Abstract
This manuscript aims to study the existence and uniqueness of solutions to a new system of differential equations. This system is a mixture of fractional operators and stochastic variables. The study has been completed under nonlocal functional boundary conditions. In the study, we used the fixed-point method to examine the existence of a solution to the proposed system, mainly focusing on the theorems of Leray, Schauder, and Perov in generalized metric spaces. Finally, an example has been provided to support and underscore our results.
Keywords:
existence solutions; fixed point techniques; fractional derivatives; boundary conditions; Perov’s and Leray–Schauder’s theorems; evaluation metrics MSC:
5R60; 60H15; 60G18; 35A01
1. Introduction
In 1940, fractional Brownian motion (FBM), often known as a Wiener Helix, was first described by Kolmogorov [1] in the setting of a Hilbert space (HS) and after giving a stochastic integral description of this process in terms of a standard BM, Mandelbrot and Van Ness introduced fractional BM in 1968. Reliability, asymptotic behavior, and character of moderate solutions to fractional BM stochastic delay evolution equations have yet to be well explored in many works. Sadovskii’s fixed point (FP) theorem was utilized by Cui and Yan [2] to investigate the possibility of a moderate solution to neutral stochastic integro-differential equations (DEs) with infinite delay. Following the proof of the existence of a mild solution to a nonlocal fractional stochastic DE by Sakthivel et al. [3], Jingyun and Xiaoyuan [4] provided sufficient conditions for the existence and uniqueness (EU) of mild solutions to a system with nonlocal fractional stochastic BM and Hurst index . Additional findings about fractional BM in stochastic equations can be discovered in [5,6,7,8,9,10,11].
Differential equations (DEs) incorporating fractional derivatives in time provide a more accurate description of many scientific processes, including those in economics, finance, chemistry, physics, and biology. Many physical phenomena, as represented by evolution equations, show some degree of dependence on previous events. As a result, recent years have seen a notable advancement in the theory of fractional integro-DEs. In particular, state-dependent delays in functional DEs arise frequently as mathematical models in a variety of applications. In recent years, much research has been conducted in this field because of the considerable differences in specific properties between these equations and those with constant or time-dependent delays. To learn more, go to [12,13,14,15].
One practical approach for solving nonlinear engineering issues is the FP technique. By utilizing this technology, engineers can efficiently address complicated systems when typical linear approaches fail. By identifying points that do not change under a given transformation, this technique allows for the iterative determination of solutions. It benefits tasks like structural stability analysis, design optimization, and solving various nonlinear equations commonly encountered in engineering applications. For other diverse applications of this approach, go to [16,17,18,19,20,21].
Recent years have seen a significant interest in the literature for problems pertaining to the presence of solutions of various equation types incorporating nonlocal conditions, as seen by the publications [22,23,24,25,26,27]. This paper investigates the EU of a mild solution to the fractional DE system driven by BM
where is the fractional-order of the Caputo fractional derivative (CFD) formulation with lower limit 0. On a Banach space (BS) are linear operators, which generates a strongly continuous semigroup of contractions Assume that is a probability space (PS) and is a real Hilbert space (HS), for the stochastic process (SP) and are given functions and are given functional, where takes values in Further, for on a real HS W, refer to the fractional BM via Hurst index
The spaces below will be used in the next sections.
2. Preliminaries
In this part, we will collect most of the definitions and theorems related to the subject of our study, briefly and clearly. We begin with the notation of a generalized metric space (GMS) and its topological properties [28].
Definition 1.
Assume that and the distance mapping fulfills the following conditions: for all
- (i)
- and if then
- (ii)
- (iii)
Then, the pair is called a GMS.
Here, means and ; means for It is clear that
- for anyis a metric space on S,
- forrepresents the open ball with the center at and radius also, the closure of is denoted by
- is a GMS with
- d is a GMS if and only if are metrics on S for
- for the vector valued metric is generalized Banach space (BS) if S is complete with respect to (w.r.t.) d.
Definition 2.
Assume that V is a square matrix in with a spectral radius We say that V is convergent to zero if
Theorem 1
([29]). Assume that then the axioms below are equivalent
- (1)
- (2)
- as
- (3)
- that is, the matrix is nonsingular andwhere I denotes the identity matrix in
- (4)
- has nonnegative elements, provided that
Definition 3.
Let ℵ be a self-mapping defined on a GMS If there exists a convergent matrix V to zero such that
Then, ℵ is called a contractive mapping.
It should be noted that, the classical contraction mapping can be obtained if we take .
Next, we present two FP theorems, which we used it in our proofs; see [30,31].
Theorem 2
(Perov theorem). Assume that is a GMS and ℵ is a contractive mapping, then ℵ has a unique FP and
A note was made in [31] regarding the function of spectral radius smaller than one matrices in the analysis of semilinear operator systems and their relation to other abstract ideas from nonlinear functional analysis.
Theorem 3
(Leray–Schauder theorem). Let be a BS, , and = and the operator be a completely continuous. If for every solution ϖ of the equation and any then χ has at least one FP.
