COMPUTING UPPER CLUSTER ALGEBRAS

arXiv:1307.0579v1 [] 2 Jul 2013

JACOB MATHERNE AND GREG MULLER
Abstract. This paper develops techniques for producing presentations of upper cluster algebras. These techniques are suited to computer implementation, and will always
succeed when the upper cluster algebra is totally coprime and finitely generated. We
include several examples of presentations produced by these methods.

1. Introduction
1.1. Cluster algebras. Many notable varieties have a cluster structure, in the following
sense. They are equipped with distinguished regular functions called cluster variables,
which are grouped into clusters, each of which form a transcendence basis for the field
of rational functions. Each cluster is endowed with mutation rules for moving to other
clusters, and in this way, every cluster can be reconstructed from any other cluster. Excamples of this include semisimple Lie groups [BFZ05], Grassmannians [Sco06], partial
flag varieties [GLS08], moduli of local systems [FG06], and others.
The obvious algebra to consider in this situation is the cluster algebra A, the ring
generated by the cluster variables.1 However, from a geometric perspective, the more
natural algebra to consider is the upper cluster algebra U, defined by intersecting certain
Laurent rings (see Remark 3.2.2 for the explicit geometric interpretation).
The Laurent phenomenon guarantees that A ⊆ U. This can be strengthened to an
equality A = U in many of the geometric examples and simpler classes of cluster algebras
(such as acyclic and locally acyclic cluster algebras [BFZ05, Mul13]). In most cases where
A = U is known, the structures and properties of the algebra A = U are fairly wellunderstood; for example, [BFZ05, Corollary 1.21] presents an acyclic cluster algebra as a
finitely generated complete intersection.
However, there are examples where A ( U; the standard counterexample is the Markov
cluster algebra (see Remark 6.2.1 for details). In these examples, both A and U are more
difficult to work with directly, and either can exhibit pathologies. For example, the Markov
cluster algebra is non-Noetherian [Mul13], and Speyer recently produced a non-Noetherian
upper cluster algebra [Spe13].
1.2. Presenting upper cluster algebras. Nevertheless, because of its geometric nature,
the authors expect that an upper cluster algebra U is generally better behaved than its
cluster algebra A. This is supported in the few concretely understood examples where
A ( U; however, the scarcity of examples makes investigating U difficult.
2010 Mathematics Subject Classification. Primary 13F60, Secondary 14Q99.
Keywords: Cluster algebras, upper cluster algebras, presentations of algebras, computational algebra.
The second author was supported by the VIGRE program at LSU, National Science Foundation grant
DMS-0739382.
1Technically, the construction of the cluster algebra used in this note includes the inverses to a finite set.
1

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JACOB MATHERNE AND GREG MULLER

The goal of this note is to alleviate this problem by developing techniques to produce
explicit presentations of U. The main tool is the following lemma, which gives several
computationally distinct criteria for when a Noetherian ring S is equal to U.
Lemma 1.2.1. If A is a cluster algebra with deep ideal D, and S is a Noetherian ring
such that A ⊆ S ⊆ U, then the following are equivalent.
(1)
(2)
(3)
(4)
(5)

S = U.
S is normal and codim(SD) ≥ 2.
S is S2 and codim(SD) ≥ 2.
Ext1S (S/SD, S) = 0.
Sf = (Sf : (SD)∞ ), where f := x1 x2 ...xm for some cluster x = {x1 , ..., xn }.

If Sf 6= (Sf : (SD)∞ ), then (Sf : (SD)∞ )f −1 contains elements of U not in S.
Here, the deep ideal D is the ideal in A defined by the products of the mutable cluster
variables (see Section 3.2).
This lemma is constructive, in that a negative answer to condition (5) explicitly provides
new elements of U. Even without a clever guess for a generating set of U, iteratively
checking this criterion and adding new elements can produce a presentation for U. Speyer’s
example demonstrates that this algorithm cannot always work; however, if U is finite, this
approach will always produce a generating set (Corollary 5.2.2).
Naturally, we include several examples of these explicit presentations. Sections 6 and 7
contain presentations for the upper cluster algebras of the seeds pictured in Figure 1.
c

f1
a

x1

x1

a

x1
b

x2

x3

x2

x3

a
x2

a
∀a ≥ 2

f2

x3
f3

d
f

Figure 1. Seeds of upper cluster algebras presented in this note.
Remark 1.2.2. To compute examples, we use a variation of Lemma 4.4.1 involving lower
bounds and upper bounds, which requires that our cluster algebras are totally coprime.
2. Cluster algebras
Cluster algebras are a class of commutative unital domains. Up to a finite localization, they are generated in their field of fractions by distinguished elements, called cluster
variables. The cluster variables (and hence the cluster algebra) are produced by an recursive procedure, called mutation. While cluster algebras are geometrically motivated, their
construction is combinatorial and determined by some simple data called a ’seed’.
2.1. Ordered seeds. A matrix M ∈ Matm,m (Z) is skew-symmetrizable if there is a nonnegative, diagonal matrix D ∈ Matm,m (Z) such that DM is skew-symmetric; that is, that
(DM)⊤ = −DM.

COMPUTING UPPER CLUSTER ALGEBRAS

3

Let n ≥ m ≥ 0 be integers, and let B ∈ Matn,m (Z) be an integer valued n × m-matrix.
Let B0 ∈ Matm,m (Z) be the principal part, the submatrix of B obtained by deleting the
last n − m rows.
An ordered seed is a pair (x, B) such that...
• B ∈ Matn,m (Z),
• B0 is skew-symmetrizable, and
• x = (x1 , ..., xn ) is an n-tuple of elements in a field F of characteristic zero, which
is a free generating set for F as a field over Q.
The various parts of an ordered seed have their own names.
• The matrix B is the exchange matrix.
• The n-tuple x is the cluster.
• Elements xi ∈ x are cluster variables.2 These are further subdivided by index.
– If 0 < i ≤ m, xj is a mutable variable.
– If m < i ≤ n, xj is a frozen variable.
The ordering of the cluster variables in x is a matter of convenience. A permutation
of the cluster variables which preserves the flavor of the cluster variable (mutable/frozen)
acts on the ordered seed by reordering x and conjugating B.
A skew-symmetric seed (x, B) can be diagrammatically encoded as an ice quiver (Figure
2). Put each mutable variable xi in a circle, and put each frozen variable xi in a square.
For each pair of indices i < j with i ≤ m, add Bji arrows from i to j, where ‘negative
arrows’ go from j to i.






