# The anti-k_t jet clustering algorithm

**Authors:** Matteo Cacciari, Gavin P. Salam, Gregory Soyez  
**arXiv:** [0802.1189](https://arxiv.org/abs/0802.1189)  
**Date:** 2008-02-08  
**Summary page:** https://www.summarizepaper.com/en/arxiv-id/0802.1189v2/

## Key points

- The anti-k_t algorithm is a new jet finding algorithm characterized by a negative power of the energy scale in the distance measure.
- Jets formed using the anti-k_t algorithm exhibit conical shapes with equal active and passive areas, zero area anomalous dimensions, and universal Milan factor.
- The properties of the anti-k_t algorithm distinguish it from existing sequential recombination algorithms and cone algorithms like SISCone.
- The anti-k_t algorithm aligns closely with the collinear unsafe plain "iterative cone" algorithm but offers faster performance and ensures infrared and collinear safety in jet clustering processes.
- This study introduces a novel approach to jet clustering in high-energy physics research, highlighting how negative powers of energy scale can impact the efficiency of recombination algorithms in particle collision studies.

## Summary

The  and Cambridge/Aachen inclusive jet finding algorithms used in hadron-hadron collisions are part of a larger class of sequential recombination jet algorithms that are characterized by the power of the energy scale in the distance measure. In this study, Matteo Cacciari, Gavin P. Salam, and Gregory Soyez explore the properties of a new algorithm within this class, where the power is negative, known as the "anti-k_t" algorithm. The anti-k_t algorithm exhibits behavior similar to an idealized cone algorithm, where jets with only soft fragmentation form conical shapes. Notably, the active and passive areas within these jets are equal, the area anomalous dimensions are zero, non-global logarithms resemble those of a rigid boundary, and the Milan factor is universal. These unique characteristics distinguish the anti-k_t algorithm from existing sequential recombination algorithms and cone algorithms like SISCone. Interestingly, these properties align closely with those of the collinear unsafe plain "iterative cone" algorithm. The anti-k_t algorithm serves as a natural replacement for this traditional approach due to its fast nature and ability to ensure infrared and collinear safety in jet clustering processes. Overall, this study sheds light on a novel approach to jet clustering in high-energy physics research, offering insights into how negative powers of energy scale can impact the behavior and efficiency of recombination algorithms in particle collision studies.