Abstract
This paper is devoted to the general theory of systems of linear time-fractional differential-operator equations. The representation formulas for solutions of systems of ordinary differential equations with single (commensurate) fractional order is known through the matrix-valued Mittag-Leffler function. Multi-order (incommensurate) systems with rational components can be reduced to single-order systems, and, hence, representation formulas are also known. However, for arbitrary fractional multi-order (not necessarily with rational components) systems of differential equations, the representation formulas are still unknown, even in the case of fractional-order ordinary differential equations. In this paper, we obtain representation formulas for the solutions of arbitrary fractional multi-order systems of differential-operator equations. The existence and uniqueness theorems in appropriate topological vector spaces are also provided. Moreover, we introduce vector-indexed Mittag-Leffler functions and prove some of their properties.
1. Introduction
Let X be a reflexive Banach space and a closed linear operator with a domain Consider the systems of time-fractional differential operator equations, which we will write in the form
with the initial condition
In Equation (1), fractional orders of the system is an abstract vector-valued function with components to be found, and
Here, is the fractional-order derivative of order in the sense of Riemann–Liouville or Caputo. The matrix-valued operator on the right-hand side of Equation (1) has the form
is a given vector-valued function satisfying some conditions clarified later. In initial condition (2), the operator B depends on whether is in the sense of Riemann–Liouville or Caputo and is a given element of some topological vector space specified later. The operator has a matrix symbol the entries of which may have singularities in the spectrum of the operator The exact definitions of operators and are given in Section 2.
It is well known (see, e.g., [1,2]) that if , then the solution is represented in the form
where
is the solution operator, which has an exponential form. It is also known [3,4,5,6,7,8,9,10] that, in the case of various fractional-order differential equations (not systems), the solution can be represented through the Mittag-Leffler (ML) function
which generalizes the exponential function. Namely, if then we have In the case of systems, when has equal components, i.e., a representation formula for the solution is obtained via the matrix-valued ML function [11,12,13,14,15]. Namely, the solution operator emerges in the form
where for a matrix Z is defined by
In the case where the components of the vector-order in Equation (1) are rational, i.e., where and are co-prime numbers, the corresponding system can be reduced to a system with a scalar order [16,17,18]. However, the number of equations in the reduced system may increase significantly. Let M be the lowest common multiple of numbers and Then, the number of equations in the reduced system becomes For example, if the orders in the original system of four equations are and then and Thus, the reduced system will contain 467 equations of order although, originally, we had only four equations in the system. Even numerical solutions of such reduced systems consume a significant amount of computing and time resources; thus, the method of reducing to a scalar-order system should be considered ineffective. Therefore, developing direct general techniques for the solution and qualitative analysis of systems of fractional-order differential equations with any positive real order is important.
The representation formula for the solution of fractional-order systems in the sense of Riemann–Liouville with equal orders (commensurate case) and constant matrix was first obtained in [11]. The authors of [19] derived representations in the case of Riemann–Liouville, Caputo, and sequential Miller–Ross derivatives under the same conditions for orders and matrix Applications to multi-term commensurate fractional-order ordinary differential equations, as well as various techniques for the calculation of the matrix-valued ML functions, are considered in [13]. In [16], the procedure for the reduction of incommensurate rational orders to the commensurate case is discussed. The authors of [17] use this technique to derive a representation formula for the solution. Note that, in these works, also is a constant matrix—that is, the corresponding systems are of ordinary differential equations, and fractional derivatives are in the sense of Caputo. The representation formulas for a fractional multi-order system of pseudo-differential equations are found in [18], in both commensurate and incommensurate rational-order cases, for Riemann–Liouville and Caputo derivatives. Moreover, in this work, representation formulas are obtained for systems of arbitrary positive time-fractional-order pseudo-differential equations with upper or lower triangular matrix-valued pseudo-differential operators.
In the current paper, we obtain representation formulas for arbitrary multi-order with real components (not necessarily rational) and arbitrary matrix-valued operator The results obtained in this paper are new even for time-fractional systems of linear ordinary differential equations. We also introduce more general ML functions, called vector-indexed matrix-valued ML functions. We show that the solution of systems (1) and (2) is represented through an operator-dependent matrix-valued ML function.