0 −3
x = {x1 , x2 , x3 }, B =  3
0 
−2 1

x1
Q=
x2

x3

Figure 2. The ice quiver associated to a seed
A seed (x, B) is called acyclic if Q does not contain a directed cycle of mutable vertices.
The seed in Figure 2 is acyclic.
2.2. Cluster algebras. Given an ordered seed (x, B) and some 1 ≤ k ≤ m, define the
mutation of (x, B) at k to be the ordered seed (x′ , B′ ), where

)
( Q
Q
−B
B
if i = k
xj jk + Bjk <0 xj jk xi−1
′
B
>0
jk
xi :=
xi
otherwise


−Bij
if i = k or j = k
′
Bij :=
|B |B +B |B |
Bij + ik kj 2 ik kj
otherwise

Since (x′ , B′ ) is again an ordered seed, mutation may be iterated at any sequence of indices
in 1, 2, ..., m. Mutation twice in a row at k returns to the original ordered seed.
Two ordered seeds (x, B) and (y, C) are mutation-equivalent if (y, C) is a obtained from
(x, B) by a sequence of mutations and permutations.
2Many authors do not consider frozen variables to be cluster variables, instead referring to them as

‘geometric coefficients’, following [FZ07].

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JACOB MATHERNE AND GREG MULLER

Definition 2.2.1. Given an ordered seed (x, B), the associated cluster algebra A(x, B)
is the subring of the ambient field F generated by
[
y
{xi−1 | m < i ≤ n} ∪
(y,C)∼(x,B)

A cluster variable in A(x, B) is a cluster variable in any ordered seed mutation-equivalent
to (x, B), and it is mutable or frozen based on its index in any seed. A cluster in A(x, B)
is a set of cluster variables appearing as the cluster in some ordered seed. Mutationequivalent seeds define the same cluster algebra A. The seed will often be omitted from
the notation when clear.
A cluster algebra A is acyclic if there exists an acyclic seed of A; usually, an acyclic
cluster algebra will have many non-acyclic seeds as well. Acyclic cluster algebras have
proven to be the most easily studied class; for example, [BFZ05, Corollary 1.21] gives a
presentation of A with 2n generators and n relations.
2.3. Upper cluster algebras. A basic tool in the theory of cluster algebras is the following theorem, usually called the Laurent phenomenon.
Theorem 2.3.1 (Theorem 3.1, [FZ02]). Let A be a cluster algebra, and x = {x1 , x2 , ..., xn }
be a cluster in A. As subrings of F ,
±1
A ⊂ Z[x±1
1 , ..., xn ]

This is the localization of A at the mutable variables x1 , ..., xm .
The theorem says elements of A can be expressed as Laurent polynomials in many
different sets of variables (one such expression for each cluster). The set of all rational
functions in F with this property is an important algebra in its own right, and the central
object of study in this note.
Definition 2.3.2. Given a cluster algebra A, the upper cluster algebra U is defined
\
U :=
Z[x1±1 , ..., x±1
n ] ⊂F
clusters
x={x1 ,...,xn } in A

The Laurent phenomenon is equivalent to the containment A ⊆ U.
Proposition 2.3.3. [Mul13, Proposition 2.1] Upper cluster algebras are normal.
Remark 2.3.4. Any intersection of normal domains in a fraction field is normal.
2.4. Lower and upper bounds. The cluster algebras that have finitely many clusters
have an elegant classification by Dynkin diagrams [FZ03]. However, such finite-type cluster
algebras are quite rare; even the motivating examples are frequently infinite-type. Working
with infinite-type A or U can be daunting because the definitions involve infinite generating
sets or intersections (this is especially a problem for computer computations).
Following [BFZ05], to any seed x, we associate bounded analogs of A and U called
lower and upper bounds. The definitions are the same, except the only seeds considered
are x and those seeds a single mutation away from x.
As a standard abuse of notation, for a fixed seed (x = {x1 , x2 , ..., xn }, B), let x′i denote
the mutation of xi in (x, B).
Definition 2.4.1. Let (x, B) be a seed in F .
The lower bound Lx is the subring of F generated by {x1 , x2 , ..., xn }, the one-step
−1
mutations {x′1 , x′2 , ..., x′m }, and the inverses to invertible frozen variables {x−1
m+1 , ..., xn }.

COMPUTING UPPER CLUSTER ALGEBRAS

5

The upper bound Ux is the intersection in F of the n + 1 Laurent rings corresponding
to x and its one-step mutations.
\
±1
′±1
±1
±1
±1
Z[x±1
Ux := Z[x±1
1 , ..., xi−1 , xi , xi+1 ..., xn ]
1 , ..., xn ] ∩
i

The names ‘lower bound’ and ‘upper bound’ are justified by the obvious inclusions
L x ⊆ A ⊆ U ⊆ Ux

When does U = Ux ? A seed (x, B) is coprime if every pair of columns in B are linearly
independent. A cluster algebra is totally coprime if every seed is coprime.
Theorem 2.4.2 (Corollary 1.7, [BFZ05]). If A is totally coprime, then U = Ux for any
seed (x, B).
Mutating a seed can make coprime seeds non-coprime (and vice versa), so verifying a
cluster algebra is totally coprime may be hard in general. A stronger condition is that the
exchange matrix B has full rank (ie, kernel 0); this is preserved by mutation, so it implies
the cluster algebra A(B) is totally coprime.
Theorem 2.4.3 (Proposition 1.8, [BFZ05]). If the exchange matrix B of a seed of A is
full rank, then A is totally coprime.
Of course, there are many totally coprime cluster algebras which are not full rank.3
3. Regular functions on an open subscheme
This section collects some generalities about the ring we denote Γ(R, I) – the ring of
regular functions on the open subscheme of Spec(R) whose complement is V (I) – and
relates this idea to cluster algebras.
3.1. Definition. Let R be a domain with fraction field F (R).4 For any ideal I ⊂ R,
define the ring Γ(R, I) as the intersection (taken in F (R))
\
Γ(R, I) :=
R[r−1 ]
r∈I

Remark 3.1.1. In geometric terms, Γ(R, I) is the ring of rational functions on Spec(R)
which are regular on the complement of V (I). As a consequence, Γ(R, I) only depends on
I up to radical. Neither of these facts are necessary for the rest of this note, however.

Proposition 3.1.2. If I is generated by a set π ⊂ R, then
\
Γ(R, I) =
R[r−1 ]
P

r∈π

Proof. Choose some f ∈ I, and write f = r∈π0 br r, where π0 is a finite subset of π. Let
T
g ∈ r∈π R[r−1 ]; therefore, there are nr ∈ R and αr ∈ N such that g = rnαrr for all r ∈ π.
Define
X
αr
β =1+
r∈π0

P
β
and consider f g. Expanding f = ( br r) , every monomial expression in the {r}
′
contains at least one r ∈ π0 with exponent greater orTequal to αr′ . Since r′αr′ g = nr′ ∈ R,

it follows that f β g ∈ R and g ∈ R[f −1 ]. Therefore, r∈π R[r−1 ] ⊆ Γ(R, I).
β

β

3Proposition 6.1.2 provides a class of such examples.
4All rings in this note are commutative and unital, but need not be Noetherian.

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JACOB MATHERNE AND GREG MULLER

Proposition 3.1.3. If R ⊆ S ⊆ Γ(R, I), then Γ(R, I) = Γ(S, SI).
Proof. For i ∈ I, Γ(R, I) ⊂ R[r−1 ], and so S ⊂ R[r−1 ]. Then S[r−1 ] = R[r−1 ] for all
r ∈ I. If π generates I over R, then π generates SI over S. By Proposition 3.1.2,
\
\
Γ(R, I) =
R[r−1 ] =
S[r−1 ] = Γ(S, SI)
r∈π

r∈π

This completes the proof.



