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A search is performed for long-lived heavy neutral leptons (HNLs), produced through the decay of a $W$ boson along with a muon or electron. Two channels are explored: a leptonic channel, in which the HNL decays into two leptons and a neutrino, and a semi-leptonic channel, in which the HNL decays into a lepton and a charged pion. The search is performed with 140~fb$^{-1}$ of $\sqrt{s} = 13$ TeV proton--proton collision data collected by ATLAS during Run 2 of the Large Hadron Collider. No excess of events is observed; Dirac-like and Majorana-like HNLs with masses below 14.5 GeV and mixing coefficients as small as 10$^{-7}$ are excluded at the 95% confidence level. The results are interpreted under different assumptions on the flavour of the leptons from the HNL decays.
The DV reconstruction efficiency for an HNL with $m_N = 2$ GeV and $c\tau_N = 10$ mm, as a function of the DV radius $r_{DV}$ using the customised vertex reconstruction for a selection of the fully leptonic MC samples. Different flavour combinations are shown.
The DV reconstruction efficiency for an HNL with $m_N = 2$ GeV and $c\tau_N = 10$ mm, as a function of the DV radius $r_{DV}$ using the customised vertex reconstruction for a selection of the semi-leptonic MC samples. Different flavour combinations are shown.
The DV reconstruction efficiency for an HNL with $m_N = 2$ GeV and $c\tau_N = 10$ mm, as a function of the DV radius $r_{DV}$ using the customised vertex reconstruction for a selection of the fully leptonic MC samples. Decays from HNLs are shown for $\mu\mu$ DVs for HNLs with various masses.
The DV reconstruction efficiency for an HNL with $m_N = 2$ GeV and $c\tau_N = 10$ mm, as a function of the DV radius $r_{DV}$ using the customised vertex reconstruction for a selection of the fully leptonic MC samples. Decays from HNLs are shown for $ee$ DVs for HNLs with various masses.
Expected 95% CL for the 1SFH $e$ Dirac model.
+1$\sigma$ Expected 95% CL for the 1SFH $e$ Dirac model.
-1$\sigma$ Expected 95% CL for the 1SFH $e$ Dirac model.
+2$\sigma$ Expected 95% CL for the 1SFH $e$ Dirac model.
-2$\sigma$ Expected 95% CL for the 1SFH $e$ Dirac model.
Observed 95% CL for the 1SFH $e$ Dirac model.
Expected 95% CL for the 1SFH $\mu$ Dirac model.
+1$\sigma$ Expected 95% CL for the 1SFH $\mu$ Dirac model.
-1$\sigma$ Expected 95% CL for the 1SFH $\mu$ Dirac model.
+2$\sigma$ Expected 95% CL for the 1SFH $\mu$ Dirac model.
-2$\sigma$ Expected 95% CL for the 1SFH $\mu$ Dirac model.
Observed 95% CL for the 1SFH $\mu$ Dirac model.
Expected 95% CL for the 2QDH NH Dirac model.
+1$\sigma$ Expected 95% CL for the 2QDH NH Dirac model.
-1$\sigma$ Expected 95% CL for the 2QDH NH Dirac model.
+2$\sigma$ Expected 95% CL for the 2QDH NH Dirac model.
-2$\sigma$ Expected 95% CL for the 2QDH NH Dirac model.
Observed 95% CL for the 2QDH NH Dirac model.
Expected 95% CL for the 2QDH IH Dirac model.
+1$\sigma$ Expected 95% CL for the 2QDH IH Dirac model.
-1$\sigma$ Expected 95% CL for the 2QDH IH Dirac model.
+2$\sigma$ Expected 95% CL for the 2QDH IH Dirac model.
-2$\sigma$ Expected 95% CL for the 2QDH IH Dirac model.
Observed 95% CL for the 2QDH IH Dirac model.
Expected 95% CL for 1SFH $e$ Majorana model.
+1$\sigma$ Expected 95% CL for 1SFH $e$ Majorana model.
