A Projection Argument for Differential Inclusions, with Applications to Persistence of Mass-Action Kinetics
Motivated by questions in mass-action kinetics, we introduce the notion of vertexical family of differential inclusions. Defined on open hypercubes, these families are characterized by particular good behavior under projection maps. The motivating examples are certain families of reaction networks –...
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irk-123456789-1492292019-02-20T01:23:11Z A Projection Argument for Differential Inclusions, with Applications to Persistence of Mass-Action Kinetics Gopalkrishnan, M. Miller, E. Shiu, A. Motivated by questions in mass-action kinetics, we introduce the notion of vertexical family of differential inclusions. Defined on open hypercubes, these families are characterized by particular good behavior under projection maps. The motivating examples are certain families of reaction networks – including reversible, weakly reversible, endotactic, and strongly endotactic reaction networks – that give rise to vertexical families of mass-action differential inclusions. We prove that vertexical families are amenable to structural induction. Consequently, a trajectory of a vertexical family approaches the boundary if and only if either the trajectory approaches a vertex of the hypercube, or a trajectory in a lower-dimensional member of the family approaches the boundary. With this technology, we make progress on the global attractor conjecture, a central open problem concerning mass-action kinetics systems. Additionally, we phrase mass-action kinetics as a functor on reaction networks with variable rates. 2013 Article A Projection Argument for Differential Inclusions, with Applications to Persistence of Mass-Action Kinetics / M. Gopalkrishnan, E. Miller, A. Shiu // Symmetry, Integrability and Geometry: Methods and Applications. — 2013. — Т. 9. — Бібліогр.: 22 назв. — англ. 1815-0659 2010 Mathematics Subject Classification: 34A60; 80A30; 92C45; 37B25; 34D23; 37C10; 37C15; 92E20; 92C42; 54B30; 18B30 DOI: http://dx.doi.org/10.3842/SIGMA.2013.025 http://dspace.nbuv.gov.ua/handle/123456789/149229 en Symmetry, Integrability and Geometry: Methods and Applications Інститут математики НАН України |
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Motivated by questions in mass-action kinetics, we introduce the notion of vertexical family of differential inclusions. Defined on open hypercubes, these families are characterized by particular good behavior under projection maps. The motivating examples are certain families of reaction networks – including reversible, weakly reversible, endotactic, and strongly endotactic reaction networks – that give rise to vertexical families of mass-action differential inclusions. We prove that vertexical families are amenable to structural induction. Consequently, a trajectory of a vertexical family approaches the boundary if and only if either the trajectory approaches a vertex of the hypercube, or a trajectory in a lower-dimensional member of the family approaches the boundary. With this technology, we make progress on the global attractor conjecture, a central open problem concerning mass-action kinetics systems. Additionally, we phrase mass-action kinetics as a functor on reaction networks with variable rates. |
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Gopalkrishnan, M. Miller, E. Shiu, A. A Projection Argument for Differential Inclusions, with Applications to Persistence of Mass-Action Kinetics Symmetry, Integrability and Geometry: Methods and Applications |
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Gopalkrishnan, M. Miller, E. Shiu, A. |
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A Projection Argument for Differential Inclusions, with Applications to Persistence of Mass-Action Kinetics |
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A Projection Argument for Differential Inclusions, with Applications to Persistence of Mass-Action Kinetics |
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A Projection Argument for Differential Inclusions, with Applications to Persistence of Mass-Action Kinetics |
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A Projection Argument for Differential Inclusions, with Applications to Persistence of Mass-Action Kinetics |
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A Projection Argument for Differential Inclusions, with Applications to Persistence of Mass-Action Kinetics |
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projection argument for differential inclusions, with applications to persistence of mass-action kinetics |
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Інститут математики НАН України |
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A Projection Argument for Differential Inclusions, with Applications to Persistence of Mass-Action Kinetics / M. Gopalkrishnan, E. Miller, A. Shiu // Symmetry, Integrability and Geometry: Methods and Applications. — 2013. — Т. 9. — Бібліогр.: 22 назв. — англ. |
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Symmetry, Integrability and Geometry: Methods and Applications |
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AT gopalkrishnanm aprojectionargumentfordifferentialinclusionswithapplicationstopersistenceofmassactionkinetics AT millere aprojectionargumentfordifferentialinclusionswithapplicationstopersistenceofmassactionkinetics AT shiua aprojectionargumentfordifferentialinclusionswithapplicationstopersistenceofmassactionkinetics AT gopalkrishnanm projectionargumentfordifferentialinclusionswithapplicationstopersistenceofmassactionkinetics AT millere projectionargumentfordifferentialinclusionswithapplicationstopersistenceofmassactionkinetics AT shiua projectionargumentfordifferentialinclusionswithapplicationstopersistenceofmassactionkinetics |
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Symmetry, Integrability and Geometry: Methods and Applications SIGMA 9 (2013), 025, 25 pages
A Projection Argument for Differential Inclusions,
with Applications to Persistence of Mass-Action
Kinetics
Manoj GOPALKRISHNAN †, Ezra MILLER ‡ and Anne SHIU §
† School of Technology and Computer Science, Tata Institute of Fundamental Research,
1 Homi Bhabha Road, Mumbai 400 005, India
E-mail: manojg@tifr.res.in
URL: http://www.tcs.tifr.res.in/~manoj/
‡ Department of Mathematics, Duke University, Box 90320, Durham, NC 27708-0320, USA
E-mail: ezra@math.duke.edu
URL: http://www.math.duke.edu/~ezra/
§ Department of Mathematics, University of Chicago,
5734 S. University Avenue, Chicago, IL 60637, USA
E-mail: annejls@math.uchicago.edu
URL: http://math.uchicago.edu/~annejls/
Received August 07, 2012, in final form March 23, 2013; Published online March 26, 2013
http://dx.doi.org/10.3842/SIGMA.2013.025
Abstract. Motivated by questions in mass-action kinetics, we introduce the notion of
vertexical family of differential inclusions. Defined on open hypercubes, these families are
characterized by particular good behavior under projection maps. The motivating examples
are certain families of reaction networks – including reversible, weakly reversible, endotactic,
and strongly endotactic reaction networks – that give rise to vertexical families of mass-
action differential inclusions. We prove that vertexical families are amenable to structural
induction. Consequently, a trajectory of a vertexical family approaches the boundary if
and only if either the trajectory approaches a vertex of the hypercube, or a trajectory in
a lower-dimensional member of the family approaches the boundary. With this technology,
we make progress on the global attractor conjecture, a central open problem concerning
mass-action kinetics systems. Additionally, we phrase mass-action kinetics as a functor on
reaction networks with variable rates.
Key words: differential inclusion; mass-action kinetics; reaction network; persistence; global
attractor conjecture
2010 Mathematics Subject Classification: 34A60; 80A30; 92C45; 37B25; 34D23; 37C10;
37C15; 92E20; 92C42; 54B30; 18B30
1 Introduction
The global attractor conjecture has been a central open problem in reaction network theory since
its formulation by Horn in 1974 [16]. It asserts that any complex-balanced mass-action kinetics
system of ordinary differential equations with positive initial conditions possesses a globally at-
tracting stationary point in each stoichiometric compatibility class (see Conjecture 6.1 for a more
precise statement). It is well-known that this conjecture is implied by Feinberg’s persistence con-
jecture [11, Remark 6.1.E], a version of which asserts the following: for weakly reversible net-
works taken with mass-action kinetics, no species asymptotically becomes extinct or unbounded.
An a priori special case of the persistence conjecture asserts that at least one species survives
asymptotically. In this paper, we show that this a priori special case in fact implies the entire
mailto:manojg@tifr.res.in
http://www.tcs.tifr.res.in/~manoj/
mailto:ezra@math.duke.edu
http://www.math.duke.edu/~ezra/
mailto:annejls@math.uchicago.edu
http://math.uchicago.edu/~annejls/
http://dx.doi.org/10.3842/SIGMA.2013.025
2 M. Gopalkrishnan, E. Miller and A. Shiu
persistence conjecture (Corollary 6.3). As a consequence, if the persistence conjecture is false,
then in every minimal counterexample each species becomes either extinct or unbounded. It
follows that the persistence conjecture in dimension n implies the global attractor conjecture in
dimension n+ 1 (Theorems 6.8 and 6.10).
Pantea [20], building on earlier work by Craciun, Nazarov, and Pantea [10], used the persis-
tence conjecture in two dimensions to prove the global attractor conjecture in three dimensions.
Pantea’s work relied in part on projecting trajectories to lower-dimensional faces. Here, we
generalize this projection argument in two ways. First, our main result, Theorem 3.15, applies
in arbitrary dimensions. Second, our results hold not only for mass-action kinetics networks,
but for certain families of differential inclusions that we call vertexical (Definition 3.13). The
notion of vertexical family makes precise the essential structure required of a family of dynamical
systems on hypercubes of varying dimensions to permit a structural induction argument of this
sort. Theorem 3.15 shows that a trajectory in a vertexical family approaches the boundary if
and only if either it approaches a vertex of the hypercube, or a lower-dimensional trajectory in
the family approaches the boundary.
Vertexical families of differential inclusions arise naturally in reaction network theory by way
of mass-action kinetics or, more generally, power-law dynamics that are considered in biochemical
systems theory (Remark 4.2), on networks that are reversible, weakly reversible, endotactic,
strongly endotactic (Definition 4.6.4), and so on. We prove that these networks, and more
generally, projective classes of networks (Definition 5.1), give rise to vertexical families of mass-
action differential inclusions (Theorem 5.23 and Corollary 5.24).
In the course of proving this result, we are led to view mass-action kinetics as a functor (Theo-
rem 5.20). No more category theory is required in this paper beyond the definition of a functor.
Functoriality itself is used as a convenient shorthand for a list of properties spelled out at the
beginning of Section 5. The use of this shorthand clarifies the concept of vertexical family
and suggests that other questions concerning mass-action kinetics systems may be amenable
to structural induction (Question 5.26). Section 6 discusses the implications of our results for
persistence of mass-action kinetics systems.
2 Dynamical properties of differential inclusions
In this section, we recall certain dynamical properties of differential inclusions defined on mani-
folds. For background on manifolds, see [19]. All manifolds considered here have finite dimen-
sion. For background on differential inclusions, see [7].
Definition 2.1. Let M be a smooth manifold with tangent bundle πM : TM → M . A diffe-
rential inclusion on M is a subset X ⊆ TM .
Example 2.2. The simplest differential inclusions on M are vector fields on M . The subset
X ⊆ TM for a given vector field is the image of the corresponding section M ↪→ TM .
Definition 2.3. Fix a differential inclusion X on a smooth manifold M . Let I ⊆ R≥0 be
a nonempty interval (in particular, connected) containing its left endpoint. A differentiable
curve f : I →M is a trajectory of X if the tangent vectors to the curve lie in X. An unbounded
interval is a ray. A trajectory defined on a ray eventually has a property P if there exists T > 0
such that property P holds for the function for all t ≥ T .
