Extremal rays in families of inequalities (II)
(This is Yan Sheng.)
Last time we studied a family of inequalities involving absolute values on linear polynomials, and asked the question of how lazy we can be to prove inequalities of that form. This week, we will be applying the same approach to a different family: 3-variable homogeneous symmetric inequalities of low degree.
A polynomial in 3 variables is called homogeneous of degree if each of its terms is of degree , and symmetric if for all permutations of . Inequalities involving homogeneous symmetric polynomials include the AM-GM inequalityand the Schur inequalityfor integers .
For the rest of this post, write for the family of all homogeneous symmetric polynomials of degree such that holds for all . Our Main Problem is to describe .
Exercise: Determine for . (The most interesting inequality here is .)
Warmup: degree 3
From here on, we will use the symmetric sum notationwhere there are 6 terms in the sum, one for each permutation of . For instance, we haveBy AM-GM (or Muirhead, iykyk), we have .
Let's start by considering our Main Problem in degree 3. It should be clear that every homogeneous symmetric polynomial of degree 3 can be written asfor some constants , so the Main Problem becomes: "for which triples do we have for all ?"
It seems sensible as a first step to plug in specific points to get some conditions that have to satisfy: Hence if at these points, then we must haveGeometrically, this is a region in cut out by 3 planes; the pairwise intersections of the planes give us 3 vectors in the directions of the edges, whose nonnegative linear combinations generate the whole region. Hence we havefor some .
But now note thatso every in this region does in fact yield a nonnegative ! Hence we have proved:
Theorem: Let be a homogeneous symmetric polynomial of degree 3. Then the following are equivalent:
- holds for all (i.e., );
- holds at ; and
- is a nonnegative linear combination of the three polynomials:
- ;
- ; and
- .
The slogan here is "every 3-variable homogeneous symmetric inequality of degree 3 can be proved by checking 3 points/can be proved with AM-GM and Schur". I first noticed and posted about this fact in 2011, but it has been known since at least Stolarsky (1971) and van Albada (1971), in the context of triangle inequalities.
I'd say that this theorem a pretty satisfactory, complete solution of our Main Problem in degree 3. In fact we see that there are actually two different aspects of the Main Problem:
- The Decision Problem: Find a minimal set of points such that for all implies that for all .
- The Generation Problem: Find a minimal set of homogeneous symmetric polynomials of degree , whose nonnegative linear combinations form exactly .
By the discussion above and the preceding exercise, we may take for exampleand
It turns out that the decision problem is easier, thanks to a powerful theory developed in the late-2000's.
The pqr/uvw method
Recall that every symmetric polynomial can be written in terms of the elementary symmetric polynomials, given by Some people like to write as instead, presumably to track degrees, but of course this is purely an aesthetic choice.
Much of the power of rewriting symmetric inequalities in terms of lies in the following result, which gives simple conditions on the range of one of these variables in terms of the other two:
"Tejs's Theorem": Suppose that .
- (-lemma) For fixed , the value of attains its maximum only when two of are equal, and its minimum only when two of are equal or one of is 0.
- (-lemma) For fixed , the value of attains its maximum or minimum only when two of are equal.
- (-lemma) For fixed , the value of attains its maximum or minimum only when two of are equal.
Proof sketch: Consider the cubic polynomial , which has three nonnegative real roots. If we fix , the question of "what is the maximum possible value of ?" is equivalent to "how far can we push the graph of down such that it still has 3 nonnegative real roots?"; the answer is clearly "until we reach the local maximum of ", at which point two of the roots become equal:
On the other hand, "what is the minimum possible value of ?" is equivalent to "how far can we push the graph of up such that it still has 3 nonnegative real roots?", and the answer is "until either (a) we reach the local minimum of (at which point two of the roots become equal), or (b) one of the roots becomes 0":
This proves the -lemma.
For the -lemma and the -lemma, if then one of is 0, and it's easy to handle this case separately. Otherwise, we apply the same argument to and , respectively: now we have implies , so case (b) doesn't happen, and we are done.
Exercise: Make the above argument rigorous. Hint: if a cubic polynomial has 3 real roots, then its derivative has two real roots by Rolle's theorem; hence is increasing on , decreasing on , and increasing on . Now consider on each of these intervals.