We note that systems of fractional-order ordinary and partial differential equations have rich applications. For example, they are used in the modeling of processes in bio-systems [20,21,22], ecology [23,24], epidemiology [25,26], quantum systems [27,28,29], etc.
This paper is organized as follows. In Section 2, we provide some preliminary facts about the ML functions, including matrix-valued versions. To our knowledge, Lemmas 1 and 2 are new. Here, we also introduce the vector-indexed matrix-valued ML functions and study some of their properties used in this paper. This section introduces the basic topological vector spaces on which the corresponding matrix-valued operators with singular symbols act. In Section 3 and Section 4, we formulate the main results. The representation formulas for the solution of the initial value problem (1), (2) are obtained in the general case: for arbitrary multi-order and matrix-valued operator The main idea of the method used to obtain the representation formula is demonstrated for clarity, first in the case and then for arbitrary Note that some particular representation formulas were obtained in [18] in the case of systems of pseudo-differential operators. These results are also extended to the differential-operator case. Finally, in Section 5, we discuss some applications and examples.
2. Preliminaries
2.1. Fractional Derivatives
By definition, the Riemann–Liouville fractional derivative of order of a function defined on is the integral
subject to existence, where is Euler’s gamma function. Similarly, if then the Caputo derivative is defined by the integral
subject to existence.
The Laplace transforms of the Riemann–Liouville and Caputo derivatives are
respectively. We will use these formulas in the vector form. Namely, for a vector-valued function we have
where
with fractional integrals
Similarly,
In these formulas,
for both operators and
2.2. Matrix-Valued Functions
Let Z be a square matrix of size m with the Jordan normal form
where M is an invertible transformation matrix, is a diagonal matrix with eigenvalues on the diagonal and N is the nilpotent matrix. Suppose that are Jordan blocks of Z and is the matrix norm of Then, for a function analytic in a neighborhood of , one has the spectral representation
where the spectral measure is formed by projection operators determined by eigenvalues of the matrix Z of multiplicity In the explicit form, this means that
where
2.3. Classical ML Functions
The classical two-parameter ML function is defined by
where is the set of complex numbers and parameters This function plays an important role in the theory of fractional-order differential equations. For various properties of the ML function, we refer the reader to sources [30,31] and the references therein. Here, we only mention some properties of used in the current paper. The function is an entire function of order and recovers the exponential function when It is known [30,31] that for the ML function has asymptotic behavior
and
For derivatives of , the following formulas are valid:
Consider the function with a parameter This function plays an important role in the theory of fractional-order differential equations. For the Laplace transform of this function and its derivatives, the following formulas hold [3,10,30]:
where In particular, if then one obtains
and if in (20),
The convolution of functions is defined by
The following lemmas will be used in our further analysis.
Lemma 1.
For and the following relations hold:
- (a)
- (b)
where I is the identity operator and is the fractional integral of order
Proof. (a) To prove this statement, we show that the Laplace transforms of both sides in (24) coincide. Indeed, applying the Laplace transform to the left side of (24), we have
This is obviously the Laplace transform of the right-hand side of (24), as well.
Lemma 2.
For any and parameters , the following relations hold:
- (i)
- (ii)
where “*” is the convolution operation.
Proof. (i) Again, we show that the Laplace transforms of both sides in Equations (26) and (27) coincide. For the Laplace transform of the left-hand side of (26), we have
where
This is obviously the Laplace transform of the right-hand side of (26), as well.
(ii) Similarly, the Laplace transform of the left-hand side of (27) is
On the other hand, due to the convolution theorem, the Laplace transform of the right-hand side of (27) also results in the same expression. □
2.4. Matrix-Valued ML Functions
Since is an entire function, in accordance with (14) and (15), for a matrix Z, one can introduce a matrix-valued version of the ML function as
where
with the block matrices
corresponding to (algebraic) eigenvalues of the matrix It is not difficult to verify that, using Formulas (19), (20), and (30), one obtains the Laplace transforms of the matrix-valued function
2.5. Vector-Indexed Matrix-Valued ML Functions
Let and be vector indices with components For a diagonal matrix D with diagonal entries we use the notation
Definition 1.
Let Z be a square matrix of size with complex entries. A vector-indexed matrix-valued ML function denoted by is defined by
where
The vector-indexed matrix-valued ML function generalizes the classical and above-considered matrix-valued ML functions. Below are some examples.