Let M be a smooth manifold with corners. That is, M is a space locally modeled on the
closed nonnegative orthant [19, p. 363]. Then ∂M denotes the boundary of M , which is the set
of points of M that are not in the relative interior of M . The relative interior M \ ∂M of M is
a smooth manifold [19, p. 386, Examples 14–19].
A Projection Argument for Differential Inclusions 3
Definition 2.4. Let M be a smooth manifold with corners with relative interior M = M \∂M ,
and let V ⊆ ∂M be a subset of the boundary.
1. A differential inclusion X ⊆ TM is persistent relative to V if the closure in M of every
trajectory of X is disjoint from the closure V of V in M .
2. A differential inclusion X ⊆ TM is repelled by V if for every open set O1 ⊆ M with
V ⊆ O1, there exists a smaller open set O2 ⊆ O1 with V ⊆ O2 such that for every
trajectory f : I →M of X, if f(inf I) /∈ O1 then f(I)∩O2 is empty; in other words, if the
trajectory begins outside of O1, then the trajectory never enters O2.
3. If M is compact, then a differential inclusion X ⊆ TM is permanent if it is persistent and
there is a compact subset Ω ⊆M such that for every ray I, every trajectory of X defined
on I is eventually contained in Ω.
More generally, a set X of differential inclusions on M is persistent relative to V , repelled by V ,
or permanent if every member X ∈ X has the corresponding property.
Definition 2.5. Differential inclusions that are persistent relative to the boundary ∂M are
simply called persistent and similarly for repelled. A collection of differential inclusions, possibly
on a family of different manifolds with corners, is persistent, permanent, or repelled if each
differential inclusion in the collection has the respective property.
Remark 2.6. Any differential inclusion repelled by V is also persistent relative to V . The con-
verse is false in general because different trajectories starting outside O1 could get arbitrarily
close to V . However, certain extra conditions could guarantee that the original differential inclu-
sion is repelled by V . For example, suppose M is compact and that the differential inclusion X
has a continuous extension X to M . Assume further that every trajectory of X starting in ∂M
but outside V has its closure disjoint from V . If the projection X → M is sufficiently nice –
we are unsure what conditions to impose, but we have in mind properness – then it should be
possible to conclude that X is repelled by V .
Remark 2.7. A differential inclusion that is permanent need not be repelled by the bound-
ary of M . The reason appeared already in Remark 2.6: different trajectories starting out-
side O1 could get arbitrarily close to the boundary (on the way to ending up in Ω). Conversely,
a differential inclusion repelled by the boundary need not be permanent, even if M is compact,
because O2 might necessarily be smaller when O1 is smaller. That is, trajectories that start
closer to the boundary could eventually remain closer to the boundary; see Example 2.8.
Example 2.8. Fix a differential inclusion X on a planar disk M whose trajectories form con-
centric circles about its center. X is repelled by the boundary circle V = ∂M . Indeed, if O1 ⊆M
is an open set containing V , then the compact set M \ O1 achieves a maximum radius r from
the center, so we can take O2 to be the set of all points in M of radius > r.
Lemma 2.9. If the differential inclusion X in Definition 2.4 is persistent, then for every trajec-
tory f : I → M of X, there exist disjoint open sets Of and OV in M containing the closures
in M of f(I) and V respectively.
Proof. A manifold with corners is metrizable, and hence it is a normal Hausdorff space. �
Remark 2.10. Consider a differential inclusion defined on a positive orthant M = Rn>0. Dis-
tinct partial compactifications M of M yield distinct notions of persistence. In the case of
M = Rn≥0, even with Lemma 2.9, our definition of persistence is weaker than the standard
definition [14] that requires each coordinate of a trajectory to remain bounded away from 0 for
all time. However, the mass-action differential inclusions that we consider are viewed in the
4 M. Gopalkrishnan, E. Miller and A. Shiu
compactification M = [0,∞]S (Remark 5.18), so in the context of reaction network theory, our
definition of persistence is in fact stronger than the standard definition because coordinates of
trajectories not only must be bounded away from zero but also must avoid going to infinity.
Mathematically, the definition we adopt has the advantage of being purely topological, so it
behaves well under homeomorphism. Our definition also allows, if required, to separate the usual
concept of persistence into the two questions of whether trajectories are bounded and whether ω-
limit points exist on the boundary. Both properties are conjectured to hold for weakly reversible
and, more generally, endotactic (see Definition 4.6) reaction networks. When trajectories are
bounded, our definition of persistence is equivalent to the standard one. Indeed, the mass-action
differential inclusions that we introduce later are viewed in the compactification [0,∞]S , so our
definition of persistence automatically implies boundedness of trajectories; see Remark 5.18.
Remark 2.11. Suppose a manifold M has a metric d, and V is a compact subset of M .
A differential inclusion X is repelled by V if for every d1 ∈ R>0, there exists d2 ∈ R>0 such that
every trajectory f : I →M of X starting with d(f(inf I), V ) ≥ d1 maintains d(f(I), V ) ≥ d2.
Remark 2.12. Our notion of “repelled” is new, motivated by the requirements of Theorem 3.15.
The motivations are further explained in Remark 3.24. Cognate but distinct concepts bearing
similar names have been defined by others. Anderson and Shiu define a boundary face to
have a “repelling neighborhood” if there is a neighborhood of the face such that whenever
a trajectory enters that neighborhood, it can get no closer to the face while remaining in that
neighborhood [4]. Banaji and Mierczynski define a “repelling face” as a boundary face for which
any trajectory that begins in that face immediately exits the face into the interior of the relevant
invariant set [8]. Neither of these concepts is adequate for our purposes.
Remark 2.13. Suppose a differential inclusion X is a subset of a persistent differential inclu-
sion Y . Then X must be persistent, since each of its trajectories is a trajectory of Y . More
generally, consider properties P of differential inclusions X of the form “P (f) holds for all trajec-
tories f of X.” If property P is true for a differential inclusion Y , and a differential inclusion Z
factors through Y , then property P is true for Z as well.
3 Vertexical families of differential inclusions
A mass-action kinetics system is naturally defined on the positive orthant RS>0 corresponding
to the space of concentrations of species. In this section we work instead with open hypercubes
(0, 1)S , and not directly with positive orthants themselves.
To justify this choice, first we argue that nothing is lost by working with hypercubes. Open
hypercubes (0, 1)S are diffeomorphic to positive orthants RS>0, so differential inclusions can be
transferred from one space to the other by fixing a diffeomorphism and using its Jacobian (see
Section 5.2). Additionally, properties such as persistence are defined topologically on the tangent
bundle – and therefore invariant under diffeomorphism – so they can be analyzed on either space.
An advantage of working with open hypercubes is that they have natural “cubical” com-
pactifications [0, 1]S that appear to be optimally relevant in the context of mass-action kinetics.
Alternatively, we could have achieved a cubical compactification by considering the hypercubes
[0,∞]S . Nevertheless, there is a stylistic advantage to working with the hypercubes [0, 1]S : we
can treat symmetrically the cases where a species concentration goes to infinity or to zero. This
makes some of our definitions more transparent, and the structural induction becomes cleaner.
Definition 3.1. For any finite nonempty set S, let DS be the set of all differential inclusions
on the open hypercube (0, 1)S . Fix a collection S of finite nonempty sets. If XS is a set of
differential inclusions on (0, 1)S for each S ∈ S, then the collection X = {XS ⊆ DS}S∈S of
sets XS is a family of differential inclusions on open hypercubes indexed by S.
A Projection Argument for Differential Inclusions 5
3.1 Definitions concerning hypercubes
The definition of vertexical families requires some preliminary notation on hypercubes.
Notation 3.2. Let S be a finite nonempty set.
1. For every i ∈ S, let ei ∈ RS be the standard basis vector indexed by i; that is, ei : S → R
sends i to 1 and S \ {i} to 0.
2. For each subset U ⊆ S and vertex x ∈ {0, 1}S of the hypercube [0, 1]S , let
FU (x) =
(
x+ span{ei | i ∈ U}
)
∩ [0, 1]S
denote the face of the hypercube [0, 1]S along U at vertex x.
3. For p =
∑
i∈S
piei ∈ RS , let |p| =
√∑
i∈S
p2i denote its Euclidean norm.
4. For subsets P,Q ⊆ RS , denote by d(P,Q) = inf
{
|p − q|
∣∣ p ∈ P and q ∈ Q
}
the distance
between them.
Remark 3.3. Our notation for faces differs from that in related references [3, 4, 5, 9, 22].
What those works call FU is close to what we call FS\U (0), where 0 denotes the origin. This
correspondence is not perfect; the sets FU in the related works are faces of the nonnegative
orthant RS≥0, whereas here the sets FU (x) denote faces of hypercubes.
In the context of reaction networks, S indexes the set of reacting chemical species; a chemical
complex, being a linear combination of these species, is therefore viewed as a vector in RS (see
Definition 4.1), which has preferred basis vectors ei for i ∈ S.
Definition 3.4. Fix a finite nonempty set S. For a face F of [0, 1]S and a real number η > 1/2,
the centered shrinking
ηF =
{
x ∈ F
∣∣d(x, ∂F ) ≥ (1− η)/2
}
of F is the set of points in F whose distance from the boundary ∂F is at least (1− η)/2.
Example 3.5. A centered shrinking of the rightmost face of the 3-cube looks as follows,
where the inner shaded square is centered in F and has side length η times that of F .
Definition 3.6. Fix a finite nonempty set S and a subset U ⊆ S. Let P ⊆ [0, 1]S , and suppose
that ε ∈ (0, 1/2) ⊆ R. The ε-pile of the subset P along U is the set
pile(P, ε, U) :=
{
x+
∑
i∈U
εiei
∣∣∣x ∈ P and − ε ≤ εi ≤ ε for all i ∈ U
}
∩ [0, 1]S .
Definition 3.7. Fix a finite nonempty set S and a proper face F of the hypercube [0, 1]S
containing a vertex x. Let U ⊆ S be such that F = FS\U (x). For a real number ε ∈ (0, 1/2),
the ε-block Fε is pile
(
(1− 2ε)F, ε, U
)
, the ε-pile along U of the centered shrinking (1− 2ε)F .
6 M. Gopalkrishnan, E. Miller and A. Shiu
Example 3.8. If ε = (1− η)/2 in Example 3.5, the block Fε looks like the following:
Note that the face F is orthogonal to the basis vector indexed by U , and the thickness ε of the
block Fε equals its distance from the edges of F . The vertex x in Definition 3.7 could equally
well be any of the four vertices of F .
