An introduction to p-adic L-functions — Lean blueprint

6.3. The p-adic value at s = 1🔗

By definition of L_p(\theta,s),

L_p(\theta,1) = \int_{\Zpx}\chi(x)x^{-1}\,d\mu_\eta = \int_{\Zpx}x^{-1}\,d\mu_\theta.

The obstruction is that multiplication by x^{-1} is not an operation on measures: x^{-1}\mu_\theta is ill-defined. On the power-series side, where the Mahler transform \sA_{\mu_\theta}(T)=F_\theta(T) of \mu_\theta lives, this is mirrored by the indeterminacy of the formal antiderivative \partial^{-1}. The strategy is to guess an explicit antiderivative \widetilde F_\theta of F_\theta, show it has just enough convergence to be a distribution (rather than a measure), and then read off L_p(\theta,1) from it.

Recall the explicit formula for the Mahler transform of \mu_\theta,

F_\theta(T)=-\frac{1}{G(\theta^{-1})}\sum_{c\in(\Z/N\Z)^\times}\frac{\theta^{-1}(c)}{(1+T)\varepsilon_N^{\,c}-1},

and the differential operator \partial = (1+T)\tfrac{d}{dT} corresponding to multiplication by x on measures. Define the candidate antiderivative

\widetilde F_\theta(T)=-\frac{1}{G(\theta^{-1})}\sum_{c\in(\Z/N\Z)^\times}\theta^{-1}(c)\,\log\!\big((1+T)\varepsilon_N^{\,c}-1\big).

Let \sR^+ denote the ring of power series \sum a_nT^n with \abs{a_n}r^n\to0 for every 0\le r<1 (the functions analytic on the open unit disc).

Lemma6.3.1
uses 0used by 1XL∃∀N

The power series \widetilde F_\theta(T) lies in \sR^+.

Proof for Lemma 6.3.1

Expand each logarithm as \log((1+T)\varepsilon_N^{\,c}-1)=\log_p(\varepsilon_N^{\,c}-1)+\log\!\big(1+\tfrac{\varepsilon_N^{\,c}T}{\varepsilon_N^{\,c}-1}\big), whose T^n-coefficient is \tfrac{(-1)^{n-1}}{n}\,\varepsilon_N^{\,cn}(\varepsilon_N^{\,c}-1)^{-n}. If (N,p)=1 then \varepsilon_N^{\,c}-1 is a p-adic unit, so this coefficient has valuation \ge -v_p(n); the coefficients grow only logarithmically and hence \widetilde F_\theta\in\sR^+. For general N=Dp^n, write \theta=\eta\chi and note, exactly as for F_\theta, the twisting formula \widetilde F_\theta(T)=-G(\chi^{-1})^{-1}\sum_{c\in(\Z/p^n\Z)^\times}\chi^{-1}(c)\,\widetilde F_\eta\big((1+T)\varepsilon_{p^n}^{\,c}-1\big). Since \widetilde F_\eta\in\sR^+ by the prime-to-p case and \sR^+ is stable under the substitution T\mapsto(1+T)\zeta-1 for a root of unity \zeta, the same holds for \widetilde F_\theta. This uses Definition 3.4.3.

This node stays unwired: the distribution-free route (replan R6.6) never needs full \sR^+-membership, only the weaker coefficient bound \|\,[T^n]\widetilde F_\theta\|\le C(n+1) that makes the boundary evaluations \widetilde F_\theta(\xi^i-1) converge (the Lean lemma summable_seriesEval_Ftilde, guarded by the norm-one fact for the contributing coprime roots).

By the theory of locally analytic distributions, a power series in \sR^+ is the Mahler transform of a locally analytic distribution. Let \widetilde\mu_\theta be the distribution with \sA_{\widetilde\mu_\theta}=\widetilde F_\theta.

Lemma6.3.2
Statement uses 2
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used by 1L∃∀N

We have x\,\widetilde\mu_\theta=\mu_\theta as distributions on \Zp. In particular \Res_{\Zpx}(\widetilde\mu_\theta)=x^{-1}\Res_{\Zpx}(\mu_\theta), making sense of the ill-defined product in L_p(\theta,1)=\sA_{x^{-1}\Res_{\Zpx}(\mu_\theta)}(0). This depends on Definition 4.1.4 and Definition 3.7.3.

