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. 2015 Apr 17;75(4):152. doi: 10.1140/epjc/s10052-015-3344-6

Search for long-lived particles decaying to jet pairs

R Aaij 41, B Adeva 37, M Adinolfi 46, A Affolder 52, Z Ajaltouni 5, S Akar 6, J Albrecht 9, F Alessio 38, M Alexander 51, S Ali 41, G Alkhazov 30, P Alvarez Cartelle 37, A A Alves Jr 25,38, S Amato 2, S Amerio 22, Y Amhis 7, L An 3, L Anderlini 17, J Anderson 40, R Andreassen 57, M Andreotti 16, J E Andrews 58, R B Appleby 54, O Aquines Gutierrez 10, F Archilli 38, A Artamonov 35, M Artuso 59, E Aslanides 6, G Auriemma 25, M Baalouch 5, S Bachmann 11, J J Back 48, A Badalov 36, C Baesso 60, W Baldini 16, R J Barlow 54, C Barschel 38, S Barsuk 7, W Barter 47, V Batozskaya 28, V Battista 39, A Bay 39, L Beaucourt 4, J Beddow 51, F Bedeschi 23, I Bediaga 1, S Belogurov 31, K Belous 35, I Belyaev 31, E Ben-Haim 8, G Bencivenni 18, S Benson 38, J Benton 46, A Berezhnoy 32, R Bernet 40, A Bertolin 22, M-O Bettler 47, M van Beuzekom 41, A Bien 11, S Bifani 45, T Bird 54, A Bizzeti 17, P M Bjørnstad 54, T Blake 48, F Blanc 39, J Blouw 10, S Blusk 59, V Bocci 25, A Bondar 34, N Bondar 30,38, W Bonivento 15, S Borghi 54, A Borgia 59, M Borsato 7, T J V Bowcock 52, E Bowen 40, C Bozzi 16, D Brett 54, M Britsch 10, T Britton 59, J Brodzicka 54, N H Brook 46, A Bursche 40, J Buytaert 38, S Cadeddu 15, R Calabrese 16, M Calvi 20, M Calvo Gomez 36, P Campana 18, D Campora Perez 38, L Capriotti 54, A Carbone 14, G Carboni 24, R Cardinale 19,38, A Cardini 15, L Carson 50, K Carvalho Akiba 2,38, RCM Casanova Mohr 36, G Casse 52, L Cassina 20, L Castillo Garcia 38, M Cattaneo 38, Ch Cauet 9, R Cenci 23, M Charles 8, Ph Charpentier 38, M Chefdeville 4, S Chen 54, S-F Cheung 55, N Chiapolini 40, M Chrzaszcz 26,40, X Cid Vidal 38, G Ciezarek 41, P E L Clarke 50, M Clemencic 38, H V Cliff 47, J Closier 38, V Coco 38, J Cogan 6, E Cogneras 5, V Cogoni 15, L Cojocariu 29, G Collazuol 22, P Collins 38, A Comerma-Montells 11, A Contu 15,38, A Cook 46, M Coombes 46, S Coquereau 8, G Corti 38, M Corvo 16, I Counts 56, B Couturier 38, G A Cowan 50, D C Craik 48, AC Crocombe 48, M Cruz Torres 60, 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Fiutowski 27, P Fol 53, M Fontana 10, F Fontanelli 19, R Forty 38, O Francisco 2, M Frank 38, C Frei 38, M Frosini 17, J Fu 21,38, E Furfaro 24, A Gallas Torreira 37, D Galli 14, S Gallorini 22,38, S Gambetta 19, M Gandelman 2, P Gandini 59, Y Gao 3, J García Pardiñas 37, J Garofoli 59, J Garra Tico 47, L Garrido 36, D Gascon 36, C Gaspar 38, U Gastaldi 16, R Gauld 55, L Gavardi 9, G Gazzoni 5, A Geraci 21, E Gersabeck 11, M Gersabeck 54, T Gershon 48, Ph Ghez 4, A Gianelle 22, S Gianì 39, V Gibson 47, L Giubega 29, V V Gligorov 38, C Göbel 60, D Golubkov 31, A Golutvin 31,38,53, A Gomes 1, C Gotti 20, M Grabalosa Gándara 5, R Graciani Diaz 36, L A Granado Cardoso 38, E Graugés 36, E Graverini 40, G Graziani 17, A Grecu 29, E Greening 55, S Gregson 47, P Griffith 45, L Grillo 11, O Grünberg 63, B Gui 59, E Gushchin 33, Yu Guz 35,38, T Gys 38, C Hadjivasiliou 59, G Haefeli 39, C Haen 38, S C Haines 47, S Hall 53, B Hamilton 58, T Hampson 46, X