From 29cae4315ff61a3124e77ff91fe401874e120612 Mon Sep 17 00:00:00 2001 From: Jaron Kent-Dobias Date: Mon, 15 Mar 2021 15:51:58 +0100 Subject: Big rewrite for clarity. --- bezout.tex | 394 +++++++++++++++++++++++++++++++------------------------------ 1 file changed, 202 insertions(+), 192 deletions(-) (limited to 'bezout.tex') diff --git a/bezout.tex b/bezout.tex index f950b8c..f050707 100644 --- a/bezout.tex +++ b/bezout.tex @@ -42,11 +42,11 @@ \maketitle -Spin-glasses have long been considered the paradigm of many variable `complex -landscapes,' a subject that includes neural networks and optimization problems, -most notably constraint satisfaction \cite{Mezard_2009_Information}. The most tractable family of these -are the mean-field spherical $p$-spin models \cite{Crisanti_1992_The} (for a -review see \cite{Castellani_2005_Spin-glass}) defined by the energy +Spin-glasses are the paradigm of many-variable `complex landscapes,' a category +that also includes neural networks and optimization problems like constraint +satisfaction \cite{Mezard_2009_Information}. The most tractable family of +these are the mean-field spherical $p$-spin models \cite{Crisanti_1992_The} +(for a review see \cite{Castellani_2005_Spin-glass}) defined by the energy \begin{equation} \label{eq:bare.hamiltonian} H_0 = \frac1{p!}\sum_{i_1\cdots i_p}^NJ_{i_1\cdots i_p}z_{i_1}\cdots z_{i_p}, \end{equation} @@ -58,11 +58,10 @@ from several angles: the replica trick to compute the Boltzmann--Gibbs distribution \cite{Crisanti_1992_The}, a Kac--Rice \cite{Kac_1943_On, Rice_1939_The, Fyodorov_2004_Complexity} procedure (similar to the Fadeev--Popov integral) to compute the number of saddle-points of the energy -function \cite{Crisanti_1995_Thouless-Anderson-Palmer}, and the -gradient-descent---or more generally Langevin---dynamics staring from a -high-energy configuration \cite{Cugliandolo_1993_Analytical}. Thanks to the -simplicity of the energy, all these approaches yield analytic results in the -large-$N$ limit. +function \cite{Crisanti_1995_Thouless-Anderson-Palmer}, and gradient-descent +(or more generally Langevin) dynamics starting from a high-energy configuration +\cite{Cugliandolo_1993_Analytical}. Thanks to the simplicity of the energy, all +these approaches yield analytic results in the large-$N$ limit. In this paper we extend the study to complex variables: we shall take $z\in\mathbb C^N$ and $J$ to be a symmetric tensor whose elements are @@ -77,7 +76,7 @@ random laser problems \cite{Antenucci_2015_Complex}. Quiver Hamiltonians---used to model black hole horizons in the zero-temperature limit---also have a Hamiltonian very close to ours \cite{Anninos_2016_Disordered}. A second reason is that, as we know from experience, extending a real problem to the complex -plane often uncovers underlying simplicity that is otherwise hidden, sheding +plane often uncovers underlying simplicity that is otherwise hidden, shedding light on the original real problem, e.g., as in the radius of convergence of a series. @@ -86,15 +85,16 @@ $2N$-dimensional complex space has turned out to be necessary for correctly defining and analyzing path integrals with complex action (see \cite{Witten_2010_A, Witten_2011_Analytic}), and as a useful palliative for the sign problem \cite{Cristoforetti_2012_New, Tanizaki_2017_Gradient, -Scorzato_2016_The}. In order to do this correctly, the features of landscape +Scorzato_2016_The}. In order to do this correctly, features of landscape of the action in complex space---like the relative position of its saddles---must be understood. Such landscapes are in general not random: here we propose to follow the strategy of computer science of understanding the -generic features of random instances, expecting that this sheds light on the +generic features of random instances, expecting that this sheds light on practical, nonrandom problems. Returning to our problem, the spherical constraint is enforced using the method -of Lagrange multipliers: introducing $\epsilon\in\mathbb C$, our energy is +of Lagrange multipliers: introducing $\epsilon\in\mathbb C$, our constrained +energy is \begin{equation} \label{eq:constrained.hamiltonian} H = H_0+\frac p2\epsilon\left(N-\sum_i^Nz_i^2\right). \end{equation} @@ -102,35 +102,35 @@ One might balk at the constraint $z^Tz=N$---which could appropriately be called a \emph{hyperbolic} constraint---by comparison with $z^\dagger z=N$. The reasoning behind the choice is