Abstract
In this paper, we merge two theories: that of pulse processes on weighted digraphs and that of evolution algebras. We enrich both of them. In fact, we obtain new results in the theory of pulse processes thanks to the new algebraic tool that we introduce in its framework, also extending the theory of evolution algebras, as well as its applications.
1. Introduction
A complex system can be understood as a system determined by many components which may interact with each other (see [1] for a deeper discussion about the term). Such systems are usually described by a weighted digraph (that is, a network) where the nodes represent the components of the system, and the arcs their interactions. The study of complex networks is a modern, active, and interdisciplinary area of research addressed to the empirical study of complex systems, such as computer networks, technological networks, brain networks, and social networks.
To understand a complex network, a mathematical framework is needed in order to determine the properties of the underlying weighted digraph, for instance, to make predictions on the evolution of the system.
A pulse process is a structural model to analyze a complex network. Its mathematical foundation is established in [2] (see also [3]) and is summarized in [4,5]. Such a process is a simple dynamic model to study the propagation of changes, through the vertices of a weighted digraph, after introducing an “initial pulse” in the system at a particular vertex. It is based on a spectral analysis of the corresponding weighted digraph to face large scale decision making problems.
Pulse processes have been applied to topics, such as food production, energy, air pollution, transportation systems, coastal resources, health care delivery, manpower, water policy, inland waterway traffic, ecosystems, and the analysis of historical events, to make decisions (see for instance [2,6,7,8,9,10,11,12,13,14,15,16,17]). Particularly, the pulse process analysis has been used in many reports of the National Science Foundation, especially in those of the study entitled “Evaluation Measures to Conserve Energy” achieved by the Rand Corporation (see National Science Foundation (NSF) reports R-756-NSF, R-926-NSF, R-927/1-NSF, R-927/2-NSF, and R-1578-NSF referenced in [3,7,18,19,20]). In the last report [20], pulse processes were used in the context of energy demand, air pollution, and related environmental problems in order to analyze the transportation system of a hypothetical metropolitan area similar to San Diego, California. As it is stated in R-756-NSF, the result of using graph theory to model such problems, “while it does not necessarily provide a complete solution to the problem, it often brings a better understanding of what the possible solutions are or an insight into the qualitative interrelationships that underlie the problem, or an identification of significant or vulnerable points of attack”.
Evolution algebras are non-associative algebras with a dynamic nature. They were introduced in 2008 by J. P. Tian [21] for the study of Non-Mendelian Genetics. As it is shown in this pioneering monograph, they have strong connections with group theory, Markov processes, theory of knots, adynamic systems and graph theory. Because of this, a vast literature around them has grown since 2008, with direct applications in Biology, Physics and Mathematics itself (see for instance [22,23,24,25,26,27] and references therein).
In Section 2 of this paper, we summarize the mathematical substrate of the pulse processes analysis and, similarly, in Section 3, we briefly review the notion of evolution algebra with emphasis in the associated weighted digraph relative to a natural basis.
In Section 4, we merge the theory of evolution algebras with the theory of pulse processes, enlightening an original way to introduce algebraic techniques into the study of pulse processes that simultaneously enriches the theory of evolution algebras. We illustrate this approach with new results that help to understand in a deeper way many aspects of the aforementioned NSF’s reports.
In Section 5, we explore the role of the ideals of the evolution algebra associated to a pulse process. We apply this to get a better knowledge of what, in report [20], are called “interesting strong connected components” by showing, in algebraic terms, that the behavior of such components is not always the same. More precisely, we describe when the stability of one or more of these components determines the stability of the given pulse process (see Examples 8,10,11). To do this, we apply some results such as Theorem 9, Theorem 11 and Corollary 5. Moreover, we use these results in Section 6 to describe what we name the “reduction process”. This is a method to obtain, from a given pulse process, another very simplified one, called the reduced process, which is such that its stability (in pulse and/or value) is equivalent to that of the original pulse process. With the examples quoted above, we also show in an explicit way how the reduction process simplifies and enriches the analysis achieved in [20].