3.2. Upper cluster algebras. The relation between a cluster algebra A and its upper
cluster algebra U is an example of this construction. Define the deep ideal D of A by
X
Ax1 x2 ...xm
D :=
clusters {x1 ,x2 ,...,xn }

That is, it is the A-ideal generated by the product of the mutables variables in each cluster.
Proposition 3.2.1. Γ(A, D) = U.
Proof. Since D is generated by the products of the mutable variables in the clusters,
\
A[(x1 x2 ...xm )−1 ]
Γ(A, D) =
clusters {x1 ,x2 ,...,xn }

=

\

±1
Z[x1±1 , x±1
2 , ..., xn ]

clusters {x1 ,x2 ,...,xn }

Thus, Γ(A, D) = U.



Remark 3.2.2. The proposition is equivalent to the following well-known geometric interpretation of U. If {x1 , ..., xn } is a cluster, then the isomorphism
±1
±1
A[(x1 x2 ...xm )−1 ] ≃ Z[x±1
1 , x2 , ..., xn ]

determines an open inclusion GnZ ֒→ Spec(A).5 The union of all such open affine subschemes is a smooth open subscheme in Spec(A), whose complement is V (D).6 The
proposition states that U is the ring of regular functions on this union.
3.3. Upper bounds. Let (x, B) be a seed with x = {x1 , x2 , ..., xn }. As in Section 2.4,
let x′i denote the mutation of xi in x. The lower deep ideal Dx is the Lx -ideal
X
Lx (x1 x2 ...xi−1 x′i xi+1 ...xm )
Dx := Lx (x1 x2 ...xm ) +
i

Proposition 3.2.1 has an analog.

Proposition 3.3.1. Γ(Lx , Dx ) = Ux
Proof. Since Dx is generated by the products of the mutable variables in Lx ,
\
Lx [(x1 x2 ...x′i ...xm )−1 ]
Γ(Lx , Dx ) = Lx [(x1 x2 ...xm )−1 ] ∩
=

±1
Z[x±1
1 , ..., xn ]

∩

\

i

±1
Z[x1±1 , ..., x′±1
i , ..., xn ]

i

Thus, Γ(Lx , Dx ) = Ux .

5These open algebraic tori are called toric charts in [Sco06] and cluster tori in [Mul13].
6This union is called the cluster manifold in [GSV03].



COMPUTING UPPER CLUSTER ALGEBRAS

7

In practice, Γ(Lx , Dx ) is much easier to work with than Γ(A, D), because the objects
involved are defined by finite generating sets.
Remark 3.3.2. For any set of clusters S in A, one may define LS generated by the variables
in S, US as the intersection of the Laurent rings of clusters in S, and DS an ideal in LS
generated by the products of clusters in S. Again, one has US = Γ(LS , DS ).
4. Criteria for Γ(R, I)
Given a ‘guess’ for Γ(R, I) – a ring S such that R ⊆ S ⊆ Γ(R, I) – there are several
criteria for verifying if S = Γ(R, I). This section develops these criteria.
4.1. Saturations. Given two ideals I, J in R, define the saturation
(J : I ∞ ) = {r ∈ R | ∀g ∈ I, ∃n ∈ N s.t. rg n ∈ J}
Computer algebra programs can compute saturations, at least when R is finitely generated.
Remark 4.1.1. When I Sis not finitely generated, this definition of saturation may differ
from the infinite union n (J : I n ), which amounts to reversing the order of quantifiers.

Saturations can be used to compute the sub-R-module of Γ(R, I) with denominator f .

Proposition 4.1.2. If f ∈ R, then
Rf −1 ∩ Γ(R, I) = (Rf : I ∞ )f −1
Proof. If g ∈ R ∩ f Γ(R, I), then for any r ∈ I, we may write gf −1 = hr−m for some h ∈ R
and m ∈ N. Then grm = hf ∈ Rf ; and so g ∈ (Rf : I ∞ ).
If g ∈ (Rf : I ∞ ), then for any r ∈ I, there is some m such that grm ∈ Rf . It follows
that gf −1 ∈ Rr−m ⊂ R[r−1 ]. Therefore, gf −1 ∈ Γ(R, I), and so g ∈ f Γ(R, I).

Saturations can also detect when R = Γ(R, I).
Proposition 4.1.3. Let f ∈ I. Then R = Γ(R, I) if and only if Rf = (Rf : I ∞ ).
Proof. If R = Γ(R, I), then (Rf : I ∞ ) = Rf ∩ Γ(R, I) = Rf .
Assume Rf = (Rf : I ∞ ). Let g ∈ Γ(R, I), and let n be the smallest integer such that
n
f g ∈ R. If n ≥ 1, then
f (f n−1 g) ∈ R ∩ (f Γ(R, I)) = (Rf : I ∞ ) = Rf
and so f n−1 g ∈ R, contradicting minimality of n. So g ∈ R, and so Γ(R, I) = R.



4.2. The saturation criterion. Given a ring S with R ⊆ S ⊆ Γ(R, I), the following
lemma gives a necessary and computable criterion for when S = Γ(R, I). Perhaps more
importantly, if S ( Γ(R, I), it explicitly gives new elements of Γ(R, I), which can be used
to generate a better guess S ′ ⊆ Γ(R, I).
Lemma 4.2.1. Let R ⊆ S ⊆ Γ(R, I). For and f ∈ I,
S ⊆ (Sf : (SI)∞ )f −1 ⊂ Γ(R, I)
Furthermore, either
• S = Γ(R, I), or
• S ( (Sf : (SI)∞ )f −1 ⊆ Γ(R, I).
Proof. By Proposition 3.1.3, Γ(R, I) = Γ(S, SI). The containment (Sf : (SI)∞ )f −1 ⊂
Γ(R, I) follows from Proposition 4.1.2. The containment S ⊆ (Sf : (SI)∞ )f −1 is clear
from the definition of the saturation. If (Sf : (SI)∞ )f −1 = S, then Proposition 4.1.3
implies that S = Γ(R, I).


