In the collider phenomenology of extensions of the Standard Model with partner particles, cascade decays occur generically, and they can be challenging to discover when the spectrum of new particles is compressed and the signal cross section is low. Achieving discovery-level significance and measuring the properties of the new particles appearing as intermediate states in the cascade decays is a longstanding problem, with analysis techniques for some decay topologies already optimized. We focus our attention on a benchmark decay topology with four final state particles where there is room for improvement, and where multidimensional analysis techniques have been shown to be effective in the past. Using machine learning techniques, we identify the optimal kinematic observables for discovery, spin determination and mass measurement. In agreement with past work, we confirm that the kinematic observable Δ4 is highly effective. We quantify the achievable accuracy for spin determination and for the precision for mass measurements as a function of the signal size.
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FlashRoute: Efficient Traceroute on a Massive Scale
We propose a new traceroute tool, FlashRoute for efficient large-scale topology discovery. FlashRoute reduces the time required for tracerouting the entire /24 IPv4 address space by a factor of three and half compared to previous state of the art. Additionally, we present a new technique to measure hop-distance to a destination using a single probe and uncover a bias of the influential ISI Census hitlist [18] in topology discovery.
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- Award ID(s):
- 1647145
- PAR ID:
- 10227490
- Date Published:
- Journal Name:
- Proceedings of the ACM Internet Measurement Conference
- Page Range / eLocation ID:
- 443 to 455
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1145/3419394.3423619