2. Pulse Processes on Weighted Digraphs: A Brief Review
In this section, we review the main results about the stability of the pulse processes, following [2,4,5].
Let D be a weighted digraph with vertices . We suppose that each vertex attains a value at each discrete time Then, the successive value is determined from the last time period t according to the following model:
where
- is the value of vertex at time t,
- is the value of the external pulse introduced at vertex at time (therefore, the possibility of externally influencing the variables of the system at each time is considered in this model),
- is the weight of the arc (that is the value which measures the strength of the effect that vertex has over ), and
- is the pulse at vertex at time t, defined by:
Hence, the value of vertex at time is obtained by the value that had at the last time period, the external pulse introduced in at time , and the weighted pulse that the vertices , adjacent to , transmit to vertex from t to .
Consequently, the pulse process on a weighted digraph with vertices is defined by Equation (1), along with an initial vector of values
and the vector providing the value of the external pulse introduced at each vertex at each time period, denoted by
Finally, the vector , defined by Equation (2), is called the pulse vector and shows the evolution of the system.
It is clear that Equation (1) describes a discrete-time system with parameters , which can be rewritten as:
The weights of the weighted digraph associated to the pulse process have a specific interpretation. In fact, means that an increase of k units in vertex at any time t leads to an increase of units in vertex at time (or a decrease, whenever the value is negative).
Definition 1.
A pulse process with vertices is called an autonomous pulse process when
Therefore, these are pulse processes with no external pulses introduced in the system (that is at any vertex) for An autonomous pulse process for which
for some is called a simple pulse process starting at vertex
Example 1.
Consider the following weighted digraph Figure 1.
Figure 1.
Signed digraph.
(here, the values of the weights are , and because of this it is said that it is signed digraph). The simple pulse process starting at is described by the following values and pulses:
If , then
If , then the value of the vertex decreases in one unit, while increases one unit and does not change. Therefore, with a pulse value
If then, because
with pulse value etc.
In this paper, we will consider only autonomous pulse processes. From the above definition, we obtain that an autonomous pulse process with vertices is given by
or, equivalently, by the weighted digraph D with vertices and weights , along with the initial pulse vector In this case, the adjacency matrix of the graph D is given by
and in [2], Theorem 3, it was established the following fact, easy to check.
Theorem 1.
In an autonomous pulse process on a weighted digraph with adjacency matrix the pulse vector is given by
Example 2.
Therefore, for we have
For we obtain:
For ,
Similarly, and etc.
The main qualitative property studied on a complex system is the stability. Within the framework of the pulse processes associated to a weighted digraph, two notions of stability are considered in [2]. These are the following:
Definition 2.
Let D be a weighted digraph. We say that a vertex of D is pulse stable under a pulse process if the sequence
is bounded. Similarly, is value stable under a pulse process if the sequence
is bounded. (Pulse and/or value) unstable processes are those that are not stable. A weighted digraph D is pulse (resp. value) stable under the pulse process if each vertex of D is pulse (resp. value) stable.
Let D be a weighted digraph. Under any pulse process, the value stability at a vertex of D implies the pulse stability at . This is due to the fact that,
for The next result (see [2], Theorem 4) provides a sufficient condition for pulse and value instability.
Theorem 2.
Let D be a weighted digraph, with adjacency matrix A. If D has an eigenvalue λ with , then D is pulse unstable under some simple pulse process.
The next result is nothing but [2], Theorem 5, and describes the pulse stability.
Theorem 3.
Let D be a weighted digraph, with adjacency matrix A. Then, the following assertions are equivalent:
- (i)
- D is pulse stable under all autonomous pulse processes.
- (ii)
- D is pulse stable under all simple pulse processes.
- (iii)
- If λ is an eigenvalue of A then , and if the algebraic multiplicity of λ differs from its geometric multiplicity then
The next result (see [2], Theorem 6) characterizes the value stability.