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JACOB MATHERNE AND GREG MULLER

4.3. Noetherian algebraic criteria. When the ring S is Noetherian, there are several
alternative criteria to verify that S = Γ(R, I).7 When S is also normal, these criteria are
sharp, but none of them can give a constructive negative answer similar to Lemma 4.2.1.
The definitions of ‘codimension’, ‘S2’ and ‘depth’ used here are found in [Eis95].
Lemma 4.3.1. Let R ⊆ S ⊆ Γ(R, I). If S is Noetherian, then each of the following
statements implies the next.
(1) S is normal and codim(SI) ≥ 2.
(2) S is S2 and codim(SI) ≥ 2.
(3) depthS (SI) ≥ 2; that is, Ext1S (S/SI, S) = 0.
(4) S = Γ(R, I).
If S is normal and Noetherian, then the above statements are equivalent.
Proof. (1) ⇒ (2). By Serre’s criterion [Eis95, Theorem 11.5.i], a normal Noetherian
domain is S2.
(2) ⇒ (3). The S2 condition implies that every ideal of codimension ≥ 2 has depth ≥ 2;
see the proof of [Eis95, Theorem 18.15].8
(Not 4) ⇒ (Not 3). Assume that S ( Γ(R, I), and let f ∈ I. By Lemma 4.2.1 and
Proposition 4.1.2,
S ( (Sf : (SI)∞ )f −1 = Sf −1 ∩ Γ(S, SI)
Since S is Noetherian, SI is finitely-generated, and so it is possible to find an element
g ∈ Sf −1 ∩ Γ(S, SI) such that g 6∈ S but gI ⊆ S. The natural short exact sequence
0 → S ֒→ Sg → Sg/S → 0
is an essential extension, and so Ext1S (Sg/S, S) 6= 0.
The map S/SI → Sg/S which sends 1 to g is a surjection, and its kernel K is a torsion
S-module. Hence, there is a long exact sequence which contains
· · · → HomS (K, S) → Ext1S (Sg/S, S) → Ext1S (S/SI, S) → ...
Since K is torsion, HomS (K, S) = 0, and so Ext1S (S/SI, S) 6= 0.
(S normal) + (Not 1) ⇒ (Not 4). Assume that S is normal, and that codim(SI) = 1.
Therefore, there is a prime S-ideal P containing SI with codim(P ) = 1. By Serre’s
criterion [Eis95, Theorem 11.5.ii], the localization SP is a discrete valuation ring. Let
ν : F (S)∗ → Z be the corresponding valuation.
Let a1 , a2 , ..., aj generate P over S. Then a1 , a2 , ..., aj generate SP P over SP . There
must be some ai with ν(ai ) = 1, and this element generates SP P . Reindexing as needed,
assume that ν(a1 ) = 1. For each ai , there exists fi , gi ∈ S − P such that
fi ν(a )
ai = a1 i
gi
Let d = gcd(ν(ai )). Then, for all 1 ≤ k ≤ j,




d


Y ν(ad )
Y ν(ad ) 
fk ν(ak ) 
1
−1

x := d 
gi i 
gi i  =
d
 ∈ S[ak ]

a1 1<i≤j
ak
1<i≤j
i6=k

It follows that x ∈ Γ(S, P ) ⊆ Γ(S, SI) = Γ(R, I). However, since ν(x) = −d, it follows
that x 6∈ S, and so S 6= Γ(R, I).


7However, even when R is Noetherian, one cannot always expect that Γ(R, I) is Noetherian.
8Some sources take this as the definition of S2.

COMPUTING UPPER CLUSTER ALGEBRAS

9

Remark 4.3.2. The implication (1) ⇒ (4) is one form of the ‘algebraic Hartog lemma’, in
analogy with Hartog’s lemma in complex analysis.
Remark 4.3.3. The assumption that S is Noetherian is essential. If
R = S = C[[xt | t ∈ Q≥0 ]]
is the ring of Puiseux series without denominator, and I is generated by {xt }t>0 , then R
is normal and Ext1 (R/I, R) = 0. Nevertheless,
Γ(R, I) = C[[xt | t ∈ Q]] 6= R
is the field of all Puiseux series.
4.4. Criteria for U. We restate the previous criteria for upper cluster algebras.
Lemma 4.4.1. If A is a cluster algebra with deep ideal D, and S is a Noetherian ring
such that A ⊆ S ⊆ U, then the following are equivalent.
(1) S = U.
(2) S is normal and codim(SD) ≥ 2.
(3) S is S2 and codim(SD) ≥ 2.
(4) Ext1S (S/SD, S) = 0.
(5) Sf = (Sf : (SD)∞ ), where f := x1 x2 ...xm for some cluster x = {x1 , ..., xn }.
If Sf 6= (Sf : (SD)∞ ), then (Sf : (SD)∞ )f −1 contains elements of U not in S.
However, we are interested in infinite-type cluster algebras, where the containments
A ⊆ S ⊆ U cannot be naively verified by hand or computer. This is where lower and
upper bounds are helpful, since the analogous containments can be checked directly.
Lemma 4.4.2. If (x, B) is seed in a totally coprime cluster algebra A and S a Noetherian
ring such that Lx ⊆ S ⊆ Ux , then the following are equivalent.
(1) S = Ux = U.
(2) S is normal and codim(SDx ) ≥ 2.
(3) S is S2 and codim(SDx ) ≥ 2.
(4) Ext1S (S/SDx , S) = 0.
(5) Sf = (Sf : (SDx )∞ ), where f is the product of the mutable variables in x.
If Sf 6= (Sf : (SDx )∞ ), then (Sf : (SDx )∞ )f −1 contains elements of U not in S.
Note that Ux is normal by Remark 2.3.4, and so the strong form of Lemma 4.3.1 applies.
Remark 4.4.3. Criterion (2) was used implicitly in the proofs of [BFZ05, Theorem 2.10]
and [Sco06, Proposition 7], and a form of it is stated in [FP13, Proposition 3.6].
5. Presenting U
This section outlines the steps for checking if a set of Laurent polynomials generates a
totally coprime upper cluster algebra U over the subring of frozen variables.
5.1. From conjectural generators to a presentation. Fix a seed (x = {x1 , ..., xm }, B)
in a totally coprime cluster algebra A. Let
±1
±1
ZP := Z[x±1
m+1 , xm+2 , ..., xn ]

be the coefficient ring – the Laurent ring generated by the frozen variables and their
inverses.

10

JACOB MATHERNE AND GREG MULLER

Start with a finite set of Laurent polynomials in Z[x1±1 , ..., x±1
n ], which hopefully generates U over ZP. We assume that all the initial mutable variables x1 , ..., xn are in this set.
Write this set as
x1 , x2 , ...xm , y1 , ...., yp
where
yi =

Ni (x1 , ..., xn )
±1
±1
αni ∈ Z[x1 , ..., xn ]
1i α2i
xα
1 x2 ...xn

for some polynomial Ni (x1 , ..., xn ).
• Compute the ideal of relations. Let
Se := ZP[x1 , ..., xm , y1 , ..., yp ]

be a polynomial ring over ZP (here, the yi s are just symbols). Define Ie to be the
e
S-ideal
generated by elements of the form
αni
1i α2i
yi (xα
1 x2 ...xn ) − Ni (x1 , ..., xn )

e 1 ...xm )∞ ) be the saturation of I by the
as i runs from 1 to p. Let I := (Ie : S(x
e
principal S-ideal
generated by the product of the mutable variables x1 x2 ...xm .
±1
Lemma 5.1.1. The sub-ZP-algebra of Z[x±1
1 , ..., xn ] generated by

x1 , x2 , ...xm , y1 , ...., yp
e
is naturally isomorphic to the quotient S := S/I.

e 1 x2 ...xm )−1 ] is the ring
Proof. Let the localization S[(x
±1
Z[x±1
1 , ..., xn , y1 , ..., yp ]

e 1 x2 ...xm )−1 ]Ie is generated by elements of the form
The induced ideal S[(x
ni
yi − (x1−α1i x2−α2i ...x−α
)Ni (x1 , ..., xn )
n

e 1 x2 ...xm )−1 ]/S[(x
e 1 x2 ...xm )−1 ]Ie eliminates the yi s and is
and so the quotient S[(x
±1
±1
isomorphic to Z[x1 , ..., xn ]. The kernel of the composition
e 1 x2 ...xm )−1 ] → Z[x±1 , ..., x±1 ]
Se → S[(x
n
1

consists of elements r ∈ Se such that (x1 x2 ...xm )i r ∈ I for some i; this is the
saturation I.


