entropy 2021, 23(12), 1566; https://0-doi-org.brum.beds.ac.uk/10.3390/e23121566 - 25 Nov 2021
Cited by 5 | Viewed by 1492
Abstract
The invitation to contribute to this anthology of articles on the fractional calculus (FC) encouraged submissions in which the authors look behind the mathematics and examine what must be true about the phenomenon to justify the replacement of an integer-order derivative with a [...] Read more.
The invitation to contribute to this anthology of articles on the fractional calculus (FC) encouraged submissions in which the authors look behind the mathematics and examine what must be true about the phenomenon to justify the replacement of an integer-order derivative with a non-integer-order (fractional) derivative (FD) before discussing ways to solve the new equations [...] Full article
(This article belongs to the Special Issue Fractional Calculus and the Future of Science)

Research

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21 pages, 5118 KiB  
Article
Variable-Order Fractional Models for Wall-Bounded Turbulent Flows
by Fangying Song and George Em Karniadakis
Entropy 2021, 23(6), 782; https://0-doi-org.brum.beds.ac.uk/10.3390/e23060782 - 20 Jun 2021
Cited by 3 | Viewed by 2707
Abstract
Modeling of wall-bounded turbulent flows is still an open problem in classical physics, with relatively slow progress in the last few decades beyond the log law, which only describes the intermediate region in wall-bounded turbulence, i.e., 30–50 y+ to 0.1–0.2 R+ in a [...] Read more.
Modeling of wall-bounded turbulent flows is still an open problem in classical physics, with relatively slow progress in the last few decades beyond the log law, which only describes the intermediate region in wall-bounded turbulence, i.e., 30–50 y+ to 0.1–0.2 R+ in a pipe of radius R. Here, we propose a fundamentally new approach based on fractional calculus to model the entire mean velocity profile from the wall to the centerline of the pipe. Specifically, we represent the Reynolds stresses with a non-local fractional derivative of variable-order that decays with the distance from the wall. Surprisingly, we find that this variable fractional order has a universal form for all Reynolds numbers and for three different flow types, i.e., channel flow, Couette flow, and pipe flow. We first use existing databases from direct numerical simulations (DNSs) to lean the variable-order function and subsequently we test it against other DNS data and experimental measurements, including the Princeton superpipe experiments. Taken together, our findings reveal the continuous change in rate of turbulent diffusion from the wall as well as the strong nonlocality of turbulent interactions that intensify away from the wall. Moreover, we propose alternative formulations, including a divergence variable fractional (two-sided) model for turbulent flows. The total shear stress is represented by a two-sided symmetric variable fractional derivative. The numerical results show that this formulation can lead to smooth fractional-order profiles in the whole domain. This new model improves the one-sided model, which is considered in the half domain (wall to centerline) only. We use a finite difference method for solving the inverse problem, but we also introduce the fractional physics-informed neural network (fPINN) for solving the inverse and forward problems much more efficiently. In addition to the aforementioned fully-developed flows, we model turbulent boundary layers and discuss how the streamwise variation affects the universal curve. Full article
(This article belongs to the Special Issue Fractional Calculus and the Future of Science)
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32 pages, 4858 KiB  
Article
Why Do Big Data and Machine Learning Entail the Fractional Dynamics?
by Haoyu Niu, YangQuan Chen and Bruce J. West
Entropy 2021, 23(3), 297; https://0-doi-org.brum.beds.ac.uk/10.3390/e23030297 - 28 Feb 2021
Cited by 18 | Viewed by 5098
Abstract
Fractional-order calculus is about the differentiation and integration of non-integer orders. Fractional calculus (FC) is based on fractional-order thinking (FOT) and has been shown to help us to understand complex systems better, improve the processing of complex signals, enhance the control of complex [...] Read more.
