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REVIEW 2 major objections 5 minor 53 references

Improved reconstruction of highly boosted $\tau$-lepton pairs in the $\tau\tau\rightarrow(\mu\nu_{\mu}\nu_{\tau})({hadrons}+\nu_{\tau})$ decay channels with the ATLAS detector

T0 review · 2 major / 5 minor · reviewed 2026-08-11 · deepseek-v4-flash

Pith's one-line read The ATLAS collaboration claims that removing the muon's track and calorimeter deposits from the seed jet of a highly boosted tau-mu tau-had pair restores hadronic-tau identification efficiency to the isolated-tau level, and validates this…

desk verdict Muon-removal preprocessing is a genuinely useful new trick for boosted semileptonic tau pairs; the central efficiency-recovery claim holds, with a legitimate but non-fatal caveat about merged clusters. read the letter →

arxiv 2412.14937 v2 pith:43AQZMIY submitted 2024-12-19 hep-ex

classification hep-ex PACS 14.60.Fg
keywords tauleptonreconstructionboostedpairsmuonremovalhadronicidentificationIDRNNZbosonvalidationATLASdetectorLHC
verification ladder T0 review T1 audit T2 compute T3 formal

The pith

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The reading

This paper tries to establish that a simple preprocessing step recovers the sensitivity to highly boosted semileptonic tau pairs, where one tau decays to a muon and two neutrinos and the other to hadrons plus a neutrino. In such events the muon often lands inside the seed jet of the hadronic tau, and the standard tau identification algorithm sees the muon as contamination and fails. The new procedure removes the muon's inner-detector track and calorimeter clusters from the seed jet and then re-runs the standard tau reconstruction and a recurrent-neural-network kaon identifier. In simulation, the identification efficiency returns to the level of an isolated tau for both one-prong and three-prong decays. In data, a validation using $Z\to\tau_\mu\tau_{\mathrm{had}}$ events from 140 $\mathrm{fb}^{-1}$ of 13 TeV collisions finds the observed yield agrees with the prediction within 12%.

What carries the argument

The central mechanism is the muon-removal re-reconstruction: for each tau seed jet that contains a Medium-working-point muon, the muon's inner-detector track is removed and calorimeter clusters are removed only when their energies match the expected muon energy loss, and then the standard tauhad reconstruction and the TauID recurrent neural network are re-run on the cleaned jet. The muon's minimum-ionising behaviour and isolation-independent reconstruction make the subtraction clean enough that the RNN receives a jet that looks like an isolated tauhad.

What would settle it

Measure the $Z\to\tau_\mu\tau_{\mathrm{had}}$ yield ratio in a larger data set (for example the full LHC Run 3) with a total uncertainty below 5%: if the observed-to-predicted ratio moves away from unity, or if the TauID score distribution of muon-removed jets in data disagrees with isolated-tau jets from $Z\to\tau\tau$ events with the same reconstructed transverse momentum, the assumption that the cleaned jet behaves as an isolated tau would be falsified.

Watch

Extended reading notes

Core claim

The central claim is that the hadronic tau candidate reconstructed after muon removal, denoted $\tau^{\mu\backslash}_{\mathrm{had}}$, recovers the tauhad identification efficiency of the standard ATLAS TauID algorithm to the level expected for an isolated tauhad, across all working points, for both one-prong and three-prong decays. Muon removal keeps only the inner-detector track and calorimeter clusters associated with a Medium-working-point muon, and cluster removal is additionally gated on compatibility with the expected muon energy loss, so the seed jet becomes a clean tauhad signature. The validation in $Z\to\tau_\mu\tau_{\mathrm{had}}$ events shows a data-to-prediction ratio of $0.97 \pm 0.12$ in the signal region and roughly three times more signal events than the standard reconstruction selects, confirming that the procedure works on real data.

Load-bearing premise

The load-bearing premise is that the muon's track and calorimeter deposits inside the seed jet can be identified and removed without also removing genuine tau-hadron energy, so that the standard tau-id neural net, trained on isolated taus, works unchanged on the cleaned jet.

