ScalingStacks

An example [01KJ]

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An example

Let us give some explicit formulae for the lower-bound above, in some particular cases. We consider X=𝐏1X=\mathbf{P}^{1} over 𝐐{\mathbf{Q}} and the metrized line bundle π’ͺ⁑(1)Β―W\overline{\mathscr{O}(1)}_{\mathrm{W}}. Let Ο†\varphi and ψ\psi be polynomials with integral coefficients, of degrees β„“\ell and mm respectively ; let us pose LΒ―=Ο†βˆ—β€‹π’ͺ⁑(1)Β―W\overline{L}=\varphi^{*}\overline{\mathscr{O}(1)}_{\mathrm{W}}, MΒ―=Οˆβˆ—β€‹π’ͺ⁑(1)Β―W\overline{M}=\psi^{*}\overline{\mathscr{O}(1)}_{\mathrm{W}}. The line bundle LΒ―mβŠ—LΒ―βˆ’β„“\overline{L}^{m}\otimes\overline{L}^{-\ell} is trivial and its metric is given by a family of functions (fv)(f_{v}). Since Ο†\varphi and ψ\psi have integral coefficients, fv=0f_{v}=0 at all finite places. Moreover, since gL¯​(x)=log⁑max⁑(|φ⁑(x)|​,1)g_{\overline{L}}(x)=\log\max(\left|{\varphi(x)}\right|,1) and gM¯​(x)=log⁑max⁑(|ψ⁑(x)|​,1)g_{\overline{M}}(x)=\log\max(\left|{\psi(x)}\right|,1) are the Green functions for the divisors ℓ⁑[∞]\ell[\infty] and m⁑[∞]m[\infty] respectively, one has

fβˆžβ€‹(x)=log⁑max⁑(|φ⁑(x)|m​,1)max⁑(|ψ⁑(x)|ℓ​,1).f_{\infty}(x)=\log\frac{\max(\left|{\varphi(x)}\right|^{m},1)}{\max(\left|{\psi(x)}\right|^{\ell},1)}.

Then,

ddc⁑f∞=m2​π​d​Arg⁑φ⁑(x)∧δ|φ⁑(x)|=1βˆ’β„“2​π​d​Arg⁑ψ⁑(x)∧δ|ψ⁑(x)|=1\mathop{\mathrm{d}\mathrm{d}^{c}}f_{\infty}=\frac{m}{2\pi}\mathrm{d}\operatorname{Arg}\varphi(x)\wedge\delta_{\left|{\varphi(x)}\right|=1}-\frac{\ell}{2\pi}\mathrm{d}\operatorname{Arg}\psi(x)\wedge\delta_{\left|{\psi(x)}\right|=1}

From this, we deduce that

π’Ÿβ‘(f∞)\displaystyle\mathscr{D}(f_{\infty}) =ℓ​m2​π​(∫|ψ⁑(x)|=1log⁑max⁑(|φ⁑(x)|​,1)​d​Arg⁑ψ⁑(x)CLOSE\displaystyle=\frac{\ell m}{2\pi}\left(\int_{\left|{\psi(x)}\right|=1}\log\max(\left|{\varphi(x)}\right|,1)\mathrm{d}\operatorname{Arg}\psi(x)\right.
+∫|φ⁑(x)|=1logmax(|ψ(x)|,1)dArgΟ†(x)),\displaystyle\qquad{}\left.+\int_{\left|{\varphi(x)}\right|=1}\log\max(\left|{\psi(x)}\right|,1)\mathrm{d}\operatorname{Arg}\varphi(x)\right),

the two others terms vanishing. In fact, Stokes’s formula implies that the two terms within the parentheses in the previous formula are equal and we have

π’Ÿβ‘(f∞)=ℓ​mΟ€β€‹βˆ«|φ⁑(x)|=1log⁑max⁑(|ψ⁑(x)​,1|)​d​Arg⁑φ⁑(x).\mathscr{D}(f_{\infty})=\frac{\ell m}{\pi}\int_{\left|{\varphi(x)}\right|=1}\log\max(\left|{\psi(x),1}\right|)\mathrm{d}\operatorname{Arg}\varphi(x).