Theorem 4.
Let D be a weighted digraph, with adjacency matrix A. Then, the following assertions are equivalent:
- (i)
- D is value stable under all autonomous pulse processes.
- (ii)
- D is value stable under all simple pulse processes.
- (iii)
- D is pulse stable under all simple pulse processes and is not an eigenvalue of
3. Evolution Algebras and Weighted Digraphs: A Brief Review
An algebra is a vector space A over a field provided with a bilinear map called the product of A, given by , for . An algebra is said to be associative if for every , and commutative if for every . Through this paper, all the algebras that we consider are finite-dimensional.
Definition 3
([21]). A finite-dimensionalevolution algebrais an algebra A over (= or ) provided with anatural basis. This is a basis such that if , with This is nothing but a basis B such that the multiplication table of A relative to B is diagonal. If such a table is
then, the coefficients determine a matrix , named the structure matrix of A relative to B, that encodes the product of A as well as the dynamic nature of More precisely, this matrix is obtained by writing the coefficients of in columns as follows:
It is easy to check that if and then, where
The dynamic nature of is described by theevolution operatorof associated to B, which is defined as the unique linear operator such that It is easy to check that where Therefore, fixed the natural basis we have that is the linear operator determined by the structure matrix
Evolution algebras are non-associative algebras (in fact, it is easy to see that they are not even power-associative), and they are commutative. On the other hand, except in very special cases, they do not have a unit as we show next.
Definition 4.
An evolution algebra A with a natural basis is said to be a non-zero trivial evolution algebra if there exist constants such that for every
The evolution algebras that have a unit were characterized in [28] as follows.
Theorem 5.
The only evolution algebras that have a unit are the trivial finite-dimensional evolution algebras.
In [29], the following notion of spectrum of an element in a non-necessarily associative algebra was introduced, and therefore many results of the spectral theory of Banach algebras were extended to the non-associative framework.
Definition 5.
The multiplicative spectrum (or m-spectrum) of an element a in a complex algebra A with a unit e is defined as the set:
An element is said to be m-invertible if the left () and right () multiplication operators by the element b are bijective. If A does not have a unit then where denotes the unitization of Similarly, if A is real then , where denotes the complexification of
Recall that, as usual, and Moreover, if A is a real algebra without a unit, then for every see [29] for details.
On the other hand, as proved in [29], Proposition 2.5, if is a non-associative Banach algebra then is a set of complex numbers such that for every In fact, the m-spectrum extends the classical notion of spectrum of an element in an associative algebra to the non-associative framework by keeping a good number of its essential properties.
As proved in [29], Proposition 2.2, for an arbitrary complex algebra A and , we have that, if A has not a unit then
whereas if A has a unit then
where, for a linear operator , the set denotes the spectrum of T in the associative algebra of all linear operators on A. This is,
Next, we show the behavior of the m-spectrum of surjective homomorphisms.
Recall that an homomorphism between two arbitrary algebras A and is a linear map such that for every Surjective homomorphism are named epimorphisms, while the bijective ones are named isomorphisms.
Theorem 6.
Let A and be algebras and an homomorphism.
(i) If θ is an isomorphism then for every
(ii) If θ is an epimorphism then for every .
Proof.
It is not restrictive to assume that A and are complex algebras. In fact, if A and are real algebras, and if is replaced by where then we obtain an isomorphism that extends . Since in the real case, by definition, and for every we have that, to prove the theorem, we can replace by .
(i) Suppose that is an isomorphism. Let For simplicity, suppose that A is commutative. Then, from Equations (8) and (9), we obtain that if A does not have a unit, whereas if A has a unit. Let and denote the pointwise spectrum and the surjective spectrum of respectively. That is,
Since , we have that, for every ,
Moreover, if and only if for every as is an isomorphism. Thus and consequently, for
Hence, regardless of whether A has a unit or not, we obtain as desired.
