Analyzing N-Point Energy Correlators inside Jets with CMS Open Data.

Jets of hadrons produced at high-energy colliders provide experimental access to the dynamics of asymptotically free quarks and gluons and their confinement into hadrons. In this Letter, we show that the high energies of the Large Hadron Collider (LHC), together with the exceptional resolution of its detectors, allow multipoint correlation functions of energy flow operators to be directly measured within jets for the first time. Using Open Data from the CMS experiment, we show that reformulating jet substructure in terms of these correlators provides new ways of probing the dynamics of QCD jets, which enables direct imaging of the confining transition to free hadrons as well as precision measurements of the scaling properties and interactions of quarks and gluons. This opens a new era in our understanding of jet substructure and illustrates the immense unexploited potential of high-quality LHC data sets for elucidating the dynamics of QCD.

Learning Uncertainties the Frequentist Way: Calibration and Correlation in High Energy Physics.

Calibration is a common experimental physics problem, whose goal is to infer the value and uncertainty of an unobservable quantity Z given a measured quantity X. Additionally, one would like to quantify the extent to which X and Z are correlated. In this Letter, we present a machine learning framework for performing frequentist maximum likelihood inference with Gaussian uncertainty estimation, which also quantifies the mutual information between the unobservable and measured quantities. This framework uses the Donsker-Varadhan representation of the Kullback-Leibler divergence-parametrized with a novel Gaussian ansatz-to enable a simultaneous extraction of the maximum likelihood values, uncertainties, and mutual information in a single training. We demonstrate our framework by extracting jet energy corrections and resolution factors from a simulation of the CMS detector at the Large Hadron Collider. By leveraging the high-dimensional feature space inside jets, we improve upon the nominal CMS jet resolution by upward of 15%.

The LHC Olympics 2020 a community challenge for anomaly detection in high energy physics.

A new paradigm for data-driven, model-agnostic new physics searches at colliders is emerging, and aims to leverage recent breakthroughs in anomaly detection and machine learning. In order to develop and benchmark new anomaly detection methods within this framework, it is essential to have standard datasets. To this end, we have created the LHC Olympics 2020, a community challenge accompanied by a set of simulated collider events. Participants in these Olympics have developed their methods using an R&D dataset and then tested them on black boxes: datasets with an unknown anomaly (or not). Methods made use of modern machine learning tools and were based on unsupervised learning (autoencoders, generative adversarial networks, normalizing flows), weakly supervised learning, and semi-supervised learning. This paper will review the LHC Olympics 2020 challenge, including an overview of the competition, a description of methods deployed in the competition, lessons learned from the experience, and implications for data analyses with future datasets as well as future colliders.

OmniFold: A Method to Simultaneously Unfold All Observables.

Collider data must be corrected for detector effects ("unfolded") to be compared with many theoretical calculations and measurements from other experiments. Unfolding is traditionally done for individual, binned observables without including all information relevant for characterizing the detector response. We introduce OmniFold, an unfolding method that iteratively reweights a simulated dataset, using machine learning to capitalize on all available information. Our approach is unbinned, works for arbitrarily high-dimensional data, and naturally incorporates information from the full phase space. We illustrate this technique on a realistic jet substructure example from the Large Hadron Collider and compare it to standard binned unfolding methods. This new paradigm enables the simultaneous measurement of all observables, including those not yet invented at the time of the analysis.

Sorting Out Quenched Jets.

We introduce a new "quantile" analysis strategy to study the modification of jets as they traverse through a droplet of quark-gluon plasma. To date, most jet modification studies have been based on comparing the jet properties measured in heavy-ion collisions to a proton-proton baseline at the same reconstructed jet transverse momentum (p_{T}). It is well known, however, that the quenching of jets from their interaction with the medium leads to a migration of jets from higher to lower p_{T}, making it challenging to directly infer the degree and mechanism of jet energy loss. Our proposed quantile matching procedure is inspired by (but not reliant on) the approximate monotonicity of energy loss in the jet p_{T}. In this strategy, jets in heavy-ion collisions ordered by p_{T} are viewed as modified versions of the same number of highest-energy jets in proton-proton collisions, and the fractional energy loss as a function of jet p_{T} is a natural observable (Q_{AA}). Furthermore, despite nonmonotonic fluctuations in the energy loss, we use an event generator to validate the strong correlation between the p_{T} of the parton that initiates a heavy-ion jet and the p_{T} of the vacuum jet which corresponds to it via the quantile procedure (p_{T}^{quant}). We demonstrate that this strategy both provides a complementary way to study jet modification and mitigates the effect of p_{T} migration in heavy-ion collisions.