• Verify that Lx ⊆ S ⊆ Ux . For the first containment, it suffices to check that
x′1 , x′2 , ..., x′m ∈ S, because the other generators of Lx are in S by construction.
For the second containment, it suffices to check that for each 1 ≤ i ≤ m and
1 ≤ k ≤ p,
′±1
±1
yk ∈ Z[x±1
1 , ..., xi , ..., xn ]
±1
This is because x1 , ..., xm , x±1
m+1 , ..., xn are in Ux by the Laurent phenomenon.
• Check whether S = U using Lemma 4.4.2. Any of the four criteria (2) − (5)
in Lemma 4.4.2 can be used. They all may be implemented by a computer, and
each method potentially involves a different algorithm, so any of the four might
be the most efficient computationally.

COMPUTING UPPER CLUSTER ALGEBRAS

11

• If S ( U, find additional generators and return to the beginning. If
S 6= U, then (Sf : (SDx )∞ )f −1 contains elements of U which are not in S (where
f = x1 x2 ...xm ). One or more of these elements may be added to the original list
of Laurent polynomials to get a larger guess S ′ for U. Note that any S ′ produced
this way satisfies Lx ⊆ S ′ ⊆ Ux .
5.2. An iterative algorithm. The preceeding steps can be regarded as an iterative algorithm for producing successively larger subrings S ⊆ U as follows. Start with an initial
guess Lx ⊆ S ⊆ Ux . In lieu of cleverness, the lower bound Lx = S makes an functional
initial guess; this amounts to starting with generators x1 , ..., xm , x′1 , ..., x′m .
Denote S1 := S, and inductively define Si+1 to be the sub-ZP-algebra of Q(x1 , x2 , ..., xn )
generated by Si and (Si f : (Si I)∞ )f −1 . If Si is finitely generated over ZP (resp. Noetherian), then the saturation (Si f : (Si I)∞ ) is finitely generated over Si and so Si+1 is
finitely generated over ZP (resp. Noetherian).
This gives a nested sequence of subrings
Lx ⊆ S = S1 ⊆ S2 ⊆ S3 ⊆ ... ⊆ U = Ux
By Lemma 4.2.1, if Si = Si+1 , then Si = Si+1 = Si+2 = ... = U = Ux .
Proposition 5.2.1. If U is finitely generated over S, then for some i, Si = U.
Proof. Let f = x1 x2 ...xm . By Proposition 4.1.2,
(Si f : (Si Dx )∞ ) = Si f −1 ∩ U
Induction on i shows that Sf −i ∩ U ⊆ Si+1 . If U is finitely generated over S, then there
is some i such that Sf −i+1 contains a generating set, and so Si = U.

Corollary 5.2.2. Let be A a totally coprime cluster algebra, and S = Lx for some seed
in A. If U is finitely generated, then U = Si for some i.
In other words, this algorithm will always produce U in finitely many steps, even starting
with the ‘worst’ guess Lx .
Remark 5.2.3. This algorithm can be implemented by computational algebra software,
so long as the initial guess S is finitely presented. However, in the authors’ experience,
naively implementing this algorithm was computationally prohibitive after the first step.
A more effective approach was to pick a few simple elements of (Si f : (Si I)∞ ) and use
them to generate a bigger ring Si+1 .
6. Examples: m = n = 3
The smallest non-acyclic seed will have m = n = 3; that is, 3 mutable variables and no
frozen variables. We consider these examples.
6.1. Generalities. Consider an arbitrary skew-symmetric seed (x, Ba,b,c ) with m = n =
3, as in Figure 3. Let Aa,b,c and Ua,b,c be the corresponding cluster algebra and upper
cluster algebra, respectively.9
The seed (x, Ba,b,c ) is acyclic unless a, b, c > 0 or a, b, c < 0, and permuting the variables
can exchange these two inequalities. Even when a, b, c > 0, the cluster algebra Aa,b,c
may not be acyclic, since there may be a acyclic seed mutation equivalent to (x, Ba,b,c ).
Thankfully, there is a simple inequality which detects when Aa,b,c is acyclic.
9The notation U
a,b,c is dangerous, in that it leaves no room to distinguish between the upper cluster
algebra and the upper bound of Ba,b,c . However, we will only consider non-acyclic examples, and so by
Theorem 2.4.2, these two algebras coincide. The reader is nevertheless warned.

12

JACOB MATHERNE AND GREG MULLER

Ba,b,c



0
= a
−c



−a c
0 −b 
b
0

a

x1

c

Qa,b,c =
x2

x3
b

Figure 3. A general skew-symmetric seed with 3 mutable variables
Theorem 6.1.1. [BBH11, Theorem 1.1] Let a, b, c > 0. The seed (x, Ba,b,c ) is mutationequivalent to an acyclic seed if and only if a < 2, b < 2, c < 2, or
abc − a2 − b2 − c2 + 4 < 0
Acyclic Aa,b,c = Ua,b,c can be presented using [BFZ05, Corollary 1.21]; and so we focus
on the non-acyclic cases. As the next proposition shows, these cluster algebras are totally
coprime, and so it will suffice to present Ux .
Proposition 6.1.2. Let A be a cluster algebra with m = 3. If A is not acyclic, then A is
totally coprime.
Proof. Let (x, B) be a non-acyclic seed for A with quiver Q; that is, there is a directed
cycle of mutable cluster variables. There are no 2-cycles in Q by construction, and so the
directed cycle in Q passes through every vertex. It follows that Bij 6= 0 if i 6= j. Then the
ith and jth columns are linearly independent, because Bii = 0 and Bij 6= 0. Hence, (x, B)
is a coprime seed, and A is totally coprime.

Remark 6.1.3. This proof does not assume that B0 is skew-symmetric or that n = 3 (ie,
that there are no frozen variables).
6.2. The (a, a, a) cluster algebra. Consider a = b = c ≥ 0 as in Figure 4.