-1$\sigma$ Expected 95% CL for the 1SFH $e$ Majorana model.
+2$\sigma$ Expected 95% CL for the 1SFH $e$ Dirac model.
-2$\sigma$ Expected 95% CL for the 1SFH $e$ Dirac model.
Observed 95% CL for the 1SFH $e$ Dirac model.
Expected 95% CL for 1SFH $\mu$ Majorana model.
+1$\sigma$ Expected 95% CL for 1SFH $\mu$ Majorana model.
-1$\sigma$ Expected 95% CL for the 1SFH $\mu$ Majorana model.
+2$\sigma$ Expected 95% CL for the 1SFH $\mu$ Majorana model.
-2$\sigma$ Expected 95% CL for the 1SFH $\mu$ Majorana model.
Observed 95% CL for the 1SFH $\mu$ Majorana model.
Expected 95% CL for 2QDH NH Majorana model.
+1$\sigma$ Expected 95% CL for 2QDH NH Majorana model.
-1$\sigma$ Expected 95% CL for 2QDH NH Majorana model.
+2$\sigma$ Expected 95% CL for 2QDH NH Majorana model.
-2$\sigma$ Expected 95% CL for the 2QDH NH Majorana model.
Observed 95% CL for 2QDH NH Majorana model.
Expected 95% CL for 2QDH IH Majorana model
+1$\sigma$ Expected 95% CL for 2QDH IH Majorana model.
-1$\sigma$ Expected 95% CL for the 2QDH IH Majorana model.
+2$\sigma$ Expected 95% CL for the 2QDH IH Majorana model.
-2$\sigma$ Expected 95% CL for the 2QDH IH Majorana model.
Observed 95% CL for the 2QDH IH Majorana model.
Expected 95% CL for the 1SFH $e$ Dirac model on the $N$ mean proper lifetime $c\tau_N$ vs. $m_N$.
+1$\sigma$ Expected 95% CL for the 1SFH $e$ Dirac model on the $N$ mean proper lifetime $c\tau_N$ vs. $m_N$.
-1$\sigma$ Expected 95% CL for the 1SFH $e$ Dirac model on the N mean proper lifetime $c\tau_N$ vs. $m_N$.
+2$\sigma$ Expected 95% CL for the 1SFH $e$ Dirac model on the $N$ mean proper lifetime $c\tau_N$ vs. $m_N$.
-2$\sigma$ Expected 95% CL for the 1SFH $e$ Dirac model on the $N$ mean proper lifetime $c\tau_N$ vs. $m_N$.
Observed 95% CL for the 1SFH $e$ Dirac model on the $N$ mean proper lifetime $c\tau_N$ vs. $m_N$.
Expected 95% CL for the 1SFH $\mu$ Dirac model on the $N$ mean proper lifetime $c\tau_N$ vs. $m_N$.
+1$\sigma$ Expected 95% CL for the 1SFH $\mu$ Dirac model on the $N$ mean proper lifetime $c\tau_N$ vs. $m_N$.
-1$\sigma$ Expected 95% CL for the 1SFH $\mu$ Dirac model on the $N$ mean proper lifetime $c\tau_N$ vs. $m_N$.
+2$\sigma$ Expected 95% CL for the 1SFH $\mu$ Dirac model on the $N$ mean proper lifetime $c\tau_N$ vs. $m_N$.
-2$\sigma$ Expected 95% CL for the 1SFH $\mu$ Dirac model on the $N$ mean proper lifetime $c\tau_N$ vs. $m_N$.
Observed 95% CL for the 1SFH $\mu$ Dirac model on the $N$ mean proper lifetime $c\tau_N$ vs. $m_N$.
Expected 95% CL for the 2QDH NH Dirac model on the $N$ mean proper lifetime $c\tau_N$ vs. $m_N$.
+1$\sigma$ Expected 95% CL for the 2QDH NH Dirac model on the $N$ mean proper lifetime $c\tau_N$ vs. $m_N$.
