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Non-resonant anomaly detection with background extrapolation

Journal Article · · Journal of High Energy Physics (Online)
 [1];  [2];  [3]
  1. Univ. of Oregon, Eugene, OR (United States); Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
  2. Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States); University of California, Berkeley, CA (United States)
  3. University of California, Berkeley, CA (United States)
+ Show Author Affiliations
Complete anomaly detection strategies that are both signal sensitive and compatible with background estimation have largely focused on resonant signals. Non-resonant new physics scenarios are relatively under-explored and may arise from off-shell effects or final states with significant missing energy. In this paper, we extend a class of weakly supervised anomaly detection strategies developed for resonant physics to the non-resonant case. Machine learning models are trained to reweight, generate, or morph the background, extrapolated from a control region. A classifier is then trained in a signal region to distinguish the estimated background from the data. The new methods are demonstrated using a semi-visible jet signature as a benchmark signal model, and are shown to automatically identify the anomalous events without specifying the signal ahead of time.
Research Organization:
Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
Sponsoring Organization:
National Science Foundation (NSF); USDOE Office of Science (SC), High Energy Physics (HEP)
Grant/Contract Number:
AC02-05CH11231; SC0020244
OSTI ID:
2407314
Journal Information:
Journal of High Energy Physics (Online), Journal Name: Journal of High Energy Physics (Online) Journal Issue: 4 Vol. 2024; ISSN 1029-8479
Publisher:
Springer NatureCopyright Statement
Country of Publication:
United States
Language:
English

References (107)