twofold. -First, we seek draw conclusions from our model that would be applicable to -generic holomorphic functions without any symmetry. Samples of $H_0$ nearly -provide this, save for a single anomaly: the value of the energy and its -gradient at any point $z$ correlate along the $z$ direction, with -$\overline{H_0\partial H_0}\propto \overline{H_0(\partial H_0)^*}\propto z$. This -anomalous direction must be neglected if we are to draw conclusions about -generic functions, and the constraint surface $z^Tz=N$ is the unique surface +First, we seek draw conclusions from our model that are applicable to generic +holomorphic functions without any symmetry. Samples of $H_0$ nearly provide +this, save for a single anomaly: the value of the energy and its gradient at +any point $z$ correlate along the $z$ direction, with $\overline{H_0\partial +H_0}\propto \overline{H_0(\partial H_0)^*}\propto z$. This anomalous direction +must be neglected, and the constraint surface $z^Tz=N$ is the unique surface whose normal is parallel to $z$ and which contains the configuration space of the real $p$-spin model as a subspace. Second, taking the constraint to be the level set of a holomorphic function means the resulting configuration space is a \emph{bone fide} complex manifold, and therefore permits easy generalization of the integration techniques -referenced above. The same cannot be said for the space defined by $z^\dagger z=N$, -which is topologically the $(2N-1)$-sphere and cannot admit a complex +referenced above. The same cannot be said for the space defined by $z^\dagger +z=N$, which is topologically the $(2N-1)$-sphere and cannot admit a complex structure. A consequence of the constraint is that the model's configuration space is not -compact, nor is its energy bounded. This is not necessarily a problem, as many +compact, nor is its energy bounded. This is not necessarily problematic, as many related problems have similar properties but are concerned with subspaces on -which the energy is bounded. (In fact, identifying the appropriate subspace on -which to define one's model often requires the study of critical points in the -whole space.) Where it might be a problem, we introduce the additional -constraint $z^\dagger z\leq Nr^2$. The resulting configuration space is a complex -manifold with boundary. We shall see that the `radius' $r$ proves an insightful -knob in our present problem, revealing structure as it is varied. Note -that taking $r=1$ reduces the problem to that of the ordinary $p$-spin. - -The critical points are of $H$ given by the solutions to the set of equations +which the energy is bounded. (In fact, identifying the appropriate subspace +often requires the study of critical points in the whole space.) Where it might +become problematic, we introduce an additional constraint that bounds the +`radius' per spin $r^2\equiv z^\dagger z/N\leq R^2$. The resulting +configuration space is a complex manifold with boundary. We shall see that the +`radius' $r$ and its upper bound $R$ prove to be insightful knobs in our present +problem, revealing structure as they are varied. Note that taking $R=1$ reduces +the problem to that of the ordinary $p$-spin. + +The critical points are of $H$ given by the solutions to \begin{equation} \label{eq:polynomial} \frac{p}{p!}\sum_{j_1\cdots j_{p-1}}^NJ_{ij_1\cdots j_{p-1}}z_{j_1}\cdots z_{j_{p-1}} = p\epsilon z_i @@ -140,7 +140,7 @@ equations of degree $p-1$, to which one must add the constraint. In this sense this study also provides a complement to the work on the distribution of zeroes of random polynomials \cite{Bogomolny_1992_Distribution}, which are for $N=1$ and $p\to\infty$. We see from \eqref{eq:polynomial} that at any critical -point $\epsilon=H/N$, the average energy. +point $\epsilon=H_0/N$, the average energy. Since $H$ is holomorphic, any critical point of $\operatorname{Re}H$ is also one of $\operatorname{Im}H$, and therefore of $H$ itself. Writing $z=x+iy$ for @@ -149,7 +149,7 @@ function of $2N$ real variables. The number of critical points of $H$ is thus gi usual Kac--Rice formula applied to $\operatorname{Re}H$: \begin{equation} \label{eq:real.kac-rice} \begin{aligned} - \mathcal N&(\kappa,\epsilon,r) + \mathcal N&(\kappa,\epsilon,R) = \int dx\,dy\,\delta(\partial_x\operatorname{Re}H)\delta(\partial_y\operatorname{Re}H) \\ &\hspace{6pc}\times\left|\det\begin{bmatrix} \partial_x\partial_x\operatorname{Re}H & \partial_x\partial_y\operatorname{Re}H \\ @@ -157,11 +157,18 @@ usual Kac--Rice formula applied to $\operatorname{Re}H$: \end{bmatrix}\right|. \end{aligned} \end{equation} -The Cauchy--Riemann equations may be used to write this in a manifestly complex -way. With the Wirtinger derivative $\partial=\frac12(\partial_x-i\partial_y)$, -one can write $\partial_x\operatorname{Re}H=\operatorname{Re}\partial H$ and +This expression is to be averaged over $J$ to give the complexity $\Sigma$ as +$N \Sigma= \overline{\log\mathcal N}$, a calculation that involves the replica +trick. In most of the parameter space that we shall study here, the +\emph{annealed approximation} $N \Sigma \sim \log \overline{ \mathcal N}$ is +exact. + +The Cauchy--Riemann equations may be used to write \eqref{eq:real.kac-rice} in +a manifestly complex way. With the Wirtinger derivative +$\partial\equiv\frac12(\partial_x-i\partial_y)$, one can write +$\partial_x\operatorname{Re}H=\operatorname{Re}\partial H$ and $\partial_y\operatorname{Re}H=-\operatorname{Im}\partial H$. Carrying these -transformations through, we have +transformations through, one finds \begin{equation} \label{eq:complex.kac-rice} \begin{aligned} \mathcal N&(\kappa,\epsilon,r) @@ -177,8 +184,9 @@ transformations through, we have \end{aligned} \end{equation} This gives three equivalent expressions for the determinant of the Hessian: as -that of a $2N\times 2N$ real matrix, that of an $N\times N$ Hermitian matrix, -or the norm squared of that of an $N\times N$ complex symmetric matrix. +that of a $2N\times 2N$ real symmetric matrix, that of the $N\times N$ Hermitian +matrix $(\partial\partial H)^\dagger\partial\partial H$, or the norm squared of +that of the $N\times N$ complex symmetric matrix $\partial\partial H$. These equivalences belie a deeper connection between the spectra of the corresponding matrices. Each positive eigenvalue of the real matrix has a @@ -189,52 +197,13 @@ Hessian is therefore the same as the distribution of singular values of $\partial\partial H$, or the distribution of square-rooted eigenvalues of $(\partial\partial H)^\dagger\partial\partial H$. -The expression \eqref{eq:complex.kac-rice} is to be averaged over $J$ to give -the complexity $\Sigma$ as $N \Sigma= \overline{\log\mathcal N}$, a calculation -that involves the replica trick. In most of the parameter-space that we shall -study here, the \emph{annealed approximation} $N \Sigma \sim \log \overline{ -\mathcal N}$ is exact. - A useful property of the Gaussian $J$ is that gradient and Hessian at fixed -$\epsilon$ are statistically independent \cite{Bray_2007_Statistics, +energy $\epsilon$ are statistically independent \cite{Bray_2007_Statistics, Fyodorov_2004_Complexity}, so that the $\delta$-functions and the Hessian may -be averaged independently. The $\delta$-functions are converted to exponentials -by the introduction of auxiliary fields $\hat z=\hat x+i\hat y$. The average -of those factors over $J$ can then be performed. A generalized -Hubbard--Stratonovich allows a change of variables from the $4N$ original -and auxiliary fields to eight bilinears defined by $Na=z^\dagger z$, $N\hat a=\hat z^\dagger\hat z$, $N\hat c=\hat z^T\hat z$, $Nb=\hat z^\dagger z$, and $Nd=\hat z^Tz$ (and their -conjugates). The result, to leading order in $N$, is -\begin{equation} \label{eq:saddle} - \overline{\mathcal N}(\kappa,\epsilon,r) - = \int da\,d\hat a\,db\,db^*d\hat c\,d\hat c^*dd\,dd^*e^{Nf(a,\hat a,b,\hat c,d)}, -\end{equation} -where the argument of the exponential is -\begin{widetext} - \begin{equation} - f=2+\frac12\log\det\frac12\begin{bmatrix} - 1 & a & d & b \\ - a & 1 & b^* & d^* \\ - d & b^* & \hat c & \hat a \\ - b & d^* & \hat a & \hat c^* - \end{bmatrix} - +\int d\lambda\,\rho(\lambda)\log|\lambda|^2 - +p\operatorname{Re}\left\{ - \frac18\left[\hat aa^{p-1}+(p-1)|d|^2a^{p-2}+\kappa(\hat c^*+(p-1)b^2)\right]-\epsilon b - \right\}. - \end{equation} - The integral of the distribution $\rho$ of eigenvalues of $\partial\partial - H$ comes from the Hessian and is dependant on $a$ alone. This function has an - extremum in $\hat a$, $b$, $\hat c$, and $d$ at which its value is - \begin{equation} \label{eq:free.energy.a} - f(a)=1+\frac12\log\left(\frac4{p^2}\frac{a^2-1}{a^{2(p-1)}-|\kappa|^2}\right)+\int d\lambda\,\rho(\lambda)\log|\lambda|^2 - -2C_+[\operatorname{Re}(\epsilon e^{-i\theta})]^2-2C_-[\operatorname{Im}(\epsilon e^{-i\theta})]^2, - \end{equation} -\end{widetext} -where $\theta=\frac12\arg\kappa$ and -\begin{equation} - C_{\pm}=\frac{a^p(1+p(a^2-1))\mp a^2|\kappa|}{a^{2p}\pm(p-1)a^p(a^2-1)|\kappa|-a^2|\kappa|^2}. -\end{equation} -This leaves a single parameter, $a$, which dictates the norm of $z$. +be averaged independently. First we shall compute the spectrum of the Hessian, +which can in turn be used to compute the determinant. Then we will treat the +$\delta$-functions and the resulting saddle point equations. The results of +these calculations begin around \eqref{eq:bezout}. The Hessian $\partial\partial H=\partial\partial H_0-p\epsilon I$ is equal to the unconstrained Hessian with a constant added to its diagonal. The eigenvalue @@ -246,28 +215,28 @@ Hessian of the unconstrained Hamiltonian is =\frac{p(p-1)}{p!}\sum_{k_1\cdots k_{p-2}}^NJ_{ijk_1\cdots k_{p-2}}z_{k_1}\cdots z_{k_{p-2}}, \end{equation} which makes its ensemble that of Gaussian complex symmetric matrices, when the -direction along the constraint is neglected. Given its variances -$\overline{|\partial_i\partial_j H_0|^2}=p(p-1)a^{p-2}/2N$ and +anomalous direction normal to the constraint surface is neglected. Given its variances +$\overline{|\partial_i\partial_j H_0|^2}=p(p-1)r^{p-2}/2N$ and $\overline{(\partial_i\partial_j H_0)^2}=p(p-1)\kappa/2N$, $\rho_0(\lambda)$ is constant inside the ellipse \begin{equation} \label{eq:ellipse} - \left(\frac{\operatorname{Re}(\lambda e^{i\theta})}{a^{p-2}+|\kappa|}\right)^2+ - \left(\frac{\operatorname{Im}(\lambda e^{i\theta})}{a^{p-2}-|\kappa|}\right)^2 - <\frac{p(p-1)}{2a^{p-2}} + \left(\frac{\operatorname{Re}(\lambda e^{i\theta})}{r^{p-2}+|\kappa|}\right)^2+ + \left(\frac{\operatorname{Im}(\lambda e^{i\theta})}{r^{p-2}-|\kappa|}\right)^2 + <\frac{p(p-1)}{2r^{p-2}} \end{equation} where $\theta=\frac12\arg\kappa$ \cite{Nguyen_2014_The}. The eigenvalue spectrum of $\partial\partial H$ is therefore constant inside the same ellipse translated so that its center lies at $-p\epsilon$. Examples of these distributions are shown in the insets of Fig.~\ref{fig:spectra}. -The eigenvalue spectrum of the Hessian of the real part is different from the -spectrum $\rho(\lambda)$ of $\partial\partial H$, but rather equivalent to the +The eigenvalue spectrum of the Hessian of the real part is not the +spectrum $\rho(\lambda)$ of $\partial\partial H$, but instead the square-root eigenvalue spectrum of $(\partial\partial H)^\dagger\partial\partial H$; in other words, the singular value spectrum $\rho(\sigma)$ of $\partial\partial H$. When $\kappa=0$ and the elements of $J$ are standard complex normal, this is a complex Wishart distribution. For $\kappa\neq0$ the problem changes, and to our knowledge a closed form is not in the literature. We have worked out an -implicit form for this spectrum using the replica method. +implicit form for the singular value spectrum using the replica method. Introducing replicas to bring the partition function into the numerator of the Green function \cite{Livan_2018_Introduction} gives @@ -280,25 +249,24 @@ Green function \cite{Livan_2018_Introduction} gives \right] \right\}, \end{equation} - with sums taken over repeated Latin indices. The average is then made over + with sums taken over repeated Latin indices. The average is then made over $J$ and Hubbard--Stratonovich is used to change variables to the replica matrices - $N\alpha_{\alpha\beta}=(\zeta^{(\alpha)})^*\cdot\zeta^{(\beta)}$ and - $N\chi_{\alpha\beta}=\zeta^{(\alpha)}\cdot\zeta^{(\beta)}$ and a series of - replica vectors. The replica-symmetric ansatz leaves all off-diagonal - elements and vectors zero, and - $\alpha_{\alpha\beta}=\alpha_0\delta_{\alpha\beta}$, + $N\alpha_{\alpha\beta}=(\zeta^{(\alpha)})^\dagger\zeta^{(\beta)}$ and + $N\chi_{\alpha\beta}=(\zeta^{(\alpha)})^T\zeta^{(\beta)}$, and a series of + replica vectors. The replica-symmetric ansatz leaves all replica vectors + zero, and $\alpha_{\alpha\beta}=\alpha_0\delta_{\alpha\beta}$, $\chi_{\alpha\beta}=\chi_0\delta_{\alpha\beta}$. The result is \begin{equation}\label{eq:green.saddle} \overline G(\sigma)=N\lim_{n\to0}\int d\alpha_0\,d\chi_0\,d\chi_0^*\,\alpha_0 \exp\left\{nN\left[ - 1+\frac{p(p-1)}{16}a^{p-2}\alpha_0^2-\frac{\alpha_0\sigma}2+\frac12\log(\alpha_0^2-|\chi_0|^2) + 1+\frac{p(p-1)}{16}r^{p-2}\alpha_0^2-\frac{\alpha_0\sigma}2+\frac12\log(\alpha_0^2-|\chi_0|^2) +\frac p4\operatorname{Re}\left(\frac{(p-1)}8\kappa^*\chi_0^2-\epsilon^*\chi_0\right) \right]\right\}. \nonumber % He's too long, and we don't cite him (now)! \end{equation} \end{widetext} -\begin{figure}[b] +\begin{figure} \centering \includegraphics{fig/spectra_0.0.pdf} @@ -307,25 +275,27 @@ Green function \cite{Livan_2018_Introduction} gives \includegraphics{fig/spectra_1.5.pdf} \caption{ - Eigenvalue and singular value spectra of the matrix $\partial\partial H$ - for $p=3$, $a=\frac54$, and $\kappa=\frac34e^{-i3\pi/4}$ with (a) - $\epsilon=0$, (b) $\epsilon=-\frac12|\epsilon_{\mathrm{th}}|$, (c) + Eigenvalue and singular value spectra of the Hessian $\partial\partial H$ + of the $3$-spin model with $\kappa=\frac34e^{-i3\pi/4}$. Pictured + distributions are for critical points at `radius' $r=\sqrt{5/4}$ and with + energy per spin (a) $\epsilon=0$, (b) + $\epsilon=-\frac12|\epsilon_{\mathrm{th}}|$, (c) $\epsilon=-|\epsilon_{\mathrm{th}}|$, and (d) - $\epsilon=-\frac32|\epsilon_{\mathrm{th}}|$. The shaded region of each inset - shows the support of the eigenvalue distribution. The solid line on each - plot shows the distribution of singular values, while the overlaid - histogram shows the empirical distribution from $2^{10}\times2^{10}$ complex - normal matrices with the same covariance and diagonal shift as - $\partial\partial H$. + $\epsilon=-\frac32|\epsilon_{\mathrm{th}}|$. The shaded region of each + inset shows the support of the eigenvalue distribution \eqref{eq:ellipse}. + The solid line on each plot shows the distribution of singular values + \eqref{eq:spectral.density}, while the overlaid histogram shows the + empirical distribution from $2^{10}\times2^{10}$ complex normal matrices + with the same covariance and diagonal shift as $\partial\partial H$. } \label{fig:spectra} \end{figure} The argument of the exponential has several saddles. The solutions $\alpha_0$ are the roots of a sixth-order polynomial, and the root with the smallest value -of $\operatorname{Re}\alpha_0$ in all the cases we studied gives the correct -solution. A detailed analysis of the saddle point integration is needed to -understand why this is so. Given such $\alpha_0$, the density of singular -values follows from the jump across the cut, or +of $\operatorname{Re}\alpha_0$ gives the correct solution in all the cases we +studied. A detailed analysis of the saddle point integration is needed to +understand why this is so. Evaluated at such a solution, the density of +singular values follows from the jump across the cut, or \begin{equation} \label{eq:spectral.density} \rho(\sigma)=\frac1{i\pi N}\left( \lim_{\operatorname{Im}\sigma\to0^+}\overline G(\sigma) @@ -335,70 +305,109 @@ values follows from the jump across the cut, or Examples can be seen in Fig.~\ref{fig:spectra} compared with numeric experiments. -The transition from a one-cut to two-cut singular value spectrum naturally -corresponds to the origin leaving the support of the eigenvalue spectrum. -Weyl's theorem requires that the product over the norm of all eigenvalues must -not be greater than the product over all singular values \cite{Weyl_1912_Das}. -Therefore, the absence of zero eigenvalues implies the absence of zero singular -values. The determination of the threshold energy -- the energy at which the -distribution of singular values becomes gapped -- is then reduced to a -geometry problem, and yields +The formation of a gap in the singular value spectrum naturally corresponds to +the origin leaving the support of the eigenvalue spectrum. Weyl's theorem +requires that the product over the norm of all eigenvalues must not be greater +than the product over all singular values \cite{Weyl_1912_Das}. Therefore, the +absence of zero eigenvalues implies the absence of zero singular values. The +determination of the threshold energy---the energy at which the distribution +of singular values becomes gapped---is reduced to the geometry problem of +determining when the boundary of the ellipse defined in \eqref{eq:ellipse} +intersects the origin, and yields \begin{equation} \label{eq:threshold.energy} |\epsilon_{\mathrm{th}}|^2 - =\frac{p-1}{2p}\frac{(1-|\delta|^2)^2a^{p-2}} + =\frac{p-1}{2p}\frac{(1-|\delta|^2)^2r^{p-2}} {1+|\delta|^2-2|\delta|\cos(\arg\kappa+2\arg\epsilon)} \end{equation} -for $\delta=\kappa a^{-(p-2)}$. +for $\delta=\kappa r^{-(p-2)}$. Notice that the threshold depends on both the +energy per spin $\epsilon$ on the `radius' $r$ of the saddle. + +We will now address the $\delta$-functions of \eqref{eq:complex.kac-rice}. +These are converted to exponentials by the introduction of auxiliary fields +$\hat z=\hat