1. Introduction
Consider the following non-homogeneous fractional evolution boundary value problem:
      where 
, 
, 
, 
 denotes the (time) fractional derivative in the sense of Caputo, with 
, and 
; 
, is the (space) fractional derivative, in the sense of Riemann–Liouville, with 
; and 
 denotes the length of the time interval.
Let us fix the framework: When the initial data 
 and the source terms 
 are given, the direct problem consists of looking for the unknown function 
u in an adequate functional space. On the other hand, when the initial data 
 and only the spatial part 
p are given, the inverse problem consists of looking for the unknown functions 
 via, for example, the supplementary data:
      where 
 is a given function of 
.
Notice that the fractional operator 
 is unbounded, non-self-adjoint with compact resolvent admitting a countable complete basis of eigenfunctions, in 
 [
1]. This will allow us to look for classical solutions via the biorthogonal representation with respect to 
x. Indeed, the uniform convergence of the resulting series in 
 (and of their derivatives) and the uniqueness of the corresponding limits, with respect to the norms 
 and 
, will lead to the existence of classical solutions of the direct problem. For the inverse problems, we will make use of the Schauder fixed point theorem in an adequate convex and bounded subset.
Before we present and prove our results, let us dwell on the existing literature. An analytical and numerical study of inverse problems for fractional diffusion equations has undergone intensive development over the present decade. Kirane and Malik [
2] considered at some later date a one-dimensional fractional diffusion equation with a non-local, non-self-adjoint boundary condition. They developed a solution and source function using a bi-orthogonal method and obtained the uniqueness. In addition, they have prove an existence result when both the initial and the final conditions are smooth enough. In [
3], the problem in [
2] is generalized. Furati et al. used the same bi-orthogonal spatial system to obtain a separable formal solution and source function and to show their uniqueness. They then used the asymptotic expansion of the generalized Mittag–Leffler function to achieve a result of existence under certain smoothness criteria on the initial and final conditions. Aleroev et al. [
1] consider a linear heat equation, with a non-local boundary condition, involving a fractional derivative in time. They establish a space independent source term and the distribution of temperature for a problem with integral type over determining condition. They proved the solution’s existence and uniqueness, and its continuous dependence on the data. Among other papers devoted to determining unknown source terms, we may cite [
4,
5,
6].
As was mentioned in the abstract, an incorrect use of the estimates in the generalized Mittag–Leffler functions is commonly performed in the literature on this topic. This leads to false proofs of the Fourier series’ convergence to recover the equation satisfied by the solution, the initial data or the boundary conditions. Remark 1 explains this fairly widespread mistake. In the present work, the correct framework to recover the decay of fractional Fourier coefficients is established; this allows one to correctly recover the initial data, the boundary conditions and the partial differential equation satisfied within the space-time domain.
The manuscript is organized as follows: In 
Section 2, fundamental concepts of fractional calculus are recalled. In 
Section 3, we obtain results for the direct problem using Fourier’s method; we determine the existence, uniqueness and continuous dependence on the data. In 
Section 4, the inverse problem associated with the direct problem is considered, and we show the results of the existence, uniqueness and continuous dependence of the solution on the data.
  3. Direct Problem
In this section, we will study the forward problem:
      where 
p, 
f and 
 are given functions such that 
 and 
.
We are interested in classical solutions to Problem (10), that is, solutions  which are continuous on  and satisfy  and , for any .
Example 1. Consider the case  and , with  and . We fix the initial condition , the spatial and temporal source terms  and  for any  and  as the following:The exact solution is then , since it is known that  Since the problem (10) is linear, we can split its solution as follows:
      where 
 is the solution of the homogeneous problem:
      and 
 is the solution of the problem:
For every direction 
, 
, the spectral problem associated with Problem (12) is:
The eigenfunctions of (14) are given by [
9]:
      where 
 are the associated eigenvalues. Notice that these eigenvalues form a countable set that is denoted by 
. Moreover, they satisfy the following:
- (P1)
- There are only finitely many real eigenvalues and the rest appears as complex conjugate pairs; 
- (P2)
-  as ; 
- (P3)
-  for n sufficiently large and  as . 
Now, consider a real number 
 such that:
      and this is possible since 
 and consequently the interval 
 is not empty. Therefore, the property (P3) implies that
      