Fractional-order calculus is about the differentiation and integration of non-integer orders. Fractional calculus (FC) is based on fractional-order thinking (FOT) and has been shown to help us to understand complex systems better, improve the processing of complex signals, enhance the control of complex systems, increase the performance of optimization, and even extend the enabling of the potential for creativity. In this article, the authors discuss the fractional dynamics, FOT and rich fractional stochastic models. First, the use of fractional dynamics in big data analytics for quantifying big data variability stemming from the generation of complex systems is justified. Second, we show why fractional dynamics is needed in machine learning and optimal randomness when asking: “is there a more optimal way to optimize?”. Third, an optimal randomness case study for a stochastic configuration network (SCN) machine-learning method with heavy-tailed distributions is discussed. Finally, views on big data and (physics-informed) machine learning with fractional dynamics for future research are presented with concluding remarks. Full article
(This article belongs to the Special Issue Fractional Calculus and the Future of Science)
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18 pages, 2427 KiB  
Article
Statistical Assessment of Discrimination Capabilities of a Fractional Calculus Based Image Watermarking System for Gaussian Watermarks
by Mario Gonzalez-Lee, Hector Vazquez-Leal, Luis J. Morales-Mendoza, Mariko Nakano-Miyatake, Hector Perez-Meana and Juan R. Laguna-Camacho
Entropy 2021, 23(2), 255; https://0-doi-org.brum.beds.ac.uk/10.3390/e23020255 - 23 Feb 2021
Cited by 5 | Viewed by 1783
Abstract
In this paper, we explore the advantages of a fractional calculus based watermarking system for detecting Gaussian watermarks. To reach this goal, we selected a typical watermarking scheme and replaced the detection equation set by another set of equations derived from fractional calculus [...] Read more.
In this paper, we explore the advantages of a fractional calculus based watermarking system for detecting Gaussian watermarks. To reach this goal, we selected a typical watermarking scheme and replaced the detection equation set by another set of equations derived from fractional calculus principles; then, we carried out a statistical assessment of the performance of both schemes by analyzing the Receiver Operating Characteristic (ROC) curve and the False Positive Percentage (FPP) when they are used to detect Gaussian watermarks. The results show that the ROC of a fractional equation based scheme has 48.3% more Area Under the Curve (AUC) and a False Positives Percentage median of 0.2% whilst the selected typical watermarking scheme has 3%. In addition, the experimental results suggest that the target applications of fractional schemes for detecting Gaussian watermarks are as a semi-fragile image watermarking systems robust to Gaussian noise. Full article
(This article belongs to the Special Issue Fractional Calculus and the Future of Science)
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21 pages, 2067 KiB  
Article
A Simplified Fractional Order PID Controller’s Optimal Tuning: A Case Study on a PMSM Speed Servo
by Weijia Zheng, Ying Luo, YangQuan Chen and Xiaohong Wang
Entropy 2021, 23(2), 130; https://0-doi-org.brum.beds.ac.uk/10.3390/e23020130 - 20 Jan 2021
Cited by 25 | Viewed by 2389
Abstract
A simplified fractional order PID (FOPID) controller is proposed by the suitable definition of the parameter relation with the optimized changeable coefficient. The number of the pending controller parameters is reduced, but all the proportional, integral, and derivative components are kept. The estimation [...] Read more.