x+i\hat y$. The average over $J$ can then be performed. A +generalized Hubbard--Stratonovich allows a change of variables from the $4N$ +original and auxiliary fields to eight bilinears defined by $Nr=z^\dagger z$, +$N\hat r=\hat z^\dagger\hat z$, $Na=\hat z^\dagger z$, $Nb=\hat z^Tz$, and +$N\hat c=\hat z^T\hat z$ (and their conjugates). The result, to leading order +in $N$, is +\begin{equation} \label{eq:saddle} + \overline{\mathcal N}(\kappa,\epsilon,R) + = \int dr\,d\hat r\,da\,da^*db\,db^*d\hat c\,d\hat c^*e^{Nf(r,\hat r,a,b,\hat c)}, +\end{equation} +where the argument of the exponential is +\begin{widetext} + \begin{equation} + f=2+\frac12\log\det\frac12\begin{bmatrix} + 1 & r & b & a \\ + r & 1 & a^* & b^* \\ + b & a^* & \hat c & \hat r \\ + a & b^* & \hat r & \hat c^* + \end{bmatrix} + +\int d\lambda\,d\lambda^*\rho(\lambda)\log|\lambda|^2 + +p\operatorname{Re}\left\{ + \frac18\left[\hat rr^{p-1}+(p-1)|b|^2r^{p-2}+\kappa(\hat c^*+(p-1)a^2)\right]-\epsilon a + \right\}. + \end{equation} + The spectrum $\rho$ is given in \eqref{eq:ellipse} and is dependant on $r$ alone. This function has an + extremum in $\hat r$, $a$, $b$, and $\hat c$ at which its value is + \begin{equation} \label{eq:free.energy.a} + f=1+\frac12\log\left(\frac4{p^2}\frac{r^2-1}{r^{2(p-1)}-|\kappa|^2}\right)+\int d\lambda\,\rho(\lambda)\log|\lambda|^2 + -2C_+[\operatorname{Re}(\epsilon e^{-i\theta})]^2-2C_-[\operatorname{Im}(\epsilon e^{-i\theta})]^2, + \end{equation} +\end{widetext} +where $\theta=\frac12\arg\kappa$ and +\begin{equation} + C_{\pm}=\frac{r^p(1+p(r^2-1))\mp r^2|\kappa|}{r^{2p}\pm(p-1)r^p(r^2-1)|\kappa|-r^2|\kappa|^2}. +\end{equation} +Notice that level sets of $f$ in energy $\epsilon$ also give ellipses, but of +different form from the ellipse in \eqref{eq:ellipse}. -Given $\rho$, the integral in \eqref{eq:free.energy.a} may be preformed for -arbitrary $a$. The resulting expression is maximized for $a=r^2$ for all -values of $\kappa$ and $\epsilon$. Evaluating the complexity at this saddle, in -the limit of unbounded spins, gives +This expression is maximized for $r=R$, its value at the boundary, for +all values of $\kappa$ and $\epsilon$. Evaluating the complexity at this +saddle, in the limit of unbounded spins, gives \begin{equation} \label{eq:bezout} - \lim_{r\to\infty}\log\overline{\mathcal N}(\kappa,\epsilon,r) + \lim_{R\to\infty}\log\overline{\mathcal N}(\kappa,\epsilon,R) =N\log(p-1). \end{equation} -This is, to this order, precisely the Bézout bound, the maximum number of -solutions that $N$ equations of degree $p-1$ may have -\cite{Bezout_1779_Theorie}. That we saturate this bound is perhaps not -surprising, since the coefficients of our polynomial equations -\eqref{eq:polynomial} are complex and have no symmetries. Reaching Bézout in -\eqref{eq:bezout} is not our main result, but it provides a good check. -Analogous asymptotic scaling has been found for the number of pure Higgs states -in supersymmetric quiver theories \cite{Manschot_2012_From}. +This is, to leading order, precisely the Bézout bound, the maximum number of +solutions to $N$ equations of degree $p-1$ \cite{Bezout_1779_Theorie}. That we +saturate this bound is perhaps not surprising, since the coefficients of our +polynomial equations \eqref{eq:polynomial} are complex and have no symmetries. +Reaching Bézout in \eqref{eq:bezout} is not our main result, but it provides a +good check. Analogous asymptotic scaling has been found for the number of pure +Higgs states in supersymmetric quiver theories \cite{Manschot_2012_From}. \begin{figure}[htpb] \centering \includegraphics{fig/complexity.pdf} \caption{ - The complexity of the 3-spin model at $\epsilon=0$ as a function of - the maximum `radius' $r$ at several values of $\kappa$. The dashed line - shows $\frac12\log(p-1)$, while the dotted shows $\log(p-1)$. + The complexity of the 3-spin model as a function of the maximum `radius' + $R$ at zero energy and several values of $\kappa$. The dashed line shows + $\frac12\log(p-1)$, while the dotted shows $\log(p-1)$. } \label{fig:complexity} \end{figure} -For finite $r$, everything is analytically tractable at $\epsilon=0$, giving +For finite $R$, everything is analytically tractable at $\epsilon=0$: \begin{equation} \label{eq:complexity.zero.energy} - \Sigma(\kappa,0,r) - =\log(p-1)-\frac12\log\left(\frac{1-|\kappa|^2r^{-4(p-1)}}{1-r^{-4}}\right). + \Sigma(\kappa,0,R) + =\log(p-1)-\frac12\log\left(\frac{1-|\kappa|^2R^{-4(p-1)}}{1-R^{-4}}\right). \end{equation} -This is plotted as a function of $r$ for -several values of $\kappa$ in Fig.