Since 
, then applying Theorem 1, we obtain the estimate:
Remark 1. In the published papers on this topic, the mistake commonly made is due to a misapplication of Theorem 1. Indeed, the following estimatecannot hold true for all the eigenvalues , , since . Consequently, there is no real number  such thatTherefore, the conditions for applying Theorem 1 are not satisfied to obtain (18).  Based on [
11], for every 
, the family 
 is a basis of 
, which is not orthogonal, because the operator 
 is not self-adjoint. Consequently, for each 
, we introduce the family:
      corresponding to the eigenfunctions of the adjoint operator of 
, with respect to the inner product in 
: 
      where 
 denotes the conjugate of the complex number 
. In the sequel, the inner products in 
 and 
 will be simply denoted by 
 and 
, respectively.
Notice that the adjoint operator of 
 is the right-sided Riemann–Liouville fractional derivative of order 
 defined by:
	  Moreover, the family 
 is biorthogonal to 
 in 
 and satisfies
      
	  On the other hand, for any integers 
, the resulting problem in the variable 
t is:
      whose solution is given by:
      where:
      since 
 The solution of Problem (12) is then formally given by:
In the same way, we can look for the classical solution of the problem (13) as:
      where the coefficients 
 are to be found. To this end, if 
, then:
      with
      
Substituting the solution 
w given by (25) in Equation (13), we find formally:
Therefore, for each 
, the coefficient 
 satisfies the equation:
Equation (28) is supplemented with the initial condition:
Following [
12], the solution of (28) is:
Therefore, the solution of problem (13) is written as:
In what follows, c is a constant that might change from line to line.
Theorem 2. Let ,  and  such that ,  and . Then, there exists a unique classical solution of Problem (10).
 Proof.  Existence of a solution:
To lighten the proof without loss of generality, we present the case 
 and explain below the general case 
. In this situation, we consider the problem:
        
        with 
 and 
. We need to prove the convergence of series (24), (31) and the series associated with their fractional derivatives in space and time. We set 
. Then:
        
        where
        
Then, there is a constant 
 such that, for every 
, 
 and 
n are sufficiently large such that:
        
The series of general terms  is convergent since . Using the M-test of Weierstrass, the series (24) is normally convergent on . Consequently, the function  defined by (24) is continuous on . The same idea can be used for the series (31) by setting . Hence, the functions v and w verify the initial and the boundary conditions of (12) and (13), respectively.
Finally, to prove the convergence of the series associated to the fractional derivatives of 
v and 
w, it suffices to prove the convergence of series associated with: 
, 
, 
 and 
. To this end, let
        
        and
        
        so 
 and 
From above, for any 
, 
 and 
, one has:
        
        and
        
Therefore, the series  and  converges normally on , for every .
Applying the same ideas, we obtain the normal convergence of the series  and  on , for every . Whence, we obtain the desired convergence on the whole set  by Lemma 1, which achieves the claim.
- –
- Uniqueness of the solution: 
Let 
 be two classical solutions of Problem (10) and set 
. Then, 
 satisfies the following problem:
        
		Proceeding as above with 
 we obtain that 
, for every 
, which implies that 
.    □
 Remark 2. The generalization of the previous proof to the case  proceeds as follows: We set . Then,Direct computations give:  Theorem 3. Under the same conditions as in Theorem 2, the solution of the direct problem (10) depends continuously on the given data.
 Proof.  The arguments developed in Remark 2 allow, without loss of generality, to restrict ourselves to the case .
Let 
u and 
 be the solutions to the direct problem, corresponding to the data 
 and 
, respectively. Using (11), we find
        
        where 
 and 
 correspond to the data 
 and 
, respectively. The same arguments as applied to (24) before lead to
        
        where 
c is a positive constant. On the other hand, a direct computation gives
        
		It holds that
        
		Therefore, there is a constant 
 such that
        
        which achieves the proof.    □
   4. The Inverse Problem
Let us consider the problem:
      where the functions 
p, 
 and 
 are given, and the functions 
u and 
f are unknown.
Example 2. As above, consider the case  and , with  and . We fix the initial condition , the spatial source term  for any  and the “mean value” ,  of the solution  on Ω:The unknown temporal source term is given by  and the exact solution .  To solve Problem (35), we start by expanding 
 and 
, using systems (15) and obtain:
      with
      
      and
      
	  By substitution in (35), we formally obtain:
	  It follows that
      
      with the initial condition 
 and 
 is defined by (23). Using (36) and (6) we obtain:
Using (41), we formally find:
According to [
12], the solution of (41) is given by:
Replacing 
 given by (44) in (43), we then find the integral equation satisfied by the unknown function 
:
      where
      