Han 11, S Hansmann-Menzemer 11, N Harnew 55, S T Harnew 46, J Harrison 54, J He 38, T Head 39, V Heijne 41,, K Hennessy 52, P Henrard 5, L Henry 8, J A Hernando Morata 37, E van Herwijnen 38, M Heß 63, A Hicheur 2, D Hill 55, M Hoballah 5, C Hombach 54, W Hulsbergen 41, N Hussain 55, D Hutchcroft 52, D Hynds 51, M Idzik 27, P Ilten 56, R Jacobsson 38, A Jaeger 11, J Jalocha 55, E Jans 41, A Jawahery 58, F Jing 3, M John 55, D Johnson 38, C R Jones 47, C Joram 38, B Jost 38, N Jurik 59, S Kandybei 43, W Kanso 6, M Karacson 38, T M Karbach 38, S Karodia 51, M Kelsey 59, I R Kenyon 45, T Ketel 42, B Khanji 20,38, C Khurewathanakul 39, S Klaver 54, K Klimaszewski 28, O Kochebina 7, M Kolpin 11, I Komarov 39, R F Koopman 42, P Koppenburg 38,41, M Korolev 32, L Kravchuk 33, K Kreplin 11, M Kreps 48, G Krocker 11, P Krokovny 34, F Kruse 9, W Kucewicz 26, M Kucharczyk 20,26, V Kudryavtsev 34, K Kurek 28, T Kvaratskheliya 31, V N La Thi 39, D Lacarrere 38, G Lafferty 54, A Lai 15, D Lambert 50, R W Lambert 42, G Lanfranchi 18, C Langenbruch 48, B Langhans 38, T Latham 48, C Lazzeroni 45, R Le Gac 6, J van Leerdam 41, J-P Lees 4, R Lefèvre 5, A Leflat 32, J Lefrançois 7, O Leroy 6, T Lesiak 26, B Leverington 11, Y Li 3, T Likhomanenko 64, M Liles 52, R Lindner 38, C Linn 38, F Lionetto 40, B Liu 15, S Lohn 38, I Longstaff 51, J H Lopes 2, P Lowdon 40, D Lucchesi 22, H Luo 50, A Lupato 22, E Luppi 16, O Lupton 55, F Machefert 7, I V Machikhiliyan 31, F Maciuc 29, O Maev 30, S Malde 55, A Malinin 64, G Manca 15, G Mancinelli 6, A Mapelli 38, J Maratas 5, JF Marchand 4, U Marconi 14, C Marin Benito 36, P Marino 23, R Märki 39, J Marks 11, G Martellotti 25, M Martinelli 39, D Martinez Santos 42, F Martinez Vidal 65, D Martins Tostes 2, A Massafferri 1, R Matev 38, Z Mathe 38, C Matteuzzi 20, A Mazurov 45, M McCann 53, J McCarthy 45, A McNab 54, R McNulty 12, B McSkelly 52, B Meadows 57, F Meier 9, M Meissner 11, M Merk 41, D A Milanes 62, M-N Minard 4, N Moggi 14, J Molina Rodriguez 60, S Monteil 5, M Morandin 22, P Morawski 27, A Mordà 6, M J Morello 23, J Moron 27, A-B Morris 50, R Mountain 59, F Muheim 50, K Müller 40, M Mussini 14, B Muster 39, P Naik 46, T Nakada 39, R Nandakumar 49, I Nasteva 2, M Needham 50, N Neri 21, S Neubert 38, N Neufeld 38, M Neuner 11, A D Nguyen 39, T D Nguyen 39, C Nguyen-Mau 39, M Nicol 7, V Niess 5, R Niet 9, N Nikitin 32, T Nikodem 11, A Novoselov 35, D P O’Hanlon 48, A Oblakowska-Mucha 27, V Obraztsov 35, S Ogilvy 51, O Okhrimenko 44, R Oldeman 15, C J G Onderwater 66, M Orlandea 29, B Osorio Rodrigues 1, J M Otalora Goicochea 2, A Otto 38, P Owen 53, A Oyanguren 65, B K Pal 59, A Palano 13, F Palombo 21, M Palutan 18, J Panman 38, A Papanestis 38,49, M Pappagallo 51, L L Pappalardo 16, C Parkes 54, C J Parkinson 9,45, G Passaleva 17, G D Patel 52, M Patel 53, C Patrignani 19, A Pearce 49,54, A Pellegrino 41, G Penso 25, M Pepe Altarelli 38, S Perazzini 14, P Perret 5, L Pescatore 45, E Pesen 67, K Petridis 53, A Petrolini 19, E Picatoste Olloqui 36, B Pietrzyk 4, T Pilař 48, D Pinci 25, A Pistone 19, S Playfer 50, M Plo Casasus 37, F Polci 8, A Poluektov 34,48, I Polyakov 31, E Polycarpo 2, A Popov 35, D