# Seki Takakazu and the theory of Resultants

Seki Takakazu was a Japanese mathematician during the Edo period, which ran from 1603 to 1868 and “was characterized by economic growth, arts and culture, and isolationism” [1, 2]. Takakazu actually was around the time of both Leibniz and Newton, but their work was independent [1].

Among many things in Takakazu’s mathematical career, he was known for work in Elimination theory: Algorithmic approaches to getting rid of variables between polynomials of several variables [1, 3]. In regards to the Ontario secondary mathematics curriculum, there are some relevant applications of Takakazu’s work to single variable polynomials.One particular instance is Takakazu’s work on what is known as resultants [1]. Recall (MHF4U, C3.1.1) that a polynomial of degree , a nonnegative integer, is an expression of the form

where for is a real number. In particular the above is a polynomial written as a function. For we have a linear function and for we have a quadratic function . Interestingly, the work of resultants requires two polynomials. So let’s introduce another polynomial of degree :

again for real numbers . In MHF4U a lot of work is done with polynomials of degree , including graphing and factoring in many different ways. As an extension to this, consider the following question:

“With two polynomials and , how do we know if they share a common factor?”

Recall (MHF4U, C3) that this question is asking if there is for some real number such that is a factor of and . There are a few ways to accomplish this using the tools from MHF4U:

- Completely factor both polynomials and see if any one factor appears in both
- Completely factor only one of the polynomials and use methods to see if these factors are also factors of the other (e.g. polynomial division, substitution)

However both of these methods require work that seems more complicated than what the question is asking. The area of resultants that Takakazu worked on in fact addresses this. Using a formula, the “resultant of and ” is a real number that can be calculated very fast by computers. Continuing, it turns out that the number is zero if and only if and have a common factor. That is, the answer to the question is:

“Yes, if and only if the resultant of and is .”

But how do we compute this? The command

resultant[, , ]

when given to WolframAlpha does exactly this. Let’s do an example. Suppose

and

Dealing with a degree polynomial makes it not so easy to answer the question about a common factor. But in telling WolframAlpha the command

resultant[x^3 – 4x^2 – 7x + 10, x^2 + 3x – 4, x]

the answer given back is . Recall that this means that there is indeed a common factor. This is a nice example of using technology in mathematics. Unfortunately, this method does not also tell us what the common factor actualy is, just that one exists.

If you are curious about what WolframAlpha is doing when it makes this computation, then read a little further on. Note though that even though it is related to the vectors content of MCV4U, it requires content typically first covered in a first-year undergraduate course on an area of math called linear algebra.

By definition, the resultant of arbitrary polynomials and is the determinant of their Sylvester matrix [4]. This matrix is a matrix (where and are the degrees of and resp.) where:

- The first row of the matrix is the coefficients of in decreasing order of subscripts, with entries on the right for any remaining entries
- The second row is the first row but shifted to the right by one entry, so the first entry is now a and there is one less entry on the right
- This rule continues for the following rows until there are no more zeros on the right
- The remaining rows are the same but done with instead

[5]. For an example, using the and from the earlier example, the Sylvester matrix is

The resultant of these particular and is then the determinant of this matrix. This can also be computed using WolframAlpha with the command

determinant {{1,-4,-7,10,0},{0,1,-4,-7,10},{1,3,-4,0,0},{0,1,3,-4,0},{0,0,1,3,-4}}

The Sylvester matrix is named after James Joseph Sylvester, an English mathematician in the 1800s [6].

## References

[1] https://en.wikipedia.org/wiki/Seki_Takakazu

[2] https://en.wikipedia.org/wiki/Edo_period

[3] https://en.wikipedia.org/wiki/Elimination_theory

[4] https://en.wikipedia.org/wiki/Resultant

[5] https://en.wikipedia.org/wiki/Sylvester_matrix

[6] https://en.wikipedia.org/wiki/James_Joseph_Sylvester