Remark 3.9. The block Fε is a closed subset of [0, 1]S . Such sets are closely related to sets
that Pantea [20] denoted by Kε, which he used for the purpose of projecting trajectories, as we
too do in the current paper.
Notation 3.10. Let f : U → S be a map of finite sets, and view RS as functions S → R.
Denote by πf : RS → RU the linear projection that sends v ∈ RS to v ◦ f ∈ RU . When U ⊆ S
and f is inclusion, we write πU for the projection map instead of πf .
Remark 3.11. If U ⊆ S is any subset, then
1) projection is surjective on the open hypercube: πU
(
(0, 1)S
)
= (0, 1)U , and
2) πU
(
(1− 2ε)FS\U (x)
)
is a vertex of the hypercube [0, 1]U .
Example 3.12. The projection πU in Example 3.8 collapses the cube to the horizontal edge
that is [0, 1] = [0, 1]U . The projection takes F as well as the subset ηF ⊆ F to the indicated
right-hand vertex of the interval.
3.2 Definition of vertexical family and main result
The heuristic description of a vertexical family of differential inclusions begins by considering
a trajectory of a differential inclusion in the family. Suppose the trajectory remains near a face
of the hypercube. The vertexical condition requires that, while the trajectory is near the face,
the image of the trajectory under the projection map collapsing that face be the trajectory of
a fixed lower-dimensional differential inclusion in the family, up to time reparametrization. We
emphasize that only the part of the trajectory near the face and away from the boundary of the
face is required to be projectable.
Definition 3.13. Let S be the set of all finite nonempty subsets of the positive integers Z≥1.
A family X = {XS}S∈S of differential inclusions on open hypercubes indexed by S is vertexical
if for each
• set S ∈ S,
• differential inclusion X ⊆ T (0, 1)S in XS ,
• proper nonempty subset U ⊆ S, and
• face F = FS\U (x) of [0, 1]S ,
A Projection Argument for Differential Inclusions 7
there is ε′ > 0 such that for every ε ∈ (0, ε′), some differential inclusion Y ∈ XU has the property
that for every trajectory f : I → [0, 1]S of X with image in the block Fε, there exist
• a trajectory g : J → [0, 1]U of Y , and
• an order-preserving continuous map α : I → J
such that πU ◦ f = g ◦ α.
Examples of vertexical families of differential inclusions include those arising from reversible,
weakly reversible, endotactic, or strongly endotactic chemical reaction networks (Definitions 4.3
and 5.16); this is the content of Corollary 5.24, the goal of Sections 4 and 5. Some nuances in
the definition are further discussed in Remark 5.21.
We now give a definition, followed by our main result on abstract vertexical families.
Definition 3.14. Fix a finite set S and an index set R ⊆ Z≥1, called the repulsing index set.
Embed the hypercube [0, 1]R∩S into the hypercube [0, 1]S as the face [0, 1]R∩S×{0}S\R. A vertex
of [0, 1]S is charged if it lies in [0, 1]R∩S . A face F of [0, 1]S is opposite if F ∩ [0, 1]R∩S is empty.
The charged set is the set [0, 1]R∩S ∩ ∂[0, 1]S .
In practice, R and S are both subsets of a fixed set, and R need not be finite. If R is empty,
then by convention [0, 1]R∩S × {0}S\R is the origin. Thus the origin is always charged. The
charged set equals [0, 1]R∩S unless R ⊇ S, in which case the charged set is ∂[0, 1]S .
Theorem 3.15. Fix a vertexical family X = {XS}S∈S on open hypercubes indexed by the set S
of all finite nonempty subsets of the positive integers Z≥1, and a repulsing index set R ⊆ Z≥1.
Assume that for every set S ∈ S, every differential inclusion X ∈ XS is
• persistent relative to the union of all opposite faces of [0, 1]S and
• repelled by the charged vertices of its hypercube [0, 1]S.
Then
1. Every such differential inclusion X is persistent relative to the entire boundary ∂[0, 1]S
and repelled by the charged set [0, 1]R∩S ∩ ∂[0, 1]S of its hypercube.
2. Fix S ∈ S and X ∈ XS. If, in addition, X is repelled by the union of all opposite faces of
[0, 1]S, then X is repelled by the boundary ∂[0, 1]S.
Remark 3.16. The differential inclusion in Theorem 3.15.1 is repelled either by the entire
boundary of its hypercube (if R ⊇ S) or by the proper face [0, 1]R∩S .
Proof of Theorem 3.15. Fix S ∈ S. Let X ∈ XS . We prove that for every proper, positive-
dimensional face F = FS\U (x) of [0, 1]S , the following two claims hold.
A. If X is persistent relative to the boundary ∂F of F , then X is persistent relative to F .
B. If F is not an opposite face and X is repelled by the boundary ∂F of F , then X is repelled
by F .
The remainder of this proof has two components: we first explain how Claims A and B imply
parts 1 and 2 of the theorem, and then we prove the two claims.
To start, consider part 1 of the theorem. The differential inclusion X is persistent relative to
all vertices of [0, 1]S , because each vertex is either charged or an opposite face. Using this fact as
a base case, Claim A implies, by induction on the dimension of F , that X is persistent relative
to every proper face of [0, 1]S . Since the hypercube [0, 1]S has only finitely many faces, X is
therefore persistent relative to the entire boundary. For repulsion, all vertices of [0, 1]S that lie
8 M. Gopalkrishnan, E. Miller and A. Shiu
in the charged set are charged vertices (see Remark 3.16), so X is repelled by all such vertices
by hypothesis. Using this fact as a base case, Claim B implies, by induction on the dimension of
faces F of [0, 1]S that are in the charged set (and thus are not opposite faces), that X is repelled
by the charged set. Hence, part 1 of the theorem holds for X, after we prove the two claims.
As for part 2, now assume that X is repelled by the union of opposite faces of [0, 1]S . We
need that X is repelled by non-opposite faces as well. Each vertex of [0, 1]S is either charged
or an opposite face, so each vertex repels X. Using this fact as a base case, Claim B implies,
by induction on the dimension of proper non-opposite faces F , that X is repelled by every
non-opposite face.
It remains to prove Claims A and B for a proper, positive-dimensional face F = FS\U (x)
of [0, 1]S . If F is an opposite face, then Claim A holds by hypothesis and Claim B is vacuous.
Now assume that F is not an opposite face. Assume that X is persistent relative to the
boundary ∂F of the face. Let f : I → (0, 1)S be a trajectory of X, and let d1 = d
(
f(inf I), F
)
be the distance to F from the initial point of the trajectory. The goal is to exhibit ε > 0 so that
the trajectory remains at distance greater than ε from F ; that is, d
(
f(I), F
)
≥ ε. Claim A then
follows as a consequence.
By hypothesis, X is persistent relative to the boundary ∂F , so there exists d2 > 0 such that
d
(
f(I), ∂F
)
≥ d2. Decreasing d2 if necessary, assume that d2 ≤ d1 and that d2/2 ≤ ε′, where
ε′ > 0 is such that trajectories in the block Fε′ can be projected (Definition 3.13).
Consider the block Fd2/2 of F . If the image of the trajectory f(I) fails to intersect the
block Fd2/2, then by defining ε = d2/2 it follows that d
(
f(I), F
)
> ε, and we are done. Therefore,
we can and do assume that I ′ ⊆ I is a maximal nonempty subinterval such that f(I ′) ⊆ Fd2/2,
and let ι = f(inf I ′) denote the corresponding initial point, as in the following illustration.
Note that d(ι, F ) = d2/2. Indeed, by maximality of the interval I ′ the point ι lies on the
boundary of Fd2/2, and the only boundary face of Fd2/2 that intersects the interior (0, 1)S of
the hypercube without also being contained in the d2-neighborhood of the boundary ∂F has
constant distance d2/2 from F ; see the following illustration.
Because X is a vertexical family, there exist a differential inclusion Y in XU , a trajectory
g : J → [0, 1]U of Y , and an order-preserving continuous map α : I ′ → J such that g ◦ α =
A Projection Argument for Differential Inclusions 9
πU ◦ f with domain I ′. By definition, Y depends only on X and F , and not on the particular
trajectory f or the subinterval I ′. To prove Claim A for this face F , it now suffices to show that
there exists ε > 0, depending only on d2, such that d
(
g(J), πU (F )
)
≥ ε, for this claim implies
that d
(
f(I), F
)
≥ ε, as desired.
Since F is not an opposite face, by definition it contains a charged vertex, which we assume
without loss of generality is x (recall that F = FS\U (x)). We claim that y = πU (F ) is a charged
vertex of [0, 1]U ; that is, yi = 0 for all i ∈ U \ R. Indeed, j ∈ U implies xj = yj because
x, y ∈ F = FS\U (x), and if additionally j /∈ R, then xj = 0 because x is charged.
By hypothesis of the theorem, Y is repelled by the charged vertex y = πU (F ) of [0, 1]U . Hence
there exists ε > 0 such that all trajectories of Y starting at distance d2/2 away from the vertex
πU (F ) – and in particular, the trajectory g, because ι has distance precisely d2/2 from F – never
get closer than ε to the vertex πU (F ). This choice of ε depends only on the distance d2/2, not
on any aspect of the particular trajectory f ; its existence proves Claim A.
To prove Claim B for this face F , assume X is repelled by ∂F , and let O1 ⊆ [0, 1]S be an open
set containing F . Using that X is also persistent relative to ∂F , repeat the argument above,
but with d1 > 0 now denoting the distance from [0, 1]S \ O1 to F . The assumption that X
is repelled by ∂F implies that the value of d2 as found above depends only on d1 and not on
any aspect of any trajectory f that begins outside O1. Thus, the value of ε (as above) depends
only on d2, which in turn depends only on d1. Trajectories of X starting outside O1 therefore
remain at distance at least ε from F . Hence X is repelled by F , as per Remark 2.11, proving
Claim B. �
3.3 Consequences, special cases, and clarif ications
Next, we give three corollaries of Theorem 3.15. First, when the repulsing index set R consists
of all positive integers Z≥1, the theorem specializes to the following statement.
Corollary 3.17. Fix a vertexical family X = {XS}S∈S on open hypercubes indexed by the
set S of all finite nonempty subsets of the positive integers Z≥1. If for every set S ∈ S, every
differential inclusion X ∈ XS is repelled by the vertex set {0, 1}S of its hypercube, then every
such X is repelled by, and hence persistent relative to, the boundary ∂[0, 1]S.
In words, Corollary 3.17 states that to prove that every differential inclusion in a vertexical
family is repelled by the boundary, it suffices to show that each such differential inclusion is
repelled by the vertices. The intuition behind this result is as follows. If a trajectory remains
near a proper face and away from its boundary for some time, then the vertexical property
allows us to project that part of the trajectory to a trajectory of a lower-dimensional differential
inclusion in which the projected face is a vertex, which is repelling by assumption; hence the
original trajectory stays away from the original face.