Ba,a,a



0
= a
−a



−a a
0 −a 
a
0

a

x1

a

Qa,a,a =
x2

x3
a

Figure 4. The exchange matrix and quiver for the (a, a, a) cluster algebra
If a = 0 or 1, then Aa,a,a is acyclic.10 For a ≥ 2, Aa,a,a is not acyclic by Theorem 6.1.1.
Remark 6.2.1. The case a = 2 was specifically investigated in [BFZ05], as the first example
of a cluster algebra for which A =
6 U, and it has been subsequently connected to the
Teichmüller space of the the once-punctured torus and to the theory of Markov triples
[FG07, Appendix B] (A2,2,2 is sometimes called the Markov cluster algebra). See Section
7.1 for the analog of U2,2,2 with a specific choice of frozen variables.
Proposition 6.2.2. For a ≥ 2, the upper cluster algebra Ua,a,a is generated over Z by
xa + xa2 + xa3
x1 , x2 , x3 , M := 1
x1 x2 x3
10In fact, finite-type of type A × A × A or A , respectively.
1
1
1
3

COMPUTING UPPER CLUSTER ALGEBRAS

13

The ideal of relations among these generators is generated by
x1 x2 x3 M − xa1 − xa2 − xa3 = 0
Proof. Since a3 − 3a2 + 4 ≥ 0 for a ≥ 2, Theorem 6.1.1 implies that this cluster algebra is
not acyclic, and Proposition 6.1.2 implies that it is totally coprime.
The element x1 x2 x3 M − xa1 − xa2 − xa3 in Z[x1 , x2 , x3 , M ] is irreducible. The ideal it
generates is prime and therefore it is saturated with respect to x1 x2 x3 . By Lemma 5.1.1,
S = Z[x1 , x2 , x3 , M ]/ < x1 x2 x3 M − xa1 − xa2 − xa3 >
±1
±1
is the subring of Z[x±1
1 , x2 , x3 ] generated by x1 , x2 , x3 and M .
The following identities imply that Lx ⊂ S.

x′1 =

xa2 + xa3
= x2 x3 M −xa1 ,
x1

x′2 =

xa1 + xa3
= x1 x3 M −xa2 ,
x2

x′3 =

xa1 + xa2
= x1 x2 M −xa3
x3

The following identities imply that S ⊂ Ux .
M=

x′a+1
+ (xa2 + xa3 )a
x′a+1
+ (xa1 + xa3 )a
x′a+1
+ (xa1 + xa2 )a
1
2
3
=
=
x′a
x1 x′a
x1 x2 x′a
1 x2 x3
2 x3
3

Since S is a hypersurface, it is a complete intersection, and so it Cohen-Macaulay [Eis95,
Prop. 18.13], and in particular it is S2.11
Let P be a prime ideal in S containing
Dx =< x1 x2 x3 , x′1 x2 x3 , x1 x′2 x3 , x1 x2 x′3 >
Since x1 x2 x3 ⊂ P , at least one of {x1 , x2 , x3 } ∈ P by primality. If any two xi , xj are, then
xak = xi xj xk M − xai − xaj ∈ P ⇒ xk ∈ P
If only one xi ∈ P , then x′i xj xk ∈ P implies that x′i ∈ P . Then xi + x′a
i = xj xk M ∈ P ,
which implies M ∈ P . Additionally, xaj + xak = xi xj xk M − xai ∈ P .
Therefore, P contains at least one of the four prime ideals
(6.1)

< x1 , x2 , x3 >, < x1 , xa2 + xa3 , M >, < x2 , xa1 + xa3 , M >, < x3 , xa1 + xa2 , M >

Since {x1 , x2 }, {x1 , M }, {x2 , M }, and {x3 , M } are each regular sequences in S, it follows
that codim(Dx ) ≥ 2. By Lemma 4.4.2, S = U.

Remark 6.2.3. The final step of the proof has some interesting geometric content. In
this case, D = Dx , and the four prime ideals (6.1) are the minimal primes containing D.
Geometrically, they define the irreducible components of V (D); that is, the complement
of the cluster tori.
One of these components (x1 = x2 = x3 = 0) is an affine line on which every cluster
variable vanishes. The other 3 components (xi = xaj + xak = M = 0) are geometrically
reducible; over C they each decompose into a-many affine lines. Over C, V (D) consists of
3a + 1-many affine lines, which intersect at the point x1 = x2 = x3 = M = 0 and nowhere
else.
6.3. The (3, 3, 2) cluster algebra. Consider the initial seed in Figure 5. The cluster
algebra A3,3,2 is non-acyclic, by Theorem 6.1.1. Up to permuting the vertices, it is the
only non-acyclic Aa,b,c with 0 ≤ a, b, c ≤ 3 besides A2,2,2 and A3,3,3 .
11A ring is Cohen-Macaulay if and only if it satisfies the Sn property for every n.

14

JACOB MATHERNE AND GREG MULLER



x1



0 −3 2
0 −3 
B= 3
−2 3
0

Q=
x2

x3

Figure 5. The exchange matrix and quiver for the (3, 3, 2) cluster algebra.
Proposition 6.3.1. The upper cluster algebra U3,3,2 is generated over Z by
x1 , x2 , x3 ,
x32

x21

x23

+ +
x1 x32 + x32 x3 + x31 + x33
, y1 =
,
x1 x3
x1 x2 x3
x6 + 2x21 x32 + x1 x32 x3 + 2x32 x23 + x41 + x31 x3 + x1 x33 + x43
,
y2 = 2
x21 x2 x23
x9 + 3x21 x62 + 3x62 x23 + 3x41 x32 + 3x21 x32 x23 + 3x32 x43 + x61 + 2x31 x33 + x63
y3 = 2
.
x31 x22 x33
The ideal of relations is generated by the elements
y0 =

y22 = y0 y3 + 2y3 , y02 = x2 y2 − y0 + 2
y1 y2 = x1 y3 + x3 y3 , y0 y2 = x2 y3 + y2
y0 y1 = x1 y2 + x3 y2 − 2y1 , x1 y0 + x3 y0 = x2 y1 + x1 + x3
x22 y2 = x1 x3 y3 + 3x2 y0 − y12 − 3x2 , x22 y0 = x1 x3 y2 + x22 − x1 y1 − x3 y1
x32 + x23 y0 = x2 x3 y1 − x21 + x1 x3 .
Proof. Since a = 3, b = 3, c = 2, and abc − a2 − b2 − c2 + 4 = 0, Theorem 6.1.1 implies
that A is not acyclic. Thus, Proposition 6.1.2 asserts that A is totally coprime. Let S be
the domain in F (A) generated by the seven listed elements. Using Lemma 5.1.1 and a
computer, we see that the ideal of relations in S is generated by the elements above.
The following identities imply that Lx ⊆ S.
x′1 = x3 y0 − x1 , x′2 = x1 x3 y1 − x1 x22 − x22 x3 , x′3 = −x3 y0 + x2 y1 + x1
The following identities imply that S ⊆ Ux .
y0 =
y1

3
′
(x32 + x23 )2 + x′2
(x1 + x3 )3 (x21 − x1 x3 + x23 )2 + x′3
2
1 (x2 + x3 x1 )
=
x2 x3 x′2
x1 x3 x′2
1
2
3
′
(x21 + x32 )2 + x′2
3 (x2 + x1 x3 )
x1 x2 x′2
3

