Understanding D&F Prop. 24: How Do We Know f in I => r in I?

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In summary: Your Name]In summary, the conversation is about a question regarding Proposition 24 in Dummit and Foote, which states that if the leading terms of a set of elements in an ideal are equal to the leading terms of the ideal, then the set is a Grobner basis for the ideal. The question asks for help in understanding a step in the proof where it is stated that if an element f is in the ideal, then the remainder r from polynomial division is also in the ideal. The expert clarifies this step by explaining that if the set of elements in the ideal can generate any element in the ideal, then the remainder r can also be written as a linear combination of these elements, making it also an element of the ideal
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I am reading Dummit and Foote Section 9.6 Polynomials in Several Variables Over a Field and Grobner Bases.

I have a problem understanding a step in the proof of Proposition 24, Page 322 of D&F

Proposition 24 reads as follows:

Proposition 24. Fix a monomial ordering on [TEX] R= F[x_1, ... , x_n] [/TEX] and let I be a non-zero ideal in R

(1) If [TEX] g_1, ... , g_m [/TEX] are any elements of I such that [TEX] LT(I) = (LT(g_1), ... ... LT(g_m) )[/TEX]

then [TEX] \{ g_1, ... , g_m \} [/TEX] is a Grobner Basis for I

(2) The ideal I has a Grobner BasisThe proof of Proposition 24 begins as follows:Proof: Suppose [TEX] g_1, ... , g_m \in I [/TEX] with [TEX] LT(I) = (LT(g_1), ... ... LT(g_m) )[/TEX] .

We need to see that [TEX] g_1, ... , g_m [/TEX] generate the ideal I.

If [TEX] f \in I [/TEX] use general polynomial division to write [TEX] f = \sum q_i g_i + r [/TEX] where no non-zero term in the remainder r is divisible by any [TEX] LT(g_i) [/TEX]

Since [TEX] f \in I [/TEX], also [TEX] r \in I [/TEX] ... ... etc etc
My question: How do we know [TEX] f \in I \Longrightarrow r \in I [/TEX]?

Would appreciate some help

Peter

[This has also been posted on MHF]
 
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Dear Peter,

Thank you for your question regarding Proposition 24 in Dummit and Foote. I can understand why this step in the proof may be confusing. Let me try to clarify it for you.

First, let's recall the definition of an ideal. An ideal is a subset of a ring (in this case, the polynomial ring R) that is closed under addition and multiplication by elements of the ring. In other words, if f and g are in I, then f+g and fg must also be in I.

Now, let's look at the statement in the proof: "If f \in I, then r \in I." This is saying that if we can show that r is in I, then we have shown that the set {g_1, ..., g_m} generates the ideal I. Why is this the case?

Well, we know that f is in I. And we have assumed that g_1, ..., g_m generate I. This means that any element in I can be written as a linear combination of g_1, ..., g_m. So, if we can show that r is in I, then we can write it as a linear combination of g_1, ..., g_m. And since we already know that f can be written as a linear combination of g_1, ..., g_m, we can also write r as a linear combination of g_1, ..., g_m. Therefore, r is in I.

I hope this explanation helps to clarify the step in the proof that you were struggling with. If you have any further questions, please don't hesitate to ask.


 

FAQ: Understanding D&F Prop. 24: How Do We Know f in I => r in I?

What is D&F Prop. 24?

D&F Prop. 24 refers to a proposition in the field of science that states when an input (I) is given, there will be a specific output (O) that can be found.

How does D&F Prop. 24 relate to understanding f in I => r in I?

D&F Prop. 24 is used to determine the relationship between the input (I) and the output (O). In the case of "f in I => r in I", f represents the function that maps the input (I) to the output (O), while r represents the result of that function.

Can you explain how D&F Prop. 24 is applied in scientific research?

D&F Prop. 24 is used as a guiding principle in scientific research to understand the cause-and-effect relationships between different variables. By manipulating the input (I) and observing the resulting output (O), scientists can gain insights into how the variables are related.

What are the limitations of D&F Prop. 24?

While D&F Prop. 24 is a useful tool for understanding relationships between variables, it is important to note that it is not applicable in all situations. Some phenomena may not have a predictable cause-and-effect relationship, and there may be other factors at play that affect the output (O) besides the input (I).

How can scientists verify the accuracy of D&F Prop. 24?

To verify the accuracy of D&F Prop. 24, scientists use methods such as experimentation and statistical analysis to gather data and test the relationship between the input (I) and output (O). If the results consistently support the relationship predicted by D&F Prop. 24, then it can be considered accurate and applicable.

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