In the distribution-free route (replan R6.6) the content x\,\widetilde\mu_\theta =\mu_\theta is the Mahler-side formal identity \partial\widetilde F_\theta =F_\theta, where \partial=(1+T)\tfrac{d}{dT}. The Lean lemma one_add_mul_derivative_Ftilde is exactly this identity for the explicit power series \widetilde F_\theta; the companion measure-side fact \partial\sA_{\rho_\theta}=\sA_{\Res_{\Zpx}(\mu_\theta)} is one_add_mul_derivative_mahlerK_rhoTheta.

Lean code for Lemma6.3.21 theorem
  • theoremdefined in PadicLFunctions/ValuesAtOne.lean
    complete
    theorem PadicLFunctions.MeasureR.one_add_mul_derivative_Ftilde.{u_1} {p : }
      [hp : Fact (Nat.Prime p)] {K : Type u_1} [NormedField K]
      [NormedAlgebra ℚ_[p] K] [CharZero K] {N : } [NeZero N] (hN : 1 < N)
      {θ : DirichletCharacter K N} (hθ1 : θ  1) {ε : K}
      ( : IsPrimitiveRoot ε N)
      (hunit :  c  Finset.range N, ¬N  c  IsUnit (ε ^ c - 1)) :
      (1 + PowerSeries.X) *
          (PadicLFunctions.MeasureR.Ftilde p K θ ).derivativeFun =
        - c  Finset.range N,
            PowerSeries.C (θ⁻¹ c) *
              Ring.inverse ((1 + PowerSeries.X) * PowerSeries.C (ε ^ c) - 1)
    theorem PadicLFunctions.MeasureR.one_add_mul_derivative_Ftilde.{u_1}
      {p : } [hp : Fact (Nat.Prime p)]
      {K : Type u_1} [NormedField K]
      [NormedAlgebra ℚ_[p] K] [CharZero K]
      {N : } [NeZero N] (hN : 1 < N)
      {θ : DirichletCharacter K N}
      (hθ1 : θ  1) {ε : K}
      ( : IsPrimitiveRoot ε N)
      (hunit :
         c  Finset.range N,
          ¬N  c  IsUnit (ε ^ c - 1)) :
      (1 + PowerSeries.X) *
          (PadicLFunctions.MeasureR.Ftilde p K
              θ ).derivativeFun =
        - c  Finset.range N,
            PowerSeries.C (θ⁻¹ c) *
              Ring.inverse
                ((1 + PowerSeries.X) *
                    PowerSeries.C (ε ^ c) -
                  1)
    P6-p3: `∂F̃_θ = F_θ` — the constant terms cancel by
    `Σ_c θ⁻¹(c) = 0` for `θ ≠ 1` (TeX 2100–2110, Lem 6.3 first half in the
    formal route). 
Proof for Lemma 6.3.2
Proof uses 2
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Definition 3.4.3
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Multiplication by x corresponds to the operator \partial=(1+T)\tfrac{d}{dT} on Mahler transforms, so x\,\widetilde\mu_\theta=\mu_\theta amounts to \partial\widetilde F_\theta=\sA_{\mu_\theta}=F_\theta. Differentiating termwise, \partial\log((1+T)\varepsilon_N^{\,c}-1)=\tfrac{(1+T)\varepsilon_N^{\,c}}{(1+T)\varepsilon_N^{\,c}-1}=1+\tfrac{1}{(1+T)\varepsilon_N^{\,c}-1}; summing against -G(\theta^{-1})^{-1}\theta^{-1}(c) the constant terms 1 cancel because \sum_c\theta^{-1}(c)=0 (as \theta is non-trivial), leaving exactly F_\theta(T). For the second statement, on \Zpx multiplication by x is invertible, and x\,\Res_{\Zpx}(\widetilde\mu_\theta)=\Res_{\Zpx}(\mu_\theta) gives \Res_{\Zpx}(\widetilde\mu_\theta)=x^{-1}\Res_{\Zpx}(\mu_\theta). This uses Lemma 6.3.1 and the Definition 3.4.3 dictionary under which multiplication by x corresponds to \partial.

Combining the previous lemma with the formula for the restriction of a distribution to \Zpx, namely \Res_{\Zpx}=(1-\varphi\circ\psi), gives

L_p(\theta,1)=\sA_{\Res_{\Zpx}(\widetilde\mu_\theta)}(0)=\Big((1-\varphi\circ\psi)\widetilde F_\theta\Big)(0).

Here \varphi\circ\psi(\widetilde F_\theta) is the Mahler transform of \Res_{p\Zp}(\widetilde\mu_\theta), and concretely \varphi\circ\psi(F)(T)=\tfrac1p\sum_{\xi\in\mu_p}F((1+T)\xi-1).