Popov 10, B Popovici 29, C Potterat 2, E Price 46, JD Price 52, J Prisciandaro 39, A Pritchard 52, C Prouve 46, V Pugatch 44, A Puig Navarro 39, G Punzi 23, W Qian 4, B Rachwal 26, J H Rademacker 46, B Rakotomiaramanana 39, M Rama 23, M S Rangel 2, I Raniuk 43, N Rauschmayr 38, G Raven 42, F Redi 53, S Reichert 54, M M Reid 48, A C dos Reis 1, S Ricciardi 49, S Richards 46, M Rihl 38, K Rinnert 52, V Rives Molina 36, P Robbe 7, A B Rodrigues 1, E Rodrigues 54, P Rodriguez Perez 54, S Roiser 38, V Romanovsky 35, A Romero Vidal 37, M Rotondo 22, J Rouvinet 39, T Ruf 38, H Ruiz 36, P Ruiz Valls 65, J J Saborido Silva 37, N Sagidova 30, P Sail 51, B Saitta 15, V Salustino Guimaraes 2, C Sanchez Mayordomo 65, B Sanmartin Sedes 37, R Santacesaria 25, C Santamarina Rios 37, E Santovetti 24, A Sarti 18, C Satriano 25, A Satta 24, DM Saunders 46, D Savrina 31,32, M Schiller 38, H Schindler 38, M Schlupp 9, M Schmelling 10, B Schmidt 38, O Schneider 39, A Schopper 38, M-H Schune 7, R Schwemmer 38, B Sciascia 18, A Sciubba 25, A Semennikov 31, I Sepp 53, N Serra 40, J Serrano 6, L Sestini 22, P Seyfert 11, M Shapkin 35, I Shapoval 16,43, Y Shcheglov 30, T Shears 52, L Shekhtman 34, V Shevchenko 64, A Shires 9, R Silva Coutinho 48, G Simi 22, M Sirendi 47, N Skidmore 46, I Skillicorn 51, T Skwarnicki 59, N A Smith 52, E Smith 49,55, E Smith 53, J Smith 47, M Smith 54, H Snoek 41, M D Sokoloff 57, F J P Soler 51, F Soomro 39, D Souza 46, B Souza De Paula 2, B Spaan 9, P Spradlin 51, S Sridharan 38, F Stagni 38, M Stahl 11, S Stahl 11, O Steinkamp 40, O Stenyakin 35, F Sterpka 59, S Stevenson 55, S Stoica 29, S Stone 59, B Storaci 40, S Stracka 23, M Straticiuc 29, U Straumann 40, R Stroili 22, L Sun 57, W Sutcliffe 53, K Swientek 27, S Swientek 9, V Syropoulos 42, M Szczekowski 28, P Szczypka 38,39, T Szumlak 27, S T’Jampens 4, M Teklishyn 7, G Tellarini 16, F Teubert 38, C Thomas 55, E Thomas 38, J van Tilburg 41, V Tisserand 4, M Tobin 39, J Todd 57, S Tolk 42, L Tomassetti 16, D Tonelli 38, S Topp-Joergensen 55, N Torr 55, E Tournefier 4, S Tourneur 39, M T Tran 39, M Tresch 40, A Trisovic 38, A Tsaregorodtsev 6, P Tsopelas 41, N Tuning 41, M Ubeda Garcia 38, A Ukleja 28, A Ustyuzhanin 64, U Uwer 11, C Vacca 15, V Vagnoni 14, G Valenti 14, A Vallier 7, R Vazquez Gomez 18, P Vazquez Regueiro 37, C Vázquez Sierra 37, S Vecchi 16, J J Velthuis 46, M Veltri 17, G Veneziano 39, M Vesterinen 11, JVVB Viana Barbosa 38, B Viaud 7, D Vieira 2, M Vieites Diaz 37, X Vilasis-Cardona 36, A Vollhardt 40, D Volyanskyy 10, D Voong 46, A Vorobyev 30, V Vorobyev 34, C Voß 63, J A de Vries 41, R Waldi 63, C Wallace 48, R Wallace 12, J Walsh 23, S Wandernoth 11, J Wang 59, D R Ward 47, N K Watson 45, D Websdale 53, M Whitehead 48, D Wiedner 11, G Wilkinson 38,55, M Wilkinson 59, M P Williams 45, M Williams 56, HW Wilschut 66, F F Wilson 49, J Wimberley 58, J Wishahi 9, W Wislicki 28, M Witek 26, G Wormser 7, S A Wotton 47, S Wright 47, K Wyllie 38, Y Xie 61, Z Xing 59, Z Xu 39, Z Yang 3, X Yuan 3, O Yushchenko 35, M Zangoli 14, M Zavertyaev 10, L Zhang 3, W C Zhang 12, Y Zhang 3, A Zhelezov 11, A Zhokhov 31, L Zhong 3
PMCID: PMC4423877  PMID: 25983649

