Utente:Paolo Boldrini/Sandbox

Introduction

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These pages are a brief written report on the construction of  -adic integration. Our final goal is to give sense of integrating continuous function defined from  , or at least some particular subsets like  , with value in  . We develop a theory similar to Riemann integration for real valued functions: we define the integral as the limit of Riemann sums. The main result is Theorem 4.2. which states that for continuous functions the sequence of Riemann sums actually converges to a limit in  . We will give particular attention to Bernoulli distribution (in chapter 3) and measures (in chapter 4), because they are the most common and useful. For example they can be used to prove Kummer’s congruences. This work is mostly based on "Koblitz" .

Preliminaries.

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Some topology on   Errore del parser (errore di sintassi): {\textstyle \\} We will consider the topology induced by the metric on   . The standard basis of this topology consists of all sets of the form Errore del parser (funzione sconosciuta '\begin{split}'): {\displaystyle \begin{split} a+(p^N)&=a+p^N\mathbb{Z}_p\\&=\{x\in\mathbb{Q}_p|~x=a+tp^N, t\in\mathbb{Z}_p \}\\&=\{x\in\mathbb{Q}_p|~|x-a|_p\leq p^{-n}\}\\&=B_{p^{-n-1}}(a). \end{split}}

These sets are called open balls. They are, open, but also closed.

There is also a really unexpected property:

Proposition 1. 'Any (open) ball is compact in  .'

Proof. Consider the open ball   for some   and  . We will prove that   is sequentially compact and therefore (since it is a metric space) compact. We first observe that for any   ,  . In fact, if  , then  . We can fix   such that  , so if we expand   we get Errore del parser (funzione sconosciuta '\label'): {\displaystyle \label{starequation} \tag{$\star$} x=\sum_{i=-\alpha}^{\infty}{a_ip^i}}

Now we want to prove that any sequence in   has a convergent subsequence. To do so let   to be a sequence, any of the   can be written in the form [starequation]. We observe that for all  ,   is between   and  , so it can take only   possible values. Thus there is a subsequence   of elements with   for some  . Iterating the process, we build a subsequence   with  ,   and so on until  . Then   is clearly a convergent subsequence of the original sequence  . Thus   is sequencially compact. ◻

We say that a subset of   is compact open if it is compact and it is open.

Lemma 1. 'Let   and   be two balls, suppose  . If  , then  .Errore del parser (errore di sintassi): {\textstyle \\} If two balls have the same radius either they do not intersect or they actually are the same ball.'

Proof. Suppose   and  . We have:   thus  .Errore del parser (errore di sintassi): {\textstyle \\} If   we can apply this result in both directions, thus  . ◻

Proposition 2. 'An open subset of   is compact if and only if it is a finite union of disjoint open balls.'

Proof. Finite union of disjoint open balls are both open and compact (because balls are compact!). Conversely, if a subset is open, it is the union of open balls, and because of the compactness we can take just a finite number of them. Now Lemma Lemma 1 is sufficient to conclude. ◻

Recall 1.1. For all  ,  , for some   and  .

Recall 1.2.For all p,  . Therefore, if  , then  .

p-adic distributions

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Definition 1. Let X and Y be two topological spaces. A map   is called locally constant if it is constant in the neighborhood of each point.

Observe that in a connected space, locally constant function are not that interesting, because they have to be globally constant.

Lemma 2. 'Let   be a ball,  .'

Proof. Suppose  , then   for some  . Thus   for  . We have proven   Conversely if  , then   Thus   and we have the desired equality. ◻

Lemma Lemma 2 means that we can divide a ball of length   into   (disjoint) balls of length  . Repeating this process, Errore del parser (funzione sconosciuta '\begin{split}'): {\displaystyle \begin{split} a+(p^N)&=\bigcup \limits_{b_0=0}^{p-1}\bigcup \limits _{b_1=0}^{p-1} a+b_0p^N+b_1p^{N+1}+(p^{N+2})\\&=\bigcup \limits _{b_0,...,b_k=0}^{p-1} a+b_0p^N+...+b_kp^{N+k}+(p^{N+k+1}). \end{split}} So we can split any ball into smaller balls of arbitrary length. This construction is also unique: suppose   is an ball and   , with each   and   of length  . If  ,   for some   and by Lemma Lemma 1  , without loss of generality we can set  . Thus if we proceed we get:   and   for all  . It is easy to see that the same property still holds if   is a finite union of balls. Therefore we have the following:

Corollary 1. If   is compact open, it can be written in a unique way as the disjoint union of a finite number of balls of length  , for any N big enough.

