Symmetric functions and power sums
For roots : , , …, , and . The fundamental theorem of symmetric polynomials: every symmetric polynomial in the roots is a polynomial in — with integer coefficients if the original had them.
That theorem is the licence for the whole method: the moment an expression is symmetric in the roots, it is computable from the coefficients without ever finding a root. If , , , then — and indeed the numbers are .
With : , , , and in general .
For : , , , so and . The practical version needs no memorised identity at all — every root satisfies , so summing gives , and the same trick pushes any down to known ones. Use the recursion the polynomial itself hands you; quote Newton when you need the general shape.
If a polynomial of degree agrees with a known pattern at points, subtract the pattern: the difference has those points as roots, so it is and one extra condition pins .
For of degree with at and : set , so ; then gives and . Lagrange interpolation would get the same answer with six times the arithmetic; finite differences are the third route, and are the fastest when the given values are consecutive.
If and are two of the roots of , prove that is a root of . (USAMO 1977/3)
Step 1 — let the other roots be and put , , , . Then , and comparing coefficients: , , , .
Step 2 — eliminate: and . The third equation becomes , so and .
Step 3 — the second equation becomes . Substitute and multiply by :
So is a root of . (Here since , and because otherwise and the third equation would give .)
How to find it. A statement about a pair of roots is a statement about a quadratic factor. Writing the quartic as a product of two quadratics turns it into four equations in four unknowns, and the target polynomial is what remains after eliminating everything except .
For , tempting: ", , , so ."
Vieta's formulas , , divide by the leading coefficient. Here , , , so . Make the polynomial monic before reading off symmetric functions; every identity in this section assumes it.
If and , compute .
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. (Or: , and .)
Functional equations: the pointwise trap
Deducing " or for each " does NOT give " or ". The choice may differ from point to point until you prove it cannot.
The counterexample is one line: for rational and otherwise satisfies everywhere and is neither function. So a pointwise conclusion must be followed by a GLUING argument: assume and with , feed the pair back into the original equation, and derive a contradiction. With additivity, must equal , forcing or — so exactly two functions survive. This is the single most common way to lose points on an olympiad functional equation.
forces for rational , hence on . Over that is all you get: any regularity — continuity at ONE point, monotonicity, boundedness on an interval or on a set of positive measure — upgrades it to everywhere, and without one there are non-measurable solutions built from a Hamel basis.
So the hypotheses in the problem statement are the solution's scaffolding: if the problem says monotone, the intended path is Cauchy plus monotonicity. The standard substitutions that reduce an equation to Cauchy are worth drilling: turns into Cauchy, giving when , so .
Try ; ; ; alone; swapping and to exploit symmetry; and substituting a value that makes one side constant. Then chase injectivity () and surjectivity — they unlock the substitutions that name a specific value.
A good write-up says what each substitution BUYS: "setting gives ", "so is injective, hence the found above is unique". Keep a list of established facts as you go, and end by verifying that every candidate function actually satisfies the original equation — an olympiad answer is incomplete without the check, and graders deduct for its absence.
The question "how many satisfy AND additivity?" has the answer precisely because additivity glues the pointwise choice. Drop additivity and the answer is infinite. Knowing which hypothesis does the gluing is knowing the problem.
Find all with and for all real .
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Pointwise, with for , and . Multiplicativity at gives , so . Gluing: for , , so at every positive number. For write : , and . So (if ) or (if ). Both are multiplicative and satisfy ; note that fails, since must be . Exactly two functions — the gluing here comes from squares being positive.
Proofs & Why It Matters
Newton's identity in the case the course uses most.
Each root satisfies (its own defining cubic). Summing over the three roots gives , the appearing because the constant is added once per root. The same argument for a degree- polynomial gives for ; the identities for need the combinatorial proof, which is why the recursion from the polynomial is the practical tool.
If is additive and for all , then or .
Suppose and with . Additivity gives , while the pointwise condition gives . The plus case forces , the minus case forces — both contradictions. So the sign is the same at every nonzero point, and both signs do give solutions. Significance: the contradiction used the equation at a NEW point, . That is always the shape of the gluing step.