Tag N’ Train: a technique to train improved classifiers on unlabeled data journal January 2021
RanBox: anomaly detection in the copula space journal January 2023
Maximizing boosted top identification by minimizing N-subjettiness journal February 2012
DELPHES 3: a modular framework for fast simulation of a generic collider experiment journal February 2014
Does SUSY have friends? A new approach for LHC event analysis journal February 2021
Autoencoders for semivisible jet detection journal February 2022
Quantum anomaly detection for collider physics journal February 2023
Anomaly detection in the presence of irrelevant features journal February 2024
Identifying boosted objects with N-subjettiness journal March 2011
Challenges for unsupervised anomaly detection in particle physics journal March 2022
Mixture-of-Theories training: can we find new physics and anomalies better by mixing physical theories? journal March 2023
Discerning secluded sector gauge structures journal April 2011
Erratum to: Mass Unspecific Supervised Tagging (MUST) for boosted jets journal April 2021
Topological obstructions to autoencoding journal April 2021
Variational autoencoders for new physics mining at the Large Hadron Collider journal May 2019
Machine learning templates for QCD factorization in the search for physics beyond the standard model journal May 2019
Autoencoders for unsupervised anomaly detection in high energy physics journal June 2021
The automated computation of tree-level and next-to-leading order differential cross sections, and their matching to parton shower simulations journal July 2014
Neural embedding: learning the embedding of the manifold of physics data journal July 2023
Collider phenomenology of Hidden Valley mediators of spin 0 or 1/2 with semivisible jets journal August 2018
Anomaly detection with convolutional Graph Neural Networks journal August 2021
Boosting mono-jet searches with model-agnostic machine learning journal August 2022
Visible effects of invisible Hidden Valley radiation journal September 2010
Jet substructure from dark sector showers journal September 2020
Combining outlier analysis algorithms to identify new physics at the LHC journal September 2021
Classification without labels: learning from mixed samples in high energy physics journal October 2017
Adversarially-trained autoencoders for robust unsupervised new physics searches journal October 2019
Learning the latent structure of collider events journal October 2020
A generic anti-QCD jet tagger journal November 2017
LHC searches for dark sector showers journal November 2017
Echoes of a hidden valley at hadron colliders journal August 2007
Null hypothesis test for anomaly detection journal May 2023
LHC physics dataset for unsupervised New Physics detection at 40 MHz journal March 2022
Autoencoders on field-programmable gate arrays for real-time, unsupervised new physics detection at 40 MHz at the Large Hadron Collider journal February 2022
The anti- k t jet clustering algorithm journal April 2008
The LHC Olympics 2020 a community challenge for anomaly detection in high energy physics journal December 2021
Unsupervised outlier detection in heavy-ion collisions journal April 2021
A semi-supervised approach to dark matter searches in direct detection data with machine learning journal February 2022
Anomalous jet identification via sequence modeling journal August 2021
A method to challenge symmetries in data with self-supervised learning journal August 2022
‘Flux+Mutability’: a conditional generative approach to one-class classification and anomaly detection journal November 2022
Robust and provably monotonic networks journal August 2023
Unravelling physics beyond the standard model with classical and quantum anomaly detection journal November 2023
via machinae: Searching for stellar streams using unsupervised machine learning journal November 2021
Quantum-probabilistic Hamiltonian learning for generative modeling and anomaly detection journal December 2023
Uncovering latent jet substructure journal September 2019
Transferability of deep learning models in searches for new physics at colliders journal February 2020
Searching for new physics with deep autoencoders journal April 2020
Anomaly detection with density estimation journal April 2020
Novelty detection meets collider physics journal April 2020
Simulation assisted likelihood-free anomaly detection journal May 2020
Automating the ABCD method with machine learning journal February 2021
Unsupervised clustering for collider physics journal May 2021
Perturbative benchmark models for a dark shower search program journal June 2021
Simulation-assisted decorrelation for resonant anomaly detection journal August 2021
Online-compatible unsupervised nonresonant anomaly detection journal March 2022
Anomaly detection in high-energy physics using a quantum autoencoder journal May 2022
Bump hunting in latent space journal June 2022
Creating simple, interpretable anomaly detectors for new physics in jet substructure journal August 2022
Classifying anomalies through outer density estimation journal September 2022
Self-supervised anomaly detection for new physics journal September 2022
Anomaly detection under coordinate transformations journal January 2023
Variational autoencoders for anomalous jet tagging journal January 2023
Flow-enhanced transportation for anomaly detection journal May 2023
Resonant anomaly detection without background sculpting journal June 2023
Morphing one dataset into another with maximum likelihood estimation journal November 2023
Dark sector showers in the Lund jet plane journal August 2023
Tree-based algorithms for weakly supervised anomaly detection journal February 2024
Full phase space resonant anomaly detection journal March 2024
Extending the search for new resonances with machine learning journal January 2019
Learning new physics from a machine journal January 2019
Semivisible Jets: Dark Matter Undercover at the LHC journal October 2015
Anomaly Detection for Resonant New Physics with Machine Learning journal December 2018
Anomaly Detection with Conditional Variational Autoencoders conference December 2019
FastJet user manual: (for version 3.0.2) journal March 2012
Parameterized neural networks for high-energy physics journal April 2016
Guiding new physics searches with unsupervised learning journal March 2019
Finding new physics without learning about it: anomaly detection as a tool for searches at colliders journal January 2021
Learning multivariate new physics journal January 2021
Use of a generalized energy Mover’s distance in the search for rare phenomena at colliders journal February 2021
Comparing weak- and unsupervised methods for resonant anomaly detection journal July 2021
Anomaly detection from mass unspecific jet tagging journal February 2022
A data-directed paradigm for BSM searches: the bump-hunting example journal March 2022
Taming modeling uncertainties with mass unspecific supervised tagging journal March 2022
Learning new physics from an imperfect machine journal March 2022
Data-directed search for new physics based on symmetries of the SM journal June 2022
Learning new physics efficiently with nonparametric methods journal October 2022
GAN-AE: an anomaly detection algorithm for New Physics search in LHC data journal November 2023
The interplay of machine learning-based resonant anomaly detection methods journal March 2024
Adversarially Learned Anomaly Detection on CMS open data: re-discovering the top quark journal February 2021
Enhancing the hunt for new phenomena in dijet final states using anomaly detection filters at the high-luminosity large Hadron Collider journal March 2024
Search for resonant production of strongly coupled dark matter in proton-proton collisions at 13 TeV collection January 2022
Casting a graph net to catch dark showers journal January 2021
Better latent spaces for better autoencoders journal January 2021
The Dark Machines Anomaly Score Challenge: Benchmark Data and Model Independent Event Classification for the Large Hadron Collider journal January 2022
Deep Set Auto Encoders for Anomaly Detection in Particle Physics journal January 2022
Rare and Different: Anomaly Scores from a combination of likelihood and out-of-distribution models to detect new physics at the LHC journal January 2022
Event Generation and Density Estimation with Surjective Normalizing Flows journal September 2022
Anomaly Awareness journal August 2023
What's anomalous in LHC jets? journal October 2023
High-dimensional and permutation invariant anomaly detection journal February 2024
QCD or what? journal January 2019
A normalized autoencoder for LHC triggers journal November 2023
Uncovering hidden new physics patterns in collider events using Bayesian probabilistic models conference February 2021
Improving Variational Autoencoders for New Physics Detection at the LHC With Normalizing Flows journal February 2022
CURTAINs for your sliding window: Constructing unobserved regions by transforming adjacent intervals journal March 2023
Event-Based Anomaly Detection for Searches for New Physics journal September 2022

Figures / Tables (12)

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