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A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.
Pages
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Posts
Future Blog Post
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Blog Post number 4
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This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool. Read more
Blog Post number 3
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Blog Post number 2
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Blog Post number 1
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This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool. Read more
publications
ABCNet: An attention-based method for particle tagging
Published in Eur.Phys.J.Plus 135 (2020) 6, 463, 2020
In high energy physics, graph-based implementations have the advantage of treating the input data sets in a similar way as they are collected by collider experiments. Read more
Recommended citation: Vinicius Mikuni and Florencia Canelli Eur. Phys. J. Plus *135*, 463 (2020) https://link.springer.com/article/10.1140/epjp/s13360-020-00497-3
Unsupervised clustering for collider physics
Published in Phys.Rev.D 103 (2021) 9, 092007, 2021
We propose a new method for unsupervised clustering for collider physics named UCluster, where information in the embedding space created by a neural network is used to categorize collision events into different clusters that share similar properties. Read more
Recommended citation: Vinicius Mikuni and Florencia Canelli Phys. Rev. D *103*, 092007 https://journals.aps.org/prd/abstract/10.1103/PhysRevD.103.092007
Point cloud transformers applied to collider physics
Published in Mach.Learn.Sci.Tech. 2 (2021) 3, 035027, Sci.Technol. 2 035027, 2021
Methods for processing point cloud information have seen a great success in collider physics applications. Read more
Recommended citation: Vinicius Mikuni and Florencia Canelli 2021 Mach. Learn.: Sci. Technol. *2* 035027 https://iopscience.iop.org/article/10.1088/2632-2153/ac07f6
Online-compatible unsupervised nonresonant anomaly detection
Published in Phys.Rev.D 105 (2022) 5, 055006, 2022
There is a growing need for anomaly detection methods that can broaden the search for new particles in a model-agnostic manner. Read more
Recommended citation: Vinicius Mikuni, Benjamin Nachman, and David Shih Phys. Rev. D *105*, 055006 https://journals.aps.org/prd/abstract/10.1103/PhysRevD.105.055006
Score-based generative models for calorimeter shower simulation
Published in Phys.Rev.D 106 (2022) 9, 092009, 2022
Score-based generative models are a new class of generative algorithms that have been shown to produce realistic images even in high dimensional spaces, currently surpassing other state-of-the-art models for different benchmark categories and applications. Read more
Recommended citation: Vinicius Mikuni and Benjamin Nachman Phys. Rev. D *106*, 092009 https://journals.aps.org/prd/abstract/10.1103/PhysRevD.106.092009
Anomaly detection under coordinate transformations
Published in Phys.Rev.D 107 (2023) 1, 015009, 2022
There is a growing need for machine-learning-based anomaly detection strategies to broaden the search for beyond-the-Standard-Model physics at the Large Hadron Collider (LHC) and elsewhere. Read more
Recommended citation: Gregor Kasieczka, Radha Mastandrea, Vinicius Mikuni, Benjamin Nachman, Mariel Pettee, and David Shih Phys. Rev. D *107*, 015009 https://arxiv.org/abs/2209.06225
Optimal transport for a global event description at high-intensity hadron colliders
Published in arXiv, 2022
The CERN Large Hadron Collider was built to uncover fundamental particles and their interactions at the energy frontier. Read more
Recommended citation: Gouskos, L., Iemmi, F., Liechti, S., Maier, B., Mikuni, V., & Qu, H. (2022). Optimal transport for a global event description at high-intensity hadron colliders. arXiv preprint arXiv:2211.02029. https://arxiv.org/abs/2211.02029
Fast Point Cloud Generation with Diffusion Models in High Energy Physics
Published in arXiv, 2023
Many particle physics datasets like those generated at colliders are described by continuous coordinates. Read more
Recommended citation: Mikuni, V., Nachman, B., Pettee, M. (2023). Fast Point Cloud Generation with Diffusion Models in High Energy Physics. arXiv preprint arXiv:2304.01266. https://arxiv.org/abs/2304.01266
talks
Anomaly detection
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