We notice that this corollary implies that any ball is totally bounded. Since balls are closed they are also complete, because   is complete. Therefore this is another proof of Proposition Proposition 1.

Proposition 3. 'Let X be a compact open subset of   and  .   is locally constant if and only if it is a finite linear combinations of characteristic functions associated with compact open subsets of X.'

Proof. Suppose  , with   compact open. Notice that  , this is a disjoint union of open sets and on each of these sets   is constant. If we take any  , it is in one and only of these sets, thus it has a neighborhood where   is constant. Conversely, suppose   is locally constant, which means for all  , there exists a neighborhood of   (we call it  ), where   is constant. Since  , there exist   such that  . By Lemma Lemma 2 we can split each   into balls of length  , for some N big enough, and this partition is unique. Thus we have split   into a finite number of disjointed balls, and on each of these balls   is constant. Therefore, we can write   as a linear combination of the characteristic functions associated with these balls. ◻

Definition 2. Let   be a compact-open, we denote by   the vector space of the locally constant function from X to   (i.e. the set of linear combinations of characteristic function associated with compact open subsets of X: in fact these characteristic function form a basis).

Definition 3. Let X be a compact open, a  -adic distribution   on X is a vector space homomorphism from   to  . If   we denote   as  .

In these notes we will often omit the " -adic" in front of "distributions". We can see  -adic distributions in another interesting and useful way. If   is a  -adic distibution, it restricts to a map from the set of compact open (we will call this set  ) to  :   which is (finitely) additive. Conversely if we have such an additive map   we can extends it to a  -adic distribution   and the extension is clearly unique. From now on, we will identify   and   in the sense that we will see a  -adic distribution on   also as a map from   to  .

Proposition 4. 'Let   be a map from the set of balls contained in X to   such that for any   we have   then   extends to a unique  -adic distribution.'

Proof. By proposition Proposition 2, any compact-open is the finite disjoint union of open balls. So if  ,  , thus the only possible definition to be additive is  . We now have to prove that this is a good definition, i.e. it is independent of the partition of U. First we notice that iterating   we have: Errore del parser (funzione sconosciuta '\begin{split}'): {\displaystyle \begin{split} \mu(a+(p^N))&=\sum_{b_0=0}^{p-1}\mu(a+b_0p^N+(p^{N+1}))\\&=\sum_{b_0=0}^{p-1}\sum_{b_1=0}^{p-1}\mu(a+b_0p^N+b_1p^{N+1}+(p^{N+2}))\\&=\sum \limits _{b_0,...,b_k=0}^{p-1}\mu(a+b_0p^N+...+b_kp^{N+k}+(p^{N+k+1})). \end{split}} Suppose  . Now we set   , and we split each   into smaller balls of length  . By   (for  ) we have  . This means that in the end the value of   depends only on his value on smaller intervals. By the previous observation we know the decomposition is unique, thus the definition of   is independent of the partition. At this point   is a map from   to   which is clearly additive. Thus   extends to a p-adic distribution. ◻

Examples 1.  

  1.  : Suppose X is any compact open in   and  , we can define the Dirac distribution concentrated at   as Errore del parser (funzione sconosciuta '\begin{cases}'): {\textstyle \mu_{\alpha}(U)=\begin{cases} 1, & \mbox{if }\alpha\in U \\ 0, & \mbox{otherwise }\ \end{cases}} for any compact-open  
  2.  : We define the Haar distribution on the compact open   (it is a compact open since it is the ball of radius 1 centered at 0) as   for all   (i.e   and  ). We observe that we have defined the distribution only on balls, but it is sufficient to get a distribution by Prop Proposition 4. In fact  .
  3.  : We define the Mazur distribution on the compact open   as   for all   (i.e   and  ), where   is a positive integer such that  . It is easy to show that in any ball   exists one and only   with that property, thus by Lemma Lemma 1 we have that  , so this is a good definition. As before we can verify that  , thus it extends to a distribution. For example  , this may be apparently strange, because in real analysis we usually have distributions with positive value, but here  , thus it does not make sense to think it as a "negative number". Someone could ask why this   appears in the definition. There are actually two answer to this question. The first one is the fact that if we don’t do it, we don’t get a distribution, since the condition of Proposition Proposition 4 is not true anymore. The second and more interesting answer is related to Bernoulli numbers and it is the purpose of the next paragraph.
  4. Integrating locally constant functions: Let   be the function which associate to any   his first digit in p-adic expansion (i.e the coefficient of   in its expansion). This is clearly locally constant and naturally splits   into p subsets:  .   is constant on each   and it has value b, thus  . If we want to integrate   respect to a distribution   we get  . For example if   we have  , thus  . Instead, if    , thus  .