Abstract

A search is presented for long-lived particles with a mass between 25 and 50 GeV/c2 and a lifetime between 1 and 200ps in a sample of proton–proton collisions at a centre-of-mass energy of s=7 TeV, corresponding to an integrated luminosity of 0.62 fb-1, collected by the LHCb detector. The particles are assumed to be pair-produced by the decay of a standard model-like Higgs boson. The experimental signature of the long-lived particle is a displaced vertex with two associated jets. No excess above the background is observed and limits are set on the production cross-section as a function of the long-lived particle mass and lifetime.

Introduction

A variety of models for physics beyond the standard model (SM) feature the existence of new massive particles whose coupling to lighter particles is sufficiently small that they are long-lived. If these massive particles decay to SM particles and have a lifetime between approximately 1ps and 1ns, characteristic of weak decays, they can be identified by their displaced decay vertex. Examples of such particles are the lightest supersymmetric particle in SUSY models with baryon or lepton number violation [14], the next-to-lightest supersymmetric particle in gravity mediated SUSY [5] and the neutral πv particle in hidden valley (HV) models with a non-abelian gauge symmetry [68]. The latter model is particularly interesting as it predicts that experimental studies have sensitivity to the production of long-lived particles in SM Higgs decays.

This paper reports on a search for πv particles, pair-produced in the decay of a SM-like Higgs particle with a mass of 120 GeV/c2, close to the mass of the scalar bosondiscovered by the ATLAS and CMS experiments [9, 10].1 The πv candidates are identified by two hadronic jets originating from a displaced vertex. The vertex is required to be displaced from the proton–proton collision axis by more than 0.4 mm and less than 4.8 mm. The lower bound is chosen to reject most of the background from heavy flavour decays. The upper bound ensures that vertices are inside the LHCb beam pipe, which generates a sizeable background of hadronic interaction vertices. The signal is extracted from a fit to the di-jet invariant mass distribution. The analysis is sensitive to a πv particle with a mass between 25 and 50 GeV/c2 and a lifetime between 1 and 200ps. The lower boundary on the mass range arises from the requirement to identify two hadronic jets while the upper boundary is mostly due to the geometric acceptance of the LHCb detector.

This analysis uses data collected in proton–proton (pp) collisions at a centre-of-mass energy of s=7 TeV. The data correspond to an integrated luminosity of 0.62 fb-1, collected during the second half of the year 2011 when an analysis-specific trigger selection was implemented. Although similar searches have been reported by the CDF [11], D0 [12], ATLAS [13] and CMS [14] experiments, LHCb has a unique coverage for long-lived particles with relatively small mass and lifetime, because its trigger makes only modest requirements on transverse momentum.

Detector description

The LHCb detector [15] is a single-arm forward spectrometer covering the pseudorapidity range 2<η<5, designed for the study of particles containing b or c quarks. The detector includes a high-precision tracking system consisting of a silicon-strip vertex detector surrounding the pp interaction region [16], a large-area silicon-strip detector located upstream of a dipole magnet with a bending power of about 4 Tm, and three stations of silicon-strip detectors and straw drift tubes [17] placed downstream of the magnet. The tracking system provides a measurement of momentum, p, with a relative uncertainty that varies from 0.4 % at low momentum to 0.6 % at 100 GeV/c. The minimum distance of a track to a primary vertex, the impact parameter, is measured with a resolution of (15+29/pT)μm, where pT is the component of p transverse to the beam, in GeV/c. Different types of charged hadrons are distinguished using information from two ring-imaging Cherenkov detectors [18]. Photon, electron and hadron candidates are identified by a calorimeter system consisting of scintillating-pad and preshower detectors, an electromagnetic calorimeter and a hadronic calorimeter. Muons are identified by a system composed of alternating layers of iron and multiwire proportional chambers [19].

Event simulation

For the event simulation, pp collisions are generated using Pythia 6.4 [20] with a specific LHCb configuration [21] using CTEQ6L [22] parton density functions. Decays of hadronic particles are described by EvtGen  [23], in which final-state radiation is generated using Photos  [24]. The interaction of the generated particles with the detector and its response are implemented using the Geant4 toolkit [25, 26] as described in Ref. [27].

To simulate a signal event, a SM-like scalar Higgs boson with a mass of 120 GeV/c2 is generated with Pythia through the gluon–gluon fusion mechanism, and is forced to decay into two spin-zero πv particles, each of which decays to bb¯. Assuming the decay occurs via a vector or axial-vector coupling, the bb¯ final state is preferred to light quarks, due to helicity conservation [68]. The average track multiplicity of the πv decay, including tracks from secondary b and c decays, varies from about 15 for a πv mass of 25 GeV/c2 to about 20 for larger masses. Simulated events are retained if at least four charged tracks from the decay of the generated πv particles are within the LHCb acceptance, which corresponds to about 30 % of the cases. For πv particles within the acceptance on average about ten tracks can be reconstructed.

Simulated samples with πv lifetimes of 10ps and 100ps and πv masses of 25, 35, 43 and 50 GeV/c2 are generated; other πv lifetimes are studied by reweighting these samples. Two additional samples are generated in which πv particles with a lifetime of 10ps and a mass of 35 GeV/c2 decay to either cc¯ or ss¯ quark pairs.

Event selection and signal extraction

The selection of candidates starts with the LHCb trigger [28], which consists of a hardware stage, based on information from the calorimeter and muon systems, followed by a software stage, which applies a full event reconstruction. The hardware trigger (L0) requires a single high-pT hadron, electron, muon or photon signature. The thresholds range from pT>1.48GeV/c for muons, to transverse energy larger than 3.5GeV for hadrons. The total L0 efficiency, dominated by the hadron trigger selection, depends on the mass and final state of the πv particle and is typically 20 %, including the detector acceptance.