The next corollary is applied in our subsequent work [15] to prove persistence results for
differential inclusion families that arise from strongly endotactic reaction networks. When the
repulsing index set R is empty, Theorem 3.15.1 specializes to the following statement.
Corollary 3.18. Fix a vertexical family X = {XS}S∈S on open hypercubes indexed by the set S
of all finite nonempty subsets of the positive integers Z≥1. Suppose that for every set S ∈ S,
every differential inclusion X ∈ XS satisfies the following hypotheses:
1) X is repelled by the origin of its hypercube (0, 1)S, and
2) X is persistent relative to the union of all faces that do not contain the origin.
Then every X ∈ XS is persistent relative to the boundary ∂[0, 1]S.
10 M. Gopalkrishnan, E. Miller and A. Shiu
Our final corollary is used to prove permanence-like results in our next work [15]. More
precisely, Corollary 3.21 gives conditions under which trajectories of a differential inclusion X
that begin in a compact set K never leave a larger compact set. For ease of notation, we now
introduce the following differential inclusion.
Definition 3.19. In the setting of Definition 2.4, fix a differential inclusion X ⊆ TM and
a subset K ⊆ M . The restricted differential inclusion XK ⊆ X is the smallest differential
inclusion such that every trajectory of X that begins in K is a trajectory of XK .
In other words, XK consists of all tangent vectors to all trajectories of X that begin in K.
Lemma 3.20. Fix a finite set S and a compact set K ⊆ (0, 1)S. If a differential inclusion
X ⊆ T (0, 1)S is repelled by the boundary ∂[0, 1]S, then there exists a compact set K+ with
K ⊆ K+ ⊆ (0, 1)S such that no trajectory of X that begins in K leaves K+.
Proof. The open set O1 = [0, 1]S \ K contains the boundary ∂[0, 1]S , so by definition of
repelling, there exists an open set O2 in [0, 1]S that also contains the boundary ∂[0, 1]S such
that trajectories of XK that begin in K never leave the compact set K+ = [0, 1]S \O2. Hence,
no trajectory of X that begins in K leaves K+. �
Corollary 3.21. Fix a vertexical family X = {XS}S∈S on open hypercubes indexed by the set S
of all finite nonempty subsets of the positive integers Z≥1, and a repulsing index set R ⊆ Z≥1.
Assume the hypotheses of Theorem 3.15. Fix a set S ⊆ S, a compact set K ⊆ (0, 1)S, and
a differential inclusion X ∈ XS. If XK is repelled by the union of all opposite faces of [0, 1]S,
then there exists a compact set K+ with K ⊆ K+ ⊆ (0, 1)S such that no trajectory of X that
begins in K leaves K+.
Proof. Immediate from Theorem 3.15.2 and Lemma 3.20. �
If there exists d > 0 so that all trajectories of X starting in K remain at distance greater
than d from all opposite faces, then XK is repelled by the union of the opposite faces. Con-
sequently, in the context of Corollary 3.21, it follows that there exists a compact set K+ such
that no trajectory of X starting in K leaves K+. In particular, if the repulsing index set is the
empty set, then the existence of such a bound d simply means an upper bound 1− d ∈ (0, 1) on
all coordinate components of all trajectories of X beginning in K.
Remark 3.22. The significance of Corollary 3.21 is that, given the flow from K, promoting its
persistence relative to the opposite faces to repulsion by the opposite faces results in its repulsion
by the entire boundary. In this form, it looks like a weaker form of Corollary 3.17, but restricted
to those trajectories that begin in K. Note that it is a weaker form because in Corollary 3.21, we
assume not only that XK is repelled by all vertices, but also that it is repelled by the union of all
the opposite faces. An assumption like this appears to be necessary: without this assumption,
the projections of opposite faces are vertices in lower-dimensional differential inclusions that
need not be repelling (only for XK are the opposite faces assumed to be repelling).
Remark 3.23. In the statement of Theorem 3.15, if the goal is to prove that a particular
differential inclusion X ∈ XS is persistent relative to ∂[0, 1]S (or repelled by the charged set),
then it is enough to assume a slightly weaker hypothesis, namely that (i) X itself is persistent
relative to the union of all opposite faces and repelled by the charged vertices of the hypercube,
and (ii) the lower-dimensional set XU for each proper nonempty subset U ⊆ S is persistent
relative to the union of all opposite faces and repelled by the charged vertices of its corresponding
hypercube [0, 1]U .
A Projection Argument for Differential Inclusions 11
Remark 3.24. We devised the notion of “repelled by” (Definition 2.4) expressly for the purpose
of proving Theorem 3.15. It is natural to ask whether this notion is necessary: is a vertexical
family that is persistent relative to the charged vertices necessarily persistent relative to the
boundary? In other words, in the statement of Theorem 3.15, can instances of “repelled by” be
replaced by “persistent relative to”? The answer is no: such a replacement makes the theorem
false. Using the hypothesis that certain vertices are repelling, in the proof of Theorem 3.15 one
obtains a value ε > 0 (for a neighborhood of the face) that depends only on d2/2 (the thickness
of the block of the face). However, under the weaker assumption of persistence relative to the
vertices, this value ε depends on the specific subinterval I ′. A trajectory can repeatedly enter
and exit the block, so that there are infinitely many relevant subintervals I ′. In this case, it is
possible for the trajectory to enter arbitrarily small neighborhoods without violating persistence.
Also recall from Remark 2.6 that although repulsion implies persistence, the converse is false.
4 Reaction network theory
In this section, we define reaction networks, reaction systems, and their properties.
4.1 Reaction networks
Our networks are more general than usual for chemical reaction network theory [13, 17].
Definition 4.1. Write OpnInt =
{
(a, b) | 0 ≤ a < b ≤ ∞
}
for the set of open subintervals
of R>0 and CmpctInt =
{
[a, b] | 0 < a ≤ b <∞
}
for the set of compact subintervals.
1. A reaction network (S, C,R) is a triple of finite sets: a set S of species, a set C ⊆ RS of
complexes, and a set R ⊆ C × C of reactions.
2. The reaction graph is the directed graph (C,R) whose vertices are the complexes and
whose directed edges are the reactions.
3. A reaction r = (y, y′) ∈ R, also written y → y′, has reactant y = reactant(r) ∈ RS , product
y′ = product(r) ∈ RS , and reaction vector
flux(r) = product(r)− reactant(r).
4. The reaction diagram is the realization (C,R)→ RS of the reaction graph that takes each
reaction r ∈ R to the translate of flux(r) that joins reactant(r) to product(r).
5. A linkage class is a connected component of the reaction graph.
Remark 4.2. The chemical reaction network theory literature usually imposes the following
requirements for a reaction network.
• Each complex takes part in some reaction: for all y ∈ C there exists y′ ∈ C such that
(y, y′) ∈ R or (y′, y) ∈ R.
• No reaction is trivial: (y, y) /∈ R for all y ∈ C.
Definition 4.1 does not impose these conditions; in other words, our reaction graphs may in-
clude isolated vertices or self-loops. We drop these conditions to ensure that the projection
of a network – obtained by removing certain species – remains a network under our definition
even if some reactions become trivial (see Definition 5.1.1). In addition, like Craciun, Nazarov,
and Pantea [10, § 7], we allow arbitrary real complexes y ∈ RS , so our setting is more general
than that of usual chemical reaction networks, whose complexes y ∈ ZS≥0 are nonnegative in-
teger combinations of species, as in the following definition. The ODE systems defined in the
next subsection that result from real complexes have been studied over the years and called
“power-law systems” (see Remark 5.17).
12 M. Gopalkrishnan, E. Miller and A. Shiu
Definition 4.3. A reaction network (S, C,R) is
1) integer if C ⊆ ZS ;
2) chemical if C ⊆ ZS≥0;
3) reversible if the reaction graph of the network is undirected: a reaction (y, y′) lies in R if
and only if its reverse reaction (y′, y) also lies in R;
4) strongly connected if the reaction graph of the network is strongly connected; that is, if
the reaction graph contains a directed path between each pair of complexes;
5) weakly reversible if every linkage class of the network is strongly connected.
Note that a network is strongly connected if and only if it is weakly reversible and has only
one linkage class.
The next definitions introduce endotactic networks of [10].
Definition 4.4. The standard basis of RS indexed by S defines a canonical inner product 〈·, ·〉
on RS with respect to which the standard basis is orthonormal. Let w ∈ RS .
1. The vector w defines a preorder on RS , denoted by ≤w, in which
y ≤w y′ ⇔ 〈w, y〉 ≤ 〈w, y′〉.
Write y <w y
′ if 〈w, y〉 < 〈w, y′〉.
2. For a finite subset Y ⊆ RS , denote by initw (Y ) the set of ≤w-maximal elements of Y :
initw (Y ) =
{
y ∈ Y
∣∣ 〈w, y〉 ≥ 〈w, y′〉 for all y′ ∈ Y
}
.
3. For a reaction network (S, C,R), the set Rw ⊆ R of w-essential reactions consists of those
whose reaction vectors are not orthogonal to w:
Rw =
{
r ∈ R
∣∣ 〈w, flux(r)〉 6= 0
}
.
4. The w-support suppw (S, C,R) of the network is the set of vectors that are ≤w-maximal
among reactants of w-essential reactions:
suppw (S, C,R) = initw (reactant(Rw)) .
Remark 4.5. In order to simplify the computations in our next work [15], we differ from the
usual convention [10, 20], by letting initw (Y ) denote the ≤w-maximal elements rather than
the ≤w-minimal elements. Accordingly, the inequalities in Definition 4.6 are switched, so our
definition of endotactic is equivalent to the usual one.
Definition 4.6. Fix a reaction network (S, C,R).
1. The network (S, C,R) is w-endotactic for some w ∈ RS if
〈w, flux(r)〉 < 0
for all w-essential reactions r ∈ Rw such that reactant(r) ∈ suppw (S, C,R).
2. The network (S, C,R) is W -endotactic for a subset W ⊆ RS if (S, C,R) is w-endotactic
for all vectors w ∈W .
3. The network (S, C,R) is endotactic if it is RS-endotactic.
A Projection Argument for Differential Inclusions 13
4. (S, C,R) is strongly endotactic if it is endotactic and for every vector w that is not ortho-
gonal to the stoichiometric subspace of (S, C,R), there exists a reaction y → y′ in R such
that
(i) y >w y
′, and
(ii) y is ≤w-maximal among all reactants in (S, C,R): y ∈ initw (reactant(R)).
Remark 4.7. Endotactic chemical reaction networks, which generalize weakly reversible net-
works, were introduced by Craciun, Nazarov, and Pantea [10, § 4]. Our definition is slightly more
general still, because we do not require the reaction networks to be chemical (Definition 4.6).