We will see that distribution are not enough to extends integration to continuous functions, and then we need a more particular tool.

Bernoulli Distributions

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Definition 4. We define  -th Bernoulli number as   the  -th coefficient of the Taylor expansion of  .

By definition we can write  .Errore del parser (errore di sintassi): {\textstyle \\} We write the first few Bernoulli numbers: Errore del parser (errore di sintassi): {\displaystyle B_0=0,\ B_1=-\frac{1}{2},\ B_3=0,\ B_4=-\frac{1}{30}\} It is not difficult to show that for every odd integer greater than 1,  .Errore del parser (errore di sintassi): {\textstyle \\} Now we define in a similar way the Bernoulli polynomials.

Definition 5. Consider   where   We call  -th Bernoulli polynomial:  

In analogy with Bernoulli numbers, we notice that for a fixed  , the  -th Bernoulli polynomial evalued at   is  ! the  -th coefficient of the Taylor expansion of  .

Definition 6. We define the  -th Bernoulli distribution as   with   and  .

It is a distribution in the sense of Proposition Proposition 4, by the next:

Proposition 5. Errore del parser (funzione sconosciuta '\label'): {\displaystyle \label{1} \tag{1} \mu_{B,k}(a+(p^N))=\sum_{b=0}^{p-1}\mu_{B,k}(a+bp^N+(p^{N+1})).} Thus   extends to a p-adic distribution.

Proof. By definition the left hand side is   and the right hand side is the sum of terms of the form  . Setting  , we have to prove  . To do so, consider Errore del parser (funzione sconosciuta '\label'): {\displaystyle \label{2} \tag{2} p^{k-1}\sum_{b=0}^{p-1}\frac{te^{\alpha t+\frac{b}{p}t}}{e^t-1}=p^k\sum_{b=0}^{p-1}\frac{\frac{t}{p}e^{(\alpha p)\frac{t}{p}}}{e^{\frac{t}{p}}-1}=p^k\sum\limits_{j=0}^{\infty}\frac{B_j(\alpha p)}{j!}\frac{t^j}{p^j}.} Thus the right hand side in [1], which is  ! times the   coefficient of [2], is exactly   . ◻

Examples 2.

  1.  :  , since   we simply have  .
  2.  :  , since   we simply have Errore del parser (errore di sintassi): {\textstyle \\}  . This is the interesting reason why we need the   in the definition of  : we want it to be a Bernoulli distribution.

Measures and integration

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Definition 7. A distribution   on X is called  -adic measure if for all   compact open subsets of X we have  , for some  .

In these notes, we will often omit the " -adic" in front of "measures".

Examples 3.

  1. The Dirac distribution is bounded above by the constant 1, thus it is a measure.
  2. Bernoulli distributions are not measures. In fact for all k we can consider  , since   is a polynomial of degree k and the coefficient of   is  ,  . Thus   which is not bounded above.

Definition 8. If   and   are two distribution (resp. measures) on X and   we define:

 

 

  , where   and  

for all U compact open subsets of X.

Proposition 6. ' ,  ,   are distribution (resp. measures).'

Proof. It is a straightforward application of the definitions, so we omit the tedious details. ◻

Definition 9. Let   such that   and   , we define the  -th Bernoulli measure regularized by   as  

By Proposition Proposition 6 we know that   is a distribution, we will prove that it is also a measure. To do so we are going to focus on   which is the basic case and then we will extend to  .

