Minimum Number of Distinct Values for a Polynomial over a Finite Field

In summary: The inequality stated in the paper is true for any polynomial f, not just those of degree < q.In summary, the author is asking for help understanding an inequality relating to values sets over finite fields, but does not understand the reasoning behind it.
  • #1
korollar
5
0
Hello,

I've got a quite simple question, but I don't get it:

Say we've got a finite field [tex]\mathbb{F}_q[/tex] and a polynomial [tex]f \in \mathbb{F}_q[X][/tex]. Let [tex]v[/tex] denote the number of distinct values of [tex]f[/tex].

Then, i hope, it should be possible to proof, that [tex]\deg f \geq 1 \Rightarrow v \geq \frac{q}{\deg f}[/tex].

I'd appreciate any suggestions.

Greetings,
korollar
 
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  • #2
Isn't this just a straightforward counting argument?

Further hint: (how many inputs does it have?)
 
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  • #3
Sorry, I just don't see it.

I have q inputs. I can try out some polynomials and fields of small degree. But doesn't it demand number theoretical arguments do show this estimation?
 
  • #4
Ah, it's too easy. Each value can at most [tex]\deg f[/tex] times assumed by f. So [tex]v \geq \frac{q}{\deg f}[/tex].

But how can I show, that even [tex]v \geq \frac{q-1}{\deg f} + 1[/tex] is true?
 
  • #5
Hint: Show that for [tex]\deg f \neq 1, q[/tex], [tex]\frac{q}{\deg f}[/tex] has a remainder. Then do [tex]\deg f = 1, q[/tex] as special cases.

EDIT: Also note that the inequality, as stated, isn't true: consider [tex]f = x^{q+1}-x[/tex], which has only one value, 0, yet [tex]1 \not\geq 1+\frac{q-1}{q+1}[/tex]. You need a floor around your fraction.
 
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  • #6
Sorry, I forgot to write that I only look at polynomials of degree [tex]< q[/tex].

But I still need help.

Say [tex]\frac{q}{\deg f} = n \cdot \deg f + r[/tex] where [tex]r < \deg f[/tex]. But in general [tex]r + \frac{\deg f -1}{\deg f} > 1[/tex]. So I can't tell why the estimation is correct?
 
  • #7
You're right, I was assuming you meant to include a floor on the fraction.

I'll need to think more about this; it's not obvious to me.
 
  • #8
Wan et al's "Value Sets over Finite Fields" give this result as their Corollary 2.4; their paper may be worth a look.

If there's a simple counting argument, I don't see it.
 
  • #9
I'd love to have a look at them. You don't accidentally have it at hand?

However - I found this inequation in a paper of Gomez-Calderon, where the notation is the following:

[tex]\left[ \frac{q-1}{d} \right] + 1 \leq |V_f|[/tex] (d: degree of f, V_f: value set of f)

And it says: [tex][x][/tex] denotes the greatest integer [tex]\leq x[/tex] - which makes it trivial.

In my source there were no brackets. I assume the notation above is the correct one.
 

1. What is a polynomial over a finite field?

A polynomial over a finite field is a mathematical expression made up of variables, coefficients, and operations (such as addition, subtraction, and multiplication) that are all defined within a finite field. This means that the possible values for the variables and coefficients are limited to a finite set of elements, rather than all real numbers.

2. How are polynomials over finite fields used in cryptography?

Polynomials over finite fields are used in cryptography for their ability to provide a one-way function, meaning that it is easy to compute the output given an input, but difficult to find the input given the output. This is useful for creating secure encryption algorithms.

3. What are some common operations used with polynomials over finite fields?

The most common operations used with polynomials over finite fields are addition, subtraction, and multiplication. These operations follow specific rules within a finite field, such as the commutative and distributive properties, as well as the use of modular arithmetic.

4. How are polynomials over finite fields represented?

Polynomials over finite fields can be represented in several ways, including as a list of coefficients, a coefficient vector, or a polynomial function. The most common representation is as a list of coefficients, with the first element representing the constant term and subsequent elements representing the coefficients of increasing powers of the variable.

5. What is the significance of irreducible polynomials over finite fields?

Irreducible polynomials over finite fields are important in cryptography as they are used to create finite field extensions, which are necessary for creating larger and more secure encryption algorithms. These polynomials cannot be factored into smaller polynomials over the same finite field, making them essential for creating secure cryptographic systems.

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