A simplified fractional order PID (FOPID) controller is proposed by the suitable definition of the parameter relation with the optimized changeable coefficient. The number of the pending controller parameters is reduced, but all the proportional, integral, and derivative components are kept. The estimation model of the optimal relation coefficient between the controller parameters is established, according to which the optimal FOPID controller parameters can be calculated analytically. A case study is provided, focusing on the practical application of the simplified FOPID controller to a permanent magnet synchronous motor (PMSM) speed servo. The dynamic performance of the simplified FOPID control system is tested by motor speed control simulation and experiments. Comparisons are performed between the control systems using the proposed method and those using some other existing methods. According to the simulation and experimental results, the simplified FOPID control system achieves the optimal dynamic performance. Therefore, the validity of the proposed controller structure and tuning method is demonstrated. Full article
(This article belongs to the Special Issue Fractional Calculus and the Future of Science)
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17 pages, 1223 KiB  
Article
A Discretization Approach for the Nonlinear Fractional Logistic Equation
by Mohammad Izadi and Hari M. Srivastava
Entropy 2020, 22(11), 1328; https://0-doi-org.brum.beds.ac.uk/10.3390/e22111328 - 21 Nov 2020
Cited by 29 | Viewed by 2446
Abstract
The present study aimed to develop and investigate the local discontinuous Galerkin method for the numerical solution of the fractional logistic differential equation, occurring in many biological and social science phenomena. The fractional derivative is described in the sense of Liouville-Caputo. Using the [...] Read more.
The present study aimed to develop and investigate the local discontinuous Galerkin method for the numerical solution of the fractional logistic differential equation, occurring in many biological and social science phenomena. The fractional derivative is described in the sense of Liouville-Caputo. Using the upwind numerical fluxes, the numerical stability of the method is proved in the L norm. With the aid of the shifted Legendre polynomials, the weak form is reduced into a system of the algebraic equations to be solved in each subinterval. Furthermore, to handle the nonlinear term, the technique of product approximation is utilized. The utility of the present discretization technique and some well-known standard schemes is checked through numerical calculations on a range of linear and nonlinear problems with analytical solutions. Full article
(This article belongs to the Special Issue Fractional Calculus and the Future of Science)
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24 pages, 886 KiB  
Article
Sir Isaac Newton Stranger in a Strange Land
by Bruce J. West
Entropy 2020, 22(11), 1204; https://0-doi-org.brum.beds.ac.uk/10.3390/e22111204 - 25 Oct 2020
Cited by 7 | Viewed by 3797
Abstract
The theme of this essay is that the time of dominance of Newton’s world view in science is drawing to a close. The harbinger of its demise was the work of Poincaré on the three-body problem and its culmination into what is now [...] Read more.
The theme of this essay is that the time of dominance of Newton’s world view in science is drawing to a close. The harbinger of its demise was the work of Poincaré on the three-body problem and its culmination into what is now called chaos theory. The signature of chaos is the sensitive dependence on initial conditions resulting in the unpredictability of single particle trajectories. Classical determinism has become increasingly rare with the advent of chaos, being replaced by erratic stochastic processes. However, even the probability calculus could not withstand the non-Newtonian assault from the social and life sciences. The ordinary partial differential equations that traditionally determined the evolution of probability density functions (PDFs) in phase space are replaced with their fractional counterparts. Allometry relation is proven to result from a system’s complexity using exact solutions for the PDF of the Fractional Kinetic Theory (FKT). Complexity theory is shown to be incompatible with Newton’s unquestioning reliance on an absolute space and time upon which he built his discrete calculus. Full article
(This article belongs to the Special Issue Fractional Calculus and the Future of Science)
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21 pages, 368 KiB  
Article
Skellam Type Processes of Order k and Beyond
by Neha Gupta, Arun Kumar and Nikolai Leonenko
Entropy 2020, 22(11), 1193; https://0-doi-org.brum.beds.ac.uk/10.3390/e22111193 - 22 Oct 2020
Cited by 8 | Viewed by 2147
Abstract
In this article, we introduce the Skellam process of order k and its running average. We also discuss the time-changed Skellam process of order k. In particular, we discuss the space-fractional Skellam process and tempered space-fractional Skellam process via time changes in [...] Read more.