For sufficiently low degree, this restricts where homogeneous symmetric polynomials can attain their extrema:
Corollary: Let be a homogeneous symmetric polynomial of degree . Then holds for all if and only if it holds at and for all .
Proof: By the -lemma, for fixed values of the extrema of is attained at points of the form or . But by the degree condition, we see that written as a polynomial in must be linear in , so the same is true for the extrema of ; hence to check that is nonnegative it suffices to check points of those two forms. By homogeneity we can divide these points by , so it suffices to check points of the form or , as desired.
This corollary solves the decision problem for homogeneous symmetric inequalities in 3 nonnegative real variables of degree up to 5: any such inequality can be proven by checking two inequalities in a single variable , which is easy with calculus. (This is why you don't see such problems in olympiads any more.)
Aside: History of pqr/uvw
The uvw method has probably been independently rediscovered multiple times.
- The earliest known exposition is due to Nguyen Anh Cuong (AoPS: Ahn Cuong) from 2005, who called it the ABC ("abstract concreteness") method; he only shows the -lemma. This article first appeared in English in the book Diamonds in Mathematical Inequalities, which includes several other recent Vietnamese methods such as SOS. This book was reportedly distributed at IMO 2007 in Vietnam. (Imagine beginning a book on inequalities with "The material and spiritual world in the universe is always on the move...")
- The first appearance on AoPS (then Mathlinks) was possibly this solution to Tuymaada 2005 Q8 by Iurie Boreico (IMO 2003-07), who proves the -lemma.
- The solution to Problem M2002 from Kvant magazine in 2006 (by a certain Ya. Aliev) essentially proves the -lemma.
- The first widely available set of notes on the uvw method was written in 2009 by Mathias Tejs (AoPS: Mathias_DK), who proved all three parts of the theorem and cheekily named it after himself, which is why his name is the one most often associated to this theorem (cf. Stigler's law of eponymy). Tejs himself called it the arqady method after Michael Rozenberg (AoPS: arqady), but Rozenberg later said that Tejs used it first. In any case, it is clear that the method had become well-known within the Mathlinks inequalities forum by early 2009.
Convex cones in finite dimensions
We now turn to the generation problem, which asks for a minimal set of polynomials in which generates all the other ones by nonnegative linear combinations. First, we recall some helpful results from convex analysis.
A closed set is called a convex cone if any nonnegative linear combination of elements of is also in ; in other words, for all and we have . Examples in include the circular cone and the first octant .
Exercise: Verify that is a convex cone inside some finite-dimensional real vector space.
Given a convex cone , we're interested in its "outermost" points, namely those that are not nonnegative linear combinations of other points in (except trivially in terms of multiples of itself). For any nonzero , we write for the ray ; a ray is called an extremal ray if any line segment in which intersects actually lies entirely inside . For example, every ray contained in the boundary of the circular cone is an extremal ray; on the other hand, the first octant only has 3 extremal rays, namely the nonnegative -, - and -axes.
It is almost a true statement that convex cones are the convex hulls of their extremal rays. (The key idea we used in the previous post was morally equivalent to this statement, for the cone of convex functions.)
Exercises:
- Verify that the circular cone and the first octant are each equal to the convex hull of their respective extremal rays.
- Determine the set of extremal rays of the following sets in : (a) the half-space ; (b) the quadrant . Verify that neither set is the convex hull of their extremal rays.
Actually, we only need one more mild condition for the statement to be true. We only briefly sketch the idea of the proof here; the interested reader can find details in Rockafellar's Convex Analysis text.
Theorem (Rockafellar, Corollary 18.5.2): Let be a convex cone in which contains no lines. Then is the convex hull of its extremal rays.
Proof sketch: If then is a ray, and the result is obvious, so assume that . Then contains no lines implies that is not all of a subspace of , so its relative boundary is nonempty. (Here "relative" means "relative to the minimal affine space containing ".) Similarly, is not a half-space of a subspace, which implies that is not convex. Thus there is some line which intersects in a compact interval, which implies that every line parallel to intersects in a compact (possibly empty) interval. Hence every point in the relative interior of is a convex combination of two points in , and we finish by induction on dimension.
Exercise: Verify that contains no lines.
Hence for the generation problem, it suffices to determine the extremal rays of the convex cone , and take to consist of one nonzero polynomial taken from each extremal ray. Which polynomials lie on the extremal rays of this cone?