Editorial extensions

If this is right

  • Signal efficiency for boosted $\tau_\mu\tau_{\mathrm{had}}$ pairs is restored to the isolated-tau level at all TauID working points, for both one- and three-prong tauhad decays.
  • The $Z\to\tau_\mu\tau_{\mathrm{had}}$ validation selects about three times more signal events than the standard reconstruction, improving the statistical power of searches for boosted tau pairs.
  • The improved pseudo-rapidity and transverse-momentum resolution of the visible tauhad system (pseudo-rapidity core resolution improved by a factor of 15) makes the collinear mass reconstruction show a clear $Z$-boson peak.
  • Background rejection against semileptonic heavy-flavour jets, measured on $t\bar{t}$ events, does not degrade; the ROC curves show an order-of-magnitude gain at fixed signal efficiency.
  • The method is ready to be used in beyond-the-Standard-Model searches for high-mass resonances decaying to tau pairs, such as $G\to HH\to 4\tau$.

Reading between the lines

Editorial extensions of the paper, not claims the author makes directly.

  • The same removal logic may extend to other overlapping-object cases, such as a hadronic tau overlapping with an electron jet or with tracks from pile-up, though the electron case is harder because electromagnetic showers spread more than a muon's minimum-ionising deposits.
  • The roughly 90% muon-removal efficiency in the detector region $|\eta|<0.1$, limited by a gap in the muon spectrometer, implies a residual efficiency loss for boosted tau pairs pointing there; a future detector with more hermetic muon coverage would remove even that loss.
  • At higher luminosity or with Run 3 data, the same $Z\to\tau_\mu\tau_{\mathrm{had}}$ control region could be used to measure the tauhad energy scale for boosted objects, since the muon provides a clean tag of the true tau direction.
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Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, and a circularity audit.

Referee Report

2 major / 5 minor

Summary. This paper describes a new procedure, called τμ_had, for reconstructing hadronically decaying tau leptons in highly boosted τμτhad pairs, where the muon and the tau-hadron visible decay products overlap within a single anti-kt R=0.4 seed jet. The method removes the muon's inner-detector track and calorimeter clusters from the seed jet, when their energy is compatible with muon energy loss, and then re-runs the standard tau reconstruction and TauID RNN on the cleaned jet. Efficiency studies in simulated G→HH→4τ events show that the reconstruction and identification efficiencies are recovered to near the isolated-tau level for all TauID working points. The method is validated using Z→τμτhad events in 140 fb−1 of 13 TeV ATLAS data; the ratio of observed to predicted yields in the signal region is 0.97 ± 0.12, with a total uncertainty of 12%.

Significance. The paper addresses a real bottleneck for BSM searches with boosted tau pairs. Its strengths are the direct efficiency evaluation with generator-level truth, the ROC-curve comparison with the standard algorithm, and the data validation in a Standard Model process. If the claimed efficiency recovery holds, the method offers a substantial gain in signal sensitivity for channels such as G→HH→4τ. The validation is fit-for-purpose as a consistency check, though its precision is limited by the 10% Z+jets cross-section correction.