- Let and Then, we obtain the classical two-parameter ML function
- Let and Then, we obtain the matrix-valued ML function [13,30]Indeed, in this case,
Let be eigenvalues of (algebraic) multiplicity of the matrix and let be the Jordan block of the Jordan canonical form corresponding to Then, it is not difficult to see that
where and with blocks
Now, suppose that
and
Then, it follows from (35) that, for each
where is a diagonal matrix of size
The latter implies
We note that, in general, is not the same as unless vector indices and have equal components. Indeed, using the equality
one obtains
since matrices and M do not commute. It is not difficult to verify that these matrices commute if and only if vectors and have equal components. In this case, the following theorem holds.
Theorem 1.
Let and Then,
- 1.
- for the matrix-valued ML function , the following representation is valid
- 2.
- the following Laplace transform formula holdswhere and
Proof.
We need to prove only part 2. Using the definition (32) of the ML function, we have
since matrices and commute under the conditions to and Further, using the well-known relation we obtain
completing the proof. □
2.6. Matrix-Valued Operators with Singular Symbols
In this section, we describe matrix-valued operators on the right-hand side of system (1). Let A be a closed linear operator with a domain dense in a reflexive Banach space X and a nonempty spectrum Assume that the entry of the matrix-valued operator has the symbol analytic in an open connected domain If is bounded and G contains , then one can define the operator as (see, e.g., [1,32])
where is a contour in G containing and is the resolvent operator of Representation (41) is not valid if has singularities on the spectrum
In the case that f has singular points in the spectrum of the operator A, the corresponding operator can be constructed as follows. Denote by the set of singular points of f on Let be an open set in containing In particular, if , then as well. Consider an open set Let and . Denote by the set of elements satisfying the inequalities for all with a constant not depending on k. A sequence of elements is said to converge to an element if as . It is easy to see that if and this inclusion is continuous. Denote by the inductive limit of spaces as i.e.,
meaning that with the strongest topology. For basic notions of topological vector spaces including inductive and projective limits, we refer the reader to [33]. The space is called a space of exponential vectors of type r (see, e.g., [34,35]) associated with the operator
Let where and denote by the space whose elements are locally finite sums of the elements in with the corresponding topology. Here, is the minimal distance between the point and the boundary of the domain By definition, any has a representation
where and is a finite number.
Now, we can define operators with symbols analytic in the domain Recall that may have singular points on the spectrum but G does not contain singularities of As an analytic function in has the Taylor expansion
convergent in any open disc where Therefore, the operator defined as
on elements is well defined. Indeed, we have
Finally, for an arbitrary with the representation
the operator is defined by the formula
where is defined in (42). Using estimate (43) and representation (45), it is easy to show that the operator is well defined on the space
Further, suppose that there exists a one-parameter family of bounded invertible operators such that
Example 1.
Recall that, here, the sum with respect to is finite.
The operator defined in (45) maps to itself. Namely, the mapping
is continuous. Indeed, let have a representation Then, for , we have the estimate
with some constant and The latter means that Therefore, has a representation where implying The estimate (48) also implies the continuity of the mapping in the topology of
Remark 1.
If the spectrum of the operator A is discrete, then consists of all linear combinations of eigenvectors and associated eigenvectors corresponding to eigenvalues in the disc and the space is their locally finite sum.
Finally, it follows from the construction above that a matrix-valued operator with the matrix symbol analytic in the domain is well defined on elements of the direct product space
with the corresponding direct product topology. Moreover, the mapping
is continuous.
We note that the space is relatively narrow. For example, if acting in the space then the corresponding space is the direct product of the space of functions analytic in However, the duality construction allows us to expand the introduced spaces and consider wider classes of fractional-order systems. Let denote the dual of and be the operator adjoint to A. We denote by the space of linear continuous functionals defined on with respect to weak convergence. In other words, is the projective limit of spaces , which are dual to with the coarsest topology. Continuing the example now, one can see that the corresponding space gives rise to the space of analytic functionals (Sato’s hyperfunctions; see, e.g., [36]).
For an analytic matrix symbol defined on , we define a matrix-valued operator as follows:
where is the matrix-valued operator with the symbol analytic in and is an element of the space dual to By construction, as a dual to the space of the direct product, the space represents the direct sum
with the corresponding topology. It follows from (49) that the mapping
is continuous. Indeed, assume that a sequence converges to 0 in the topology of Then, for arbitrary , we have
where due to (49). Hence, as in the topology of obtaining the continuity of mapping (51).