Metric Space of Collider Events.

When are two collider events similar? Despite the simplicity and generality of this question, there is no established notion of the distance between two events. To address this question, we develop a metric for the space of collider events based on the earth mover's distance: the "work" required to rearrange the radiation pattern of one event into another. We expose interesting connections between this metric and the structure of infrared- and collinear-safe observables, providing a novel technique to quantify event modifications due to hadronization, pileup, and detector effects. We showcase how this metrization unlocks powerful new tools for analyzing and visualizing collider data without relying upon a choice of observables. More broadly, this framework paves the way for data-driven collider phenomenology without specialized observables or machine learning models.

Measurements of Two-Particle Correlations in e

Measurements of two-particle angular correlations of charged particles emitted in hadronic Z decays are presented. The archived e^{+}e^{-} annihilation data at a center-of-mass energy of 91 GeV were collected with the ALEPH detector at LEP between 1992 and 1995. The correlation functions are measured over a broad range of pseudorapidity and full azimuth as a function of charged particle multiplicity. No significant long-range correlation is observed in either the lab coordinate analysis or the thrust coordinate analysis, where the latter is sensitive to a medium expanding transverse to the color string between the outgoing qq[over ¯] pair from Z boson decays. The associated yield distributions in both analyses are in better agreement with the prediction from the pythia v6.1 event generator than from herwig v7.1.5. They provide new insights to showering and hadronization modeling. These results serve as an important reference to the observed long-range correlation in proton-proton, proton-nucleus, and nucleus-nucleus collisions.

First Results from ABRACADABRA-10 cm: A Search for Sub-µeV Axion Dark Matter.

The axion is a promising dark matter candidate, which was originally proposed to solve the strong-CP problem in particle physics. To date, the available parameter space for axion and axionlike particle dark matter is relatively unexplored, particularly at masses m_{a}≲1 µeV. ABRACADABRA is a new experimental program to search for axion dark matter over a broad range of masses, 10^{-12}≲m_{a}≲10^{-6} eV. ABRACADABRA-10 cm is a small-scale prototype for a future detector that could be sensitive to the QCD axion. In this Letter, we present the first results from a 1 month search for axions with ABRACADABRA-10 cm. We find no evidence for axionlike cosmic dark matter and set 95% C.L. upper limits on the axion-photon coupling between g_{aγγ}<1.4×10^{-10} and g_{aγγ}<3.3×10^{-9} GeV^{-1} over the mass range 3.1×10^{-10}-8.3×10^{-9} eV. These results are competitive with the most stringent astrophysical constraints in this mass range.

Jet Topics: Disentangling Quarks and Gluons at Colliders.

We introduce jet topics: a framework to identify underlying classes of jets from collider data. Because of a close mathematical relationship between distributions of observables in jets and emergent themes in sets of documents, we can apply recent techniques in "topic modeling" to extract jet topics from the data with minimal or no input from simulation or theory. As a proof of concept with parton shower samples, we apply jet topics to determine separate quark and gluon jet distributions for constituent multiplicity. We also determine separate quark and gluon rapidity spectra from a mixed Z-plus-jet sample. While jet topics are defined directly from hadron-level multidifferential cross sections, one can also predict jet topics from first-principles theoretical calculations, with potential implications for how to define quark and gluon jets beyond leading-logarithmic accuracy. These investigations suggest that jet topics will be useful for extracting underlying jet distributions and fractions in a wide range of contexts at the Large Hadron Collider.

Exposing the QCD Splitting Function with CMS Open Data.