major comments (2)
  1. [4.1] The cluster-removal step removes a calorimeter cluster only if its energy is compatible with the expected muon energy loss. For ΔR < 0.4, the muon and the tau-hadron shower can be merged into a single topological cluster whose energy is far above the muon's MIP loss, in which case the algorithm leaves the cluster in the seed jet; the converse failure (removing a cluster that also contains soft tau-hadron energy) is also possible. The paper does not report how often either case occurs or the residual energy after cleaning, yet the abstract attributes the efficiency recovery to the removal of muon information. Please add a quantitative assessment of the merged-cluster category—e.g., the fraction of signal seed jets with an unremoved muon cluster and the mean residual cluster energy—or otherwise demonstrate that this category does not compromise the claimed isolated-level efficiency.
  2. [5.4] The reported data/prediction ratio of 0.97 ± 0.12 is dominated by the 10% Z+jets cross-section correction applied to the simulation, so the validation has limited power to expose a 10-20% efficiency mis-modelling localized in the merged-cluster category described above. The paper should state this limitation explicitly and, if possible, quantify the validation's sensitivity to the muon-removal efficiency, for instance by comparing the SR and SRstd0 yield ratios.
minor comments (5)
  1. [Abstract and 4.2] The phrase 'raised to the level expected for an isolated τhad' is stronger than the 95% MuonRM efficiency and the small residual differences visible in Figures 3 and 5; consider using 'nearly' or quoting the residual efficiency difference.
  2. [4.2] The sentence 'The measurement precision for the charge and kinematic properties of the visible τhad system is similarly recovered' should specify that the η and pT resolutions are meant (as shown in Figure 7), since charge mis-assignment is not directly addressed there.
  3. [Table 2] The labels 'SRstd0' and 'SRstdtight' use a subscript zero that is not defined in the table caption; a one-line explanation in the caption would improve readability.
  4. [5.4] When quoting the background subtraction of 223 ± 5 events, please state that the uncertainty is statistical only, consistent with the notation used elsewhere in the table.
  5. [Figure 1] The y-axis label 'Fraction of events / 0.016' is unusual; consider 'Fraction of events per 0.016' for clarity.

Circularity Check

0 steps flagged · score 0.0 of 10

No significant circularity: the efficiency recovery is measured against generator-level truth, and the Z->tau_mu tau_had validation compares data to independent MC predictions.

full rationale

The central performance claim is an efficiency measurement in Monte Carlo against generator-level truth (Sections 4.1-4.2), not a quantity defined by the method's own output. The muon-removal step is an algorithmic preprocessing step that removes the ID track and energy-compatible calorimeter clusters, and the recovered efficiency is compared with the standard TauID working points evaluated on isolated tau_had candidates; this comparison is an external benchmark, not an input. The Z->tau_mu tau_had validation (Section 5) compares observed yields with predictions from Sherpa and Geant4 simulation. The only yield correction, a 10% Z+jets cross-section rescaling, is taken from an independent external ATLAS measurement of the Z boson transverse momentum distribution (Refs. [38,39]) and is assigned the full size as a systematic uncertainty; it is not fitted to the signal region. The observed-to-predicted yield ratio of 0.97 +/- 0.12 is therefore an independent check. The paper's ATLAS self-citations are to detector-performance references, such as muon reconstruction and isolated tau resolution, which are external measurements and are not used as an unverified uniqueness theorem or ansatz. The statement that the MuonRM efficiency is by definition 1.0 in Figure 5 applies only to the conditional subset where the muon was already required to be removed, and it does not enter the central efficiency recovery claim in Figures 3 and 10. The unquantified merged topological-cluster failure mode raised in the skepticism is a potential correctness or coverage limitation, but it is not an instance where a prediction reduces to its input by construction.

Assumptions & free parameters 1 free parameters · 4 assumptions · 0 invented entities

The central claim rests on four domain assumptions about muon/tau separation, the collinear approximation, and MC reliability. The only numerical factor inherited from outside is the 10% Z+jets yield correction. No new particles, forces, or conserved quantities are introduced.

free parameters (1)
  • Z+jets yield scale factor = 1.10
    Applied to predicted Z(->tautau)+jets event yields in the validation analysis (Section 3.2). Taken from prior ATLAS measurement, not fitted here; the full correction is quoted as a systematic uncertainty. It affects the data/MC comparison but is not a parameter of the tau_had method itself.
assumptions (4)
  • domain assumption Muon reconstruction is independent of the muon's isolation, so its track and calorimeter deposits can be removed from the tau seed jet without biasing tau reconstruction.
    Motivates the method in Section 4.1; relies on ATLAS muon reconstruction performance [11].
  • domain assumption Calorimeter clusters associated with the muon can be identified by compatibility with expected muon energy loss.
    The removal algorithm in Section 4.1 checks cluster energy against expected loss [43]; if this fails, the tau energy is biased.
  • domain assumption The collinear approximation holds: neutrinos from tau decays are collinear with visible decay products and dominate the missing transverse momentum.
    Used in Section 5.1 to reconstruct the Z boson mass; standard approximation [46], with events failing the geometric requirement discarded.
  • domain assumption Monte Carlo simulation accurately models the detector response and generator-level matching correctly identifies tau decay products.
    All efficiency measurements in Section 4.2 rely on generator-level truth; the data validation checks yields but not the per-event efficiency.