Strongly endotactic reaction networks are new; they give rise to strong results concerning per-
sistence using our techniques; see Theorem 6.11. Strongly connected networks (i.e., weakly
reversible networks with only one linkage class) are strongly endotactic.
Remark 4.8. For the geometric intuition behind Definition 4.6, imagine a hyperplane normal
to w that is sweeping across the reaction diagram in RS from “infinity in direction w”. As this
hyperplane sweeps, it stops when it first reaches the reactant y of a reaction y → y′ that is not
perpendicular to w. If all such reactions do not point into the halfspace already swept by the
hyperplane – that is, all such reactions have product y′ outside of the open swept halfspace –
then the network is w-endotactic. Equivalently, the network is endotactic if no such reaction
makes an acute angle with w. Illustrations can be found in [10].
As for strongly endotactic networks, the sweeping hyperplane now stops when it first touches
the reactant of any reaction, whether or not it is perpendicular to w. Again we require that the
products of all such reactions lie outside of the open swept halfspace, and in addition at least
one of these reactions is not perpendicular to w. If this condition is satisfied for all vectors w
not orthogonal to the stoichiometric subspace, then the network is strongly endotactic. Both
endotactic and strongly endotactic networks capture the idea that extreme reactions should not
point outward.
Example 4.9. Here we follow the usual convention of depicting a network by its reaction graph
or reaction diagram and writing a complex as, for example, 2A+B rather than y = (2, 1). The
Lotka–Volterra reaction network, consisting of the three reactions
A→ 2A, A+B → 2B, B → 0,
is not endotactic. Reversing all three reactions yields the network
2A→ A, 2B → A+B, 0→ B, (1)
which is strongly endotactic, as can be verified from its reaction diagram:
Example 4.10. Every weakly reversible reaction network is endotactic [10]. However, even
a reversible reaction network may fail to be strongly endotactic, as in the following example of
14 M. Gopalkrishnan, E. Miller and A. Shiu
a pair of reversible reactions. For w = (0,−1), the ≤w-maximal reactant complexes are at the
bottom, but both of the corresponding reactions are perpendicular to w.
4.2 Reaction systems
Definition 4.11. The stoichiometric subspace H of a network is the span of its reaction vectors.
For a positive vector x0 ∈ RS>0, the invariant polyhedron of x0 is the polyhedron
P = (x0 +H) ∩ RS≥0 . (2)
This polyhedron is also referred to as the stoichiometric compatibility class in the chemical
reaction network theory literature [13].
Definition 4.12. Let (S, C,R) be a reaction network.
1. A tempering is a map κ : R → CmpctInt that assigns to each reaction a nonempty compact
positive interval.
2. A set D ⊆ RS>0 is a domain if its intersection with every invariant polyhedron P of (S, C,R)
is open in P.
A reaction system is a triple consisting of a reaction network, a tempering, and a domain.
Remark 4.13. Mass-action differential inclusions of reaction systems (Definition 5.16) genera-
lize the usual mass-action kinetics ODE systems; see Remark 5.17. One thinks of a domain as
a promise that concentrations of species remain within the domain. To explain the motivation
behind temperings, recall that a reaction network gives rise to a dynamical system by way of re-
action rates. For biochemical reaction networks, one is typically unable to measure precise values
for the rates. This occurs both because of incomplete information, and because of molecular and
environmental variability. One way to model this uncertainty is to allow reaction rates κ(r) to be
time-dependent, as long as they are uniformly bounded away from 0 and ∞. Craciun, Nazarov,
and Pantea called such systems κ-variable [10]. In a similar spirit, we have chosen to work with
differential inclusions, allowing κ(r) to take on every value from an appropriate interval.
Definition 4.14.
1. A confined reaction system is a reaction system whose domain is an invariant polyhedron
of the underlying reaction network.
2. An allotment is a map µ : S → OpnInt sending each species s ∈ S to an open positive
interval. The allotment hypercube of an allotment µ is the open hypercube �µ =
∏
s∈S
µ(s) ⊆
RS>0. A subconfined reaction system is specified by a reaction system and an allotment,
in which the domain of the reaction system is the intersection of the allotment hypercube
and an invariant polyhedron of the underlying reaction network.
Remark 4.15. Every confined system is viewed as a subconfined system in which the allotment
is understood to send every species s to (0,∞), so the allotment hypercube is the entire positive
orthant.
A Projection Argument for Differential Inclusions 15
Remark 4.16. The mathematical motivation prompting temperings and allotments is to ensure
that projections of trajectories “stay in the family”. Projections forget the exact concentrations
of eliminated species. Absorbing the effect of pre-projection dynamics into post-projection
dynamics requires a guarantee that the projected species concentrations never leave a certain
sufficiently large interval. Therefore, in post-projection dynamics, the reaction rates remain
within appropriately enlarged intervals. Allotments and tempering reaction rates provide the
extra flexibility for this construction.
This intuition is made precise in Section 5: interval-valued rates allow us to define an ap-
propriate domain category on which mass-action kinetics becomes functorial (Theorem 5.20).
As a consequence, projective classes of reaction systems (Definition 5.1) give rise to families of
differential inclusions that are vertexical.
Remark 4.17. Invariant polyhedra are forward-invariant sets with respect to the dynamics
arising from mass-action kinetics; see Remark 5.19. Therefore, a confined reaction system
allows us to restrict our attention to the dynamics on a specific invariant set.
5 Functoriality of mass-action kinetics
To every reaction system N we assign a differential inclusion M(N) (Definition 5.16). This
assignment M generalizes the usual mass-action kinetics ODE system in the chemical reaction
network theory literature [13, 17]. It is the goal of this section to analyze how M behaves
under projections of subconfined reaction systems. The main result (Theorem 5.23) states
that projective classes of reaction systems (Definition 5.1) give rise to vertexical families of
differential inclusions. In particular, chemical, reversible, weakly reversible, endotactic, and
strongly endotactic reaction systems all give rise to vertexical families (Corollary 5.24).
The first task, which occupies Section 5.1, is to make precise what is meant by projection,
and by maps between differential inclusions. It then becomes routine to verify two properties
that are key to the proof of Theorem 5.23, namely that for every pair of subconfined reaction
systems N1 and N2 such that N2 = p(N1) is a projection of N1, the assignment M induces
a map M(p) : M(N1)→M(N1) between the corresponding differential inclusions such that
1) the identity projection gets sent to the identity map on differential inclusions, and
2) the composition p = p2 ◦ p1 of two projection maps p1 : N1 → N2 and p2 : N2 → N3 gets
sent to the composition M(p2) ◦M(p1) of the corresponding maps between differential
inclusions; that is,
M(p) = M(p2) ◦M(p1).
These two properties of M are precisely the ones required by the definition of a functor in
category theory. Therefore, we find it economical to use this language (Theorem 5.20). Readers
unfamiliar with the language of category theory should read the word “functor” as shorthand
for the two properties. This is the extent of the category theory used in this paper.
5.1 Categorical definitions
Definition 5.1. Recall, from Definition 3.10, the projection πU : RS → RU for U ⊆ S, and
denote by π×2U = πU × πU : RS × RS → RU × RU the product of πU with itself.
1. For a reaction network (S, C,R), and a nonempty subset U ⊆ S of species, the reduced
reaction network is the reaction network πU (S, C,R) =
(
U, πU (C), π×2U (R)
)
.
16 M. Gopalkrishnan, E. Miller and A. Shiu
2. A property P of reaction networks is projective if for all finite nonempty sets S, reaction
networks (S, C,R), and nonempty subsets U ⊆ S, if (S, C,R) has property P then the
reduced reaction network πU (S, C,R) has property P .
3. The set of all reaction networks with a given projective property is a projective class.
Remark 5.2. The reduced reaction network πU (S, C,R) is obtained from the reaction network
(S, C,R) by deleting all species outside of U . This concept was defined by Anderson [2, § 3.2],
who required that any trivial reactions be removed from the reduced reaction set (πU ×πU )(R).
In contrast, we allow trivial reactions (Remark 4.2). Another related notion in the context of
reversible reactions is that of “reduced event-system” introduced in [1].
Example 5.3. For U = {A}, the reduced network
2A→ A← 0← 0
of the network (1) in Example 4.9 is obtained by removing species B. The reduced network is
strongly endotactic, as is the original network (1).
Next we see that the implication in Example 5.3 holds in general for strongly endotactic
networks. Such an implication was already completed for weakly reversible networks by Ander-
son [2, Lemma 3.4], and for endotactic networks by Pantea [20, Proposition 3.1].
Lemma 5.4. The classes of integer, chemical, reversible, strongly connected, weakly reversible,
endotactic, or strongly endotactic reaction networks are projective. Further, if P1 and P2 are
projective properties, then so are the conjunction P1 ∧ P2 and disjunction P1 ∨ P2.
Proof. Projectivity holds for integer and chemical networks because projection preserves inte-
grality and nonnegativity of points in RS . Projectivity holds for reversible, strongly connected,
and weakly reversible networks because these conditions depend only on the reaction graph, on
whose vertices and edges projection is surjective.
Next, consider an endotactic network with species set S and the reduced network arising from
a nonempty subset U ⊆ S. Take any vector w ∈ RU . For any reduced reaction πU (r), where r
is a reaction in the original network,〈
w, flux(πU (r))
〉
=
〈
(w, 0), flux(r)
〉
. (3)
Thus, the w-essential reactions of the reduced network are the projections under π×2U of the
(w, 0)-essential reactions of the original network, where we write (w, 0) ∈ RU ×RS\U . Similarly,
the w-support of the reduced network is the projection under πU of the (w, 0)-support of the
original network. So, if πU (r) is a w-essential reaction of the reduced network with reactant in
the w-support, then the original reaction r is a (w, 0)-essential reaction of the original network
with reactant in the (w, 0)-support. By (3) and the definition of endotactic,
〈
w, flux(πU (r))
〉
=〈
(w, 0), flux(r)
〉
< 0. Hence the reduced network is endotactic.
Next, let H denote the stoichiometric subspace of a strongly endotactic network, so πU (H) is
the stoichiometric subspace of the reduced network. Take a vector w ∈ RU that is not orthogonal
to πU (H). We need only show that there exists a reaction πU (y) → πU (y′), where y → y′ is
a reaction in the original network, such that πU (y) >w πU (y′) and πU (y) is ≤w-maximal among
all reactant vectors in the reduced network. Again consider (w, 0) ∈ RU × RS\U . As w is not
orthogonal to πU (H), it follows that (w, 0) is not orthogonal to H, and the preorder ≤w on the
reduced reactant complexes is the projection under πU of the preorder ≤(w,0) on the original
reactant complexes. Since the original network is strongly endotactic, there is a reaction y → y′
in the original network with y >(w,0) y
′ such that y is ≤(w,0)-maximal among all reactant vectors.