If A is not commutative, then the same reasoning with the operator shows that and the result follows from Equations (8) and (9), as
if A does not have a unit. Similarly, if A has a unit, then
(ii) Since is an ideal of from Lemma 19 in [30], we have that
and it follows from Equation (10) that for every □
The spectrum of an element a in an evolution algebra A with a natural basis was determined in [28]. From Proposition 5.1,5.3 in [28], we obtain the following description of the spectrum of an element in an evolution algebra.
Theorem 7.
Let A be an evolution algebra over or with a natural basis and structure matrix Let Then, is such that if and only if is an eigenvalue of the following matrix
If A is a non-zero trivial evolution algebra, then and from the above result we obtain that, if , then
Similarly, if A is not a non-zero trivial evolution algebra (that is, is not diagonal with non-zero entries), then , for every . Indeed, since in this case A does not have a unit as shown in Theorem 5, it follows that is not invertible in as the unit of cannot belong to A. Thus, if A does not have a unit (which means that A is not a non-zero trivial evolution algebra) then is given by the eigenvalues of the product matrix (12) joint with zero.
4. Evolution Algebras and Pulse Process
Every couple , where A is an evolution algebra and is a natural basis of A, uniquely determines a weighted graph with set of vertices B and adjacency matrix (we consider the transposition of the structure matrix of A since, in graph theory, it is usual to determine the i-th row of the adjacency matrix by the weight of the arcs with origin in the vertex ). Consequently, and conversely, every weighted graph G with set of vertices B and adjacency matrix uniquely determines an evolution algebra A provided with a natural basis B in which structure matrix is (thus, we have that the associated graph to is ).
From now on, if A is an evolution algebra and B is a natural basis of A then, we will denote the graph associated to A relative to B by .
Example 3.
Consider the following weighted digraph Figure 2 taken from R-1578-NSF [20].
Figure 2.
Weighted digraph with vertices . Captured from [20], p. 40. Copyright permission from The Rand Corporation.
The associated evolution algebra A has a natural basis and structure matrix
Note that is the adjacency matrix of the given graph.
From Theorem 7 we obtain the following result.
Corollary 1.
Let A be an evolution algebra, a natural basis, and . Let be the weighted digraph associated to A relative to B. Let be the adjacency matrix of and its spectrum.
- (i)
- If A is a non trivial evolution algebra, then .
- (ii)
- If is a trivial evolution algebra, then .
The above result and the fact that the evolution operator of A relative to B is the multiplication operator by the element motivate the following definition.
Definition 6.
If A is an evolution algebra and a natural basis then, we define theevolution elementof A relative to B as
Next, we translate the theory of pulse processes on weighted digraphs to the framework of evolution algebras.
Definition 7.
Let A be an evolution algebra and a natural basis. We say that A is pulse (resp. value) stable relative to under all autonomous pulse processes, if the associated weighted digraph is pulse (resp. value) stable.
Consequently, a graph G is pulse and/or value stable if, and only if, its associated evolution algebra is pulse and/or value stable.
If A is not pulse (resp. value) stable relative to a natural basis B, then we say that A is unstable relative to B.
From Theorem 3, Theorem 4 and Corollary 1, we obtain the following result, where denotes the closed unit disk and the open unit disk.
Theorem 8.
Let A be an evolution algebra with a natural basis and let be the corresponding evolution element. Then, the following assertions are equivalent:
- (i)
- A is pulse stable relative to under all autonomous pulse processes, if and only if and it satisfies that, if is an eigenvalue in which algebraic and geometric multiplicities do not coincide, then .
- (ii)
- A is value stable relative to under all autonomous pulse processes, if and only if A is pulse stable relative to B, under all autonomous pulse processes, and
Moreover, the pulse and/or value stability of A under all autonomous pulse processes is equivalent to that of simple pulse processes.
From the above result, we have that the value stability ofArelative toBis equivalent to the fact that and the property that if is an eigenvalue in which algebraic and geometric multiplicities do not coincide, then .
Corollary 2.