The software trigger is divided into two stages and consists of algorithms that run a simplified version of the offline track reconstruction, which allows identification of displaced tracks and vertices. For this analysis the primary signature in the first software stage (HLT1) is a single high-quality displaced track with high pT . The efficiency of HLT1 relative to L0 accepted events is typically 60 %. However, this efficiency reduces rapidly for vertices that are displaced by more than about 5 mm from the beamline due to limitations in the track reconstruction in the vertex detector.

In the final trigger stage (HLT2) two different signatures are exploited. The first of these relies on the generic reconstruction of a displaced vertex, using an algorithm similar to that used for the primary vertex (PV) reconstruction [29]. Secondary vertices are distinguished from PVs using the distance to the interaction region in the transverse plane (Rxy). To eliminate contributions from interactions with material, a so-called ‘material veto’ removes vertices in a region defined as an envelope around the detector material [30]. Events are selected when they have a displaced vertex with at least four tracks, a sum of the scalar pT of all tracks that is larger than 3 GeV/c, a distance Rxy larger than 0.4 mm and an invariant mass of the particles associated with this vertex mvtx above 4.5 GeV/c2. To further refine the selection, vertices are required to have either Rxy>2 mm or mvtx>10GeV/c2.

The second HLT2 signature is designed to identify two-, three- and four-body exclusive b-hadron decays [31]. A multivariate algorithm is used for the identification of secondary vertices consistent with the decay of a b hadron. The combined efficiency of the two HLT2 selections relative to events accepted by L0 and HLT1 is about 60 %.

The offline candidate reconstruction starts from a generic secondary vertex search, similar to that applied in the trigger, but using tracks from the offline reconstruction as input. At this stage at least six tracks per vertex are required and the sum of the scalar pT of all tracks must be above 3 GeV/c. The vertex is required to have either Rxy>0.4 mm and mvtx>9.7GeV/c2, or Rxy>2.5 mm and mvtx>8.5GeV/c2, or Rxy>4 mm and mvtx>6.5GeV/c2.

The vertex reconstruction is followed by a jet reconstruction procedure. Inputs to the jet clustering are obtained using a particle flow approach [32] that selects charged particles, neutral calorimeter deposits and a small contribution from Ks0 and Λ0 decays. To reduce contamination from particles that do not originate from the displaced vertex, only charged particles that have a smaller distance of closest approach relative to the displaced vertex than to any PV in the event are retained. Furthermore, the distance to the displaced vertex is required to be less than 2 mm, which also allows tracks from displaced b and c vertices in the πvbb¯ decay chain to be accepted.

The jet clustering uses the anti-kT algorithm [33] with a cone size of 0.7. Only jets with a pT above 5 GeV/c are used. Additional requirements are made to enhance the fraction of well-reconstructed hadronic jets: first, the charged particle with the largest pT in the jet must have a pT above 0.9 GeV/c, yet carry no more than 70 % of the pT of the jet. Second, to remove jets whose energy is dominated by neutral particles, which cannot be unambiguously associated with a vertex, at least 10 % of the pT of the jet must be carried by charged particles.

The di-jet invariant mass is computed from the reconstructed four-momenta of the two jets. Correction factors to the jet energy are determined from the simulation and parameterised as a function of the number of reconstructed PVs in the event, to account for effects due to multiple interactions and the underlying event [32].

Two further requirements are made to enhance signal purity. First, a corrected mass is computed as

mcorr=m2+psinθ2+psinθ, 1

where m is the di-jet invariant mass and θ is the pointing angle between the di-jet momentum vector p and its displacement vector d=xDV-xPV, where xDV is the position of the displaced vertex and xPV the position of the PV. To select candidates pointing back to a PV, only events with m/mcorr>0.7 are retained. A requirement on this ratio is preferred over a requirement on the pointing angle itself, since its efficiency depends less strongly on the boost and the mass of the candidate.

Second, a requirement is made on the distance ΔR=Δϕ2+Δη2 between the two jets, where ϕ is the azimuthal angle and η the pseudorapidity. A background consisting of back-to-back jet candidates, for example di-jet bb¯-events, appears mainly at large values of reconstructed mass, and is characterised by a large difference between the jets in both ϕ and η. Only candidates with ΔR<2.2 are accepted.

Finally, in order to facilitate a reliable estimate of the trigger efficiency, only candidates triggered by particles belonging to one of the jets are kept. Table 1 shows the efficiency to select a πv particle, for an illustrative mass of 35 GeV/c2 and lifetime of 10ps, together with the yield in the data after the most important selection steps. The total efficiency for other masses and lifetimes, as well as for the decays to light quark jets, is shown in Table 2. The efficiencies listed in Tables 1 and 2 represent the number of selected candidates divided by the number of generated events. As the selection efficiencies for the two πv particles in an event are practically independent, the fraction of selected events with more than one candidate is less than a few percent in simulated signal. In data no events with more than one πv candidate are found.

Table 1.