-1$\sigma$ Expected 95% CL for the 2QDH NH Dirac model on the $N$ mean proper lifetime $c\tau_N$ vs. $m_N$.
+2$\sigma$ Expected 95% CL for the 2QDH NH Dirac model on the $N$ mean proper lifetime $c\tau_N$ vs. $m_N$.
-2$\sigma$ Expected 95% CL for the 2QDH NH Dirac model on the $N$ mean proper lifetime $c\tau_N$ vs. $m_N$.
Observed 95% CL for the 2QDH NH Dirac model on the $N$ mean proper lifetime $c\tau_N$ vs. $m_N$.
Expected 95% CL for the 2QDH IH Dirac model on the $N$ mean proper lifetime $c\tau_N$ vs. $m_N$.
+1$\sigma$ Expected 95% CL for the 2QDH IH Dirac model on the $N$ mean proper lifetime $c\tau_N$ vs. $m_N$.
-1$\sigma$ Expected 95% CL for the 2QDH IH Dirac model on the $N$ mean proper lifetime $c\tau_N$ vs. $m_N$.
+2$\sigma$ Expected 95% CL for the 2QDH IH Dirac model on the $N$ mean proper lifetime $c\tau_N$ vs. $m_N$.
-2$\sigma$ Expected 95% CL for the 2QDH IH Dirac model on the $N$ mean proper lifetime $c\tau_N$ vs. $m_N$.
Observed 95% CL for the 2QDH IH Dirac model on the $N$ mean proper lifetime $c\tau_N$ vs. $m_N$.
Expected 95% CL for 1SFH $e$ Majorana model on the $N$ mean proper lifetime $c\tau_N$ vs. $m_N$.
+1$\sigma$ Expected 95% CL for 1SFH $e$ Majorana model on the $N$ mean proper lifetime $c\tau_N$ vs. $m_N$.
-1$\sigma$ Expected 95% CL for the 1SFH $e$ Majorana model on the $N$ mean proper lifetime $c\tau_N$ vs. $m_N$.
+2$\sigma$ Expected 95% CL for the 1SFH $e$ Dirac model on the $N$ mean proper lifetime $c\tau_N$ vs. $m_N$.
-2$\sigma$ Expected 95% CL for the 1SFH $e$ Dirac model on the $N$ mean proper lifetime $c\tau_N$ vs. $m_N$.
Observed 95% CL for the 1SFH $e$ Dirac model on the $N$ mean proper lifetime $c\tau_N$ vs. $m_N$.
Expected 95% CL for 1SFH $\mu$ Majorana model on the $N$ mean proper lifetime $c\tau_N$ vs. $m_N$.
+1$\sigma$ Expected 95% CL for 1SFH $\mu$ Majorana model on the $N$ mean proper lifetime $c\tau_N$ vs. $m_N$.
-1$\sigma$ Expected 95% CL for the 1SFH $\mu$ Majorana model on the $N$ mean proper lifetime $c\tau_N$ vs. $m_N$.
+2$\sigma$ Expected 95% CL for the 1SFH $\mu$ Majorana model on the $N$ mean proper lifetime $c\tau_N$ vs. $m_N$.
-2$\sigma$ Expected 95% CL for the 1SFH $\mu$ Majorana model on the $N$ mean proper lifetime $c\tau_N$ vs. $m_N$.
Observed 95% CL for the 1SFH $\mu$ Majorana model on the $N$ mean proper lifetime $c\tau_N$ vs. $m_N$.
Expected 95% CL for 2QDH NH Majorana model on the $N$ mean proper lifetime $c\tau_N$ vs. $m_N$.
+1$\sigma$ Expected 95% CL for 2QDH NH Majorana model on the $N$ mean proper lifetime $c\tau_N$ vs. $m_N$.
-1$\sigma$ Expected 95% CL for 2QDH NH Majorana model on the N mean proper lifetime $c\tau_N$ vs. $m_N$.