Next, we introduce some basic concepts of one-dimensional fractional BM. For more details about fractional BM, see [32,33,34].
Definition 4.
For Hurst index the one-dimensional fractional BM = is a Gaussian process, that is, continuous, centered, and has a covariance function
Remark 1.
- (i)
- is a standard BM if
- (ii)
- can be described over a finite interval, for aswhere represents a Wiener process (WP),and is a constant depending on
- (iii)
- The process is a usual BM if
- (iv)
- If , then (2) takes the form that is, no have independent increments and has α-Hölder continuous paths for
In the rest of the manuscript, we shall consider
Assume that be a linear space defined on the following step function in
where Also, we denote the closure of by with w.r.t. The Wiener integral of w.r.t. is presented by
In addition, there exists an isometric mapping
between and linear space span viewed as a subspace of One can expand this mapping to an isometric between and the fractional BM’s first Wiener chaos
Based on this isometric, the image of is called the Wiener integral of f w.r.t.
Suppose that is a linear operator described as
Clearly, an isometric between and that can be extended to is produced by the operator The relation between the Itô integral w.r.t. the WP and the Wiener integral w.r.t. fractional BM is as follows:
Moreover, for
Further, we have
provided that
According to the results of [35], for , we get
Next, we provide the definition of the related random integral and the infinite dimensional fractional BM. Assume that is a non-negative self-adjoint trace (Tr) class operator described by such that
where and represent the orthonormal basis for W.
In the context of the PS with covariance operator R, define the W-valued R-cylindrical fractional BM by
where contained in , independent, one-dimensional fractional BM. This process has zero mean, zero covariance and is a W-valued Gaussian process. It begins at 0. Hence, one can write
and possesses W-valued and sample paths over P.
Define the space by
It should be noted that is called an R-HSO if
The space endowed with the inner product
is a separable HS.
Definition 5
([36]). Assume that satisfy
Then, the random integral of Φ w.r.t. is given by
Lemma 1
([37]). If fulfills (5), then
where is a constant depending on Further, if is uniformly convergent, then
From the fractional calculus, we now provide some fundamental definitions and properties. Here, the integer part of p is represented by , and is the Gamma function.
Definition 6
([38]). For the function
- (i)
- the Riemann–Liouville (RL) integral of order p is described asprovided that the integral exists on where
- (ii)
- the RL derivative of order p is given byfor all and all
- (iii)
- the CFD of order p is defined byIn addition, if we get
The meaning of a mild solution to the system (1) is then defined. We need the following ideas in order to accomplish this.
Definition 7
([34]). Assume that is a PS. If the filtration satisfies the axioms below
- (i)
- if
- (ii)
Then Θ is called a family of algebras indexed by and all belonging to
Definition 8
([34]). Let be a PS. If the random variable is measurable relative to we say that the SP is adapted.
Now, we present our definition about a mild solution in this paper.
Definition 9.
Let be a PS. A real-valued SP is said to be a mild solution to the system (1) if the following assumptions are true:
- (i)
- and
- (ii)
- for all is adapted,
- (iii)
- for all owns a limit from the left and is right continuous,
- (iv)
- for fulfillswhereis our strongly continuous semigroup inthe function is a probability density described on with
Moreover, we need the following lemma:
Lemma 2.
The following hypotheses are true:
- (1)
- for each fixed and are BLOs. Particularly, there is a positive constant K such that
- (2)
- for all and are strongly continuous,
- (3)
- the operators and are compact, provided that is compact for every
We can consider our system as a FP problem in for the nonlinear operator
which is described as
3. Main Theorems
In this section, we present the existence and uniqueness of the solution to the system (1) under mild conditions. We start with the following assertions:
- (A1)
- There exist the constants , and such thatfor all and
- (A2)
- There exists the constants , and such thatfor all .
Here, we apply Perov’s FP theorem to study the existence and uniqueness of the FP, which is consider a unique solution of our system.
Theorem 4.
Via the hypotheses and , if the matrix
convergence to 0. Then, the system (1) has a unique solution.
Proof.
We obtain the proof by fulfilling the assumptions of Perov’s FP theorem. Consider
and applying Lemma 2, the hypotheses and , Hölder’s inequality, and Fubini’s theorem, we can write
which implies that
Analogously, we get
and
Hence, one has
Therefore,
According to Theorem 2, ℶ has a unique FP which it is a unique solution to the system (1). □
Now, using the nonlinear alternative of the Leray-Schauder type, we shall present an existence result. To get our result, we need the following circumstances:
- (A3)
- and are -Carathédory functions;
- (A4)
- There exist positive constants and such thatfor all
- (A5)
- There exist the functions and in for such thatfor every , and
- (A6)
- For there exist measurable functions and there exist positive constants such that
- (i)
- (ii)
- ,
- (iii)
- is uniformly convergent.
Theorem 5.
Proof.