3. Main Results
Below, we derive representation formulas for the solutions of fractional-order systems of differential-operator equations. We demonstrate the derivation in the case of the Caputo fractional derivative. For the sake of clarity, we start with the case and then the general case. The case of the Riemann–Liouville fractional derivative can be treated similarly (see Section 4).
3.1. Fractional Multi-Order Systems of Differential-Operator Equations:
In this section, we demonstrate the formal method of obtaining the representation formula for the solution of time-fractional arbitrary multi-order systems of differential-operator equations in the particular case of two equations. Namely, consider the system
where is a given vector-valued function, and
with the initial condition
where We assume that G does not contain the roots of the equation
To find entries of the solution operator , we consider the homogeneous counterpart of system (52), writing it in the explicit form
Applying the Laplace transform and replacing A with the parameter z, we have
The solution of system (55) is
where
and is the real part of the roots of the equation This solution is uniquely defined, since, by assumption, where We have
For large enough, the inequality
is verified, and, therefore, the series in (61) is convergent. Now, for the solution of system (55), we have
Consider the expressions
and
Further, let
Since and we have if and Taking this into account, we obtain
Now, taking the inverse Laplace transform, due to formula (21), we obtain
Similarly,
and
Thus, we prove the following theorem.
Theorem 2.
Theorem 3.
Let Then, the solution operator has the matrix symbol with entries
where “*” is the convolution operation.
Proof.
The fact that obviously follows from (65). Now, we show the equality for First, we notice that implies Taking this fact into account and utilizing the semigroup property [3,10] of the fractional integration operator , we can express in the form
where I is the identity operator. Now, due to Lemma 1 with and , one has
valid for all Thus, (71) reduces to
Using the relation (72), we have
Similarly, in (67) can be written as
Finally, using Lemma 1, we obtain
In the last step, we used relation (27) with and □
Remark 2.
Theorem 3 states that the representation formula presented in Theorem 2 coincides with the representation formula obtained in [18] for the solution of fractional-order systems with a lower triangular matrix-valued operator.
3.2. Fractional Multi-Order Systems of Differential-Operator Equations:
The method demonstrated in the previous section for works, in fact, for an arbitrary number of equations. To derive the solution operator, consider the homogeneous system
with the initial condition
Here, is an arbitrary vector order. We can assume, without loss of generality, that Applying the Laplace transform and replacing A with a parameter , we obtain
where This is a system of linear algebraic equations dependent on parameters and The determinant of the matrix on the left has the structure
where and has the form
In other words, is the sum of functions of the form
where is a multi-index taking values in the subsets of the set except the function is the sum and multiplication combination of entrees of the matrix symbol Let be the real part of the largest root of the equation Then, for , system (76) has a unique solution
It follows that the solution operator has the matrix-valued symbol
The components of the solution have the structure (as an implication of the well-known Cramer’s rule)
where is the j-th component of and is the determinant of the matrix obtained by replacing the j-th column of the matrix with the vector The latter can be rewritten in the form
where are components of and functions have form (77). Let We have
where is the coefficient in the term in (77) and
Further, similar to the case we represent in the infinite functional series form
For large enough, the inequality
is valid, and, therefore, the series in (81) is convergent.
Further, it follows from (80) that
Hence, the matrix symbol of the solution operator has entries
Now, using (81), we have
Taking into account the fact that and functions can be represented in form (77), we can write the expressions as
where are the sum and product combinations of and exponents depend on the sum combinations of and their multiples. Therefore,
Further, let By construction, for all indices Then,
Hence, the solution to Cauchy problem (74), (75) has the form
where is the matrix-valued solution operator with the matrix symbol defined by (83).
Theorem 4.
Let where arbitrary numbers and . Let A be a closed operator defined on a Banach space and the set G satisfies the condition where , and
Proof.
It follows from (49) that for every fixed continuous on and infinitely differentiable on in the topology of due to the construction of the solution operator Similarly, by virtue of the continuity in of operators with symbols analytic in G (see (49)), for each fixed t, we have for each fixed The continuity of on in the variable t and its infinite differentiability on follow from the construction of the solution operator in the standard way. □
Theorem 5.