+2$\sigma$ Expected 95% CL for 2QDH NH Majorana model on the $N$ mean proper lifetime $c\tau_N$ vs. $m_N$.
-2$\sigma$ Expected 95% CL for the 2QDH NH Majorana model on the $N$ mean proper lifetime $c\tau_N$ vs. $m_N$.
Observed 95% CL for 2QDH NH Majorana model on the $N$ mean proper lifetime $c\tau_N$ vs. $m_N$.
Expected 95% CL for 2QDH IH Majorana model on the $N$ mean proper lifetime $c\tau_N$ vs. $m_N$.
+1$\sigma$ Expected 95% CL for 2QDH IH Majorana model on the $N$ mean proper lifetime $c\tau_N$ vs. $m_N$.
-1$\sigma$ Expected 95% CL for the 2QDH IH Majorana model on the $N$ mean proper lifetime $c\tau_N$ vs. $m_N$.
+2$\sigma$ Expected 95% CL for the 2QDH IH Majorana model on the $N$ mean proper lifetime $c\tau_N$ vs. $m_N$.
-2$\sigma$ Expected 95% CL for the 2QDH IH Majorana model on the $N$ mean proper lifetime $c\tau_N$ vs. $m_N$.
Observed 95% CL for the 2QDH IH Majorana model on the $N$ mean proper lifetime $c\tau_N$ vs. $m_N$.
Cutflow for background MC samples all channels
Raw cutflow for $\mu\mu\mu$ 0.1 mm signal samples
Raw cutflow for $\mu\mu\mu$ 1 mm signal samples
Raw cutflow for $\mu\mu\mu$ 10 mm signal samples
Raw cutflow for $\mu\mu\mu$ 100 mm signal samples
Raw cutflow for $\mu\mu\mu$ 1000 mm signal samples
Raw cutflow for $\mu\mu e$ 0.1 mm signal samples
Raw cutflow for $\mu\mu e$ 1 mm signal samples
Raw cutflow for $\mu\mu e$ 10 mm signal samples
Raw cutflow for $\mu\mu e$ 100 mm signal samples
Raw cutflow for $\mu\mu e$ 1000 mm signal samples
Raw cutflow for uee 0.1 mm signal samples
Raw cutflow for uee 1 mm signal samples
Raw cutflow for uee 10 mm signal samples
Raw cutflow for uee 100 mm signal samples
Raw cutflow for uee 1000 mm signal samples
Raw cutflow for eee 0.1 mm signal samples
Raw cutflow for eee 1 mm signal samples
Raw cutflow for eee 10 mm signal samples
Raw cutflow for eee 100 mm signal samples
Raw cutflow for eee 1000 mm signal samples
Raw cutflow for $ee\mu$ 0.1 mm signal samples
Raw cutflow for $ee\mu$ 1 mm signal samples
Raw cutflow for $ee\mu$ 10 mm signal samples
Raw cutflow for $ee\mu$ 100 mm signal samples
Raw cutflow for $ee\mu$ 1000 mm signal samples
Raw cutflow for $e\mu\mu$ 0.1 mm signal samples
Raw cutflow for $e\mu\mu$ 1 mm signal samples
Raw cutflow for $e\mu\mu$ 10 mm signal samples
Raw cutflow for $e\mu\mu$ 100 mm signal samples
Raw cutflow for $e\mu\mu$ 1000 mm signal samples
Raw cutflow for $\mu\mu\pi$ 10 mm signal samples
Raw cutflow for $\mu\mu\pi$ 100 mm signal samples
Raw cutflow for $\mu\mu\pi$ 1000 mm signal samples
Raw cutflow for $\mu e\pi$ 10 mm signal samples
Raw cutflow for $\mu e\pi$ 100 mm signal samples
Raw cutflow for $\mu e\pi$ 1000 mm signal samples
Raw cutflow for $e\mu\pi$ 10 mm signal samples
Raw cutflow for $e\mu\pi$ 100 mm signal samples
Raw cutflow for $e\mu\pi$ 1000 mm signal samples
Raw cutflow for $ee\pi$ 10 mm signal samples
Raw cutflow for $ee\pi$ 100 mm signal samples
Raw cutflow for $ee\pi$ 1000 mm signal samples
Cross sections of eee channels for Dirac models
Cross sections of $ee\mu$ channels for Dirac models
Cross sections of $e\mu\mu$ channels for Dirac models
Cross sections of $\mu\mu\mu$ channels for Dirac models