~\ref{fig:complexity}. For any $|\kappa|<1$, -the complexity goes to negative infinity as $r\to1$, i.e., as the spins are -restricted to the reals. This is natural, given that the $y$ contribution to -the volume shrinks to zero as that of an $N$-dimensional sphere $\sum_i y_i^2=N(r^2-1)$ with volume -$\sim(r^2-1)^N$. However, when the result is analytically continued to +This is plotted as a function of $R$ for several values of $\kappa$ in +Fig.~\ref{fig:complexity}. For any $|\kappa|<1$, the complexity goes to +negative infinity as $R\to1$, i.e., as the spins are restricted to the reals. +This is natural, since volume of configuration space vanishes in this limit +like $(R^2-1)^N$. However, when the result is analytically continued to $\kappa=1$ (which corresponds to real $J$) something novel occurs: the -complexity has a finite value at $r=1$. Since the $r$-dependence gives a -cumulative count, this implies a $\delta$-function density of critical points -along the line $y=0$. The number of critical points contained within is +complexity has a finite value at $R=1$. This implies a $\delta$-function +density of critical points on the $r=1$ (or $y=0$) boundary. The number of +critical points contained there is \begin{equation} - \lim_{r\to1}\lim_{\kappa\to1}\log\overline{\mathcal N}(\kappa,0,r) + \lim_{R\to1}\lim_{\kappa\to1}\log\overline{\mathcal N}(\kappa,0,R) = \frac12N\log(p-1), \end{equation} half of \eqref{eq:bezout} and corresponding precisely to the number of critical -points of the real $p$-spin model (note the role of conjugation symmetry, -already underlined in \cite{Bogomolny_1992_Distribution}). The full +points of the real $p$-spin model. (Note the role of conjugation symmetry, +already underlined in \cite{Bogomolny_1992_Distribution}.) The full $\epsilon$-dependence of the real $p$-spin is recovered by this limit as $\epsilon$ is varied. @@ -406,7 +415,7 @@ $\epsilon$ is varied. \centering \includegraphics{fig/desert.pdf} \caption{ - The value of `radius' $r$ for which $\Sigma(\kappa,\epsilon,r)=0$ as a + The value of bounding `radius' $R$ for which $\Sigma(\kappa,\epsilon,R)=0$ as a function of (real) energy per spin $\epsilon$ for the 3-spin model at several values of $\kappa$. Above each line the complexity is positive and critical points proliferate, while below it the complexity is negative and @@ -416,25 +425,25 @@ $\epsilon$ is varied. } \label{fig:desert} \end{figure} -In the thermodynamic limit \eqref{eq:complexity.zero.energy} implies that most -critical points are concentrated at infinite radius, i.e., at complex vectors with -very large squared norm. For finite $N$ the average radius of critical points is likewise finite. By differentiating $\overline{\mathcal N}$ with -respect to $r$ and normalizing, one has the distribution -of critical points as a function of $r$. The average radius this yields is -$\propto N^{1/4}+O(N^{-3/4})$. One therefore expects typical -critical points to have a norm that grows modestly with system size. +In the thermodynamic limit, \eqref{eq:complexity.zero.energy} implies that most +critical points are concentrated at infinite radius $r$. For finite $N$ the +average radius of critical points is likewise finite. By differentiating +$\overline{\mathcal N}$ with respect to $R$ and normalizing, one obtains the +distribution of critical points as a function of $r$. This yields an average +radius proportional to $N^{1/4}$. One therefore expects typical critical +points to have a norm that grows modestly with system size. These qualitative features carry over to nonzero $\epsilon$. In -Fig.~\ref{fig:desert} we show that for $\kappa<1$ there is always a gap of $r$ -close to one for which there are no solutions. When $\kappa=1$---the analytic -continuation to the real computation---the situation is more interesting. In -the range of energies where there are real solutions this gap closes, which is -only possible if the density of solutions diverges at $r=1$. Another -remarkable feature of this limit is that there is still a gap without solutions -around `deep' real energies where there is no real solution. A moment's thought -tells us that this is a necessity: otherwise a small perturbation of the $J$s -could produce an unusually deep solution to the real problem, in a region where -this should not happen. +Fig.