Examples 4.

  1.  :   since   is invariant for translation and  .
  2.  : Errore del parser (funzione sconosciuta '\begin{split}'): {\displaystyle \begin{split} &\mu_{1,\alpha}(a+(p^N))=\mu_{B,1}(a+(p^N))-\alpha^{-1}\mu_{B,1}(\alpha(a+(p^N)))\\=&\frac{a}{p^N}-\frac{1}{2} -\alpha^{-1}(\frac{<\alpha a>_N}{p^N}-\frac{1}{2})=\frac{a}{p^N}+\frac{1-\alpha}{2\alpha}-\frac{1}{\alpha}(\frac{\alpha a}{p^N}-\left[\frac{\alpha a}{p^N}\right])\\=&\frac{1-\alpha}{2\alpha}+\frac{1}{\alpha}\left[\frac{\alpha a}{p^N}\right], \end{split}} where   is the only integer between   and   which is congruent to   modulo   and   is the greatest integer function.

Lemma 3. 'A distribution   on X is a measure if and only if   for all  .'

Proof. If   is a measure   is bounded above since   is a compact open. Conversely, if   is a compact open, by Proposition Proposition 2, Errore del parser (errore di sintassi): {\textstyle \\U=\bigcup\limits_{i=1}^{n}a_j+(p^{N_j})} , and this is a disjointed union. Thus, Errore del parser (errore di sintassi): {\textstyle \\|\mu(U)|_p=|\sum_{i=1}^n\mu(a_j+(p^{N_j}))|_p\leq \underset{i=1,...,n}{max}\{\mu(a_j+(p^{N_j}))\}\leq C_0} . ◻

Proposition 7. '  for all   compact-open of  .'

Proof. By Lemma Lemma 3 it is sufficient to prove it for   with  . By the example (2)  . Let’s first consider  ,   is an integer and  , thus   and  . Therefore  . We have now to check the case  . By definition  , thus   is odd and   is even.   for some  . Therefore   and we can conclude as before. ◻

Up to now we have proven   is a measure, we want to extend this result to   for all k.

Theorem 1. 'Let   be the least common denominator of the polynomial  .  '
Proof. For simplicity we omit to write  , any congruence in this proof should be thought in this sense. First we notice that   We can consider just these two first terms because the others have   in the denominator for  , thus when we multiply by   at least a factor   survives (and   removes every denominator of the polynomial). Thus,

Errore del parser (funzione sconosciuta '\begin{split}'): {\displaystyle \begin{split} &d_k\mu_{k,\alpha}(a+(p^N))\\\equiv &d_k\left(\mu_{B,k}(a+(p^N))-\alpha^{-k}\mu_{B,k}(\alpha a+(p^N))\right)\\ \equiv & d_kp^{N(k-1)}\left(B_k(\frac{a}{p^N})-\alpha^{-k}B_k(\frac{<\alpha a>_N)}{p^N}\right)\\\equiv & d_kp^{N(k-1)}\left( \frac{a^k}{p^{Nk}}-\frac{k}{2}\frac{a^{k-1}}{p^{N(k-1)}}-\alpha^{-k}\left((\frac{<\alpha a>_N}{p^N})^k-\frac{k}{2}(\frac{<\alpha a>}{p^N})^{k-1}\right)\right), \end{split}} As in the previous example  , in fact   also we notice that  , thus  . So the extreme right side of the previous congruence is congruent to  Now, using the binomial expansion, and omitting every term with   in the denominator for  , this is congruent to Errore del parser (funzione sconosciuta '\begin{split}'): {\displaystyle \begin{split} &d_k p^{N(k-1)}\left(\left( \frac{a^k}{p^{Nk}}-\alpha^{-k}(\frac{\alpha^k a^k}{p^{Nk}}-\frac{k\alpha^{k-1}a^{k-1}}{p^{N(k-1)}}\left[\frac{\alpha a}{p^N}\right])\right) -\frac{k}{2}\left(\frac{a^{k-1}}{p^{N(k-1)}}-\alpha^{-k}(\frac{\alpha^{k-1} a^{k-1}}{p^{N(k-1)}}\right)\right)\\ \equiv &d_kka^{k-1}\left(\frac{1}{\alpha}\left[\frac{\alpha a}{p^N}\right]+\frac{1-\alpha}{2\alpha}\right)\equiv d_kka^{k-1}\mu_{1,\alpha}(a+(p^N)). \end{split}}

Corollary 2. 'for all k and   (for which we have defined it)   is a measure.'

