arXiv subjects

Carsten Burgard

Publications and source records attributed to Carsten Burgard.

7 recordsLinked to original sources

arXiv2026

HS3: A Descriptive, Interoperable Serialization Standard for Statistical Models in High-Energy Physics

Statistical models in high-energy physics formally encode the relationship between observed data, physics parameters of interest, and experimental and theoretical uncertainties. Likelihood-based inference is the central tool for precision measurements, effective field theory fits, and cross-analysis combinations. Consequently, there is an increasing need for machine-readable, descriptive, and portable model representations. Existing formats such as ROOT workspaces, pyhf JSON, and CMS DataCards provide valuable capabilities but remain tied to specific software stacks and offer no universal standard for exchange, validation, or long-term preservation. We introduce HS3, the High-Energy Physics Statistics Serialization Standard, an implementation-agnostic, human-readable, and extensible serialization format for statistical models. HS3 is designed such that new statistical constructs can be incorporated through backward-compatible extensions, while inference procedures and implementation-specific execution details remain the responsibility of downstream frameworks. HS3 represents likelihoods as computational graphs composed of named distributions, functions, datasets, domains, and analysis prescriptions. It supports binned and unbinned likelihoods as well as hierarchical composite models. HS3 is convertible from and to ROOT/RooFit and is a superset of pyhf. We describe the design principles, structure, and semantics of HS3 and summarize existing implementations in C++, Python, and Julia. We also present early applications to public likelihoods on HEPData, cross-framework validation, and reproducibility efforts. HS3 provides a foundation for FAIR (Findable, Accessible, Interoperable, Reusable), long-lived statistical models at the LHC and beyond. The standard is intended to serve the broader scientific community and to evolve over time for application across a wide range of domains.

hep-ex↗

arXiv2026

Hypothesis Tests for Observing Quantum Entanglement in HWW at the LHC

We present a novel experimental strategy for testing quantum entanglement in Higgs boson decays to $W$ boson pairs at the Large Hadron Collider. Unlike theoretical approaches that rely on expectation values of Bell operators, which are highly sensitive to outliers and detector effects, we introduce a continuous formulation of the CGLMP inequality that enables standard hypothesis testing between entangled and separable states. To overcome the fundamental challenge of reconstructing invisible neutrino momenta in the $H \rightarrow WW^* \rightarrow \ell\nu\ell\nu$ channel, we employ conditional denoising diffusion probabilistic models (cDDPM), which provide unbiased, multidimensional unfolding applicable to the full measured dataset, including backgrounds. We evaluate the diffusion-based reconstruction against analytical methods through profile likelihood hypothesis tests implemented in RooFit, with systematic uncertainties from background normalisation and unfolding shape fully propagated. Our results demonstrate that the diffusion-based approach enables robust hypothesis testing of quantum entanglement in a realistic collider environment, with 3$\sigma$ evidence of quantum entanglement projected at approximately 555~fb$^{-1}$ and exceeding 5$\sigma$ at 1600~fb$^{-1}$ to be well within the expected limits of the HL-LHC luminosity targets.

hep-ex↗

arXiv2025

Systematic Uncertainties in Unfolding Considering the Likelihood Formalism

This paper describes the treatment of systematic uncertainties in a Likelihood formalism. RooUnfold, which includes most of the unfolding methods that are commonly used in particle physics, is used to compare a newly implemented method inside this toolkit to existing methods. The interface with the RooFit statistical software package is used for the treatment of systematic uncertainties. The RooUnfold package with RooFit interface, commonly called RooFitUnfold, provides a common interface to unfolding algorithms as well as common uniform methods to evaluate their performance in terms of bias, variance and coverage. This paper exploits this common interface to compare the performance of unfolding with a Tikhonov regularisation term directly in the likelihood with an unfolding method that optimises a Tikhonov regularisation applied separately of the likelihood formalism. Comparisons are made with and without the treatment of (systematic) uncertainties and are applied to an example problem.

hep-ex↗

arXiv2025

Reinterpretation and preservation of data and analyses in HEP

Data from particle physics experiments are unique and are often the result of a very large investment of resources. Given the potential scientific impact of these data, which goes far beyond the immediate priorities of the experimental collaborations that obtain them, it is imperative that the collaborations and the wider particle physics community publish and preserve sufficient information to ensure that this impact can be realised, now and into the future. The information to be published and preserved includes the algorithms, statistical information, simulations and the recorded data. This publication and preservation requires significant resources, and should be a strategic priority with commensurate planning and resource allocation from the earliest stages of future facilities and experiments.

hep-ph↗

arXiv2024

Effective Lagrangian Morphing

With the LHC entering the precision era, focus on interpreting the measurements performed in an effective field theory holds key to testing the Standard Model. An effective field theory provides a well-defined theoretical formalism which extends the Standard Model by introduce new terms with free coefficients that can be measured with experimental data. Constructing models parametric in these new coefficients is achieved by virtue of combining predictions from Monte Carlo generators for different interactions. This paper builds upon earlier works and describes a state-of-the-art approach to build multidimensional parametric models for new physics using effective Lagrangians. Documentation and tutorials for an associated toolkit that have been contributed to the ROOT data analysis software framework is included.

physics.data-an↗

arXiv2020

Comparison of unfolding methods using RooFitUnfold

In this paper we describe RooFitUnfold, an extension of the RooFit statistical software package to treat unfolding problems, and which includes most of the unfolding methods that commonly used in particle physics. The package provides a common interface to these algorithms as well as common uniform methods to evaluate their performance in terms of bias, variance and coverage. In this paper we exploit this common interface of RooFitUnfold to compare the performance of unfolding with the Richardson-Lucy, Iterative Dynamically Stabilized, Tikhonov, Gaussian Process, Bin-by-bin and inversion methods on several example problems.

physics.data-an↗

arXiv2018

BlurRing

A code package, BlurRing, is developed as a method to allow for multi-dimensional likelihood visualisation. From the BlurRing visualisation additional information about the likelihood can be extracted. The spread in any direction of the overlaid likelihood curves gives information about the uncertainty on the confidence intervals presented in the two-dimensional likelihood plots.

physics.data-an↗