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author | Jaron Kent-Dobias <jaron@kent-dobias.com> | 2024-08-01 10:42:24 +0200 |
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committer | Jaron Kent-Dobias <jaron@kent-dobias.com> | 2024-08-01 10:42:24 +0200 |
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tree | e22c0428c0df3e8efa3d5be98c3e565acda01f05 /topology.tex | |
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Some writing.
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diff --git a/topology.tex b/topology.tex index 84b871d..de4576c 100644 --- a/topology.tex +++ b/topology.tex @@ -34,33 +34,77 @@ exponentially large in $N$, indicating a shattering transition in the space of solutions. Finally, when $\alpha_\mathrm a^*\leq\alpha$, the number of solutions vanish. We further compute the average logarithm of the Euler - characteristic, which is representative of typical manifolds. + characteristic, which is representative of typical manifolds. We compare + these results with the analogous calculation for the topology of level sets + of the spherical spin glasses, whose connected phase has a negative Euler + characteristic indicative of many holes. \end{abstract} \maketitle -$\Omega=\{\mathbf x\in\mathbb R^N\mid \|\mathbf x\|^2=N,0=V_k(\mathbf x)\text{ for all $1\leq k\leq M$}\}$. -$\Omega$ is almost always a manifold without singular points due to -intersections. The conditions of a singular point are that +We consider the problem of finding configurations $\mathbf x\in\mathbb R^N$ +lying on the $(N-1)$-sphere $\|\mathbf x\|^2=N$ that simultaneously satisfy $M$ +nonlinear constraints $V_k(\mathbf x)=0$ for $1\leq k\leq M$. The nonlinear +constraints are taken to be centered Gaussian random functions with covariance +\begin{equation} \label{eq:covariance} + \overline{V_i(\mathbf x)V_j(\mathbf x')}=\delta_{ij}f\left(\frac{\mathbf x\cdot\mathbf x'}N\right) +\end{equation} +for some choice of $f$. +When the covariance function $f$ is polynomial, the $V_k$ are also polynomial, with terms of degree $p$ in $f$ corresponding to all possible terms of degree $p$ in $V_k$. In particular, taking +\begin{equation} + V_k(\mathbf x) + =\sum_{p=0}^\infty\frac1{p!}\sqrt{\frac{f^{(p)}(0)}{N^p}} + \sum_{i_1\cdots i_p}^NJ^{(k,p)}_{i_1\cdots i_p}x_{i_1}\cdots x_{i_p} +\end{equation} +and each of the elements of the tensors $J^{(k,p)}$ as independently +distributed with a unit normal distribution satisfies \eqref{eq:covariance}. + + +This problem or small variations thereof have attracted attention recently for +their resemblance to encryption, optimization, and vertex models of confluent +tissues \cite{Fyodorov_2019_A, Fyodorov_2020_Counting, + Fyodorov_2022_Optimization, Urbani_2023_A, Kamali_2023_Dynamical, + Kamali_2023_Stochastic, Urbani_2024_Statistical, Montanari_2023_Solving, +Montanari_2024_On}. In each of these cases, the authors studied properties of +the cost function +\begin{equation} + \mathcal C(\mathbf x)=\frac12\sum_{k=1}^MV_k(\mathbf x)^2 +\end{equation} +which achieves zero cost only for configurations that satisfy all the +constraints. Here we dispense with defining a cost function, and instead study +the set of solutions directly. + +The set of solutions to our nonlinear random constraint satisfaction problem +can be written as +\begin{equation} + \Omega=\{\mathbf x\in\mathbb R^N\mid \|\mathbf x\|^2=N,0=V_k(\mathbf x) + \;\forall\;k=1,\ldots,M\} +\end{equation} +$\Omega$ is almost always a manifold without singular points. The conditions for a singular point are that $0=\frac\partial{\partial\mathbf x}V_k(\mathbf x)$ for all $k$. This is equivalent to asking that the constraints $V_k$ all have a stationary point at the same place. When the $V_k$ are independent and random, this is vanishingly unlikely, requiring $NM$ independent equations to be simultaneously satisfied. - -The Euler characteristic $\chi$ of a manifold is a topological invariant. It is -perhaps most familiar in the context of connected compact 2-manifolds, where it -characterizes the number of holes in the surface: $\chi=2(1-\#)$ for $\#$ -holes. +This means that different connected components of the set of solutions do not +intersect, nor are there self-intersections, without extraordinary fine-tuning. + +The Euler characteristic $\chi$ of a manifold is a topological invariant \cite{Hatcher_2002_Algebraic}. It is +perhaps most familiar in the context of connected compact orientable surfaces, where it +characterizes the number of handles in the surface: $\chi=2(1-\#)$ for $\#$ +handles. For general $d$, the Euler characteristic of the $d$-sphere is $2$ if $d$ is even and 0 if $d$ is odd. The canonical method for computing the Euler characteristic is done by +defining a complex on the manifold in question, essentially a +higher-dimensional generalization of a polygonal tiling. Then $\chi$ is given +by an