In this article, we introduce the Skellam process of order k and its running average. We also discuss the time-changed Skellam process of order k. In particular, we discuss the space-fractional Skellam process and tempered space-fractional Skellam process via time changes in Skellam process by independent stable subordinator and tempered stable subordinator, respectively. We derive the marginal probabilities, Lévy measures, governing difference-differential equations of the introduced processes. Our results generalize the Skellam process and running average of Poisson process in several directions. Full article
(This article belongs to the Special Issue Fractional Calculus and the Future of Science)
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18 pages, 2056 KiB  
Article
Fractal and Entropy Analysis of the Dow Jones Index Using Multidimensional Scaling
by José A. Tenreiro Machado
Entropy 2020, 22(10), 1138; https://0-doi-org.brum.beds.ac.uk/10.3390/e22101138 - 08 Oct 2020
Cited by 6 | Viewed by 3742
Abstract
Financial time series have a fractal nature that poses challenges for their dynamical characterization. The Dow Jones Industrial Average (DJIA) is one of the most influential financial indices, and due to its importance, it is adopted as a test bed for this study. [...] Read more.
Financial time series have a fractal nature that poses challenges for their dynamical characterization. The Dow Jones Industrial Average (DJIA) is one of the most influential financial indices, and due to its importance, it is adopted as a test bed for this study. The paper explores an alternative strategy to the standard time analysis, by joining the multidimensional scaling (MDS) computational tool and the concepts of distance, entropy, fractal dimension, and fractional calculus. First, several distances are considered to measure the similarities between objects under study and to yield proper input information to the MDS. Then, the MDS constructs a representation based on the similarity of the objects, where time can be viewed as a parametric variable. The resulting plots show a complex structure that is further analyzed with the Shannon entropy and fractal dimension. In a final step, a deeper and more detailed assessment is achieved by associating the concepts of fractional calculus and entropy. Indeed, the fractional-order entropy highlights the results obtained by the other tools, namely that the DJIA fractal nature is visible at different time scales with a fractional order memory that permeates the time series. Full article
(This article belongs to the Special Issue Fractional Calculus and the Future of Science)
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13 pages, 321 KiB  
Article
Time Fractional Fisher–KPP and Fitzhugh–Nagumo Equations
by Christopher N. Angstmann and Bruce I. Henry
Entropy 2020, 22(9), 1035; https://0-doi-org.brum.beds.ac.uk/10.3390/e22091035 - 16 Sep 2020
Cited by 12 | Viewed by 3237
Abstract
A standard reaction–diffusion equation consists of two additive terms, a diffusion term and a reaction rate term. The latter term is obtained directly from a reaction rate equation which is itself derived from known reaction kinetics, together with modelling assumptions such as the [...] Read more.
A standard reaction–diffusion equation consists of two additive terms, a diffusion term and a reaction rate term. The latter term is obtained directly from a reaction rate equation which is itself derived from known reaction kinetics, together with modelling assumptions such as the law of mass action for well-mixed systems. In formulating a reaction–subdiffusion equation, it is not sufficient to know the reaction rate equation. It is also necessary to know details of the reaction kinetics, even in well-mixed systems where reactions are not diffusion limited. This is because, at a fundamental level, birth and death processes need to be dealt with differently in subdiffusive environments. While there has been some discussion of this in the published literature, few examples have been provided, and there are still very many papers being published with Caputo fractional time derivatives simply replacing first order time derivatives in reaction–diffusion equations. In this paper, we formulate clear examples of reaction–subdiffusion systems, based on; equal birth and death rate dynamics, Fisher–Kolmogorov, Petrovsky and Piskunov (Fisher–KPP) equation dynamics, and Fitzhugh–Nagumo equation dynamics. These examples illustrate how to incorporate considerations of reaction kinetics into fractional reaction–diffusion equations. We also show how the dynamics of a system with birth rates and death rates cancelling, in an otherwise subdiffusive environment, are governed by a mass-conserving tempered time fractional diffusion equation that is subdiffusive for short times but standard diffusion for long times. Full article
(This article belongs to the Special Issue Fractional Calculus and the Future of Science)
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Review

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32 pages, 459 KiB  
Review
Telegraphic Transport Processes and Their Fractional Generalization: A Review and Some Extensions
by Jaume Masoliver
Entropy 2021, 23(3), 364; https://0-doi-org.brum.beds.ac.uk/10.3390/e23030364 - 18 Mar 2021
Cited by 14 | Viewed by 1860
Abstract
We address the problem of telegraphic transport in several dimensions. We review the derivation of two and three dimensional telegrapher’s equations—as well as their fractional generalizations—from microscopic random walk models for transport (normal and anomalous). We also present new results on solutions of [...] Read more.