Let A be an evolution algebra with a natural basis, and let be the corresponding evolution element. If , then A is pulse and value stable relative to B, under all autonomous pulse processes.
Example 4.
Let A be an evolution algebra with a natural basis relative to which the associated graph is
Then, A is pulse and value stable. This is due to the fact that .
Corollary 3.
Let A be an evolution algebra with a natural basis, and let be its evolution element. If then, A is pulse unstable under some simple pulse process and, consequently, value unstable.
5. Pulse Processes, Evolution Algebras, Cycles, And Ideals
The ideals, and mainly the basic ideals of evolution algebras associated to a pulse process, play a main role in determining the pulse and/or value stability of the given pulse process, as we show next. In R-1578-NSF (see [20]), the behavior of the so-called “interesting strong connected components” was checked as a “logical” preliminary test. However, the fact of making clear to what extent the behavior of such components determines the stability of the whole pulse process was omitted. By means of the notion of basic ideal we will clarify the role of these “interesting strong connected components”, showing that such components often determine the stability of the whole pulse process, and giving the reasons for this.
Recall that a subspace M of a commutative algebra A is said to be an ideal if (which means that is an algebra with the canonical product for ). An ideal M of an evolution algebra A is a subalgebra. Nevertheless, an ideal M is not necessarily an evolution subalgebra. In other words, not every ideal of an evolution algebra has a natural basis.
Example 5.
Let A be the evolution algebra determined by the natural basis where and (and for )Then, it is easy to check that the ideal M generated by and given by
is an ideal that does not have a natural basis. In fact, it does not exist linearly independent and such that because if and for then it follows that
Thus, if and only if and If , then with (as ), so that and hence and are proportional (and, therefore, linearly dependent). A similar situation is obtained if This proves that M does not have a natural basis.
This motivates the following definition:
Definition 8.
Let A be an evolution algebra. An evolution ideal of A is an ideal M having a natural basis (this is an ideal M that, regarded as an algebra, is an evolution algebra).
If A is an evolution algebra and M is an ideal, then is an evolution algebra. In fact, if it turns out that , with , if However the set does not need to be linearly independent, as the next example shows. This means that contains a natural basis of but this set needs to be linearly independent to become a natural basis of .
Example 6.
Let A be the evolution algebra from Example 5, and the natural basis provided there. If M is the ideal defined in (13), then we have that so they are proportional and therefore a natural basis of is given, for instance, by
An outstanding type of ideals of an evolution algebra are the following ones.
Definition 9.
Let A be an evolution algebra. We say that M is a basic ideal of A if M is an evolution ideal having a natural basis such that for some natural basis of In this case, more explictly, we also say that M is a basic ideal relative to the natural basis
Not every evolution ideal of an evolution algebra is a basic ideal.
Example 7.
Let A be an evolution algebra and a natural basis such that and Then, is an evolution ideal such that any of its natural basis is contained in (or can be extended to) a natural basis of A; see [22], Example 2.11, for details.
An interesting property of the basic ideals is the following one.
Proposition 1.
Let A be an evolution algebra and M a basic ideal of If is a natural basis of A such that M is a basic ideal of A relative to B, then the set
is a natural basis of
Proof.
If then the result is obvious. Otherwise, by reordering B if needed, it is not restrictive to assume that is a natural basis of with and Note that the set is a natural basis of if, and only if, it is linearly independent (as it generates and if ). To prove that is linearly independent, let be such that Since , we obtain that
Therefore, there exists such that This means that
hence, as B is a basis of This shows that the set
is linearly independent; hence, is a natural basis of as desired. □
Corollary 4.
Let A be an evolution algebra and a natural basis. Let M be a basic ideal relative to B and
If is pulse and/or value unstable relative to then A is pulse and/or value unstable relative to
Proof.