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Cite this review

Pith. "Pith review of Improved reconstruction of highly boosted $\tau$-lepton pairs in the $\tau\tau\rightarrow(\mu\nu_{\mu}\nu_{\tau})({hadrons}+\nu_{\tau})$ decay channels with the ATLAS detector." pith.science (2026). https://pith.science/paper/43AQZMIY

@misc{pith2026241214937,
  author       = {Pith},
  title        = {Pith review of: Improved reconstruction of highly boosted $\tau$-lepton pairs in the $\tau\tau\rightarrow(\mu\nu_\mu\nu_\tau)(hadrons+\nu_\tau)$ decay channels with the ATLAS detector},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/43AQZMIY}},
  note         = {Machine review of arXiv:2412.14937}
}
abstract

This paper presents a new $\tau$-lepton reconstruction and identification procedure at the ATLAS detector at the Large Hadron Collider, which leads to significantly improved performance in the case of physics processes where a highly boosted pair of $\tau$-leptons is produced and one $\tau$-lepton decays into a muon and two neutrinos ($\tau_{\mu}$), and the other decays into hadrons and one neutrino ($\tau_{had}$). By removing the muon information from the signals used for reconstruction and identification of the $\tau_{had}$ candidate in the boosted pair, the efficiency is raised to the level expected for an isolated $\tau_{had}$. The new procedure is validated by selecting a sample of highly boosted $Z\rightarrow\tau_{\mu}\tau_{had}$ candidates from the data sample of $140$ ${fb}^{-1}$ of proton-proton collisions at $13$ TeV recorded with the ATLAS detector. Good agreement is found between data and simulation predictions in both the $Z\rightarrow\tau_{\mu}\tau_{had}$ signal region and in a background validation region. The results presented in this paper demonstrate the effectiveness of the $\tau_{had}$ reconstruction with muon removal in enhancing the signal sensitivity of the boosted $\tau_{\mu}\tau_{had}$ channel at the ATLAS detector.

Discussion (0). Continue with ORCID to comment.

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Works this paper leans on

53 extracted references · 4 canonical work pages

  1. [10]

    ATLAS Collaboration, Reconstruction and identification of boosted di-𝜏 systems in a search for Higgs boson pairs using13TeVproton–proton collision data in ATLAS, ATLAS-CONF-2020-012, 2020, url: https://cds.cern.ch/record/2719518

  2. [1]

    Navas et al.,Review of Particle Physics, Phys

    Particle Data Group, S. Navas et al.,Review of Particle Physics, Phys. Rev. D110(2024) 030001

  3. [2]

    ATLAS Collaboration, Identification and energy calibration of hadronically decaying tau leptons with the ATLAS experiment in𝑝𝑝 collisions at√𝑠= 8TeV, Eur. Phys. J. C75 (2015) 303, arXiv: 1412.7086 [hep-ex]

  4. [3]

    ATLAS Collaboration, Measurement of the tau lepton reconstruction and identification performance in the ATLAS experiment using𝑝𝑝 collisions at√𝑠= 13TeV, ATLAS-CONF-2017-029, 2017,url: https://cds.cern.ch/record/2261772

  5. [4]

    ATLAS Collaboration, Identification of hadronic tau lepton decays using neural networks in the ATLAS experiment, ATL-PHYS-PUB-2019-033, 2019,url: https://cds.cern.ch/record/2688062

  6. [5]

