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Related papers: How to Unfold Top Decays

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Matrix inversion problems are often encountered in experimental physics, and in particular in high-energy particle physics, under the name of unfolding. The true spectrum of a physical quantity is deformed by the presence of a detector,…

Machine Learning · Statistics 2020-09-08 Pietro Vischia

The unfolding of detector effects is a key aspect of comparing experimental data with theoretical predictions. In recent years, different Machine-Learning methods have been developed to provide novel features, e.g. high dimensionality or a…

Data Analysis, Statistics and Probability · Physics 2024-12-17 Mathias Backes , Anja Butter , Monica Dunford , Bogdan Malaescu

The production at the LHC of boosted top quarks (top quarks with a transverse momentum that greatly exceeds their rest mass) is a promising process to search for phenomena beyond the Standard Model. In this contribution several examples are…

High Energy Physics - Experiment · Physics 2014-09-01 Elin Bergeaas Kuutmann

We study the reconstruction of high p_T hadronically-decaying top quarks at the LHC. The main challenge in identifying energetic top quarks is that the decay products become increasingly collimated. This reduces the efficacy of conventional…

High Energy Physics - Phenomenology · Physics 2009-06-11 Leandro G. Almeida , Seung J. Lee , Gilad Perez , Ilmo Sung , Joseph Virzi

Top tagging is a recent approach to identifying boosted hadronic top quarks. It avoids reconstructing individual top decay products and instead uses a jet algorithm to reconstruct the entire top decay. Quite generally, geometrically large…

High Energy Physics - Phenomenology · Physics 2015-06-03 Tilman Plehn , Michael Spannowsky

We review some recent theoretical progresses towards the determination of the top-quark couplings beyond the standard model. We briefly introduce the global effective field theory approach to the top-quark production and decay processes,…

High Energy Physics - Phenomenology · Physics 2017-08-31 Cen Zhang

Learning disentangled representations is regarded as a fundamental task for improving the generalization, robustness, and interpretability of generative models. However, measuring disentanglement has been challenging and inconsistent, often…

Machine Learning · Statistics 2021-03-19 Sharon Zhou , Eric Zelikman , Fred Lu , Andrew Y. Ng , Gunnar Carlsson , Stefano Ermon

Recent innovations from machine learning allow for data unfolding, without binning and including correlations across many dimensions. We describe a set of known, upgraded, and new methods for ML-based unfolding. The performance of these…

The experimental status of measurements of the top quark mass is reviewed. After an introduction to the definition of the top quark mass and the production and decay of top quarks, an in-depth comparison of the analysis techniques used in…

High Energy Physics - Experiment · Physics 2010-03-03 Frank Fiedler

Several recent new measurements of the top-quark mass that use alternative observables and reconstruction techniques are presented, performed by the ATLAS and CMS collaborations at the CERN LHC. Alternative observables can help provide…

High Energy Physics - Experiment · Physics 2016-06-09 Benjamin Stieger

(Report of the Top Physics working group at the 1996 DPF/DPB Snowmass workshop, to appear in the proceedings). We discuss the study of the top quark at future experiments and machines. Top's large mass makes it a unique probe of physics at…

High Energy Physics - Phenomenology · Physics 2009-02-20 Raymond Frey , David Gerdes , John Jaros , Steve Vejcik

The ongoing perplexing scenario with no hints of new physics at the Large Hadron Collider can be elucidated amicably if the exotic particle spectrum in many of the well-motivated theoretical models possesses degenerate mass. We investigate…

High Energy Physics - Phenomenology · Physics 2017-11-22 Partha Konar , Tanmoy Mondal , Abhaya Kumar Swain

We demonstrate a new likelihood method for extracting the top quark mass from events of the type ttbar-->bW(l+nu)bW(l+nu) This method estimates the top quark mass correctly from an ensemble of dilepton events. The method proposed by Dalitz…

High Energy Physics - Experiment · Physics 2009-12-30 Rajendran Raja

Top taggers are established analysis tools to reconstruct boosted hadronically decaying top quarks for example in searches for heavy resonances. We first present a dedicated study of signal efficiency versus background rejection, allowing…

High Energy Physics - Phenomenology · Physics 2014-04-30 Christoph Anders , Catherine Bernaciak , Gregor Kasieczka , Tilman Plehn , Torben Schell

It has previously been hypothesized, and supported with some experimental evidence, that deeper representations, when well trained, tend to do a better job at disentangling the underlying factors of variation. We study the following related…

Machine Learning · Computer Science 2012-07-19 Yoshua Bengio , Grégoire Mesnil , Yann Dauphin , Salah Rifai

Optimal kinematic observables are often defined in specific frames and then approximated at the reconstruction level. We show how multi-dimensional unfolding methods allow us to reconstruct these observables in their proper rest frame and…

High Energy Physics - Phenomenology · Physics 2024-07-03 Jona Ackerschott , Rahool Kumar Barman , Dorival Gonçalves , Theo Heimel , Tilman Plehn

The top quark mass plays an important role in a variety of discussions both within and beyond the Standard Model. However, a precise determination of a theoretically well-defined top quark mass is still missing. Towards a precise…

High Energy Physics - Phenomenology · Physics 2015-11-11 Sayaka Kawabata

Biased enhanced sampling methods utilizing collective variables (CVs) are powerful tools for sampling conformational ensembles. Due to high intrinsic dimensions, efficiently generating conformational ensembles for complex systems requires…

Machine Learning · Computer Science 2023-12-19 Yikai Liu , Tushar K. Ghosh , Guang Lin , Ming Chen

We briefly review common tools and methods to identify boosted, hadronically decaying top quarks at the LHC experiments. This includes generic jet substructure variables, specific top identification algorithms, and recent developments in…

High Energy Physics - Phenomenology · Physics 2018-01-15 Gregor Kasieczka

Unsupervised training of generative models is a machine learning task that has many applications in scientific computing. In this work we evaluate the efficacy of using quantum circuit-based generative models to generate synthetic data of…

Quantum Physics · Physics 2022-11-23 Andrea Delgado , Kathleen E. Hamilton