This reaction achieves our requirements.
The claim about conjunctions and disjunctions follows formally by Definition 5.1.2. �
A Projection Argument for Differential Inclusions 17
Notation 5.5. Let I, J ⊆ R≥0 be two intervals, and S a finite nonempty set.
1. Define I · J = {i · j | i ∈ I, j ∈ J} ⊆ R>0 and
⊙
s∈S Is pointwise.
2. For n ∈ Z≥1 define In recursively as I · In−1 with I1 = I.
3. I × J and
∏
s∈S Is denote Cartesian products of intervals, as usual.
Definition 5.6. Let S be a finite nonempty set, and consider a function µ : S → OpnInt to
the set of open positive intervals. A nonempty subset U ⊆ S is µ-projectable if 0 < inf µ(s) and
supµ(s) < ∞ for all s ∈ S \ U ; that is, the left and right endpoints of the intervals µ(s) are
bounded away from 0 and ∞ for those s outside of U .
Remark 5.7. The condition of Definition 5.6 is on the complement S \ U because those are
the species removed in projecting to U , and so it is those species that must be bounded away
from 0 and ∞. The set S itself is trivially µ-projectable, for all µ : S → OpnInt .
We show that subconfined reaction systems form a category whose morphisms are projections,
where the projection pU from one object N to another corresponds to substituting intervals from
the allotment of N in place of a set S \ U of forgotten species.
Definition 5.8. The category N of subconfined reaction systems with projections is given by
the following data.
1. Objects: each is a subconfined reaction system N , specified by a reaction network (S, C,R)
along with a tempering κ : R → CmpctInt , an allotment µ : S → OpnInt , and an invariant
polyhedron P = (x0 +H) ∩ RS≥0.
2. Morphisms: pU : N → N ′ if
• the network of N ′ is (S′, C′,R′) = πU (S, C,R) for a µ-projectable subset U ⊆ S;
• the tempering of N ′ is κ′ : πU (r) 7→ κ(r) ·
⊙
s∈S\U
µ(s)reactant(r)s , where the exponent
on µ(s) is the component indexed by s in the vector reactant(r);
• the allotment of N ′ is µ′ = µ|U , gotten by restricting the allotment of N to U ; and
• the invariant polyhedron of N ′ is P ′ = (πU (x0) + πU (H)) ∩ RU≥0.
Remark 5.9. In Definition 5.8.2, πU (H) is the stoichiometric subspace of N ′ because it
is spanned by the vectors flux(πU (r)) = πU (flux(r)), where r is a reaction of N . Thus,
(πU (x0) + πU (H)) ∩ RU≥0 is an invariant polyhedron of N ′.
Remark 5.10. Composition in N is well-defined because first projecting to U ⊆ S and then
projecting to V ⊆ U is the same as projecting directly to V .
Mass-action kinetics assigns to each subconfined reaction system a differential inclusion on
its domain. Theorem 5.20 states that this assignment makes mass-action kinetics a functor,
with domain category N and codomain category as follows.
Definition 5.11. The category DI of differential inclusions is given by the following data.
1. Objects: each is a choice of manifold with corners and a differential inclusion on it.
2. Morphisms: a morphism from X ⊆ TM to Y ⊆ TN is a continuous map k : M → N such
that for each trajectory f : I → M of X, there is a trajectory g : J → N of Y and an
order-preserving continuous map α : I → J satisfying
k ◦ f = g ◦ α. (4)
18 M. Gopalkrishnan, E. Miller and A. Shiu
Lemma 5.12. Composition of continuous maps induces a well-defined composition on DI.
Specifically, assume Xj ⊆ TMj for j = 1, 2, 3 are differential inclusions, with morphisms k12 :
M1 → M2 and k23 : M2 → M3 in DI. If f1 : I1 → M1 is a trajectory of X1, then there is
a trajectory f3 : I3 →M3 of X3 and an order-preserving continuous map α13 : I1 → I3 such that
the composite continuous map k13 = k23 ◦ k12 satisfies k13 ◦ f1 = f3 ◦ α13.
Proof. Given f1, since k12 is a morphism in DI, there is a trajectory f2 : I2 → M2 of X2
and a continuous order-preserving map α12 : I1 → I2 such that k12 ◦ f1 = f2 ◦ α12. For the
desired trajectory f3 : I3 → M3 of X3 use the one afforded by virtue of k23 being a morphism
in DI, given f2, which comes with a continuous order-preserving map α23 : I2 → I3 such that
k23 ◦ f2 = f3 ◦ α23. Set α13 = α23 ◦ α12. Then
k13 ◦ f1 = k23 ◦ k12 ◦ f1 = k23 ◦ f2 ◦ α12 = f3 ◦ α23 ◦ α12 = f3 ◦ α13,
as desired. �
Remark 5.13. Compare the notion of morphism in DI (Definition 5.11) with that of vertexical
family (Definition 3.13). Equation (4) also occurs in Definition 3.13, with k being a particular
type of continuous map πU . However, Definition 5.11 asks for a global map k, whereas the maps
in Definition 3.13 are required only locally, on blocks of faces.
Remark 5.14. One motivation for defining the category of differential inclusions this way
comes from the dynamical systems concept of topological equivalence [18], which identifies two
phase portraits as qualitatively the same, even if the details of the dynamics may differ. The
isomorphisms in our category DI correspond exactly to topological equivalence.
For this reason, morphisms between differential inclusions may also be called topological mor-
phisms. Intuitively, if a topological morphism is a monomorphism, then its target differential
inclusion qualitatively simulates the domain differential inclusion. Maps that are not monomor-
phisms can of course result in the loss of information, in general. The categorical message of
Theorem 3.15 is that it is sometimes possible to piece together many “lossy” maps on the same
domain to regain substantial information about the domain dynamics.
Another concept from dynamical systems, topological conjugacy [18], is a stronger notion
than topological equivalence that disallows time reparameterization. This motivates looking at
a subcategory DI1 of DI in which the order-preserving map α in Definition 5.11 is required to
be the identity map; the definition follows.
Definition 5.15. The category DI1 of differential inclusions with topological semiconjugacy
morphisms is the subcategory of DI with the following data.
1. Objects: the same objects as in DI.
2. Morphisms: a morphism from X ⊆ TM to Y ⊆ TN is a continuous map k : M → N such
that k ◦ f is a trajectory of Y whenever f : I →M is a trajectory of X.
The proof of Lemma 5.12 makes it plain that any composition in DI of morphisms in DI1
is a morphism in DI1, because every reparameterization map αij in that proof can be taken to
be the identity map on I1.
The next definition uses the multinomial notation xy := xy11 x
y2
2 · · ·x
ym
m for x, y ∈ Rm.
Definition 5.16. The mass-action differential inclusion of a reaction system, specified by a re-
action network (S, C,R) with tempering κ and domain D, is the differential inclusion on RS>0
whose fiber over each point x ∈ D is{∑
r∈R
krx
reactant(r) flux(r)
∣∣ kr ∈ κ(r) for all r ∈ R
}
⊆ RS = TxRS>0 (5)
A Projection Argument for Differential Inclusions 19
and whose fiber over all points x ∈ RS>0 \D is empty. The mass-action functor M : N → DI1
from the category N of subconfined reaction systems to the category DI1 is defined on
1) objects N ∈ N by letting M(N) be the mass-action differential inclusion of N , and on
2) morphisms pU : N → N ′ by letting M(pU ) be the projection πU : �µ → �µ′ .
Remark 5.17. The usual mass-action kinetics ODE systems are the special cases in which the
reaction network is chemical, the tempering κ assigns not an interval of positive length but
a point – the reaction rate constant – to each reaction, and the allotment hypercube is the
entire positive orthant: �µ = RS>0. The more general setting where stoichiometric coefficients
are allowed to be arbitrary (positive or negative) real numbers has been studied in biochemical
systems theory under the names “power-law” and “generalized mass-action”. This research area
goes back to early work of Savageau in the 1960s [21].
Remark 5.18. In the next subsection, we use a diffeomorphism `S : RS>0 → (0, 1)S to push
forward mass-action differential inclusions to be defined on hypercubes rather than orthants
(Definition 5.22). Therefore, for mass-action differential inclusions, the closure M of the allot-
ment hypercube M = �µ is taken in the compactification [0,∞]S when we are interested in the
properties of being persistent, permanent, or repelled.
Remark 5.19. In a mass-action differential inclusion, only points in a specified domain have
nonempty fiber. Imagine that we had instead defined a larger differential inclusion, so that
all fibers in the positive orthant are nonempty and take the form given by mass-action (5).
Then, recalling that the stoichiometric subspace of a network is spanned by the reaction vectors
flux(r), it follows from (5) that every trajectory of this larger differential inclusion would be
confined to some invariant polyhedron (2). (This also uses the fact that trajectories remain
nonnegative [6, § 2].) That is, the invariant polyhedra are forward-invariant with respect to
the larger differential inclusion. Therefore it is in fact appropriate to restrict the differential
inclusion to a given invariant polyhedron (as we did in Definition 5.16) and then to analyze
properties such as persistence of the restriction.
5.2 Functorial results and consequences
Theorem 5.20. The mass-action functor M is a functor from the category N of subconfined
reaction systems with projection morphisms to the category DI1 of differential inclusions with
topological semiconjugacy morphisms.
Proof. The content of the statement is twofold: first, that M(pU ) = πU in Definition 5.16.2
indeed defines a morphism M(N)→M(N ′), and second, that M preserves identity morphisms
as well as compositions. The second is straightforward (projections are sent to projections).
For the first, it suffices to observe that for any nonempty U ⊆ S, the projection πU ◦ f of
a trajectory f of M(N) is a trajectory of M(pU (N)) by definition of pU . This observation uses
the fact that the image of f is in the invariant polyhedron P of N , so the image of πU ◦ f is in
πU (P) which is contained in the invariant polyhedron of pU (N). �
Remark 5.21. When we fix an allotment, we do not, and can not, insist that trajectories stay
within the allotment for all time. Our assertion of functoriality is to the effect that for the
period of time that a trajectory does stay within the allotment, its projection factors through
a smaller system. The definition of vertexical family (Definition 3.13) is weak enough to tolerate
such a weak guarantee, and yet strong enough to be able to prove theorems on persistence
and permanence. In fact, the definition of vertexical requires even less: the projection of
a trajectory is required to factor through a smaller system only for the period of time that
it lies in a corresponding block.
20 M. Gopalkrishnan, E. Miller and A. Shiu
Vertexical families are defined in terms of differential inclusions on unit hypercubes (0, 1)S .
In contrast, the mass-action functor produces differential inclusions on positive orthants RS>0.
To translate back and forth, our next definition fixes a smooth, order-preserving diffeomorphism
R>0 → (0, 1). The actual choice is irrelevant for our purposes, but if it helps, the reader may
consider the function x 7→ x/(1 + x).