Characterising extremal rays of
Recall that is an extremal ray of if there are no nontrivial line segments in which contain in its interior (the trivial line segments being the ones contained in ). As such, we should really try to understand line segments in : given polynomials which are not multiples of each other, what can we say about the polynomials in the family for ?
Well, the most natural thing to do is to fix a point and look at the values , where , , with . There's not much we can say about this value, except if then for all . In fact, the converse also holds: if for some , then . So all polynomials in the interior of a line segment have the same set of roots, which is the intersection of the set of roots of the polynomials at the two endpoints.
Thus if is an extremal ray of , what that means is something like "the only polynomials in with all the roots of are multiples of ", i.e., the set of roots of is maximal among nonzero polynomials in .
There is a technical issue with formalising the above intuitive argument: we need to keep track of the multiplicities of the roots, and for polynomials of more than one variable I'd have to say words I don't understand, like "divisors" and "projective". Fortunately, recall that for we can restrict to polynomials of one variable to determine membership in , and those are much easier to deal with.
Lemma: Let be polynomials such that on , and write . Let denote the set of roots of a polynomial on , counting multiplicity. Then:
- for all ; and
- If , then there exists such that on .
Exercise: Prove the above lemma. Hint: all roots in must appear with even multiplicity; hence doesn't change sign in . Now we may divide and by , and assume that ; the rest is easy.
For , we know by pqr/uvw that any homogeneous symmetric of degree lies in if and only if the two polynomialsare nonnegative on . (The factor of 3 is just to get rid of some annoying constants later.) Now we can almost give a characterisation of the extremal rays of in terms of the roots of and by using the previous lemma, but is not a compact interval. This isn't a big issue, sinceSo just for the sake of the next result, defineThen if and only if on . Let be the set of roots of viewed as a 1-variable polynomial when restricted to each of the three line segments in , counted with multiplicity.
Proposition: Let . For any , we have that is an extremal ray of if and only if is maximal among polynomials in .
Proof: If is not an extremal ray, then is contained in some line segment which is not contained in ; in particular, . Now since contains no lines, this line segment when extended must leave ; without loss of generality we may assume that this happens at , i.e., there does not exist such that .
By (1) of the previous lemma, we have ; by (2) of the lemma, we have . Hence is not maximal in .
If is not maximal in , then there exists such that ; in particular, is not a multiple of . Now by (2) of the lemma, there exists such that on . Hence lies on the line segment which is not contained in , so is not an extremal ray.
Finally, let's translate back in terms of the roots of and . For example, since , we have:
- For , the multiplicity of as a root of is equal to the multiplicity of as a root of ;
- For , the multiplicity of 0 as a root of is equal to . In other words, the "degree deficit" of can be viewed as "roots of at ".
Hence we will define to be the set of roots of counted with multiplicity, together with with multiplicity ; define similarly. Now we have the characterisation of the extremal rays of in terms of and like we wanted:
Theorem: For and , we have is an extremal ray of if and only if is inclusion-maximal among polynomials in .
In other words, for any , if then . (Here we're abusing notation and writing to mean the pair of inclusions and .)
Remark: It's possible a priori that even if ; in this case, we should consider every point in as a root of with infinite multiplicity, and we write in this case; similarly for .
Almost maximal subsets of roots
We can think of the above theorem as saying: if we restrict by specifying some roots, until we're left with a 1-dimensional subset, then what we're left with is an extremal ray of , and the set of roots that we have specified is maximal.
What happens if the set of roots is almost maximal, and we're left with a 2-dimensional subset instead? Geometrically, any convex cone in 2 dimensions which contains no lines must be a sector in the plane, generated by nonnegative linear combinations of the two rays which bound it; so we should expect that these are precisely the two extremal rays of in this subset.
As such, we will conclude this section with the following result, which will help us in our quest to do as little work as possible when we go back to actually solving the generation problem.
Theorem: For , let be multisets with elements in , and let
- If , then is an extremal ray of .
- If , and are given such that neither of and contains the other, then and are exactly the extremal rays of which are contained in .
Proof: (1): Clear from the definition of extremal rays, and the fact that contains no lines.
(2): Note that are not multiples of each other, so every element of is some linear combination . By the given condition, there exists which is a root of but not of , so implies that . Similarly, we have . HenceNow any element of not in either or must have , so thatwhich is strictly smaller than either or . Hence both and have maximal zero sets, so and are both extremal rays of .