~\ref{fig:desert} we show that for $\kappa<1$ there is always a gap in $r$ +close to one in which solutions are exponentially suppressed. When +$\kappa=1$---the analytic continuation to the real computation---the situation +is more interesting. In the range of energies where there are real solutions +this gap closes, which is only possible if the density of solutions diverges at +$r=1$. Outside this range, around `deep' real energies where real solutions are +exponentially suppressed, the gap remains. A moment's thought tells us that +this is necessary: otherwise a small perturbation of the $J$s could produce +an unusually deep solution to the real problem, in a region where this should +not happen. \begin{figure}[t] \centering @@ -447,37 +456,38 @@ this should not happen. \caption{ Energies at which states exist (green shaded region) and threshold energies (black solid line) for the 3-spin model with - $\kappa=\frac34e^{-i3\pi/4}$ and (a) $a=2$, (b) $a=1.325$, (c) $a=1.125$, - and (d) $a=1$. No shaded region is shown in (d) because no states exist at + $\kappa=\frac34e^{-i3\pi/4}$ and (a) $r=\sqrt2$, (b) $r=\sqrt{1.325}$, (c) $r=\sqrt{1.125}$, + and (d) $r=1$. No shaded region is shown in (d) because no states exist at any energy. } \label{fig:eggs} \end{figure} The relationship between the threshold and ground, or extremal, state energies -is richer than in the real case. In Fig.~\ref{fig:eggs} these are shown in the +is richer than in the real case. In Fig.~\ref{fig:eggs} these are shown in the complex-$\epsilon$ plane for several examples. Depending on the parameters, the -threshold might always come at smaller magnitude than the extremal state, or -always come at larger magnitude, or cross as a function of complex argument. -For sufficiently large $r$ the threshold always comes at larger magnitude than -the extremal state. If this were to happen in the real case, it would likely -imply our replica symmetric computation is unstable, since having a ground -state above the threshold implies a ground state Hessian with many negative -eigenvalues, a contradiction. However, this is not an obvious contradiction in -the complex case. The relationship between the threshold, i.e., where the gap -appears, and the dynamics of, e.g., a minimization algorithm or physical -dynamics, are a problem we hope to address in future work. - - This paper provides a first step towards the study of a complex landscape with - complex variables. The next obvious one is to study the topology of the +threshold might have a smaller or larger magnitude than the extremal state, or +cross as a function of complex argument. For sufficiently large $r$ the +threshold is always at a larger magnitude. If this were to happen in the real +case, it would likely imply our replica symmetric computation were unstable, +since having a ground state above the threshold implies a ground state Hessian +with many negative eigenvalues, a contradiction. However, this is not an +contradiction in the complex case, where the energy is not bounded from below. +The relationship between the threshold, i.e., where the gap appears, and the +dynamics of, e.g., a minimization algorithm, deformed integration cycle, or +physical dynamics, are a problem we hope to address in future work. + + This paper provides a first step towards the study of complex landscapes with + complex variables. The next obvious step is to study the topology of the critical points, the sets reached following gradient descent (the Lefschetz thimbles), and ascent (the anti-thimbles) \cite{Witten_2010_A, Witten_2011_Analytic, Cristoforetti_2012_New, Behtash_2017_Toward, Scorzato_2016_The}, which act as constant-phase integrating `contours.' Locating and counting the saddles that are joined by gradient lines---the Stokes points, which play an important role in the theory---is also well within - reach of the present-day spin-glass literature techniques. We anticipate - that the threshold level, where the system develops a mid-spectrum gap, will - play a crucial role as it does in the real case. + reach of the present-day spin-glass literature techniques. We anticipate + that the threshold level, where the system develops a mid-spectrum gap, plays + a crucial role in determining whether these Stokes points proliferate under + some continuous change of parameters. \begin{acknowledgments} We wish to thank Alexander Altland, Satya Majumdar and Gregory Schehr for a useful suggestions. -- cgit v1.2.3-54-g00ecf