      and
      
Theorem 4. Let
-  such that  and . 
- Let  such that . 
-  such that  and . 
Then, there exists at least one solution to Problem (35).
 Before proving Theorem 4, we introduce the functional framework for the fixed point integral Equation (45). First, applying the same arguments as before, we can show that the functions  and  defined by (48) and (47) are -differentiable on . Moreover, the condition  implies that the real number .
At this stage, we will establish the existence of at least a solution to the inverse problem (35) and that this solution depends continuously on the data. First of all, we will use the Schauder fixed point theorem in Banach spaces with the Arzela–Ascoli compactness result. To this end, we start by defining the following operator: 
	  To prove that the operator 
B admits a fixed point, start by showing that 
B maps a certain closed convex set into itself, in the space 
 equipped with the Bielecki norm. For every 
, we introduce the Bielecki norm:
	  The space 
 is a Banach space, and the two norms 
 and 
 are equivalent.
Lemma 2. Under the above notations, there exists a positive constant  such that for any , there is a radius  such that the closed convex ballis stable by the operator B; that is, .  Proof.  For any 
, 
 and 
, we have:
        
At this stage, recall that for any 
, the function 
 is integrable on 
. Moreover, it holds that 
; consequently:
        
That is, there are two real constants 
 and 
 satisfying 
 and 
 such that:
        
Whence, for any , there exists  such that the closed ball K of radius R in  is stable by the operator B; this achieves the proof.    □
 Remark 3. Using the Bielecki norm allows one to have no constraint on the maximum value that T can take. On the other hand, if we use the classical infinite norm, then T must be less than a finite quantity depending on the data of the problem.
 Lemma 3. The family  is equicontinuous, that is:  Proof.  It suffices to prove that the family 
 is equicontinuous, where
        
We introduce the functions 
 and 
, which are clearly integrable on 
. Let 
t and 
 in 
. We can assume, without loss of generality, that 
.
        
First, for every 
, we have
        
Using the fact that the map 
 is in 
 and applying the dominated convergence theorem of Lebesgue, we deduce that
        
Fixing now an 
 and 
, it follows that
        
On the other hand, using the fact that the map 
 is in 
 and applying the dominated convergence theorem of Lebesgue, we deduce that
        
		That is:
        
Let us point out that radii 
 and 
 depend only on 
t and 
, but are independent of 
f. Whence, for any 
 and 
, there exists 
 such that
        
        which achieves the proof.    □
 By Arzela–Ascoli theorem, 
 is relatively compact. Now, we are able to use the Schauder fixed-point theorem [
13].
Theorem 5 (Schauder fixed-point theorem). Let  be a Banach space, and let  be convex and closed. Let  be a continuous operator such that  is relatively compact. Then,  has a fixed point in K.
 Proof of Theorem 4. 
We know from Lemmas 2 and 3 that B is a continuous operator and  is relatively compact, with K convex and closed. By Theorem 5, the operator B admits a fixed point in K, so the integral Equation (45) has a solution in .
Once the existence of the source term f is established, the existence of u follows in a similar way with the arguments developed above for the direct problem.    □
 Theorem 6. Under the conditions of Theorem 4, every solution of the inverse problem (35) depends continuously on the given data φ, p and ψ.
 Proof.  Let 
, 
 be two solution sets of the inverse problem, corresponding to the data 
, 
, respectively. Using (45), we have:
        
        and
        
        where 
 correspond to the data 
, 
, respectively.
Remark first that 
, 
a and 
 depend continuously on 
p and 
. Indeed, for the function 
, using (39) and (48), we have the estimate:
        
For the real constant 
a, using (46) and (39), we have the estimate:
        
For the function 
, using (47) and (23), we have the estimate:
        
Let 
 and 
 be such that
        
Now,
        
        and consequently,
        
        where 
 is a positive constant such that 
. Similarly, we obtain:
        
		It follows that
        
        where 
 is a positive constant such that 
. Finally, we obtain:
        
        where 
 is a positive constant such that 
 and
        
		Similarly, we obtain:
        
		Then,
        
		Therefore, we obtain the estimate:
        
		Combining the last estimate and (55), we deduce the estimate on the source term:
        
        where 
 is a positive constant depending on 
a, 
, 
T, 
, 
 and 
.
Since 
 there is 
 such that
        
        holds true. Whence, there is a positive constant 
, independent of 
f and 
 such that
        
		That is, the solution 
f depends continuously on the data.
The continuity of the part u of the solution follows with classical arguments for linear problems with the norm: .    □