    ATLAS Collaboration,Reconstruction, Identification, and Calibration of hadronically decaying tau leptons with the ATLAS detector for the LHC Run 3 and reprocessed Run 2 data, ATL-PHYS-PUB-2022-044, 2022,url: https://cds.cern.ch/record/2827111

  7. [6]

    Cacciari, G

    M. Cacciari, G. P. Salam and G. Soyez,The anti-𝑘𝑡 jet clustering algorithm, JHEP04(2008) 063, arXiv: 0802.1189 [hep-ph]

  8. [7]

    Cacciari, G

    M. Cacciari, G. P. Salam and G. Soyez,FastJet user manual, Eur. Phys. J. C72 (2012) 1896, arXiv: 1111.6097 [hep-ph]

Show all 53 references
  1. [8]

    ATLAS Collaboration, Topological cell clustering in the ATLAS calorimeters and its performance in LHC Run 1, Eur. Phys. J. C77(2017) 490, arXiv:1603.02934 [hep-ex]

  2. [9]

    Barillari et al.,Local Hadronic Calibration, ATL-LARG-PUB-2009-001-2, 2008, url: https://cds.cern.ch/record/1112035

    T. Barillari et al.,Local Hadronic Calibration, ATL-LARG-PUB-2009-001-2, 2008, url: https://cds.cern.ch/record/1112035

  3. [11]

    ATLAS Collaboration, Muon reconstruction and identification efficiency in ATLAS using the full Run 2𝑝𝑝 collision data set at√𝑠= 13TeV, Eur. Phys. J. C81(2021) 578, arXiv: 2012.00578 [hep-ex]

  4. [12]

    Randall and R

    L. Randall and R. Sundrum,Large Mass Hierarchy from a Small Extra Dimension, Phys. Rev. Lett.83(1999) 3370, arXiv:9905221 [hep-ph]

  5. [13]

    ATLAS Collaboration, The ATLAS Experiment at the CERN Large Hadron Collider, JINST3 (2008) S08003

  6. [14]

    Evans and P

    L. Evans and P. Bryant,LHC Machine, JINST3 (2008) S08001

  7. [15]

    Avoni et al.,The new LUCID-2 detector for luminosity measurement and monitoring in ATLAS, JINST13 (2018) P07017

    G. Avoni et al.,The new LUCID-2 detector for luminosity measurement and monitoring in ATLAS, JINST13 (2018) P07017

  8. [16]

    ATLAS Collaboration, Performance of the ATLAS trigger system in 2015, Eur. Phys. J. C77(2017) 317, arXiv:1611.09661 [hep-ex]

  9. [17]

    ATLAS Collaboration, Software and computing for Run 3 of the ATLAS experiment at the LHC, Eur. Phys. J. C85(2025) 234, arXiv:2404.06335 [hep-ex]. 23

  10. [18]

    ATLAS Collaboration, The ATLAS Simulation Infrastructure, Eur. Phys. J. C70(2010) 823, arXiv: 1005.4568 [physics.ins-det]

  11. [19]

    J. Alwall et al.,The automated computation of tree-level and next-to-leading order differential cross sections, and their matching to parton shower simulations, JHEP07(2014) 079, arXiv: 1405.0301 [hep-ph]

  12. [20]

    NNPDF Collaboration, R. D. Ball et al.,Parton distributions with LHC data, Nucl. Phys. B867 (2013) 244, arXiv:1207.1303 [hep-ph]

  13. [21]

    Frixione, G

    S. Frixione, G. Ridolfi and P. Nason, A positive-weight next-to-leading-order Monte Carlo for heavy flavour hadroproduction, JHEP 09(2007) 126, arXiv:0707.3088 [hep-ph]

  14. [22]

    Nason, A new method for combining NLO QCD with shower Monte Carlo algorithms, JHEP 11(2004) 040, arXiv:hep-ph/0409146

    P. Nason, A new method for combining NLO QCD with shower Monte Carlo algorithms, JHEP 11(2004) 040, arXiv:hep-ph/0409146

  15. [23]

