The energy landscape for soft sphere packings exists in a high-dimensional space and plays host to an astronomical number of local minima in a hierarchical and ultrametric arrangement. Each point in the landscape is a configuration that can be mapped to its inherent state, defined as the local minima that the configuration will flow to under perfectly overdamped continuous dynamics. Typically, discrete in time dynamics are used to computationally find local minima, but it is not known whether these algorithms are capable of reliably finding inherent states. Here, we use steepest descent dynamics to find the distribution of the largest time step, ${\delta }_{\text{best}}$, which finds the inherent state. We find that ${\delta }_{\text{best}}$ is Weibull distributed. Additionally, for systems of $N$ particles, ${\delta }_{\text{best}}$ falls rapidly with increasing $N$, with a functional form somewhere in between an exponential and inverse power law, and is weakly dependent on $d$ and $\phi$, where $d$ is the packing dimension and $\phi$ is the packing fraction. We argue that this rapid fall is due to saddle points in the energy landscape. Our results suggest that it is impossible, in practice, to reliably find inherent states for systems of about 64 particles or more.

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• Granular materials
• Granular packing
• Jamming
• Glassy systems