Theorem6.3.3
uses 1used by 0L∃∀N

Theorem Theorem 6.1.1 (ii) holds: with \widetilde F_\theta as above one has L_p(\theta,1)=(1-\theta(p)p^{-1})\widetilde F_\theta(0), and evaluating \widetilde F_\theta(0) gives the closed formula for L_p(\theta,1). This rests on Theorem 5.1.1.

The Lean statement LpFunction_one is the displayed closed formula, proved for the tame conductor D>1 (the \S 5.2 standing hypotheses; the pure p-power case D=1 is deferred — decomposition R6, replan 4). The proof follows a distribution-free route (replan R6.6): rather than constructing the locally analytic distribution \widetilde\mu_\theta, it works with the genuine measure \rho_\theta=x^{-1}\Res_{\Zpx}(\mu_\theta) and the explicit power series \widetilde F_\theta over K, pinning the constant of integration in \ker\psi. The root \varepsilon_N is taken in split form \varepsilon_N=\zeta\,\varepsilon_{p^n} (a primitive tame root times a primitive wild root), which realises the Gauss-sum factorisation G(\theta^{-1})=G(\eta^{-1})G(\chi^{-1}) of the displayed prefactor.

Lean code for Theorem6.3.31 theorem
  • theoremdefined in PadicLFunctions/ValuesAtOne.lean
    complete
    theorem PadicLFunctions.MeasureR.LpFunction_one.{u_1} {p : }
      [hp : Fact (Nat.Prime p)] {K : Type u_1} [NormedField K]
      [NormedAlgebra ℚ_[p] K] [IsUltrametricDist K] [CompleteSpace K]
      [CharZero K] {D : } [NeZero D] (hD1 : 1 < D)
      {η : DirichletCharacter (↥(PadicLFunctions.integerRing K)) D}
      ( : η.IsPrimitive) {ζ : (PadicLFunctions.integerRing K)}
      ( : IsPrimitiveRoot ζ D) (hD : ¬p  D) {n : }
      {χ : DirichletCharacter (↥(PadicLFunctions.integerRing K)) (p ^ n)}
      ( : χ.IsPrimitive) {θK : DirichletCharacter K (D * p ^ n)}
      (hθ1 : θK  1)
      (hθK :
        θK =
          PadicLFunctions.MeasureR.toFieldChar
            ((DirichletCharacter.changeLevel ) η *
              (DirichletCharacter.changeLevel ) χ))
      (hprim : θK.IsPrimitive) {ε : K} ( : IsPrimitiveRoot ε (D * p ^ n))
      {εp : (PadicLFunctions.integerRing K)}
      (hεp : IsPrimitiveRoot εp (p ^ n)) (hsplit : ε = ζ * εp) {ξ : K}
      ( : IsPrimitiveRoot ξ p) {G : K} (_hG : IsUnit G)
      (hGval : G = gaussSum θK⁻¹ (AddChar.zmodChar (D * p ^ n) )) :
      PadicLFunctions.MeasureR.LpFunction p K η  hD χ 1 =
        -(1 - θK p * (↑p)⁻¹) * G⁻¹ *
           c  Finset.range (D * p ^ n),
            θK⁻¹ c * PadicLFunctions.extLog p (1 - ε ^ c)
    theorem PadicLFunctions.MeasureR.LpFunction_one.{u_1}
      {p : } [hp : Fact (Nat.Prime p)]
      {K : Type u_1} [NormedField K]
      [NormedAlgebra ℚ_[p] K]
      [IsUltrametricDist K] [CompleteSpace K]
      [CharZero K] {D : } [NeZero D]
      (hD1 : 1 < D)
      {η :
        DirichletCharacter
          (↥(PadicLFunctions.integerRing K))
          D}
      ( : η.IsPrimitive)
      {ζ : (PadicLFunctions.integerRing K)}
      ( : IsPrimitiveRoot ζ D) (hD : ¬p  D)
      {n : }
      {χ :
        DirichletCharacter
          (↥(PadicLFunctions.integerRing K))
          (p ^ n)}
      ( : χ.IsPrimitive)
      {θK : DirichletCharacter K (D * p ^ n)}
      (hθ1 : θK  1)
      (hθK :
        θK =
          PadicLFunctions.MeasureR.toFieldChar
            ((DirichletCharacter.changeLevel
                  )
                η *
              (DirichletCharacter.changeLevel
                  )
                χ))
      (hprim : θK.IsPrimitive) {ε : K}
      ( : IsPrimitiveRoot ε (D * p ^ n))
      {εp : (PadicLFunctions.integerRing K)}
      (hεp : IsPrimitiveRoot εp (p ^ n))
      (hsplit : ε = ζ * εp) {ξ : K}
      ( : IsPrimitiveRoot ξ p) {G : K}
      (_hG : IsUnit G)
      (hGval :
        G =
          gaussSum θK⁻¹
            (AddChar.zmodChar (D * p ^ n)
              )) :
      PadicLFunctions.MeasureR.LpFunction p K
          η  hD χ 1 =
        -(1 - θK p * (↑p)⁻¹) * G⁻¹ *
           c  Finset.range (D * p ^ n),
            θK⁻¹ c *
              PadicLFunctions.extLog p
                (1 - ε ^ c)
    **RJW Theorem 6.1(ii)** (Leopoldt; `s=1 theorem`(ii), TeX 1992–1995):
    "We have `L_p(θ,1) = −(1 − θ(p)p⁻¹)·G(θ⁻¹)⁻¹·
    Σ_{c∈(ℤ/N)ˣ} θ⁻¹(c)·log_p(1−ε_N^c)`." Stated for tame conductor `D > 1`
    (replan R6.4; the §5.2 standing hypotheses), with `log_p` the extended
    logarithm `extLog` and the Gauss factor through the §5 clearing plus the
    coprime factorisation (C6-c4).
    