alternating sum over the number of cells of increasing dimension, which +for 2-manifolds corresponds to the number of vertices, minus the number of +edges, plus the number of faces. Morse theory offers another way to compute the Euler characteristic using the -statistics of stationary points of function $H$ defined on the manifold. For -function $H$ without any symmetries with respect to the manifold, the surfaces -of gradient flow between adjacent stationary points form a complex, i.e., a -higher-dimension polygonization of the surface. The standard counting argument -to compute $\chi$ of vertices minus edges plus faces generalizes to an -alternating sum over the counts of stationary points that make up the complex, -or +statistics of stationary points of a function $H:\Omega\to\mathbb R$ \cite{Audin_2014_Morse}. For +functions $H$ without any symmetries with respect to the manifold, the surfaces +of gradient flow between adjacent stationary points form a complex. The +alternating sum over cells to compute $\chi$ becomes an alternating sum over +the count of stationary points of $H$ with increasing index, or \begin{equation} \chi=\sum_{i=0}^N(-1)^i\mathcal N_H(\text{index}=i) \end{equation} @@ -69,20 +113,27 @@ using a small variation on the Kac--Rice formula for counting stationary points. Since the sign of the determinant of the Hessian matrix of $H$ at a stationary point is equal to its index, if we count stationary points including the sign of the determinant, we arrive at the Euler characteristic, or -\begin{equation} +\begin{equation} \label{eq:kac-rice} \chi=\int_\Omega d\mathbf x\,\delta\big(\nabla H(\mathbf x)\big)\det\operatorname{Hess}H(\mathbf x) \end{equation} When the Kac--Rice formula is used to \emph{count} stationary points, the sign of the determinant is a nuisance that one must take pains to preserve \cite{Fyodorov_2004_Complexity}. Here we are correct to exclude it. +We treat the integral over the implicitly defined manifold $\Omega$ using the +method of Lagrange multipliers. We introduce one multiplier $\omega_0$ to +enforce the spherical constraint and $M$ multipliers $\omega_k$ to enforce the vanishing of +each of the $V_k$, resulting in the Lagrangian \begin{equation} L(\mathbf x,\pmb\omega) =H(\mathbf x)+\frac12\omega_0\big(\|\mathbf x\|^2-N\big) - +\sum_{k=1}^M\omega_iV_k(\mathbf x) + +\sum_{k=1}^M\omega_kV_k(\mathbf x) \end{equation} +The integral over $\Omega$ in \eqref{eq:kac-rice} then becomes \begin{equation} - \chi=\int_{\mathbb R^N} d\mathbf x\,d\pmb\omega\,\delta\big(\partial L(\mathbf x,\pmb\omega)\big)\det\partial\partial L(\mathbf x,\pmb\omega) + \chi=\int_{\mathbb R^N} d\mathbf x\int_{\mathbb R^{M+1}}d\pmb\omega + \,\delta\big(\partial L(\mathbf x,\pmb\omega)\big) + \det\partial\partial L(\mathbf x,\pmb\omega) \end{equation} where $\partial=[\frac\partial{\partial\mathbf x},\frac\partial{\partial\pmb\omega}]$ is the vector of partial derivatives with respect to all $N+M+1$ variables. @@ -104,7 +155,7 @@ Using standard manipulations, we find \end{equation} Now we are forced to make a decision about the function $H$. Because $\chi$ is a topological invariant, any choice will work so long as it does not share some -symmetry with the underlying manifold. Because our manifold of random +symmetry with the underlying manifold, i.e., that it $H$ satisfies the Smale condition. Because our manifold of random constraints has no symmetries, we can take a simple height function $H(\mathbf x)=\mathbf x_0\cdot\mathbf x$ for some $\mathbf x_0\in\mathbb R^N$ with $\|\mathbf x_0\|^2=N$. $H$ is a height function because when $\mathbf x_0$ is @@ -117,25 +168,13 @@ $\mathbb M(1)=\frac1N\phi(1)\cdot\mathbf x_0$, the result is \overline{\chi}&=\int d\mathbb Q\,d\mathbb M\,d\sigma_0\,\exp\Bigg\{ \frac N2\log\operatorname{sdet}(\mathbb Q-\mathbb M\mathbb M^T) -\frac M2\log\operatorname{sdet}f(\mathbb Q) \notag \\ - &+N\int d1\,\left[ - (1+\hat\beta\bar\theta_1\theta_1)\mathbb M(1)+\frac12\sigma_0(1)\big(\mathbb Q(1,1)-1\big) + &\quad+N\int d1\,\left[ + \mathbb M(1)+\frac12\sigma_0(1)\big(\mathbb Q(1,1)-1\big) \right] \Bigg\} \end{align} \begin{equation} - 0=\int d2\,(\mathbb Q(1,2)-\mathbb M(1)\mathbb M(2)^T)(1+\bar\theta_2\theta_2\hat\beta)+\mathbb M(1) -\end{equation} - -\[ - D=\beta R - \quad - \beta=-\frac{m+\sum_aR_{1a}}{\sum_aC_{1a}} - \quad - \hat m=0 -\] - -\begin{equation} \begin{aligned} &\frac1N\log\overline\chi =\frac12\Bigg[ @@ -152,8 +191,19 @@ $\mathbb M(1)=\frac1N\phi(1)\cdot\mathbf x_0$, the result is \end{equation} + +\begin{equation} + D=\beta R + \qquad + \beta=-\frac{m+\sum_aR_{1a}}{\sum_aC_{1a}} + \qquad + \hat m=0 +\end{equation} + + \begin{acknowledgements} JK-D is supported by a \textsc{DynSysMath} Specific Initiative of the INFN. + The authors thank Pierfrancesco Urbani for helpful conversations on these topics. \end{acknowledgements} \bibliography{topology} |