It is evident that the system (1) can be solved by the FPs of the operator ℶ stated in (6). We first demonstrate that ℶ is completely continuous in order to apply Theorem 2. We split the proof onto the following stages:
- Stage 1:
- is continuous. Assume that is a sequence such that as Then,Using the hypothesis we haveSince as then, by the Lebesgue dominated convergence theorem (LDCT), we have as Again, from Hölder’s inequality and Lemma 2, one hasApplying the hypothesis and using the LDCT, we have as because is -Carathédory (Hypothesis and as Similarly, one can writeandThis proves that ℶ is continuous.
- Stage 2:
- ℶ maps bounded sets into bounded sets in It’s enough to demonstrate that for any there exists a constant such that, for we haveFor each from , we can writewhereApplying the hypothesis Hölder’s inequality and Lemma 2, we haveTo estimate we use the hypothesis and Lemma 2 as follows:Therefore,Analogously,andwhereThis implies that the inequality (7) holds.
- Stage 3:
- ℶ maps bounded sets into equicontinuous sets in Assume that is a bounded set defined in Stage 2. Also, assume that and with we haveSince is strongly continuous, thenApplying the hypothesis and Lemma 2, we haveBy the LDCT, we conclude thatNow,Using the hypothesis , Hölder’s inequality, Lemma 2, and Fubini’s stochastic theorem, we can writeHence, Again, by using the hypothesis , Hölder’s inequality, Lemma 2, we getHence, Now,Using the condition and Lemma 2, we getTherefore, Also,Therefore, Thus, and as Consequently,Similarly,andHence,Therefore, the function is continuous on By Arzelá-Ascoli theorem, is completely continuous.
- Stage 4:
- Solutions are a priori bounded. For using the hypotheses and we getSimilarly,andHence,which implies thatwhereandBy using Gronwall’s inequality on (7), there is such thatSettingand consider the operator From the definition of there is no such that for some Theorem 3 leads to having a FP in J, which is a solution to the problem (1).
□
4. Numerical Example
In this section, we conclude our results by giving an illustrative example and as an application to support the theoretical results, which is finding a solution to the partial neutral stochastic functional differential system. A stochastic process can be used to model phenomena that change randomly over time, like traffic flow in a network or financial markets. Specific examples discussed including using continuous-time Markov chains to model packet networks, Poisson processes to model message generations in telecommunications systems, the growth of a bacterial population, an electrical current fluctuating due to thermal noise, or the movement of a gas molecule. Stochastic deferential equations have many applications throughout pure mathematics and are used to model various behaviors of stochastic models such as stock prices, random grows models or physical systems that are subjected to thermal fluctuations.
Example 1.
Consider the following stochastic problem:
where represents a fractional BM, and the functions and are continuous. Consider
for each Take and define an operator ℑ as with domain
It is clear that
Define an analytic semigroup by
Clearly, the operator ℑ is an infinitesimal generator of where is the orthogonal set of eigenvectors of ℑ.
Further, is compact, and there is a constant such that Thus, the system (9) reduces to
Now, we consider the continuous functions
with
Moreover, if we take
we find that the hypotheses are satisfied. Therefore, by Theorem 5, there is at least one solution to the Problem 5 on
5. Conclusions and Future Work
Understanding nonlinear fractional stochastic systems is essential for systematizing real-world processes with memory and randomness. Researchers continue to explore new mathematical tools and techniques to address the complexities posed by these equations. So, in this manuscript, we investigate the existence and uniqueness of solutions for a novel system of differential equations. This system combines fractional operators and stochastic variables. Our study is conducted under nonlocal functional boundary conditions. To analyze the existence of a solution, we employ the fixed-point method, specifically utilizing the theorems of Leray–Schauder and Perov in generalized metric spaces. Additionally, we explore an illustrative example to bolster our findings. There are many exciting avenues to explore within the field of nonlinear fractional stochastic differential systems. Researchers can build upon existing results, develop new mathematical techniques, and address practical applications in various scientific domains.
Author Contributions
All authors contributed equally in the writing and editing of this article. All authors read and approved the final version of the manuscript.
Funding
The Researchers would like to thank the Deanship of Graduate Studies and Scientific Research at Qassim University for financial support (QU-APC-2024-9/1).
Data Availability Statement
The data used to support the findings of this study are available from the corresponding author upon request.
Acknowledgments
The Researchers would like to thank the Deanship of Graduate Studies and Scientific Research at Qassim University for financial support (QU-APC-2024-9/1).
Conflicts of Interest
The authors declare that they have no conflicts of interest.
Abbreviations
The following abbreviations are used in this manuscript:
| BM | Brownian motion |
| HS | Hilbert space |
| FP | fixed point |
| DE | Differential equation |
| EU | existence and uniqueness |
| BS | Banach space |
| CFD | Caputo fractional derivative |
| SP | stochastic process |
| PS | probability space |
| BLO | Bounded linear operator |
| GMS | generalized metric space |
| w.r.t. | with respect to |
| WP | Wiener process |
| Tr | trace |
| HSO | Hilbert–Schmidt operator |
| RL | Riemann–Liouville |
| LDCT | Lebesgue dominated convergence theorem |
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