    **Statement-fix (replan R6 step 3a, recorded 2026-06-12 in `b2_log.jsonl`):**
    the §6 root `ε` is tied to the §5 split data via `{εp} (hεp) (hsplit : ε = ζ·εp)`
    (RJW's `ε_N` is any primitive `N`-th root; the split form `ζ·ε_{p^n}` realises it
    through the tame/wild factors). This is what enables the CRT Gauss-product split
    `G(θ⁻¹) = G(η⁻¹)·G(χ⁻¹)` (`gaussSum_mul_coprime`) and the `hGtwist` closed form. 
Proof for Theorem 6.3.3

We evaluate \big((1-\varphi\circ\psi)\widetilde F_\theta\big)(0) by computing the operator \varphi\circ\psi in two cases, using Lemma 6.3.2.

Case n>1 (so \chi\neq1). Since \chi vanishes on p\Zp, the twisted distribution \widetilde\mu_\theta=(\widetilde\mu_\eta)_\chi is supported on \Zpx, so \Res_{p\Zp}(\widetilde\mu_\theta)=0 and \varphi\circ\psi(\widetilde F_\theta)=0. Hence L_p(\theta,1)=\widetilde F_\theta(0), which we record as (1-\theta(p)p^{-1})\widetilde F_\theta(0) using \theta(p)=0.

Case n=0 (so N=D is coprime to p and \theta=\eta). Then \varphi\circ\psi(\widetilde F_\theta)(T)=\tfrac1p\sum_{\xi\in\mu_p}\widetilde F_\theta((1+T)\xi-1). Evaluating at T=0, the inner sum over \xi\in\mu_p collapses by the product identity \prod_{\xi\in\mu_p}(\xi\,\varepsilon_N^{\,c}-1)=\varepsilon_N^{\,pc}-1 (the roots of X^p-1; equivalently the norm of \xi\varepsilon_N^{\,c}-1 from \Q_p(\mu_p) to \Q_p), so \sum_{\xi}\log_p(\xi\varepsilon_N^{\,c}-1) =\log_p(\varepsilon_N^{\,pc}-1). Substituting the automorphism c\mapsto c'=pc of (\Z/N\Z)^\times (valid as p\nmid N) pulls out a factor \theta(p), giving \varphi\circ\psi(\widetilde F_\theta)(0)=\tfrac{\theta(p)}{p}\widetilde F_\theta(0). Therefore L_p(\theta,1)=(1-\theta(p)p^{-1})\widetilde F_\theta(0) again.

Finally, in all cases evaluate \widetilde F_\theta(0). Using \log_p(x)=\log_p(-x) for x\in\Cp^\times, we get \widetilde F_\theta(0)=-G(\theta^{-1})^{-1}\sum_c\theta^{-1}(c)\log_p(1-\varepsilon_N^{\,c}), and so L_p(\theta,1)=-(1-\theta(p)p^{-1})G(\theta^{-1})^{-1}\sum_c\theta^{-1}(c)\log_p(1-\varepsilon_N^{\,c}), as claimed.