Average number of selected candidates per event (efficiency) in % for the main stages of the offline selection for simulated H0πvπv events with πvbb¯, mH0=120GeV/c2, mπv=35GeV/c2 and τπv=10ps. The pre-selection consists of the acceptance, trigger and offline vertex reconstruction. It represents the first stage in which the candidate yield on the total data sample, shown in the right column, can be counted. The reported uncertainty on the efficiency is only the statistical uncertainty from the finite sample size

Selection step Signal efficiency Yield in data
Pre-selection 2.125 ± 0.018 2,555,377
Jet reconstruction 1.207 ± 0.014 117,054
m/mcorr and ΔR 0.873 ± 0.012 58,163
Trigger on candidate 0.778 ± 0.012 29,921

Table 2.

Average number of selected candidates per event (efficiency) in % for different πv masses, lifetimes and decay modes. The reported uncertainty is only the statistical uncertainty from the finite sample size. No simulated samples were generated for the 100ps decay to light quarks

Decay mπv [GeV/c2 ] Signal efficiency
τπv=10ps τπv=100ps
πvbb¯ 25 0.373 ± 0.008 0.0805 ± 0.0019
35 0.778 ± 0.012 0.181 ± 0.005
43 0.743 ± 0.011 0.183 ± 0.003
50 0.573 ± 0.015 0.154 ± 0.004
πvcc¯ 35 2.18 ± 0.05
πvss¯ 35 2.06 ± 0.04

Figure 1 shows the mass and pT distributions for selected di-jet candidates in data and in simulated signal events, assuming a πv particle with a mass of 25, 35 or 50 GeV/c2. The turn-on at low values in the mass distribution of events observed in data (Fig. 1a) is caused by the minimum pT requirement on the jets. The rest of the distribution falls off exponentially. The pT distribution shown in Fig. 1b illustrates that long-lived particles with a higher mass have lower pT as there is less momentum available in the Higgs decay. This affects the selection efficiency since for a given decay time the transverse decay length is proportional to pT.

Fig. 1.

Fig. 1

Invariant mass (a) and pT distribution (b) for di-jet candidates in data and in hidden valley models with 25, 35 and 50 GeV/c2 πv masses and 10ps lifetime. For visibility, the simulated signal is scaled to 0.62 fb-1 assuming a Higgs cross-section of 10 nb and branching fractions of 100 % for B(Hπvπv) and B(πvbb¯)

Studies on simulated events have shown that both the shape and the normalisation of the mass distribution in data are compatible with the expected background from bb¯ production. It is not possible to generate sufficiently large samples of bb¯ events to use these for a quantitative estimate of the background after the final selection. Therefore, the signal yield is extracted by a fit to the invariant mass distribution assuming a smooth shape for the background, as discussed in Sect. 6.

Since the background yield, the shape of the background invariant mass distribution and the selection efficiency strongly depend on the radial displacement Rxy, limits are extracted from a simultaneous maximum likelihood fit to the di-jet invariant mass distribution in five bins of Rxy. The intervals are chosen in the most sensitive region, between 0.4 and 4.8 mm. The events at larger radii are not used as they contribute only marginally to the sensitivity. Figure 2 shows the distribution of Rxy of selected displaced vertices for data and simulated signal events, together with the bin boundaries. The effect of the reduction in efficiency at large radii due to the material veto and the HLT1 trigger is visible, as is the effect of requirements on Rxy in the trigger. The trigger effects are more pronounced in data than in simulated signal, because signal events are less affected by cuts on the vertex invariant mass.

Fig. 2.

Fig. 2

Distribution of the distance of the displaced vertex to the interaction region in the transverse plane for data and for a hidden valley model with mπv=35GeV/c2 and τπv=10ps after the full selection. For visibility, the simulated signal is scaled to 0.62 fb-1 assuming a Higgs cross-section of 10 nb and branching fractions of 100 % for B(Hπvπv) and B(πvbb¯). The boundaries of the intervals used in the fit are indicated by the dotted lines. The generated Rxy distribution is approximately exponential with an average of about 2 mm

The background di-jet invariant mass distribution is characterised by an exponential falloff, with a low-mass threshold determined mostly by the minimum pT requirement of the jets. It is modelled by a single-sided exponential function convoluted with a bifurcated Gaussian function. The parameters of the background model are fitted to data, independently in each Rxy bin. The signal is modelled by a bifurcated Gaussian function, whose parameters are determined from simulated events in bins of Rxy. The effect of the uncertainty on the jet-energy scale is included by a scale parameter for the mass, which is common to all bins and constrained using a sample of Z+jet events, as explained in Sect. 5. Additional nuisance parameters are added to account for the finite statistics of the simulated samples and the systematic uncertainties on the signal efficiency and the luminosity. The fit model is implemented using the RooFit  [34] package. Figure 3 shows the fit result in the five radial bins for a signal model with mπv=35GeV/c2 and τπv=10ps.

Fig. 3.