The splitting function is a universal property of quantum chromodynamics (QCD) which describes how energy is shared between partons. Despite its ubiquitous appearance in many QCD calculations, the splitting function cannot be measured directly, since it always appears multiplied by a collinear singularity factor. Recently, however, a new jet substructure observable was introduced which asymptotes to the splitting function for sufficiently high jet energies. This provides a way to expose the splitting function through jet substructure measurements at the Large Hadron Collider. In this Letter, we use public data released by the CMS experiment to study the two-prong substructure of jets and test the 1→2 splitting function of QCD. To our knowledge, this is the first ever physics analysis based on the CMS Open Data.

Proposed Inclusive Dark Photon Search at LHCb.

We propose an inclusive search for dark photons A^{'} at the LHCb experiment based on both prompt and displaced dimuon resonances. Because the couplings of the dark photon are inherited from the photon via kinetic mixing, the dark photon A^{'}→µ^{+}µ^{-} rate can be directly inferred from the off-shell photon γ^{*}→µ^{+}µ^{-} rate, making this a fully data-driven search. For run 3 of the LHC, we estimate that LHCb will have sensitivity to large regions of the unexplored dark-photon parameter space, especially in the 210-520 MeV and 10-40 GeV mass ranges. This search leverages the excellent invariant-mass and vertex resolution of LHCb, along with its unique particle-identification and real-time data-analysis capabilities.

Broadband and Resonant Approaches to Axion Dark Matter Detection.

When ultralight axion dark matter encounters a static magnetic field, it sources an effective electric current that follows the magnetic field lines and oscillates at the axion Compton frequency. We propose a new experiment to detect this axion effective current. In the presence of axion dark matter, a large toroidal magnet will act like an oscillating current ring, whose induced magnetic flux can be measured by an external pickup loop inductively coupled to a SQUID magnetometer. We consider both resonant and broadband readout circuits and show that a broadband approach has advantages at small axion masses. We estimate the reach of this design, taking into account the irreducible sources of noise, and demonstrate potential sensitivity to axionlike dark matter with masses in the range of 10^{-14}-10^{-6} eV. In particular, both the broadband and resonant strategies can probe the QCD axion with a GUT-scale decay constant.

Calculating track-based observables for the LHC.

By using observables that only depend on charged particles (tracks), one can efficiently suppress pileup contamination at the LHC. Such measurements are not infrared safe in perturbation theory, so any calculation of track-based observables must account for hadronization effects. We develop a formalism to perform these calculations in QCD, by matching partonic cross sections onto new nonperturbative objects called track functions which absorb infrared divergences. The track function Ti(x) describes the energy fraction x of a hard parton i which is converted into charged hadrons. We give a field-theoretic definition of the track function and derive its renormalization group evolution, which is in excellent agreement with the pythia parton shower. We then perform a next-to-leading order calculation of the total energy fraction of charged particles in e+ e-→ hadrons. To demonstrate the implications of our framework for the LHC, we match the pythia parton shower onto a set of track functions to describe the track mass distribution in Higgs plus one jet events. We also show how to reduce smearing due to hadronization fluctuations by measuring dimensionless track-based ratios.

Precision jet substructure from boosted event shapes.

Jet substructure has emerged as a critical tool for LHC searches, but studies so far have relied heavily on shower Monte Carlo simulations, which formally approximate QCD at the leading-log level. We demonstrate that systematic higher-order QCD computations of jet substructure can be carried out by boosting global event shapes by a large momentum Q and accounting for effects due to finite jet size, initial-state radiation (ISR), and the underlying event (UE) as 1/Q corrections. In particular, we compute the 2-subjettiness substructure distribution for boosted Z→qq[over ¯] events at the LHC at next-to-next-to-next-to-leading-log order. The calculation is greatly simplified by recycling known results for the thrust distribution in e(+)e(-) collisions. The 2-subjettiness distribution quickly saturates, becoming Q independent for Q > or approximately equal to 400 GeV. Crucially, the effects of jet contamination from ISR/UE can be subtracted out analytically at large Q without knowing their detailed form. Amusingly, the Q=∞ and Q=0 distributions are related by a scaling by e up to next-to-leading-log order.