Let X be a reflexive Banach space with the conjugate A be a closed operator with a domain and be a matrix operator with the symbol continuous on G and satisfying condition where is defined in (115). Assume that and Then, for any , Cauchy problem
has a unique solution having the representation
where is the operator with the matrix symbol defined in (158).
Proof.
We note that elements and belong to the space if for each fixed This fact follows from the definition of the fractional derivative and Theorem 4.
We show that defined in (90) satisfies the following conditions:
where is the conjugate transpose of for an arbitrary element in the space Indeed, to prove this fact, let us first assume that (as an element of ) for all Then, (91) takes the form
for each fixed The operator is constructed so that which implies as well. Indeed, if is a solution to Equation (74), then it follows from representation (84) that for any fixed This implies the equality Thus, Equation (91) is valid for all .
Further, it follows from the construction of the operator that the symbol at reduces to the identity matrix. Therefore, the operator corresponding to the matrix symbol is the identity operator. Hence, Thus, equality (92) is also verified.
In the general case, for non-zero representation (90) is an implication of the fractional Duhamel principle [10,37]. □
3.3. Fractional Multi-Order Systems of Differential-Operator Equations with Triangular Matrix-Valued Operators
If the matrix symbol in system (1) is a lower or upper triangular matrix, then representation (83) is significantly simplified. See Theorem 3 in the case of a lower triangular matrix for In this section, we derive representation formulas for the solution for arbitrary For fractional systems of pseudo-differential equations with lower or upper triangular matrix symbols, the representation formulas are presented in paper [18].
Assume that is an arbitrary multi-order with components and is a lower triangular matrix symbol. Then, system (76) takes the form
The latter implies the following recurrent relations:
In order to represent the solution (95) through we introduce the following notations. Let where k and j are integers satisfying conditions and respectively. By we denote the set of subsets of such that, from , exactly l numbers except k and are removed. Then, for in (95), we have
where are the multiplication and sum combinations of functions Now, making use of formula (19) and the convolution formula for the Laplace transform, it follows from (94) and (96) that
where is the fractional integration operator (see (11)) of order “*” is the convolution operation, and ”” is the convolution product. Thus, the solution of homogeneous Cauchy problem (74), (75) has the representation
where is the solution matrix operator with the matrix symbol with entries
Similarly, if the matrix symbol is upper triangular, then the components of the solution take the form
where are operators obtained from via the product and sum combinations and is the set of subsets of the set such that exactly l () numbers except k and m are removed from In turn, the matrix symbol of the solution operator in representation formula (99) takes the form
3.4. Commensurate and Non-Commensurate Rational-Order Systems
If all components of the vector-order are equal, then the transformation of the matrix symbol to the Jordan canonical form can be effectively utilized in the derivation of representation formulas for the solution. Theorem 1 serves as an important mathematical basis for such an approach. If all components of are rational (not necessarily being equal), then this case can be reduced to the case with equal components, but at the cost of an increased number of equations (see [18]). We note that both these cases were presented in [18] for time-fractional systems of pseudo-differential equations. Below, applying the same technique presented in [18], but not providing explicit details, we generalize it for fractional-order systems of differential-operator equations, which significantly expands the scope of application.
