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We use a modified version of the Peak Patch excursion set formalism to compute the mass and size distribution of QCD axion miniclusters from a fully non-Gaussian initial density field obtained from numerical simulations of axion string decay. We find strong agreement with N-Body simulations at a significantly lower computational cost. We employ a spherical collapse model and provide fitting functions for the modified barrier in the radiation era. The halo mass function at $z=629$ has a power-law distribution $M^{-0.6}$ for masses within the range $10^{-15}lesssim Mlesssim 10^{-10}M_{odot}$, with all masses scaling as $(m_a/50mumathrm{eV})^{-0.5}$. We construct merger trees to estimate the collapse redshift and concentration mass relation, $C(M)$, which is well described using analytical results from the initial power spectrum and linear growth. Using the calibrated analytic results to extrapolate to $z=0$, our method predicts a mean concentration $Csim mathcal{O}(text{few})times10^4$. The low computational cost of our method makes future investigation of the statistics of rare, dense miniclusters easy to achieve.
We give a short proof of Gaos Quantum Union Bound and Gentle Sequential Measurement theorems.
We develop taggers for multi-pronged jets that are simple functions of jet substructure (so-called `subjettiness) variables. These taggers can be approximately decorrelated from the jet mass in a quite simple way. Specifically, we use a Logistic Regr
Visual imitation learning provides a framework for learning complex manipulation behaviors by leveraging human demonstrations. However, current interfaces for imitation such as kinesthetic teaching or teleoperation prohibitively restrict our ability
Linials seminal result shows that any deterministic distributed algorithm that finds a $3$-colouring of an $n$-cycle requires at least $log^*(n)/2 - 1$ communication rounds. We give a new simpler proof of this theorem.
In this paper we present a deterministic CONGEST algorithm to compute an $O(kDelta)$-vertex coloring in $O(Delta/k)+log^* n$ rounds, where $Delta$ is the maximum degree of the network graph and $1leq kleq O(Delta)$ can be freely chosen. The algorithm