Determining extremal rays of
To summarise: is generated by nonnegative linear combinations of its extremal rays, which are in turn the polynomials with maximal zero sets . The game plan now is:
- Specify enough roots until the space of possible polynomials has dimension ;
- Construct examples in that space with maximal zero sets;
- Repeat until we exhaust all possibilities.
First, let's check that we get the same answer as before in the degree 3 case.
Degree 3
Recall that that every homogeneous symmetric polynomial of degree 3 can be written asNow we compute and : Exercise:
- Show that (i.e., ). (Hence completely determines , and therefore .)
- Show that (i.e., ).
To prove facts about and , we should first think about characterising what cubic polynomials can appear as or . Characterising is easier: we haveso is a reciprocal polynomial.
To characterise , first notice that can't be an arbitrary cubic: the space of cubics is 4-dimensional, while the space of possible 's is 3-dimensional. Hence we should find a constraint that must satisfy; after staring for a bit (for example by plotting the graphs of , and ) we come up with the following.
Exercise: Show that . (We could verify this explicitly on , and , or observe that this is a consequence of Euler's theorem on homogeneous functions.)
Hence we can collect some basic properties of and :
Proposition:
- For , we have that has even multiplicity in and ;
- ;
- ;
- For , we have that and have the same multiplicity in ;
- If , then ; similarly for .
Proof:
- This follows from the fact that and do not change sign at .
- Both and are equivalent to ; now 1 must appear with even multiplicity in , so .
- Both conditions are equivalent to .
- This follows from .
- Note that has roots on , and roots at ; similarly for .
Now there are many different ways of finding maximal zero sets with the above facts (I have typed out 4 different arguments while drafting this post), but let's stick to the game plan. Suppose that is an extremal ray of , with corresponding zero sets . We split into the following cases, calculating the dimension of the set of remaining polynomials for each case.
- Case 1: , where . Note that this implies , which contradicts unless . Hence , and is an extremal ray.
- Case 2: . From the formula for we get , so .
- Case 3: . From the formula for we get , so .
- Case 4: , where . Now implies that , so we may assume that is monic. Note that must appear with even multiplicity in , so has one of the following forms:In the second case, implies , contradiction. In the first case, we must have (since changes sign at ), and now taking the logarithmic derivative at 1 givesHence , so , contradiction. Hence , i.e., .
- Case 5: . From the formula of we get , so .
- Case 6: None of the above. Then , which any of our constructions later will show is not maximal.
Now to find all extremal rays of , it suffices to construct two elements with neither zero set containing the other in each of Cases 2, 3 and 5! (Also notice that the significance of the points , and naturally falls out of this case analysis.)
To finish, we list some members of that we already know:
- , by Schur;
- , by AM-GM;
- , by AM-GM;
- (trivial).
We compute and for each of these:Clearly the second example doesn't have maximal zero set, so we can safely remove it from consideration (even if we hadn't noticed before that it's the sum of the first and third rows).
Now the relevant constructions for each case is:
- Case 2: and ;
- Case 3: and ;
- Case 5: and .
Thus our three examples are exactly the extremal rays in .
Degree 4
We're now ready to march bravely onward to tackle the problem in degree 4. The general homogeneous symmetric polynomial of degree 4 iswhere again we have by AM-GM. Now we evaluate and : Exercise:
- Show that (i.e., ). (Hence completely determines , and therefore .)
- Prove that .
- Show that (i.e., ).
As before, suppose that is an extremal ray of , with corresponding zero sets . We split into the following cases, where in each case denotes the set of remaining polynomials. (This time, we start with the cases avoiding the special points , and .)
- Case 1: , where . Note that this implies , so is a multiple of . Since the map from to has 1-dimensional kernel, and the space of possible is 1-dimensional, we have .
- Case 2: , where . We expect that the space of quartic polynomials satisfying the constraints and has dimension ; indeed, writing , we see that is a polynomial of degree satisfyingi.e., . Clearly the space of such , and hence the space of , has dimension 2; since the map from to is invertible, we also have .
Now it turns out that the remaining conditions, namely
- ;
- ; and
- ,
each yield only one nontrivial condition on , so that in each case. To overcome this, we have to impose them together pairwise, or with higher multiplicity:
- Case 3: . We have for some with degree ; hence .