Definition 5.22. Fix a smooth, order-preserving diffeomorphism ` : R>0 → (0, 1). For every
nonempty finite set S, let `S : RS>0 → (0, 1)S , with derivative d`S : TRS>0 → T (0, 1)S .
1. The pushforward of a differential inclusion X on RS>0 under ` is the differential inclusion
d`S(X) on (0, 1)S .
2. For a subconfined reaction system N defined on a species set S with allotment µ, the
differential inclusion M`(N) is the pushforward of the mass-action differential inclu-
sion M(N), considered as a differential inclusion on the image `S(�µ) ⊆ (0, 1)S of the
allotment hypercube �µ under `.
The following is the main result of this section.
Theorem 5.23. Fix a projective property P of reaction networks. The class FP of all confined
reaction systems whose underlying reaction networks have property P yields a vertexical family
M`(FP ) =
{
M`(N) | N ∈ FP
}
of differential inclusions on open hypercubes.
Proof. By definition, M`(FP ) is a family of differential inclusions on open hypercubes. Hence
we need only prove that M`(FP ) is vertexical. Consider a confined reaction system N ∈ FP ,
specified by a reaction network (S, C,R) with tempering κ and invariant polyhedron P. Fix
a proper nonempty subset U ⊆ S and a vertex x ∈ {0, 1}S of the hypercube (0, 1)S . Denote by
F = FS\U (x) the corresponding face of the hypercube.
Fix 0 < ε < 1
2 , and define µ′ = µ′ε,U : S → OpnInt by
µ′(s) =
{
(0,∞) if s ∈ U,
`−1(ε, 1− ε) if s ∈ S \ U.
Denote by N ′ the subconfined reaction system N ′ that agrees with N except that the allotment
of N ′ is µ′. The underlying reaction network of N ′ still has property P , because N and N ′ have
the same underlying reaction network.
While N ′ itself no longer has the entire positive orthant RS>0 as its allotment hypercube,
the set U is µ′-projectable (Definition 5.6), and the reduced network pU (N ′) has allotment
hypercube RU>0. Since P is projective, pU (N ′) therefore lies in FP . Consequently, by definition
of vertexical family (Definition 3.13), it is enough to show that for any trajectory f : I → Fε
of M`(N) with image in the block Fε, the projection πU ◦f = g is a trajectory of the mass-action
differential inclusion M`(pU (N ′)).
The trajectory f is also a trajectory of M`(N ′), since Fε ⊆ `S(�µ′) by construction of µ′.
The result is now deduced easily from functoriality of mass-action kinetics (Theorem 5.20): the
morphism πU in the category DI1 from M(N ′) to M(pU (N ′)) yields the pushforward morphism
M`(N ′) → M`(pU (N ′)) in DI1, so the proof is complete by definition of morphisms in the
category DI1 (Definition 5.15.2). �
Recall that in propositional logic, a monotone (or monotonic) formula is one formed by the
application of and and or operations only, without the use of not operations.
Corollary 5.24. Each of the classes of (monotone combinations of) integer, chemical, reversible,
strongly connected, weakly reversible, endotactic, or strongly endotactic confined reaction systems
generates a vertexical family of differential inclusions.
Proof. Immediate from Theorem 5.23 and Lemma 5.4. �
A Projection Argument for Differential Inclusions 21
Remark 5.25. The category N of confined reaction systems with projections suffices for our
purposes, but it would be more natural to allow arbitrary reaction systems with an associated
domain set D ⊆ RS>0 that is not necessarily derived from a Cartesian product of intervals. In
addition, it is tempting to add to the category more morphisms, such as those corresponding
to translation of the reaction diagram within RS , or scaling, rotation, arbitrary linear maps,
graph homomorphisms, inversion z = 1/x, and so on. It is easy to verify that translation acts
as a time-reparametrization. Hence, even allowing translations, mass-action kinetics remains
a functor to DI. This leads to the following question, which we leave open.
Question 5.26. What is the richest domain category for which mass-action kinetics remains
a functor to the category DI of differential inclusions?
This question is important because a richer domain category would imply more ways of reduc-
ing the behavior of a network’s mass-action kinetics to the behaviors of related networks. This
could allow us to “program” (and analyze) instances of reaction dynamics in high dimensions
as appropriate combinations of simpler reaction dynamics.
Remark 5.27. Consider a vertexical family of mass-action differential inclusions for which the
one-dimensional differential inclusions in the family are known to be permanent. For instance,
the differential inclusions arising from weakly reversible, endotactic, or strongly endotactic net-
works have this attribute. It is tempting to attempt to argue that such a family is permanent by
the following induction: given a trajectory, all of its one-dimensional projections (which are also
in the family, due to the functoriality of mass-action kinetics and projectivity of the relevant
properties) are permanent, and hence the trajectory itself eventually remains in a compact set.
However, this does not work because of uniformity issues. It is true that for a given trajectory,
there exists a compact set that it enters eventually. However, what we need is one compact set
so that every trajectory eventually enters this set, and our inductive argument does not prove
this. A successful argument about permanence would require additional structure; for example,
see Remark 6.7.
6 Implications for persistence of mass-action systems
One of the long-standing open problems of chemical reaction network theory is the global at-
tractor conjecture concerning so-called “complex-balanced systems”. Complex-balanced sys-
tems form a well-studied subclass of weakly reversible mass-action ODE systems that contain
all so-called “detailed-balanced” systems and weakly reversible “deficiency zero” systems. Many
properties about complex-balanced systems (as well as detailed-balanced systems and deficiency
zero systems) were elucidated by Feinberg, Horn, and Jackson in the 1970s, and we provide only
an overview here. (See any of the references [9, 12, 13, 17] for a definition of complex-balanced
systems.)
For complex-balanced systems, it is known that there is a unique steady state within the
interior of each invariant polyhedron P. This steady state, called the Birch point in [9] due
to the connection to Birch’s theorem in algebraic statistics, has a strict Lyapunov function.
Therefore local asymptotic stability relative to P is guaranteed [13, 17] (see Remark 6.7). An
open question is whether all trajectories with an initial condition in the interior of P converge
to the unique Birch point of P. The assertion that the answer is “yes” is the content of the
following conjecture, which was stated first by Horn in 1974 [16] and given the name “Global
Attractor Conjecture” by Craciun et al. [9].
Conjecture 6.1 (global attractor conjecture). For any complex-balanced mass-action system
and strictly positive initial condition x0, the Birch point in P := (x0 + H) ∩ RS≥0 (see Defini-
tion 4.11) is a global attractor of the relative interior of the invariant polyhedron int(P).
22 M. Gopalkrishnan, E. Miller and A. Shiu
In 1987, Feinberg [11] conjectured the following.
Conjecture 6.2 (Feinberg’s persistence conjecture). For every confined, weakly reversible mass-
action ODE system N , the differential inclusion M`(N) is persistent.
Feinberg observed that the global attractor conjecture would follow from Conjecture 6.2, that
is, persistence of weakly reversible reaction networks.
Our functoriality results reduce persistence to bounding the dynamics away from vertices of
the hypercube – so it suffices to ensure that all species remain bounded away from 0 and ∞ in
the positive orthant – at the price of considering tempered reaction systems. More precisely, we
state the following two corollaries.
Corollary 6.3. Let P be a set of one or more of the following properties: integer, chemical,
reversible, strongly connected, weakly reversible, endotactic, and strongly endotactic. Let F be the
class of all confined reaction systems whose underlying reaction networks satisfy every property
in P. If the mass-action differential inclusions of all reaction systems in F are repelled by
vertices after pushing forward to open hypercubes by a smooth order-preserving diffeomorphism,
then they are repelled by the entire boundary.
Proof. Immediate from Corollaries 3.17 and 5.24. �
The next result states that another approach to persistence is by proving that trajectories
are bounded and that the origin is repelling; additionally, a more uniform such bound yields
a permanence-like result.
Corollary 6.4. Let P be a set of one or more of the following properties: integer, chemical,
reversible, strongly connected, weakly reversible, endotactic, and strongly endotactic. Let F
be the class of all confined reaction systems whose underlying reaction networks satisfy every
property in P. If the mass-action differential inclusions of all reaction systems in F are repelled
by the origin and every trajectory of such a differential inclusion is bounded, then
1) these differential inclusions are persistent; and
2) if X is such a differential inclusion on RS>0, and K ⊆ RS>0 is a compact set for which there
exists A ∈ R>0 such that every trajectory of X that starts in K remains bounded above
by A in each coordinate for all time, then for some compact set K+ ⊆ RS>0, no trajectory
of X that begins in K leaves K+.
Proof. A differential inclusion on RS>0 is repelled by the origin if and only if after pushing
forward to open hypercubes the resulting differential inclusion is repelled by the origin: the
open sets in the definition of repelled move between hypercubes and positive orthants via the
diffeomorphism. Additionally, persistence of a mass-action differential inclusion is viewed with
respect to the compactification [0,∞]S , so persistence is equivalent to persistence of the push-
forward with respect to [0, 1]S . Finally, compact sets K and bounds A also move between
hypercubes and positive orthants via the diffeomorphism. Thus, the conclusion follows from
Corollaries 5.24, 3.18, and 3.21 (for which the repelled set is taken to be the origin – see also
the description after Corollary 3.21). �
Recently, Craciun, Nazarov, and Pantea [10] generalized Feinberg’s persistence conjecture
(Conjecture 6.2) in the following three ways: the weakly reversible hypothesis is weakened to
endotactic, fixed reaction rate constants are allowed to vary within bounded intervals (i.e.,
a tempering), and the conclusion of persistence is strengthened to permanence [10, § 4].
Conjecture 6.5 (extended permanence conjecture). For every confined endotactic reaction
system N , the differential inclusion M`(N) is permanent.
A Projection Argument for Differential Inclusions 23
Remark 6.6. Endotactic networks constitute a projective class (Corollary 5.24), and, in our
view, it is this property that allowed Craciun, Nazarov, and Pantea to make their projection-
type arguments [10, 20]. Similarly, the property of having only one linkage class is projective:
a network with only one linkage class maintains this property after reduction. This type of
argument was used in Anderson’s proof of the global attractor conjecture for networks possessing
only one linkage class [2]. Indeed, our work was motivated in part by the works both of Anderson
and of Craciun, Nazarov, and Pantea.