    Frixione, P

    S. Frixione, P. Nason and C. Oleari, Matching NLO QCD computations with parton shower simulations: the POWHEG method, JHEP 11(2007) 070, arXiv:0709.2092 [hep-ph]

  16. [24]

    Alioli, P

    S. Alioli, P. Nason, C. Oleari and E. Re,A general framework for implementing NLO calculations in shower Monte Carlo programs: the POWHEG BOX, JHEP06 (2010) 043, arXiv: 1002.2581 [hep-ph]

  17. [25]

    NNPDF Collaboration, R. D. Ball et al.,Parton distributions for the LHC run II, JHEP04(2015) 040, arXiv:1410.8849 [hep-ph]

  18. [26]

    ATLAS Collaboration, Studies on top-quark Monte Carlo modelling for Top2016, ATL-PHYS-PUB-2016-020, 2016,url: https://cds.cern.ch/record/2216168

  19. [27]

    Sjöstrand et al.,An introduction to PYTHIA 8.2, Comput

    T. Sjöstrand et al.,An introduction to PYTHIA 8.2, Comput. Phys. Commun.191 (2015) 159, arXiv: 1410.3012 [hep-ph]

  20. [28]

    ATLAS Collaboration, ATLAS Pythia 8 tunes to7TeV data, ATL-PHYS-PUB-2014-021, 2014, url: https://cds.cern.ch/record/1966419

  21. [29]

    D. J. Lange,The EvtGen particle decay simulation package, Nucl. Instrum. Meth. A462 (2001) 152

  22. [30]

    Sjöstrand, S

    T. Sjöstrand, S. Mrenna and P. Skands,A brief introduction to PYTHIA 8.1, Comput. Phys. Commun.178 (2008) 852, arXiv:0710.3820 [hep-ph]

  23. [31]

    ATLAS Collaboration, The Pythia 8 A3 tune description of ATLAS minimum bias and inelastic measurements incorporating the Donnachie–Landshoff diffractive model, ATL-PHYS-PUB-2016-017, 2016,url: https://cds.cern.ch/record/2206965

  24. [32]

    A. D. Martin, W. J. Stirling, R. S. Thorne and G. Watt,Parton distributions for the LHC, Eur. Phys. J. C63(2009) 189, arXiv:0901.0002 [hep-ph]

  25. [33]

    Agostinelli et al.,Geant4 – a simulation toolkit, Nucl

    S. Agostinelli et al.,Geant4 – a simulation toolkit, Nucl. Instrum. Meth. A506 (2003) 250

  26. [34]

    ATLAS Collaboration,ATLAS data quality operations and performance for 2015–2018 data-taking, JINST15 (2020) P04003, arXiv:1911.04632 [physics.ins-det]

  27. [35]

    ATLAS Collaboration, Luminosity determination in𝑝𝑝 collisions at√𝑠= 13TeV using the ATLAS detector at the LHC, Eur. Phys. J. C83(2023) 982, arXiv:2212.09379 [hep-ex]. 24

  28. [36]

    Bothmann et al.,Event generation with Sherpa 2.2, SciPost Phys.7(2019) 034, arXiv: 1905.09127 [hep-ph]

    E. Bothmann et al.,Event generation with Sherpa 2.2, SciPost Phys.7(2019) 034, arXiv: 1905.09127 [hep-ph]

  29. [37]

    Höche, F

    S. Höche, F. Krauss, S. Schumann and F. Siegert,QCD matrix elements and truncated showers, JHEP05(2009) 053, arXiv:0903.1219 [hep-ph]

  30. [38]

    ATLAS Collaboration,Measurement of the transverse momentum distribution of Drell–Yan lepton pairs in proton–proton collisions at√𝑠= 13TeV with the ATLAS detector, Eur. Phys. J. C80(2020) 616, arXiv:1912.02844 [hep-ex]

  31. [39]