We address the problem of telegraphic transport in several dimensions. We review the derivation of two and three dimensional telegrapher’s equations—as well as their fractional generalizations—from microscopic random walk models for transport (normal and anomalous). We also present new results on solutions of the higher dimensional fractional equations. Full article
(This article belongs to the Special Issue Fractional Calculus and the Future of Science)
42 pages, 1487 KiB  
Review
Applications of Distributed-Order Fractional Operators: A Review
by Wei Ding, Sansit Patnaik, Sai Sidhardh and Fabio Semperlotti
Entropy 2021, 23(1), 110; https://0-doi-org.brum.beds.ac.uk/10.3390/e23010110 - 15 Jan 2021
Cited by 49 | Viewed by 4654
Abstract
Distributed-order fractional calculus (DOFC) is a rapidly emerging branch of the broader area of fractional calculus that has important and far-reaching applications for the modeling of complex systems. DOFC generalizes the intrinsic multiscale nature of constant and variable-order fractional operators opening significant opportunities [...] Read more.
Distributed-order fractional calculus (DOFC) is a rapidly emerging branch of the broader area of fractional calculus that has important and far-reaching applications for the modeling of complex systems. DOFC generalizes the intrinsic multiscale nature of constant and variable-order fractional operators opening significant opportunities to model systems whose behavior stems from the complex interplay and superposition of nonlocal and memory effects occurring over a multitude of scales. In recent years, a significant amount of studies focusing on mathematical aspects and real-world applications of DOFC have been produced. However, a systematic review of the available literature and of the state-of-the-art of DOFC as it pertains, specifically, to real-world applications is still lacking. This review article is intended to provide the reader a road map to understand the early development of DOFC and the progressive evolution and application to the modeling of complex real-world problems. The review starts by offering a brief introduction to the mathematics of DOFC, including analytical and numerical methods, and it continues providing an extensive overview of the applications of DOFC to fields like viscoelasticity, transport processes, and control theory that have seen most of the research activity to date. Full article
(This article belongs to the Special Issue Fractional Calculus and the Future of Science)
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29 pages, 2171 KiB  
Review
Why the Mittag-Leffler Function Can Be Considered the Queen Function of the Fractional Calculus?
by Francesco Mainardi
Entropy 2020, 22(12), 1359; https://0-doi-org.brum.beds.ac.uk/10.3390/e22121359 - 30 Nov 2020
Cited by 80 | Viewed by 4423
Abstract
In this survey we stress the importance of the higher transcendental Mittag-Leffler function in the framework of the Fractional Calculus. We first start with the analytical properties of the classical Mittag-Leffler function as derived from being the solution of the simplest fractional differential [...] Read more.
In this survey we stress the importance of the higher transcendental Mittag-Leffler function in the framework of the Fractional Calculus. We first start with the analytical properties of the classical Mittag-Leffler function as derived from being the solution of the simplest fractional differential equation governing relaxation processes. Through the sections of the text we plan to address the reader in this pathway towards the main applications of the Mittag-Leffler function that has induced us in the past to define it as the Queen Function of the Fractional Calculus. These applications concern some noteworthy stochastic processes and the time fractional diffusion-wave equation We expect that in the future this function will gain more credit in the science of complex systems. Finally, in an appendix we sketch some historical aspects related to the author’s acquaintance with this function. Full article
(This article belongs to the Special Issue Fractional Calculus and the Future of Science)
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