Remark 6.7. Horn and Jackson [17] established that any complex-balanced mass-action ODE
system N on a set S of species admits the strict Lyapunov function
gα(x) =
∑
i∈S
xi
(
log
xi
αi
− 1
)
,
where α ∈ RS>0 is a given complex-balanced steady state of N . Consequently, the differential
inclusion M`(N) is repelled by the vertex 0, and its trajectories are bounded away from faces
not incident to 0. The proof of this assertion, which is due in part to Anderson and Craciun
et al. [3, 9], proceeds by showing that the Lyapunov function gα has a local maximum at the
vertex 0 as well as bounded level sets that do not allow trajectories to escape to infinity. If
the class of complex-balanced systems were projective, then our arguments would have proved
the global attractor conjecture. However, this is not the case: projections of complex-balanced
systems need not be complex-balanced. Therefore, Theorem 5.23 does not apply: we can not
prove that complex-balanced systems form a vertexical family. In fact, it can be shown that this
family is not vertexical. On the other hand, weakly reversible or endotactic networks do define
a vertexical family; recall Remark 6.6.
The motivation for our work was to make progress on Conjectures 6.1, 6.2, and 6.5. The
next two theorems state what we have accomplished in this direction. First, we show that
an extension of Feinberg’s persistence conjecture in dimension n implies the global attractor
conjecture in dimension n+ 1, under an additional assumption that the origin is repelling.
Theorem 6.8. Let n be a positive integer. If for every confined, weakly reversible reaction
system N with no more than n species, both
1) M`(N) is persistent, and
2) M`(N) is repelled by the origin,
then the global attractor conjecture (Conjecture 6.1) holds for complex-balanced mass-action sys-
tems with n+ 1 or fewer species.
Proof. Let X denote the vertexical family of all differential inclusions that arise from endotactic
networks. Let N denote a confined, complex-balanced mass-action system with |S| ≤ n + 1.
As mentioned after Conjecture 6.2, it suffices to prove that N is persistent. By Remark 3.23
in the context of the empty repulsing index set, to prove that N is persistent, it suffices to
show that (i) M`(N) itself is persistent relative to all faces of [0, 1]S that do not meet the
origin and repelled by the origin of the hypercube, and (ii) the lower-dimensional set XU for
each proper nonempty subset U ⊆ S is persistent relative to all faces of [0, 1]U that do not
meet the origin and repelled by the origin of the hypercube [0, 1]U . Claim (i) follows from the
Lyapunov function, as explained in Remark 6.7: persistence relative to all faces that do not meet
the origin is equivalent to having bounded trajectories. As for claim (ii), endotactic systems
having lower dimension than X are persistent by hypothesis, and repelled by the origin also
by hypothesis. �
24 M. Gopalkrishnan, E. Miller and A. Shiu
The next theorem reduces the global attractor conjecture and Feinberg’s persistence conjec-
ture to the following assertion that for mass-action differential inclusions arising from weakly
reversible networks, trajectories are bounded and repelled by the origin.
Conjecture 6.9. For every confined, weakly reversible reaction system N , the differential in-
clusion M(N) is repelled by the origin, and every trajectory of M(N) is bounded.
Theorem 6.10. Conjecture 6.9 implies the global attractor conjecture (Conjecture 6.1).
Proof. Consider a confined weakly reversible reaction systemN . By hypothesis, the differential
inclusion M(N) is repelled by the origin, and every trajectory of M(N) is bounded, so M(N) is
persistent by Corollary 6.4.1. Thus, all weakly reversible systems are persistent, which implies
the global attractor conjecture: see the discussion after Conjecture 6.2. �
Conjectures 6.1, 6.2, 6.5, and 6.9 all remain open; for an overview of recent progress on these
problems, we refer the reader to the work of Anderson [3, § 1.1]. However, using the results
presented in the current paper, we prove the following in a subsequent paper [15], which extends
recent results of Anderson [2].
Theorem 6.11. For every confined strongly endotactic reaction system N , the differential in-
clusion M`(N) is permanent.
Proof. To be proved in a subsequent paper [15]. �
The key step contributed by the results in the current paper is Corollary 6.4 in the case of
strongly endotactic networks. The approach in [15] shows that for the mass-action differential
inclusions of strongly endotactic networks, outside a compact set the function gα(x) in Re-
mark 6.7 continues to behave like a Lyapunov function. Theorem 6.11 is established by an
argument along the lines suggested in Remark 6.7.
Acknowledgements
MG was supported by a Ramanujan fellowship from the Department of Science and Technology,
India, and, during a semester-long stay at Duke University, by the Duke MathBio RTG grant
NSF DMS-0943760. EM had support from NSF grant DMS-1001437. AS was supported by an
NSF postdoctoral fellowship DMS-1004380. The authors thank David F. Anderson, Gheorghe
Craciun, and Casian Pantea for helpful discussions, and Duke University where many of the
conversations occurred. The authors also thank the two referees, whose perceptive and insightful
comments improved this work.
References
[1] Adleman L., Gopalkrishnan M., Huang M.D., Moisset P., Reishus D., On the mathematics of the law of
mass action, arXiv:0810.1108.
[2] Anderson D.F., A proof of the global attractor conjecture in the single linkage class case, SIAM J. Appl.
Math. 71 (2011), 1487–1508, arXiv:1101.0761.
[3] Anderson D.F., Global asymptotic stability for a class of nonlinear chemical equations, SIAM J. Appl. Math.
68 (2008), 1464–1476, arXiv:0708.0319.
[4] Anderson D.F., Shiu A., The dynamics of weakly reversible population processes near facets, SIAM J. Appl.
Math. 70 (2010), 1840–1858, arXiv:0903.0901.
[5] Angeli D., De Leenheer P., Sontag E., A Petri net approach to persistence analysis in chemical reac-
tion networks, in Biology and Control Theory: Current Challenges, Lect. Notes Contr. Inf., Vol. 357,
Editors I. Queinnec, S. Tarbouriech, G. Garcia, S.I. Niculescu, Springer-Verlag, Berlin, 2007, 181–216,
q-bio/0608019.
http://arxiv.org/abs/0810.1108
http://dx.doi.org/10.1137/11082631X
http://dx.doi.org/10.1137/11082631X
http://arxiv.org/abs/1101.0761
http://dx.doi.org/10.1137/070698282
http://arxiv.org/abs/0708.0319
http://dx.doi.org/10.1137/090764098
http://dx.doi.org/10.1137/090764098
http://arxiv.org/abs/0903.0901
http://dx.doi.org/10.1007/978-3-540-71988-5_9
http://arxiv.org/abs/q-bio/0608019
A Projection Argument for Differential Inclusions 25
[6] Angeli D., De Leenheer P., Sontag E.D., Persistence results for chemical reaction networks with time-
dependent kinetics and no global conservation laws, SIAM J. Appl. Math. 71 (2011), 128–146.
[7] Aubin J.P., Cellina A., Differential inclusions. Set-valued maps and viability theory, Grundlehren der Ma-
thematischen Wissenschaften, Vol. 264, Springer-Verlag, Berlin, 1984.
[8] Banaji M., Mierczyński J., Global convergence in systems of differential equations arising from chemical
reaction networks, J. Differential Equations 254 (2013), 1359–1374, arXiv:1205.1716.
[9] Craciun G., Dickenstein A., Shiu A., Sturmfels B., Toric dynamical systems, J. Symbolic Comput. 44 (2009),
1551–1565, arXiv:0708.3431.
[10] Craciun G., Nazarov F., Pantea C., Persistence and permanence of mass-action and power-law dynamical
systems, SIAM J. Appl. Math. 73 (2013), 305–329, arXiv:1010.3050.
[11] Feinberg M., Chemical reaction network structure and the stability of complex isothermal reactors: I. The
deficiency zero and deficiency one theorems, Chem. Eng. Sci. 42 (1987), 2229–2268.
[12] Feinberg M., Complex balancing in general kinetic systems, Arch. Rational Mech. Anal. 49 (1972), 187–194.
[13] Feinberg M., Lectures on chemical reaction networks, unpublished lecture notes, 1979, available at
http://www.che.eng.ohio-state.edu/~FEINBERG/LecturesOnReactionNetworks/.
[14] Freedman H.I., Moson P., Persistence definitions and their connections, Proc. Amer. Math. Soc. 109 (1990),
1025–1033.
[15] Gopalkrishnan M., Miller E., Shiu A., A geometric approach to the global attractor conjecture, in prepara-
tion.
[16] Horn F., The dynamics of open reaction systems, in Mathematical Aspects of Chemical and Biochemical
Problems and Quantum Chemistry (Proc. SIAM-AMS Sympos. Appl. Math., New York, 1974), SIAM-AMS
Proceedings, Vol. 8, Amer. Math. Soc., Providence, R.I., 1974, 125–137.
[17] Horn F., Jackson R., General mass action kinetics, Arch. Rational Mech. Anal. 47 (1972), 81–116.
[18] Irwin M.C., Smooth dynamical systems, Pure and Applied Mathematics, Vol. 94, Academic Press Inc., New
York, 1980.
[19] Lee J.M., Introduction to smooth manifolds, Graduate Texts in Mathematics, Vol. 218, Springer-Verlag,
New York, 2003.
[20] Pantea C., On the persistence and global stability of mass-action systems, SIAM J. Math. Anal. 44 (2012),
1636–1673, arXiv:1103.0603.
[21] Savageau M.A., Biochemical systems analysis: I. Some mathematical properties of the rate law for the
component enzymatic reactions, J. Theor. Biol. 25 (1969), 365–369.
[22] Siegel D., Johnston M.D., A stratum approach to global stability of complex balanced systems, Dyn. Syst.
26 (2011), 125–146, arXiv:1008.1622.
http://dx.doi.org/10.1137/090779401
http://dx.doi.org/10.1007/978-3-642-69512-4
http://dx.doi.org/10.1007/978-3-642-69512-4
http://dx.doi.org/10.1016/j.jde.2012.10.018
http://arxiv.org/abs/1205.1716
http://dx.doi.org/10.1016/j.jsc.2008.08.006
http://arxiv.org/abs/0708.3431
http://dx.doi.org/10.1137/100812355
http://arxiv.org/abs/1010.3050
http://dx.doi.org/10.1016/0009-2509(87)80099-4
http://dx.doi.org/10.1007/BF00255665
http://www.che.eng.ohio-state.edu/~FEINBERG/LecturesOnReactionNetworks/
http://dx.doi.org/10.2307/2048133
http://dx.doi.org/10.1007/BF00251225
http://dx.doi.org/10.1137/110840509
http://arxiv.org/abs/1103.0603
http://dx.doi.org/10.1016/S0022-5193(69)80026-3
http://dx.doi.org/10.1080/14689367.2010.545812
http://arxiv.org/abs/1008.1622
1 Introduction
2 Dynamical properties of differential inclusions
3 Vertexical families of differential inclusions
3.1 Definitions concerning hypercubes
3.2 Definition of vertexical family and main result
3.3 Consequences, special cases, and clarifications
4 Reaction network theory
4.1 Reaction networks
4.2 Reaction systems
5 Functoriality of mass-action kinetics
5.1 Categorical definitions
5.2 Functorial results and consequences
6 Implications for persistence of mass-action systems
References
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