    ATLAS Collaboration, Modelling and computational improvements to the simulation of single vector-boson plus jet processes for the ATLAS experiment, JHEP08 (2022) 089, arXiv: 2112.09588 [hep-ex]

  32. [40]

    Frederix, E

    R. Frederix, E. Re and P. Torrielli, Single-top𝑡-channel hadroproduction in the four-flavour scheme with POWHEG and aMC@NLO, JHEP09(2012) 130, arXiv:1207.5391 [hep-ph]

  33. [41]

    Frixione, E

    S. Frixione, E. Laenen, P. Motylinski, C. White and B. R. Webber, Single-top hadroproduction in association with a𝑊 boson, JHEP07(2008) 029, arXiv: 0805.3067 [hep-ph]

  34. [42]

    ATLAS Collaboration,Measurements of Higgs boson production cross-sections in the𝐻→𝜏+𝜏− decay channel in𝑝𝑝 collisions at√𝑠= 13TeV with the ATLAS detector, JHEP08(2022) 175, arXiv: 2201.08269 [hep-ex]

  35. [43]

    ATLAS Collaboration,Studies of the muon momentum calibration and performance of the ATLAS detector with𝑝𝑝 collisions at√𝑠= 13TeV, Eur. Phys. J. C83 (2023) 686, arXiv: 2212.07338 [hep-ex]

  36. [44]

    ATLAS Collaboration, Reconstruction of hadronic decay products of tau leptons with the ATLAS experiment, Eur. Phys. J. C76(2016) 295, arXiv:1512.05955 [hep-ex]

  37. [45]

    ATLAS Collaboration, The performance of missing transverse momentum reconstruction and its significance with the ATLAS detector using140fb−1 of√𝑠= 13TeV𝑝𝑝 collisions, Eur. Phys. J. C85(2025) 606, arXiv:2402.05858 [hep-ex]

  38. [46]

    Ellis, I

    R. Ellis, I. Hinchliffe, M. Soldate and J. Van Der Bij,Higgs decay to𝜏+𝜏− A possible signature of intermediate mass Higgs bosons at high energy hadron colliders, Nucl. Phys. B297 (1988) 221

  39. [47]

    ATLAS Collaboration, Jet reconstruction and performance using particle flow with the ATLAS Detector, Eur. Phys. J. C77(2017) 466, arXiv:1703.10485 [hep-ex]

  40. [48]

    ATLAS Collaboration, Performance of the ATLAS muon triggers in Run 2, JINST15(2020) P09015, arXiv:2004.13447 [physics.ins-det]

  41. [49]

    ATLAS Collaboration, Performance of the missing transverse momentum triggers for the ATLAS detector during Run-2 data taking, JHEP08 (2020) 080, arXiv:2005.09554 [hep-ex]

  42. [50]

    ATLAS Collaboration,ATLAS flavour-tagging algorithms for the LHC Run 2𝑝𝑝 collision dataset, Eur. Phys. J. C83(2023) 681, arXiv:2211.16345 [physics.data-an]

  43. [51]

    ATLAS Collaboration, Jet energy scale and resolution measured in proton–proton collisions at√𝑠= 13TeV with the ATLAS detector, Eur. Phys. J. C81(2021) 689, arXiv: 2007.02645 [hep-ex]. 25

  44. [52]

    ATLAS Collaboration, Precise measurements of𝑊- and𝑍-boson transverse momentum spectra with the ATLAS detector using𝑝𝑝 collisions at√𝑠= 5.02TeV and13TeV, Eur. Phys. J. C84(2024) 1126, arXiv:2404.06204 [hep-ex]

  45. [53]

    Demokritos

    ATLAS Collaboration, ATLAS Computing Acknowledgements, ATL-SOFT-PUB-2025-001, 2025, url: https://cds.cern.ch/record/2922210. 26 The ATLAS Collaboration G. Aad 104, E. Aakvaag 17, B. Abbott 123, S. Abdelhameed 119a, K. Abeling 56, N.J. Abicht 50, S.H. Abidi 30, M. Aboelela 46, ...

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