Proof. By Theorem Theorem 1   Thus, Errore del parser (funzione sconosciuta '\begin{split}'): {\displaystyle \begin{split} &|\mu_{k,\alpha}(a+(p^N))|_p \\ &\leq max(|\mu_{k,\alpha}(a+(p^N))-ka^{k-1}\mu_{1,\alpha}(a+(p^N))|_p,~ |ka^{k-1}\mu_{1,\alpha}(a+(p^N))|_p)\\& \leq max(|\frac{1}{d_k}|_p,~ 1), \end{split}} where we used the fact that   and Proposition Proposition 7. Since   is fixed when we choose k, we have proven that   is bounded on balls, and therefore, by Lemma Lemma 3, on every compact-open. ◻

As we mentioned at the end of the third paragraph distributions are not sufficient to introduce integrals for continuous functions, but we can use measures to give a good and powerful definition of " -adic integrals". We will first give the basic idea of the construction of integrals for real valued function. The definition for   is the same as we will see.

Definition 10. Let   be a continuous function defined on  , a compact subset of  . We define the Riemann sums as:   where  

Here we are basically splitting the interval   into smaller intervals Errore del parser (errore di sintassi): {\textstyle \\}  . Then, we take a "random" point in each subinterval and we multiply the value of the function in this point by the length of the subinterval. We want this sums to converge to something as   grows to  , so we can define the integral as the limit. This is actually true for real valued continuous functions. We want to do the same thing but with   valued functions instead.

Definition 11. Let   be a measure and X a compact open,   . Suppose Errore del parser (errore di sintassi): {\textstyle \\f:X\rightarrow\mathbb{Q}_{p}} is a continuous function. We define the Riemann sums as:   where   is an element in  .

Theorem 2. 'For any measure   and any continuous function     converges to a limit in   as N goes to  .'

Proof. Since   is a measure we can fix a constant C such that   for any ball  . Since   is continuous on a compact set, it is also uniformly continuous, i.e. for all   there exist N s.t. for all     We have to prove   is a Cauchy sequence. To do so we will consider only positive integers N such that any   is either contained or outside  , and we try to estimate   for some  . Notice that:   where   is the residue of a   (in this way the   are the same as the  ). Thus, Errore del parser (funzione sconosciuta '\begin{split}'): {\displaystyle \begin{split} |S_{N,\{x_{a,N}\}}(f)-S_{M,\{x_{a,M}\}}(f)|_p&=\left |\sum\limits_{\underset{a+(p^N)\subseteq X}{0\leq a<p^N} }(f(x_{\overline{a},N})-f(x_{a,M}))\mu(a+(p^M))\right|_p \\& \leq Cmax(|f(x_{\overline{a},N})-f(x_{a,M})|_p). \end{split}} But  . Therefore if we take N big enough, by the uniform continuity  . So we have proven the convergence of the Riemann sums. Errore del parser (errore di sintassi): {\textstyle \\} Now we only need to show the limit is independent of the choice of  . Suppose for example to fix another sequence of elements   such that   and  . Then Errore del parser (funzione sconosciuta '\begin{split}'): {\displaystyle \begin{split} |S_{N,\{x_{a,N}\}}(f)-S_{N,\{y_{a,N}\}}(f)|_p&=\left |\sum\limits_{\underset{a+(p^N)\subseteq X}{0\leq a<p^N}}(f(x_{a,N})-f(y_{a,N}))\mu(a+(p^N))\right|_p\\&\leq Cmax(|f(x_{a,N})-f(y_{a,N}|_p). \end{split}} Since   and   are elements of  ,  . Thus if we take N big enough  , by the uniform continuity of  . Therefore the sequences   and   converge to the same limit. ◻

Definition 12. Let   be a continuous function from   to   , where X is a compact-open subset of  . We define   to be the limit of the Riemann sums defined respect to the measure  . Theorem Theorem 2 guarantees this is a good definition.