=
=
y2

(x3 + x33 )3 + (x21 + x23 )x′3
x2 + x32 + x′2
x32 + x23 + x′2
2
3
1
= 1
= 1
′
′3
x3 x1
x1 x3 x2
x1 x′3

=
=
=

′3
′4
(x32 + x23 )2 + x3 (x32 + x23 )x′1 + 2x32 x′2
1 + x3 x1 + x1
2
′2
x2 x3 x1
3
3 5
2
′6
(x1 + x3 ) + (2x1 + x1 x3 + 2x23 )(x31 + x23 )2 x′3
2 + (x1 + x3 )x2
2
2
′5
x1 x3 x2
′2
2
′
3
2
(x1 + x2 − x1 x3 + x3 )(x1 + x32 + 2x1 x′3 + x′2
3 )
x21 x2 x′2
3

COMPUTING UPPER CLUSTER ALGEBRAS

y3

=
=
=

15

2 3
2
′
′2
(x32 + x23 − x3 x′1 + x′2
1 ) (x2 + x3 + 2x3 x1 + x1 )
2
3
′3
x2 x3 x1
3 2
2
2
2 3
′3
((x1 + x3 ) (x1 − x1 x3 + x23 )2 + x′3
2 ) ((x1 + x3 )(x1 − x1 x3 + x3 ) + x2 )
3
3
′7
x1 x3 x2
2
3
′
′2 2 2
3
(x1 + x2 − x1 x3 + x3 ) (x1 + x2 + 2x1 x′3 + x′2
3)
x31 x22 x′3
3

A computer verifies that (Sx1 x2 x3 : (SDx )∞ ) = Sx1 x2 x3 . By Lemma 4.4.2, S = U. 
Remark 6.3.2. This example serves of a ‘proof of concept’ for the algorithm of Section
5.2. The above generating set has no distinguishing properties known to the authors; it is
merely the generating set produced by an implementation of this algorithm.
7. Larger examples
We explicitly present a few other non-acyclic upper cluster algebras.
7.1. The Markov cluster algebra with principal coefficients. Consider the initial
seed in Figure 6. As in the previous section, this seed has 3 mutable variables, but it
has principal coefficients – a frozen variable for each mutable variable, and the exchange
matrix extended by an identity matrix. Results about principal coefficients and why they
are important can be found in [FZ07].





B=




f1


0 −2 2
2
0 −2 

−2 2
0 

1
0
0 

0
1
0 
0
0
1

x1
Q=
x2

x3

f2

f3

Figure 6. The exchange matrix and quiver for the Markov cluster algebra with principal coefficients.
Proposition 7.1.1. The upper cluster algebra U is generated over Z[f1±1 , f2±1 , f3±1 ] by
x1 , x2 , x3 ,
x2 + f3 f1 x21 + f1 x22
x2 + f1 f2 x22 + f2 x23
x22 + f2 f3 x23 + f3 x21
, L2 = 3
, L3 = 1
x2 x3
x3 x1
x1 x2
f1 L21 + (f1 f2 f3 − 1)2
f2 L22 + (f1 f2 f3 − 1)2
f3 L23 + (f1 f2 f3 − 1)2
y1 =
, y2 =
, y3 =
x1
x2
x3
The ideal of relations is generated by the elements
L1 =

x1 x2 L3 = x21 + f1 f2 x22 + f2 x23 , y1 y2 L3 = f1 f2 y12 + y22 + f1 y32
x2 x3 L1 = x22 + f2 f3 x23 + f3 x21 ,
x3 x1 L2 = x23 + f3 f1 x21 + f1 x22 ,
f3 x1 L3 − x3 L1 = αx2 ,
f1 x2 L1 − x1 L2 = αx3 ,

y2 y3 L1 = f2 f3 y22 + y32 + f2 y12
y3 y1 L2 = f3 f1 y32 + y12 + f3 y22
f1 L1 y3 − L3 y1 = αy2
f2 L2 y1 − L1 y2 = αy3

16

JACOB MATHERNE AND GREG MULLER

f2 x3 L2 − x2 L3 = αx1 , f3 L3 y2 − L2 y3 = αy1
x1 L2 L3 = f1 f2 x2 L2 + f1 x1 L1 + x3 L3 , y1 L2 L3 = y2 L2 + f1 y1 L1 + f1 f3 y3 L3
x2 L3 L1 = f2 f3 x3 L3 + f2 x2 L2 + x1 L1 , y2 L3 L1 = y3 L3 + f2 y2 L2 + f2 f1 y1 L1
x3 L1 L2 = f3 f1 x1 L1 + f3 x3 L3 + x2 L2 , y3 L1 L2 = y1 L1 + f3 y3 L3 + f3 f2 y2 L2
x2 y3 = f2 f3 L2 L3 − αL1 , x3 y1 = f3 f1 L3 L1 − αL2 , x1 y2 = f1 f2 L1 L2 − αL3
x1 y3 = L1 L3 + f2 αL2 , x2 y1 = L2 L1 + f3 αL3 , x3 y2 = L3 L2 + f1 αL1
x1 y1 = f1 L21 + α2 , x2 y2 = f2 L22 + α2 , x3 y3 = f3 L23 + α2
L1 L2 L3 − f1 L21 − f2 L22 − f3 L23 = α2
where α := f1 f2 f3 − 1.
Proof. The exchange matrix B for the initial seed above contains a submatrix that is a
scalar multiple of the identity, thus B is full rank. Theorem 2.4.3 asserts that A is totally
coprime. Let S be the domain in F (A) generated by the twelve listed elements. Using
Lemma 5.1.1 and a computer, we see that the ideal of relations in S is generated by the
elements above.
The following identities imply that Lx ⊆ S.
x′1 = x3 L2 − f3 f1 x1 , x′2 = x1 L3 − f1 f2 x2 , x′3 = x2 L1 − f2 f3 x3
The following identities imply that S ⊆ Ux .
L1 =

2
2
2
′2 2
2
x′2
x2 + x23 f2 + f3 x′2
x′2 + f2 f3 (x22 + x21 f3 )
1 x2 + x1 x3 f2 f3 + f3 (x3 + x2 f1 )
2
= 1
= 3
′2
′
x1 x2 x3
x2 x3
x2 x′3

2
′2 2
2
2
2
x2 + x21 f3 + f1 x′2
x′2 + f3 f1 (x23 + x22 f1 )
x′2
3
2 x3 + x2 x1 f3 f1 + f1 (x1 + x3 f2 )
= 2
= 1
′2
′
x2 x3 x1
x3 x1
x3 x′1
2
2
2
2
x2 + x22 f1 + f2 x′2
x′2 + f1 f2 (x21 + x23 f2 )
x′2 x2 + x′2
1
3 x2 f1 f2 + f2 (x2 + x1 f3 )
= 3
= 2
L3 = 3 1
′2
′
x3 x1 x2
x1 x2
x1 x′2