Fig. 3

Di-jet invariant mass distributions for each of the five Rxy bins, superimposed with the fits for a hidden valley model with mπv=35GeV/c2 and τπv=10ps. The blue line indicates the result of the total fit to the data. The black short-dashed line is the background-only contribution, and the red long-dashed line is the fitted signal contribution. For illustration, the green dash-dotted line shows the signal scaled to a cross-section of 17 pb, which corresponds to the SM Higgs production cross-section at 7 TeV [35]

Systematic uncertainties

Several sources of systematic uncertainties have been considered. The uncertainties depend on the πv mass and are summarised in Table 3. The uncertainty on the vertex finding efficiency is assessed by comparing the efficiency of the vertexing algorithm on a sample of B0j/ψK0 with K0K+π- events in data and simulation as a function of Rxy. The efficiency difference is about 7.5 % at large Rxy, which is taken as an estimate of the uncertainty on the vertex finding algorithm efficiency. Since the B0 vertices have only four tracks, and the πv decays studied in this paper have typically more tracks, this is considered a conservative estimate. The uncertainty on the track finding efficiency for prompt tracks in LHCb is 1.4 % per track, with a small dependence on track kinematics [36]. The uncertainty for displaced tracks was evaluated in the context of a recent LHCb measurement of b-hadron lifetimes [37] and extrapolated to larger Rxy, leading to a per-track uncertainty of 2 %. Due to requirements on the minimal number of tracks in the vertex, this translates into an uncertainty on the vertex finding efficiency, which is estimated to be 2 % for signal events. Adding in quadrature the track efficiency and the vertex finding algorithm efficiency uncertainties leads to a total uncertainty of 7.9 % on the vertex reconstruction. The selection on the vertex sum-pT and mass is affected by the track finding efficiency as well. Propagating the per-track uncertainty leads to an uncertainty on the vertex selection efficiency of up to 2.9 %, depending on the πv mass.

Table 3.

Systematic uncertainties on the selection efficiency and luminosity for simulated hidden valley events with a lifetime of 10ps and various πv masses

Source Relative uncertainty (%)
πv Mass [GeV/c2 ] 25 35 43 50
Vertex reconstruction 7.9 7.9 7.9 7.9
Vertex scalar-pT and mass 2.9 2.3 2.0 1.7
Jet reconstruction 1.3 0.6 0.4 0.3
Jet identification 2.9 3.0 3.2 3.2
Jet pointing 4.6 2.9 2.6 2.0
L0 trigger 4.6 4.5 4.5 4.4
HLT1 trigger 4.1 4.0 4.0 4.3
HLT2 trigger 5.9 5.9 6.1 6.3
Luminosity 1.7 1.7 1.7 1.7
Total 13.3 12.7 12.6 12.6

The uncertainties related to the jet selection are determined by comparing jets in data and simulation on a sample of Z+jet events, analogously to a recent LHCb measurement of Z+jet production [32]. The Z candidate is reconstructed in the μ+μ- final state from two oppositely charged tracks, identified as muons, that form a good vertex and have an invariant mass in the range 60–120 GeV/c2. Jets are reconstructed using the same selection of input particles as in the reconstruction of jets for long-lived particles, except that the origin vertex is in this case the PV consistent with the Z vertex. The differences between data and simulation in the Z+jet sample are parameterised as function of the jet pT and subsequently propagated to the simulated hidden valley signal samples.

The uncertainty on the jet energy scale is derived from the ratio of transverse momenta of the jet and the Z, which are expected to have a back-to-back topology, and correlated transverse momenta. Data and simulation agree within about 2 %, resulting in an uncertainty on the di-jet invariant mass scale of 4 %. This uncertainty on the signal shape is taken into account in the fitting procedure. The uncertainty on the jet-energy scale also affects the jet reconstruction efficiency due to the requirement on the minimum jet pT. It leads to an uncertainty on the efficiency between 0.3 and 1.3 %, depending on the assumed πv particle mass. The uncertainty on the hadronic jet identification requirements are assessed using the Z+jet sample as well and amount to about 3 %.

The resolutions on the pointing angle θ and on ΔR are dominated by the resolution on the direction of the πv candidate, which in turn is determined by the jet angular resolution. The latter is estimated from the difference between data and simulation in the resolution of the azimuthal angle between the jet and the Z. Due to the limited statistics in the Z+jet sample a relatively large uncertainty between 2.0 and 4.6 % is obtained, depending on the πv mass.

The trigger selection efficiency on signal is determined from the simulation. The trigger efficiencies in data and simulation are compared using a sample of generic BJ/ψX events that contain an offline reconstructed displaced vertex, but are triggered independently of the displaced vertex trigger lines. The integrated efficiency difference for the trigger stages L0, HLT1 and HLT2 amounts to systematic uncertainties of at most 4.6, 4.3 and 6.3 % respectively. This is a conservative estimate since the trigger efficiencies for the sample of displaced J/ψ vertices are smaller than the efficiencies for the signal, which consists of heavier, more displaced objects with a larger number of tracks. Finally, the uncertainty on the luminosity at the LHCb interaction point is 1.7 % [38].

Several alternatives have been considered for the background mass model, in particular with an additional exponential component, or a component that is independent of the mass. With these models the estimated background yield at higher mass is larger than with the nominal background model, leading to tighter limits on the signal. As the nominal model gives the most conservative limit, no additional systematic uncertainty is assigned.

Results

The fit procedure is performed for a πv mass of 25, 35, 43 and 50 GeV/c2 and for several values of the lifetime in between 1 and 200ps. No significant signal is observed for any combination of πv mass and lifetime. Upper limits are extracted using the CLs method [39] with a frequentist treatment of the nuisance parameters described above, as implemented in the RooStats  [40] package.