From the previous proposition, is a natural basis of . Let be the canonical projection. Note that is an epimorphism so that, by Theorem 6,
Taking into account that the canonical projection transforms the evolution element of A relative to B (that is into the evolution element of relative to , the proof is concluded from Theorem 8. □
Note that the graph (that is the graph associated to relative to the natural basis ) is the graph that we obtain from by deleting all the nodes such that (that is ), as well as the arcs ending in these nodes.
Theorem 9.
Let A be an evolution algebra and a natural basis of A. Let M be a proper basic ideal of A with a natural basis such that . Let be the quotient algebra and let and be the evolution elements associated to and respectively.
- (i)
- If or intersect then A is not pulse and value stable relative to
- (ii)
- If and then A is pulse and value stable relative to
Proof.
It is not restrictive to assume that where by reordering B if needed. Consequently, by Proposition 1 we have that
Moreover, if and are, respectively, the structure matrices of A relative to of M relative to and of relative to , then we have
for a certain matrix Therefore, from [31], Section 3, the eigenvalues of and determine those of , and it follows from Corollary 1 that
and the result is obtained from Corollaries 2 and 3. □
Note that an application of Theorem 8, whenever or meets the boundary of , connects with the well known Carlson Problem [32].
In the next example, we apply the above theorem to a pulse process considered in R-1578-NSF, providing a new approach for the analysis achieved there.
Example 8.
In the report R-1578-NSF [20], the pulse process for the 10% bus case is given by the following weighted digraph (see Figure 3 below).
Figure 3.
Weighted digraph for the 10% Bus Case. Captured from [20], p. 40. Copyright permission from The Rand Corporation.
The associated evolution algebra A has a natural basis
(where passenger miles, fuel economy, population size, cost of the bus system, prize of the ticket, emissions, accidents, average delay, fuel consumption).
The associated structure matrix (whose columns are the coefficients of respectively) is given by
Note that is a basic ideal of The structure matrix of M relative to the natural basis is given by
whereas the structure matrix of relative to is
Since and , the pulse and value stability of A relative to and hence the pulse process described by Figure 3, follows from Theorem 9.
There are some types of basic ideals M, of an evolucion algebra A, with the property that the study of the pulse and/or value stability of A can be reduced to the corresponding study in the quotient algebra as we show next.
Recall that the annihilator of an algebra A is the ideal defined as
If A is an evolution algebra, then the annihilator of A can be obtained from each natural basis of A, as it is shown in the following proposition ([22], Proposition 2.18).
Proposition 2.
Let A be an evolution algebra and a natural basis. Then
Consequently, the annihilator of an evolution algebra is a basic ideal (with respect to any natural basis of A). The following result shows that this basis ideal is very helpful for determining the stability of
Theorem 10.
Let A be an evolution algebra with non-zero annihilator, , and let be a natural basis of A. Then, is a basic ideal of A, and
is a natural basis of Moreover,
Therefore, A is pulse and/or value stable relative to B if and only if is pulse and/or value stable, respectively, relative to
Proof.
As said before, from Proposition 2.18 in [22], we obtain (18) and, consequently, by Proposition 1, we have that (19) is a natural basis of To prove (20), it is not restrictive to assume that A is a complex algebra. Let . From Theorem 6 we obtain that On the other hand, if is such that , then is not bijective and, since we have that is not injective. Thus, there exists such that Moreover because, in this case, , and hence , so that It follows that with non-zero, so that as desired. This proves (20). The rest is clear, from Theorem 8. □
Note that the annihilator of the algebra does not need to be zero, as we show next.
Example 9.
In Example 8 we have that so that the pulse and/or value stability of is equivalent to that of relative to the natural basis given by
Since we conclude that the annihilator of the quotient algebra is not zero.
Recall that a source vertex of a graph is a node with positive outdegree but zero indegree. This means that the vertex has edges leading from, but not leading to, the node. Conversely, a sink vertex is a node with positive indegree but zero outdegree, which means that it has edges leading to, but not from, the node. An isolated node is a vertex with zero indegree and zero outdegree (that means that no edge starts or ends in this vertex). According to this, if is a natural basis of an evolution algebra A, then we split B as follows:
where is the set of elements in B that are isolated vertices of the associated graph Similarly, (resp. ) is the set of elements in B that aresink(resp. source) vertices of and is the set of standard elements in which are those nodes in having both positive outdegree and positive indegree.