L2 =

y1

=
=
=

y2

=
=
=

y3

=
=
=

2
′4 2
2 2
′2
2
2
2
2
2
2
3
′2
2
2
2
2
x′4
1 x2 +x1 x3 f1 f2 f3 +2x1 (x3 +x2 f1 )x2 f1 f3 +f1 f3 (x3 +x2 f1 ) +2x1 (x3 +x2 f1 )x3 f1 f2 f3
2 2
x′2
1 x2 x3

2
2 ′2 2
f1 (x21 + x23 f2 + f3 x′2
2 ) + (f1 f2 f3 − 1) x2 x3
2
x1 x′2
2 x3
′3
′
2
f1 (x1 (x3 + x3 f2 f3 (x2 + x21 f3 )))2 + (f1 f2 f3 − 1)2 x21 x22 x′4
3
x31 x22 x′4
3
2
′4 2
2 2
′2
2
2
2
2
2
2
3
′2
2
2
2
2
x′4
2 x3 +x2 x1 f2 f3 f1 +2x2 (x1 +x3 f2 )x3 f2 f1 +f2 f1 (x1 +x3 f2 ) +2x2 (x1 +x3 f2 )x1 f2 f3 f1
2 x2
x′2
x
2 3 1

2
2 ′2 2
f2 (x22 + x21 f3 + f1 x′2
3 ) + (f2 f3 f1 − 1) x3 x1
′2
2
x2 x3 x1
′3
′
f2 (x2 (x1 + x1 f3 f1 (x23 + x22 f1 )))2 + (f2 f3 f1 − 1)2 x22 x23 x′4
1
x32 x23 x′4
1
2
′4 2
2 2
′2
2
2
2
2
2
2
3
′2
2
2
2
2
x′4
3 x1 +x3 x2 f3 f1 f2 +2x3 (x2 +x1 f3 )x1 f3 f2 +f3 f2 (x2 +x1 f3 ) +2x3 (x2 +x1 f3 )x2 f3 f1 f2
2 x2
x′2
x
3 1 2

2
2 ′2 2
f3 (x23 + x22 f1 + f2 x′2
1 ) + (f3 f1 f2 − 1) x1 x2
′2
2
x3 x1 x2
′3
′
f3 (x3 (x2 + x2 f1 f2 (x21 + x23 f2 )))2 + (f3 f1 f2 − 1)2 x23 x21 x′4
2
x33 x21 x′4
2

A computer verifies that (Sx1 x2 x3 : (SDx )∞ ) = Sx1 x2 x3 . By Lemma 4.4.2, S = U. 

COMPUTING UPPER CLUSTER ALGEBRAS

17

This presentation is enough to demonstrate an unfortunate pathology of upper cluster
algebras. If B is an exchange matrix, and B† is an exchange matrix obtained from B by
deleting some rows corresponding to frozen variables, then there are natural ring maps
s : A(B) → A(B† ),

s : U(B) → U(B† )

which send the deleted frozen variables to 1. It may be naively hoped that the map on
upper cluster algebras is a surjection, but this does not always happen.
Corollary 7.1.2. For B be as in Figure 6 and B2,2,2 as in Figure 3, the map
s : U(B) → U(B2,2,2 )
for which s(xi ) = xi and s(fi ) = 1 is not a surjection.
7.2. The ‘dreaded torus’. Consider the initial seed in Figure 7.
c


0 −1
 1
0

−1
2
B=

 1 −1
−1 0



1
1
−2 1 

0 −1 

1
0 
0
1

b

Q=
a

d
f

Figure 7. The exchange matrix and quiver for the dreaded torus cluster algebra.
Proposition 7.2.1. The upper cluster algebra U is generated over Z[f ±1 ] by
a, b, c, d
b2 + c2 + ad
ad2 + ac2 + bcf + b2 d
a2 d + ac2 + bcf + b2 d
, Y =
, Z=
.
bc
acd
abd
The ideal of relations is generated by the elements
X=

bcX = b2 + c2 + ad,

cY − bZ = d − a

acX − adZ = ab − bd − cf, bdX − adY = cd − ac − bf
bXZ − aX − bY − cZ = f.
Proof. The exchange matrix B is full rank, and so Theorem 2.4.3 asserts that A is totally
coprime. Let S be the domain in F (A) generated by the eight listed elements. Using
Lemma 5.1.1 and a computer, we see that the ideal of relations in S is generated by the
elements above.
The following identities imply that Lx ⊆ S.
a′ = −cX + dZ + b, b′ = cX − b, c′ = bX − c, d′ = −bX + aY + c
The following identities imply that S ⊆ Ux .
X

=
=

(b2 + c2 )a′ + (bd + cf )d
c2 + ad + b′2
=
a′ bc
cb′
2
2 ′
2
(c + b )d + (ca + bf )a
b + da + c′2
=
′
d cb
bc′

18

JACOB MATHERNE AND GREG MULLER

Y

=
=

b′2 ad2 + b′2 ac2 + b′ (c2 + ad)cf + (c2 + ad)2 d
d2 + c2 + a′ b
=
cd
ab′2 cd
′2
2
′
c d + a(b + ad) + c bf
a(ac + bf ) + d′2 c + d′ b2
=
ac′ d
acd′

c′2 da2 + c′2 db2 + c′ (b2 + da)bf + (b2 + da)2 a
a2 + b2 + d′ c
=
ba
dc′2 ba
′2
2
′
d(db + cf ) + a′2 b + a′ c2
b a + d(c + da) + b cf
=
=
db′ a
dba′
∞
A computer verifies that (Sabcd : (SDx ) ) = Sabcd. By Lemma 4.4.2, S = U.
Z

=



This presentation makes it easy to explore the geometry of Spec(U). One interesting
result is the following, which can be proven by computer verification.
Proposition 7.2.2. The induced deep ideal UD is trivial.
±1
As a consequence, Spec(U) is covered by the cluster tori {Spec(Z[x±1
1 , ..., xn ])} coming
12
from the clusters of U. Since affine schemes are always quasi-compact, this cover has a
finite subcover; that is, some finite collection of cluster tori cover Spec(U).

Remark 7.2.3. This cluster algebra comes from a marked surface with boundary (via
the construction of [FST08]); specifically, the torus with one boundary component and a
marked point on that boundary component. In this perspective, the additional generators
X, Y, Z correspond to loops.
The epithet ‘the dreaded torus’ was coined by Gregg Musiker in a moment of frustation
– among cluster algebras of surfaces, it lies in the grey area between having enough marked
points to be well-behaved [Mul13, MSW11] and having few enough marked points to be
provably badly-behaved (like the Markov cluster algebra). As a consequence, it is still not
clear whether A = U in this case (despite the presentation for U above).
8. Acknowledgements
This paper would not have been possible without helpful insight from S. Fomin, J.
Rajchgot, D. Speyer, and K. Smith. This paper owes its existence to the VIR seminars in
Cluster Algebras at LSU, and to the second author’s time at MSRI’s Thematic program
on Cluster Algebras.
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Department of Mathematics, Louisiana State University, Baton Rouge, LA 70808, USA
E-mail address: jmath34@lsu.edu
Department of Mathematics, Louisiana State University, Baton Rouge, LA 70808, USA
E-mail address: gmuller@lsu.edu