Limits are set on the Higgs production cross-section multiplied by the branching fraction into long-lived particles σ(H)×B(Hπvπv). In the simulation it is assumed that both πv particles decay to the same final state. If the decay width of the πv particle is dominated by final states other than qq¯, the limits scale as 1/(Bqq¯(2-Bqq¯)) where Bqq¯ is the πvqq¯ branching fraction. The obtained 95 % CL upper limits on σ(H)×B(Hπvπv), under the assumption of a 100 % branching fraction to bb¯, are shown in Table 4 and in Fig. 4. As the background decreases with the observed di-jet invariant mass, the limits become stronger with increasing πv mass. The sensitivity has an optimal value at a lifetime of about 5ps.

Table 4.

Observed 95 % CL cross-section upper limits on σ(H)×B(Hπvπv) (in pb) on a hidden valley [68] model for various πv masses and lifetimes. Both πv particles are assumed to decay into bb¯, unless specified otherwise

πv Mass [GeV/c2 ] πv Lifetime [ps ]
1 2 5 10 20 50 100 200
25 106.3 54.6 43.8 54.2 80.0 164.1 285.7 588.5
35 19.0 10.4 8.0 8.9 13.3 25.4 46.5 89.8
43 10.5 5.6 4.4 4.7 6.7 12.4 22.7 42.8
50 10.6 5.1 3.7 3.8 4.8 9.3 16.2 29.3
35 (πvcc¯) 3.7 2.4 2.1 2.4 3.4 6.7 12.5 24.1
35 (πvss¯) 3.4 2.1 1.9 2.2 3.3 6.4 11.6 22.0

Fig. 4.

Fig. 4

Observed 95 % CL cross-section upper limits on a hidden valley model [68] for various πv masses, as a function of πv lifetime. Both πv particles are assumed to decay into bb¯, unless specified otherwise

Additional limits are set on models with a πv particle decaying to cc¯ and to ss¯. The limits for πv decay to uu¯ and dd¯ are expected to be the same as for ss¯. The light quark decays result in a higher displaced vertex track multiplicity, and lighter jets, leading to a higher selection efficiency. Consequently, the limits for decays to light quark jets are more stringent than those for decays to b-quark jets.

Conclusion

A search has been presented for massive, long-lived particles in a sample of pp collisions at s=7 TeV, corresponding to an integrated luminosity of 0.62 fb-1, collected by the LHCb experiment. The long-lived spin-zero particles are assumed to be pair-produced in the decay of a 120 GeV/c2 SM Higgs, and to decay to two hadronic jets. They appear for instance as πv particles in hidden valley models. A single πv particle is identified by a displaced vertex and two associated jets. No significant signal for πv particles with a mass between 25 and 50 GeV/c2 and a lifetime between 1 and 200ps is observed. Assuming a 100% branching fraction to b-quark jets, the 95 % CL upper limits on the production cross-section σ(H)×B(Hπvπv) are in the range 4–600 pb.

The results cover a region in mass and lifetime that so far has been unexplored at the LHC. The obtained upper limits are more restrictive than results from the Tevatron experiments in the same mass and lifetime region. The best sensitivity is obtained for πv particles with a lifetime of about 5ps and a mass above approximately 40 GeV/c2. The SM Higgs cross-section at 7 TeV is about 17 pb [35]. The measurements in the most sensitive region exclude branching fractions of greater than 25 % for a SM Higgs boson to pair produce πv particles that decay to two hadronic jets.

Acknowledgments

We express our gratitude to our colleagues in the CERN accelerator departments for the excellent performance of the LHC. We thank the technical and administrative staff at the LHCb institutes. We acknowledge support from CERN and from the national agencies: CAPES, CNPq, FAPERJ and FINEP (Brazil); NSFC (China); CNRS/IN2P3 (France); BMBF, DFG, HGF and MPG (Germany); INFN (Italy); FOM and NWO (The Netherlands); MNiSW and NCN (Poland); MEN/IFA (Romania); MinES and FANO (Russia); MinECo (Spain); SNSF and SER (Switzerland); NASU (Ukraine); STFC (United Kingdom); NSF (USA). The Tier1 computing centres are supported by IN2P3 (France), KIT and BMBF (Germany), INFN (Italy), NWO and SURF (The Netherlands), PIC (Spain), GridPP (United Kingdom). We are indebted to the communities behind the multiple open source software packages on which we depend. We are also thankful for the computing resources and the access to software R&D tools provided by Yandex LLC (Russia). Individual groups or members have received support from EPLANET, Marie Skłodowska-Curie Actions and ERC (European Union), Conseil général de Haute-Savoie, Labex ENIGMASS and OCEVU, Région Auvergne (France), RFBR (Russia), XuntaGal and GENCAT (Spain), Royal Society and Royal Commission for the Exhibition of 1851 (United Kingdom).

Footnotes

1

The results are equally valid for a Higgs particle with a mass up to 126 GeV/c2 within a few percent.

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