- Case 4: . We have for some with degree , andimplies ; hence .
- Case 5: . We have for some with degree ; hence .
- Case 6: . We have for some with degree , andimplies ; hence .
- Case 7: . Then is a multiple of , so .
- Case 8: . Then has degree and satisfies , so .
- Case 9: None of the above. Then is one of , , , or , each of which our constructions later will show is not maximal.
Okay, that's a lot of construction to do. We list down some members of that we already know; just like in the degree 3 case, one of the AM-GM ones is redundant (and is omitted from this table):
Let's keep track of which cases these constructions work for:
Looks like we'll need some families of polynomials in such that and can have general roots . Are there any other easy constructions for polynomials in ?
One idea is to just square some quadratic polynomial, sayFor this polynomial, we haveCan and have any root for an appropriate choice of ? Sure: just take and , respectively.
Sketching these two curves, we see that has the following zero sets for various values of :So these constructions are good for many of our incomplete cases:
We're now left to construct a polynomial in which has roots at the point (and thus also at and , by symmetry), and also at some point that isn't a root of the corresponding ; let's choose here. (Of course, the correct thing to do is a dimension count to make sure that there is indeed a nonzero solution.) Again, maybe we want to construct this as the square of a quadratic to ensure positivity; what quadratic polynomial has roots at those 4 points?
This is easy if we take the quadratic as the product of two linear factors: note that the 4 points lie on the union of and ; this suggests the polynomial , which is homogeneous of degree 4 but not symmetric. No worries, we can just take the cyclic sum: definewhich will have the 4 roots as desired. Finally it is easy to check that in this case, so that , which completes our list of required constructions:
Remark: Note that taking (i.e., ) will overlap with some of our previous constructions; by comparing root sets and leading coefficients, it is easy to check that and . Also, it's possible to make sense of (i.e., ) if we normalise correctly, sayand by considering the root set and leading coefficient in this case we see that in fact .
Hence we have our solution to the generation problem for degree 4:
Theorem: The extremal rays of are:Any is a nonnegative linear combination of the polynomials listed above.
The only place in the literature where I could find this statement is in Ando (2022), Proposition 1.3, where it is deduced as a consequence of the (much harder) classification of extremal rays for nonnegative homogeneous cyclic polynomials of degree 4. (Coincidentally, Tetsuya Ando is the chair of the Problem Selection Committee for IMO 2023.) As far as I know, the proof in this post is original.
Exercises
Because there are so many more things to say that these deserve their own section.
Like, an actual inequality
- Solve in 30 seconds: Find the largest value of such that the inequalityholds for all .
Extremal rays of
- For each extremal ray of , express as a nonnegative linear combination of extremal rays of .
- Consider the following attempted construction of an extremal ray in : we check that for , the polynomial with satisfies (so that on ) and . Recovering from , we must have . So this is a third construction for Case 2, where we should have . What went wrong?
- Prove that if and , then .
(Hint: we can assume that is a linear combination of polynomials of the form .)
Hence show that the following are extremal rays of :- , if ;
- , if ;
- and , if .
- Let be the degree 6 Schur polynomial,Show that is not an extremal ray of .
(Hint: we have ; show that set of polynomials in satisfying the constraint has dimension 2, and find the two rays bounding this region. Note that since we no longer have , we can't immediately conclude that these rays are extremal rays of .)
Root diagrams
It turns out that we can actually do even less work in degree 4, by drawing the correct diagrams.
Show that the roots of any can be represented by a symmetric subset of the following region:
(Hint: take the normalisation ; this is basically the same as the soil triangle.)
Note that:
- The points are projected down to the line, which is a median/altitude/angle bisector of the triangle, with at the foot, centre, and vertex, respectively;
The points are projected down to the line, which is a side of the triangle, with at the vertex, midpoint, and other vertex, respectively.
Recall that . Without using coordinate geometry, show that the roots of are given by the following diagrams.
(Hint: which conics have the same symmetries as the equilateral triangle?)
Hence recover the table of the zero sets of in each case (reproduced here):Explain how the following diagram gives the construction for :
Test sets
The following result is due to Timofte (2003); notice that this exactly recovers our previous results for and .
Theorem (Half-degree principle): Let be a homogeneous symmetric polynomial of degree in variables. Then for all if and only if on all points with and at most distinct nonzero coordinates.