The simplest case to study is for φ⁑(x)=xβ„“\varphi(x)=x^{\ell}. Then,

π’Ÿβ‘(f∞)=ℓ​mΟ€β€‹βˆ«02​πlog⁑max⁑(|ψ⁑(ei​θ)|​,1)​𝑑θ\mathscr{D}(f_{\infty})=\frac{\ell m}{\pi}\int_{0}^{2\pi}\log\max(\left|{\psi(e^{i\theta})}\right|,1)\,\mathrm{d}\theta

is 2​ℓ​m2\ell m times the logarithm of the variant M+​(ψ)\mathrm{M}^{+}(\psi) of the Mahler measure of ψ\psi :

M+​(ψ)=exp⁑(12β€‹Ο€β€‹βˆ«02​πlog⁑max⁑(|ψ⁑(ei​θ)|​,1)​𝑑θ).\mathrm{M}^{+}(\psi)=\exp\left(\frac{1}{2\pi}\int_{0}^{2\pi}\log\max(\left|{\psi(e^{i\theta})}\right|,1)\,\mathrm{d}\theta\right).

In fact, Jensen’s formula implies that

M+​(ψ)=exp⁑(1(2​π)2β€‹βˆ«02​πlog⁑|ψ⁑(ei​θ1)βˆ’ei​θ2|​d​θ1​d​θ2)\mathrm{M}^{+}(\psi)=\exp\left(\frac{1}{(2\pi)^{2}}\int_{0}^{2\pi}\log\left|{\psi(e^{i\theta_{1}})-e^{i\theta_{2}}}\right|\,\mathrm{d}\theta_{1}\mathrm{d}\theta_{2}\right)

is the Mahler measure M⁑(ψ⁑(x)βˆ’y)\mathrm{M}(\psi(x)-y) of the 2-variables polynomial ψ⁑(x)βˆ’y\psi(x)-y.

Consequently, except for finitely many exceptions, any algebraic point x∈𝐏1​(𝐐¯)x\in{\mathbf{P}}^{1}(\overline{{\mathbf{Q}}}) satisfies

ℓ​h​(x)+h⁑(ψ⁑(x))β‰₯1β„“+m​log⁑M⁑(ψ⁑(x)βˆ’y).\ell h(x)+h(\psi(x))\geq\frac{1}{\ell+m}\log\mathrm{M}(\psi(x)-y).

For β„“=1\ell=1 and ψ⁑(x)=1βˆ’x\psi(x)=1-x, we obtain that up to finitely many exceptions,

h⁑(x)+h⁑(1βˆ’x)β‰₯12​log⁑M⁑(1βˆ’xβˆ’y)β‰ˆ0.161538,h(x)+h(1-x)\geq\frac{1}{2}\log\mathrm{M}(1-x-y)\approx 0.161538,

In that particular case, Zagier [56] has proved a much more precise result : except for 5 explicit points in 𝐏1{\mathbf{P}}^{1},

h⁑(x)+h⁑(1βˆ’x)β‰₯12​log⁑(1+52)β‰ˆ0.240606.h(x)+h(1-x)\geq\frac{1}{2}\log(\frac{1+\sqrt{5}}{2})\approx 0.240606.

Observe also that if (xj)(x_{j}) is a sequence of points such that h⁑(xj)β†’0h(x_{j})\rightarrow 0, Theorem 3.3.1 implies that h⁑(1βˆ’x)β†’log⁑M⁑(1βˆ’xβˆ’y)β‰ˆ0.323076h(1-x)\rightarrow\log\mathrm{M}(1-x-y)\approx 0.323076.

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