Let be the matrix-valued operator with the matrix symbol whose Jordan normal form is
where is a transformation matrix invertible at each and are Jordan blocks corresponding to eigenvalues of the matrix
First, we derive a representation formula for the solution operator of the initial value problem for system (1) in the homogeneous case
or due to (104) equivalently
where is the transformation matrix operator with the matrix symbol
In order to solve problem (107), (108), we use the operator approach, considering the following system of ordinary fractional-order differential equations dependent on the parameter
assuming that is a vector of length Since all components of are equal, the matrix-valued operator commutes with and therefore system (109) can be expressed as
Denote Then, we have the Cauchy problem
Now, applying the Laplace transform in the vector form (12) to both sides of system (112), we obtain
where , are diagonal matrices with diagonal entries respectively. The latter implies a system of algebraic equations with parameter
Let
This matrix has the block diagonal form
with the blocks of size corresponding to the eigenvalue of multiplicity
Further, applying the inverse Laplace transform, taking into account (19) and (21), and returning to in accordance with Theorem 1, we have
where is the block diagonal matrix of the form
with blocks
for
Thus, the solution of problem (105)–(106) has the representation
where is the solution matrix operator with the matrix symbol
Now, let us consider the incommensurate case with rational components where are positive co-prime integers. Let p be the least common divisor of numbers Then, one can write as where is an integer. Therefore, the operator can be presented in the form
It follows that, for each we have
Introduce a vector function of length
where Now, system (105) can be reduced to a system of N equations with equal fractional-order derivatives on the left-hand side. The reduced system has the form
where is the matrix operator with the matrix symbol
whose diagonal block matrices are of sizes
and non-diagonal block matrices are of sizes
The initial condition for system (123) takes the form
Now, we derive a representation formula for the solution of Cauchy problem (105), (106). We notice that that the characteristic polynomial of
and the function are connected through the relationship
Let be eigenvalues of the matrix with respective multiplicities Then,
which implies
Similarly, we can write the determinant of the matrix obtained by replacing the j-th column of the matrix with the column vector in the form
where is a polynomial in the variable of order Hence, for the j-th component of the Laplace transform of the solution vector we have
Further, using the partial fraction decomposition
where do not depend on Equation (126) can be expressed as
Inverting the latter and using formula (20), we obtain
It follows that the solution operator has the matrix symbol , whose entries are
Summarizing, we obtain the following theorem on formal representations of the solutions.
4. The Riemann–Liouville Case
Similar results hold in the case that the fractional derivatives in system (1) are in the Riemann–Liouville sense. Therefore, below, we briefly formulate the corresponding assertions.
Consider the initial value problem
where and the matrix operator vector-valued elements , and are specified below. Using the same technique that was used in the case of Caputo derivatives, one can show that, in the case of Riemann–Liouville derivatives, the solution matrix operator has the symbol
The following theorems hold.
Theorem 7.
Let A be a closed operator defined on a Banach space and the set G satisfies the condition where is defined in (115), and
Theorem 8.
Let X be a reflexive Banach space with the conjugate A be a closed operator with a domain and be a matrix operator with the symbol continuous on G and satisfying condition where is defined in (115). Assume that and
Then, for any , Cauchy problem
has a unique solution having the representation
where is the operator with the matrix symbol defined in (130).
Concerning representation formulas for the solution in the case of Riemann–Liouville derivatives, their derivation is similar to the Caputo derivative case. Therefore, we demonstrate the detailed derivation of the representation formula only in the case with arbitrary multi-order and matrix symbol , providing the final result for arbitrary
4.1. The Case and
Consider the system
where is a given vector function, and
with the initial condition
where We assume that G does not contain the roots of the equation
To find entries of the solution operator , we consider the homogeneous counterpart of system (52), writing it in the explicit form
Applying the Laplace transform and replacing A with the parameter z, we have
The solution of system (55) is
where is defined in (58) and
and is the real part of the roots of the equation This solution is uniquely defined, since, by assumption, where
Introduce Obviously, and if The entries of the matrix symbol have representations
where
Theorem 9.
Theorem 10.
Let Then, the symbol of the solution operator has entries
where “*” is the convolution operation.
The proof is similar to the proof of Theorem 3.
4.2. The Case and Arbitrary
In the case of arbitrary following the same approach demonstrated in Section 3.2, one can derive the representation formula. Namely, instead of Equation (76), one has
and, therefore, instead of Equation (79), one obtains
the symbol of the solution operator. The entries of the latter are
where are the sum and product combinations of the entries of
4.3. The Case and
If the components of are equal, then, again, we can use the Jordan normal form to derive a representation formula for the solution. In this case, following the method used in Section 3.4, we consider the system of ordinary fractional-order differential equations depending on the parameter
where the symbol of the matrix operator has a representation in the Jordan block form (104). Then, for the Laplace transform of , we obtain a linear system of algebraic equations
If then the latter has a unique solution represented through the inverse matrix which has the block diagonal form
with the blocks of size corresponding to the eigenvalue of multiplicity
Now, using formula (22), one can find the inverse Laplace transform of each entry of matrices Hence, the solution matrix operator has the block matrix representation
where the block matrix operator has the matrix symbol
with blocks
for
Concluding, the solution matrix operator has the representation
where is the solution matrix operator with the matrix symbol
5. Some Applications and Examples
Example 2.
Time-fractional systems of ordinary differential equations.