Cross sections of $\mu\mu e$ channels for Dirac models
Cross sections of uee channels for Dirac models
Cross sections of eee channels for Majorana models
Cross sections of $ee\mu$ channels for Majorana models
Cross sections of $e\mu\mu$ channels for Majorana models
Cross sections of $\mu\mu\mu$ channels for Majorana models
Cross sections of $\mu\mu e$ channels for Majorana models
Cross sections of uee channels for Majorana models
Cross sections of eee channels for QD Dirac limit models
Cross sections of $ee\mu$ channels for QD Dirac limit models
Cross sections of $e\mu\mu$ channels for QD Dirac limit models
Cross sections of $\mu\mu\mu$ channels for QD Dirac limit models
Cross sections of $\mu\mu e$ channels for QD Dirac limit models
Cross sections of uee channels for QD Dirac limit models
Cross sections of eee channels for QD Majorana limit models
Cross sections of $ee\mu$ channels for QD Majorana limit models
Cross sections of $e\mu\mu$ channels for QD Majorana limit models
Cross sections of $\mu\mu\mu$ channels for QD Majorana limit models
Cross sections of $\mu\mu e$ channels for QD Majorana limit models
Cross sections of uee channels for QD Majorana limit models
Cross sections of $ee\pi$ channels for Dirac models
Cross sections of $ee\pi$ channels for Majorana models
Cross sections of $ee\pi$ channels for QD Dirac limit models
Cross sections of $ee\pi$ channels for QD Majorana limit models
Cross sections of $e\mu\pi$ channels for Dirac models
Cross sections of $e\mu\pi$ channels for Majorana models
Cross sections of $e\mu\pi$ channels for QD Dirac limit models
Cross sections of $e\mu\pi$ channels for QD Majorana limit models
Cross sections of $\mu\mu\pi$ channels for Dirac models
Cross sections of $\mu\mu\pi$ channels for Majorana models
Cross sections of $\mu\mu\pi$ channels for QD Dirac limit models
Cross sections of $\mu\mu\pi$ channels for QD Majorana limit models
Cross sections of $\mu e\pi$ channels for Dirac models
Cross sections of $\mu e\pi$ channels for Majorana models
Cross sections of $\mu e\pi$ channels for QD Dirac limit models
Cross sections of $\mu e\pi$ channels for QD Majorana limit models
Signal efficiencies for leptonic channels
Signal efficiencies for semi-leptonic channels
A search for a long-lived, heavy neutral lepton ($\mathcal{N}$) in 139 fb$^{-1}$ of $\sqrt{s}=13$ TeV $pp$ collision data collected by the ATLAS detector at the Large Hadron Collider is reported. The $\mathcal{N}$ is produced via $W \rightarrow \mathcal{N} \mu$ or $W \rightarrow \mathcal{N} e$ and decays into two charged leptons and a neutrino, forming a displaced vertex. The $\mathcal{N}$ mass is used to discriminate between signal and background. No signal is observed, and limits are set on the squared mixing parameters of the $\mathcal{N}$ with the left-handed neutrino states for the $\mathcal{N}$ mass range $3$ GeV $< m_{\mathcal{N}} < 15$ GeV. For the first time, limits are given for both single-flavor and multiflavor mixing scenarios motivated by neutrino flavor oscillation results for both the normal and inverted neutrino-mass hierarchies.
Expected and observed 95% CL for the 1SFH e Dirac model.