Looking at the structure matrix we have that if and only if both the th row and the th column of are zero, respectively. Similarly, (resp. ) if and only if the th column (resp. arrow) is zero while the th row (resp. column) is non-zero. Finally, if and only if both the th row and the th column of are non-zero.
Note that according to (18) we have Therefore,
Consequently, the structure matrix is nothing but the matrix obtained by removing from the rows and the columns corresponding to the elements in . Moreover, is the graph obtained by removing from its sinks and the arcs leading to them.
Theorem 11.
Let A be an evolution algebra and a natural basis. Let Then, is a basic ideal of A with natural basis
Moreover, A is pulse and/or value stable relative to B if and only if is pulse and/or value stable relative to In fact, if and denote the respective evolution elements (of A relative to B and of relative to ), then
Proof.
The fact that is a basic ideal of A is obvious, as B is a natural basis of A and Suppose that and which is not restrictive, by reordering B if needed (note that such a reordering of the elements of B defines an isomorphism on A and that isomorphisms preserve the spectrum of each element, as shown in Theorem 6). Then and If is the structure matrix of A relative to and is the structure matrix of relative to , then we have that
for a certain matrix Since is given by the non-zero eigenvalues of and is given by the non-zero eigenvalues of (see Corollary 1), the result follows from Theorem 8. □
Definition 10.
If A is an evolution algebra and if is a natural basis, then we define thereduced idealof A relative to B as the basic ideal
By combining Theorem 10 and Theorem 11, we obtain the following result.
Corollary 5.
Let A be an evolution algebra and a natural basis. Let Then, is an evolution algebra and
is a natural basis of Moreover, A is pulse and/or value stable if and only if is pulse and/or value stable. In fact, if is the evolution element of A relative to and if is the evolution element of relative to then
6. The Reduction Process
Let A be an evolution algebra and a natural basis. We define the first spectral reduction of as the couple where is the reduced ideal of A relative to and is the natural basis of given by
If some element in is not standard (that is, it is either an isolated, a sink or a source vertex) then, we repeat the process and define the second spectral reduction of as the first spectral reduction of We reiterate the process until we get a reduced natural basis consisting only of standard elements. Then, we say that this couple is the spectral reduction of and we denote it by . Note that, from Corollary 5, the study of the pulse and/or value stability of A relative to B is equivalent to the study of the stability of relative to .
Example 10.
Consider the evolution algebra A with a natural basis B given in Example 8. Then, we have
Therefore, and
Consequently, the first spectral reduction of is the evolution algebra with natural basis
and structure matrix
Note that is an isolated element of and that the other elements in are standard. Thus, the spectral reduction of is given by the reduced ideal of Hence, is the evolution algebra with natural basis
and structure matrix
It follows that the pulse and/or value stability of A relative to of B is nothing but the pulse and/or value stability of relative to of This means that the pulse stability of this system lies on the values of the variables: cost of the bus system, average delay and fuel consumption (marked in bold in (15)).
We point out that, concerning the pulse and/or value stability of the given system, the role of the remaining variables is the same if we replace the non-zero value of their weights for another non-zero value (therefore, it does not matter even if we change the sign of some of these values). In [20], the weighted digraph of Figure 2 is said to be an “interesting strong component” of the one in Figure 3. Note that the associated graph to the spectral reduction of is precisely such “strong component” . The associated structure matrix of is (21), whose spectrum is
This means that the process is both pulse and value stable. However, since the module of some of these eigenvalues is close to we deduce that small changes in some of these weights may produce an unstable digraph. For instance, this is the case if we replace in the first column by (as shown in [20]).
Example 11.
In the report R-1578-NSF [20], the pulse process considered for the 20% bus case is the following one. (see Figure 4 below).