Here we present the simplified approach by Reiner (2012).
- Let be a degree polynomial with distinct positive real roots. Show that there exists such that for all ], the polynomial also has distinct nonnegative real roots.
- Let be a degree polynomial with nonnegative real roots, of which there are distinct positive roots. Show that there exists and a polynomial of degree such that for all ], the polynomial also has nonnegative real roots, of which there are distinct positive roots.
(Hint: apply the previous result to for an appropriately chosen factor of .) - Let denote the elementary symmetric polynomial of degree . Recall that can be uniquely written as a polynomial in ; show that this polynomial is linear in the variables () jointly.
- Show that the locus of points with determined by fixing the values of is compact.
- Suppose that the point with is chosen in minimising , with the maximal number of distinct positive components. By considering the polynomialand applying (2), show that . Conclude.
The decision problem
Recall that the decision problem requires us to find a minimal set such that on implies that for all . This is not quite the right definition: for example, for , we can't actually take to be , since by continuity we only need to check points in with rational coordinates.
Let's fix the definition: setWe now aim to find a minimal closed set such that all homogeneous symmetric polynomials of degree which are nonnegative on must also be nonnegative on all of (and hence for all ).
- Suppose that has a unique root . Show that any choice of must contain .
(Hint: Take , so that on ; for any neighbourhood of , show that there exists such that is only negative inside of .) - For each point on the relative boundary of , construct such that only on multiples of . (This shows that is essentially ; taking shows the same for .)
- For each point in the relative interior of , construct such that only on multiples of .
(Hint: consider the polynomialThis shows that has to be all of for .
Degree 5
The approach described in this post can also be applied to classify the extremal rays of , with enough determination. Here we outline the most important cases.
The general homogeneous symmetric polynomial of degree 5 is
- Prove the usual preliminary results about and :
- the map from to is injective;
- the map from to has kernel of dimension 2 (generated by and );
- .
- For distinct , show that the set of polynomials in with has dimension(Hint: for some of degree ; take the logarithmic derivative at 1 to restrict the possible values of .)
- For , show that the set of polynomials in with has dimension 3, parametrised by . Determine the set of these triples such that for some . Hence determine the pairs such that the set of polynomials in with has dimension 1.
(Hint: show that for some polynomial of degree , and express the coefficients of as linear functions of .) - For , show that the set of polynomials in under each of the following constraints has dimension 1:
- ;
- ;
- .
In each of the above cases, we can get some expression for by recovering it from , though it would be less interpretable than our constructions in degree 4.
- Finish the classification of the extremal rays of . Check against Ando (2022), Theorem 1.4.
The dual cone
This was the original approach that I was going to write about when I first started on this post.
Degree 3
Recall the expressions Instead of analysing the cone of possible triples (which we identify with by abuse of notation), we can instead look at the dual cone of triples for whichfor all . Geometrically, every point in represents a supporting plane to .
Since the only restrictions defining are given by and for all , it should be clear that is simply the cone generated by nonnegative linear combinations of the points and for .
- Show that the cross-section of is given by the convex hull of the union of the two parametric curvesfor .
- Show that is a triangle with vertices at , , , corresponding to the points , , respectively.
Now we have to figure out what extremal rays correspond to in the picture for the dual cone .
- Show that each point represents a supporting plane to ; in the cross-section, these are supporting lines to .
- Show that each line segment in corresponds to a family of planes in passing through a fixed line; in the cross-section, these are families of supporting lines to passing through a common point.
- Hence show that each extremal ray of corresponds to a supporting line of which must intersect if you wiggle it while pivoting about any point on .
- Show that the only such are the three sides of .
Degree 4
We set up the dual cone and its cross-section analogously.
- Show that the cross-section of is given by the convex hull of the union of the two parametric curvesfor .
- Show that the boundary of consists of finitely many ruled surfaces.
- Show that extremal rays of correspond to segments lying on the boundary of , joining two points on the parametric curves.
- Complete the classification of extremal rays of .
Open questions
- Using the method in this post, determine the extremal rays in the following families of polynomials which are nonnegative on nonnegative arguments:
- Homogeneous cyclic polynomials of degree 3 in 3 variables (check against);
- Homogeneous symmetric polynomials of degree 3 in 4 variables;
- Any other family.
- Determine the extremal rays of .
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