We introduce gradient flow aggregation, a random growth model. Given existing particles  $\{x_1,\ldots,x_n\} \subset \mathbb{R}^2$, a new particle arrives from a random direction at
$\{x_1,\ldots,x_n\} \subset \mathbb{R}^2$, a new particle arrives from a random direction at  $\infty$ and flows in direction of the vector field
$\infty$ and flows in direction of the vector field  $\nabla E$ where
$\nabla E$ where  $ E(x) = \sum_{i=1}^{n}{1}/{\|x-x_i\|^{\alpha}}$,
$ E(x) = \sum_{i=1}^{n}{1}/{\|x-x_i\|^{\alpha}}$,  $0 < \alpha < \infty$. The case
$0 < \alpha < \infty$. The case  $\alpha = 0$ refers to the logarithmic energy
$\alpha = 0$ refers to the logarithmic energy  ${-}\sum\log\|x-x_i\|$. Particles stop once they are at distance 1 from one of the existing particles, at which point they are added to the set and remain fixed for all time. We prove, under a non-degeneracy assumption, a Beurling-type estimate which, via Kesten’s method, can be used to deduce sub-ballistic growth for
${-}\sum\log\|x-x_i\|$. Particles stop once they are at distance 1 from one of the existing particles, at which point they are added to the set and remain fixed for all time. We prove, under a non-degeneracy assumption, a Beurling-type estimate which, via Kesten’s method, can be used to deduce sub-ballistic growth for  $0 \leq \alpha < 1$,
$0 \leq \alpha < 1$,  $\text{diam}(\{x_1,\ldots,x_n\}) \leq c_{\alpha} \cdot n^{({3 \alpha +1})/({2\alpha + 2})}$. This is optimal when
$\text{diam}(\{x_1,\ldots,x_n\}) \leq c_{\alpha} \cdot n^{({3 \alpha +1})/({2\alpha + 2})}$. This is optimal when  $\alpha = 0$. The case
$\alpha = 0$. The case  $\alpha = 0$ leads to a ‘round’ full-dimensional tree. The larger the value of
$\alpha = 0$ leads to a ‘round’ full-dimensional tree. The larger the value of  $\alpha$, the sparser the tree. Some instances of the higher-dimensional setting are also discussed.
$\alpha$, the sparser the tree. Some instances of the higher-dimensional setting are also discussed.