Figure 4.
Weighted digraph for the 20% Bus Case. Captured from [20], p. 41. Copyright permission from The Rand Corporation.
The corresponding evolution algebra A is given by the natural basis
and structure matrix
In this case, the annihilator of A is and the reduced ideal is given by Therefore, the reduced evolution algebra is with natural basis
and structure matrix
Note that is a basic ideal of such that
The structure matrix of M relative to is
and is a natural basis of with structure matrix
Since the corresponding eigenvalues of these matrices (which determine and ) are contained in , the pulse and value stability of the whole pulse process follows from Theorem 9.
7. Conclusions
In this paper, we established the connection between the theory of pulse processes and the theory of evolution algebras. Both theories are enriched with this merged approach. Moreover, since we are simultaneously dealing with two theories, the motivation increases as it comes from two different sources. This would be the case of Proposition 1 (for evolution algebras) and Corollary 4 (for pulse processes).
The approach of Example 8 (also used in the Example 11 when Theorem 9 was applied there) enlightens the theory of pulse processes. The reduction process also gets it. Moreover, we have given a meaning to the study of the “interesting strong components” considered in R-1578-NSF [20], by showing the real role of each one of these components. For instance, in Example 10 we study a pulse process considered in R-1578-NSF [20] that according to this report has one interesting strong component, namely presented in Figure 3. We show that such a component is precisely the weighted digraph associated to the reduced evolution algebra and consequently this component determines the pulse and/or value stability of the whole pulse process (the bus case 10%). However, concerning Example 11, two “interesting strong components” are considered in R-1578-NSF [20], namely and The first one corresponds to the pulse process associated to the ideal M of the reduced evolution algebra described in Example 11, whereas is that of the quotient algebra The stability of , in Figure 4, is a necessary condition for the pulse and/or value stability of the main process, as deduced from Corollary 4, but it is not sufficient. However, Theorem 9 shows that the pulse and/or value stability of both components, and is a necessary and a sufficient condition for the pulse and/or value stability of the main pulse process (we gather this new information in Example 11). As we see, not all of the “interesting strong connected components” in the different pulse processes considered in R-1578-NSF play the same role, and our algebraic approach helps us to clarify this.
Note that all the “interesting strong components” mentioned above are evolution algebras of dimension 2 and 3. In [33], all the evolution algebras of dimension 3 were classified in 14 non-isomorphic types of algebras (meanwhile evolution algebras of dimension 2 were classified in 6 non-isomorphic types). To study if some of these types of evolution algebras are in general more stable in pulse and/or value than others, justifying the reason for this, may be a topic for future research. Note that, by Corollary 4, if some quotient algebra of an evolution algebra A, by a basic ideal M, is unstable (in pulse and/or value) then A is unstable.
Anyway, the combination of the theories of pulse processes and evolution algebras opens a window to a new and promising field of research in both frameworks.
Author Contributions
Conceptualization, M.V.V.; methodology, M.V.V. and M.B.; software, M.B. and M.V.V.; validation, M.V.V., M.B. and J.B.; formal analysis, M.V.V. and M.B.; investigation, M.V.V., M.B. and J.B.; resources, M.V.V.; data curation: M.V.V. and M.B.; writing—original draft preparation, M.V.V. and M.B.; writing—review and editing, M.V.V. and M.B.; visualization, M.V.V.; supervision, M.V.V., M.B. and J.B.; project administration, M.V.V., J.B.; funding acquisition, M.V.V. All authors have read and agreed to the published version of the manuscript.
Funding
This work was partially supported by the Spanish Project MTM2016-76327-C3-2-P (AEI∖FEDER, UE).
Acknowledgments
The graphs of these paper have been reprinted with permission expressly granted by the Rand Corporation, Santa Monica, CA. We wish explicitly to show our gratitude for this permission, with special thanks to the people of the Rand Corporation who have helped us with this management.
Conflicts of Interest
The authors declare no conflict of interest.
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