Consider the following initial-value problem for a time-fractional system of ordinary differential equations
where is a (constant) matrix, and is an absolute continuous vector function. The theorems obtained above are applicable to this case with the proper interpretation.
Let be arbitrary numbers, be entries of the matrix and Suppose that Consider first the corresponding homogeneous system
Define the function
The solution to the latter has the form where is the solution matrix. The components of due to Theorem 4 have entries
where are defined similarly to in (82), replacing with In particular, if then
Additionally, if then
Example 3.
Blood alcohol level problem.
The authors of paper [38] considered the following blood alcohol problem using fractional-order derivatives in the sense of Caputo–Djrbashian:
where A represents the concentration of alcohol in the stomach and B is the concentration of alcohol in the blood, and are some real constants, which indicate transition rates. The initial conditions are given by
This problem can be presented as where and
In accordance with Theorem 2, the solution has the representation
We note that the authors of [38] found the solution in the form and (with )
which is the same as (161), (162), due to the equality
Example 4.
Fractional-order systems for a relativistically free particle.
The wave function of a relativistically free particle of mass m is described by the Klein–Gordon equation
where c is the speed of light, ℏ is Planck’s constant, and the gradient operator. Dirac’s equation for relativistically free particles, in fact, is a system of the form
where and are matrices satisfying certain conditions, and is a multi-component wave function. Using the adopted units the latter can be written in the explicit form [39]
Multiplying this by we can rewrite system (163) in the form (1)
where is the matrix-valued operator with the symbol
Replacing on the left of (164) with , we obtain a Dirac-like fractional-order system. Note that some Dirac-like systems are considered in papers [27,28,40,41].
If then all eigenvalues are of multiplicity one, and hence diagonalizable. Consequently, there exists an invertible matrix such that with Thus, in accordance with Theorem 6, the solution is represented in the form where the solution pseudo-differential operator has the matrix symbol
and components of have Fourier transforms with compact supports in
Example 5.
A commensurate system of pseudo-differential equations.
Let the matrix-valued operator be given by the matrix symbol
Consider the system with the matrix-valued operator on the right corresponding to the symbol
with as the adjoint of and the initial condition
Assume that Then, one can easily verify that the eigenvalues of are Therefore, where
Then, due to Theorem 6, the solution operator has the matrix symbol
where
Suppose that where is the Laplace operator, with the domain
Here, is the Fourier transform of It is known that the spectrum of A is the positive semi-axis, and hence we can accept . Then, the symbol simplifies to
If then has a double eigenvalue and has the Jordan form where
Assume for simplicity that Then, in accordance with Theorem 6, the solution operator has the matrix symbol
Thus, the solution has components
Example 6.
An incommensurate system of pseudo-differential equations.
Now, assume that and is as in Example 5 with Then, since and are rational numbers, we can use the technique described in Section 3.4 and reduce problem (166), (167) to a system of five equations with equal orders The reduced system has the form
with the initial condition
The components and correspond to the solution of (166), (167) with . Applying the Fourier and Laplace transforms, we can transform system (170) into the following algebraic equations:
It follows that
and
Thus, the solution of problem (166), (167) in accordance with Theorem 6 has the following components:
Note that Theorem 3 is applicable to this problem as well, resulting in the same solution.
6. Discussion
In this paper, the representation formula for the solution of the Cauchy problem for arbitrary time-fractional multi-order linear systems of differential-operator equations is obtained. Heretofore, the representation formulas were known in particular cases of commensurate multi-order and in incommensurate multi-order cases with rational components. The latter can be reduced to the former. The results obtained in this paper are new, even in the case of linear time-fractional multi-order ordinary differential equations with a constant matrix. The existence of a solution and its uniqueness is proven in some appropriate topological vector spaces. Examples illustrating the obtained results are provided.
Funding
This research received no external funding.
Data Availability Statement
No new data were created or analyzed in this study. Data sharing is not applicable to this article.
Acknowledgments
The author is grateful to the anonymous reviewers for their insightful comments, which significantly improved the content of this work. The author acknowledges support from the Ministry of Higher Education, Science and Innovation of the Republic of Uzbekistan, Grant No. F-FA-2021-424.
Conflicts of Interest
The author declares no conflicts of interest.
Abbreviations
The following abbreviation is used in this manuscript:
| ML | Mittag-Leffler |
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