REVIEW 4 cited by
Isolating Unisolated Upsilons with Anomaly Detection in CMS Open Data
Not yet reviewed by Pith; the record is open.
This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.
SPECIMEN: schema-true, not a live event
T0 review · schema-true
One-sentence machine reading of the paper's core claim.
pith:XXXXXXXX · record.json · timestamp
Isolating Unisolated Upsilons with Anomaly Detection in CMS Open Data
read the original abstract
We present the first study of anti-isolated Upsilon decays to two muons ($\Upsilon \to \mu^+ \mu^-$) in proton-proton collisions at the Large Hadron Collider. Using a machine learning (ML)-based anomaly detection strategy, we "rediscover" the $\Upsilon$ in 13 TeV CMS Open Data from 2016, despite overwhelming anti-isolated backgrounds. We elevate the signal significance to $6.4 \sigma$ using these methods, starting from $1.6 \sigma$ using the dimuon mass spectrum alone. Moreover, we demonstrate improved sensitivity from using an ML-based estimate of the multi-feature likelihood compared to traditional "cut-and-count" methods. Our work demonstrates that it is possible and practical to find real signals in experimental collider data using ML-based anomaly detection, and we distill a readily-accessible benchmark dataset from the CMS Open Data to facilitate future anomaly detection developments.
Forward citations
Cited by 4 Pith papers
-
Explicit or Implicit? Encoding Physics at the Precision Frontier
On three precision classification tasks — reweighting-based unfolding, likelihood-ratio estimation, and weakly supervised anomaly detection — a Lorentz-equivariant transformer and a pretrained foundation model perform...
-
Look everywhere effects in anomaly detection
Weakly supervised anomaly detectors that train and test on the same data produce badly miscalibrated p-values; independent test sets are calibrated but insensitive, while k-fold cross-validation is a workable middle ground.
-
Time-dependent signals of new physics at the LHC
Incorporating timing information from time-dependent new physics signals can improve LHC search sensitivity by up to a factor of two compared to standard time-invariant analyses.
-
Kitchen Sink Anomaly Detection
A combined kitchen sink observable set of Energy Flow Polynomials and subjettiness variables outperforms standard baselines in sensitivity to a wide range of resonant signals, with new public benchmarks released and a...
discussion (0)
Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.