Expected and observed 95% CL for the 1SFH e Majorana model.
Expected and observed 95% CL for the 1SFH mu Dirac model.
Expected and observed 95% CL for the 1SFH mu Majorana model.
Expected and observed 95% CL for the 2QDH NH Dirac model.
Expected and observed 95% CL for the 2QDH NH Majorana model.
Expected and observed 95% CL for the 2QDH IH Dirac model.
Expected and observed 95% CL for the 2QDH IH Majorana model.
Cutflow for six simulated signal channels showing the weighted number of expected events based on the single-flavour mixing model in the Majorana limit. Each column uses the generated signal sample with the mass hypothesis $m_N = 10$ GeV and proper decay length $c\tau_N = 10$ mm.
Cutflow for the six channels in data showing the number of events passing each successive signal selection for Majorana HNLs.
The event selection efficiency for each mass-lifetime point in all six studied channels. Shown is the fraction of the produced MC simulation events that pass all signal region selections. An entry of 0 indicates no events were selected.
The dominant signal uncertainty is due to differences in reconstruction of displaced vertices and tracks between data and MC. This is evaluated by comparing $K^{0}_{S} \rightarrow \pi^+\pi^-$ event yields in the VR and in MC produced with Pythia8.186 in bins of $p_\mathrm{T}$ and $r_\mathrm{DV}$. The data/MC ratio is normalized to the bin nearest the IP where the tracking and vertexing reconstruction algorithms are expected to be most robust. The symmetrized difference from 1.0 is applied to each signal vertex as a per-event systematic variation.
Expected and observed yields in the different analysis regions (prefit) for the 1SFH e Dirac model (10 GeV, 10mm).
Expected and observed yields in the different analysis regions (postfit) for the 1SFH e Dirac model (10 GeV, 10mm).
Expected and observed yields in the different analysis regions (prefit) for the 1SFH e Majorana model (10 GeV, 10mm).
Expected and observed yields in the different analysis regions (postfit) for the 1SFH e Majorana model (10 GeV, 10mm).
Expected and observed yields in the different analysis regions (prefit) for the 1SFH u Dirac model (10 GeV, 10mm).
Expected and observed yields in the different analysis regions (postfit) for the 1SFH u Dirac model (10 GeV, 10mm).
Expected and observed yields in the different analysis regions (prefit) for the 1SFH u Majorana model (10 GeV, 10mm).
Expected and observed yields in the different analysis regions (postfit) for the 1SFH u Majorana model (10 GeV, 10mm).
Expected and observed yields in the different analysis regions (prefit) for the 2QDH (NH) Dirac model (10 GeV, 10mm).
Expected and observed yields in the different analysis regions (postfit) for the 2QDH (NH) Dirac model (10 GeV, 10mm).
Expected and observed yields in the different analysis regions (prefit) for the 2QDH (NH) Majorana model (10 GeV, 10mm).
Expected and observed yields in the different analysis regions (postfit) for the 2QDH (NH) Majorana model (10 GeV, 10mm).
Expected and observed yields in the different analysis regions (prefit) for the 2QDH (IH) Dirac model (10 GeV, 10mm).
Expected and observed yields in the different analysis regions (postfit) for the 2QDH (IH) Dirac model (10 GeV, 10mm).
Expected and observed yields in the different analysis regions (prefit) for the 2QDH (IH) Majorana model (10 GeV, 10mm).
Expected and observed yields in the different analysis regions (postfit) for the 2QDH (IH) Majorana model (10 GeV, 10mm).
The total displaced vertexing efficiency as a function of $r_{DV}$ for the custom configuration used in this analysis. The definition of the secondary vertex efficiency can be found in defined in \cite{ATL-PHYS-PUB-2019-013}. The efficiency is shown for $\mu-\mu\mu$, $\mu-\mu e$ and $\mu-ee$ signals with $m_N=10$~GeV and $c\tau_N=10$~mm.
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