EUROPEAN ORGANIZATION FOR NUCLEAR RESEARCH (CERN)
LHCb-PAPER-2011-017
CERN-PH-EP-2011-163
December 26, 2013
arXiv:1110.3970v1 [hep-ex] 18 Oct 2011
Search for CP violation in D+ → K − K + π + decays
R. Aaij23 , B. Adeva36 , M. Adinolfi42 , C. Adrover6 , A. Affolder48 , Z. Ajaltouni5 , J. Albrecht37 , F. Alessio37 ,
M. Alexander47 , G. Alkhazov29 , P. Alvarez Cartelle36 , A.A. Alves Jr22 , S. Amato2 , Y. Amhis38 , J. Anderson39 ,
R.B. Appleby50 , O. Aquines Gutierrez10 , F. Archilli18,37 , L. Arrabito53 , A. Artamonov 34 , M. Artuso52,37 ,
E. Aslanides6 , G. Auriemma22,m , S. Bachmann11 , J.J. Back44 , D.S. Bailey50 , V. Balagura30,37 , W. Baldini16 ,
R.J. Barlow50 , C. Barschel37 , S. Barsuk7 , W. Barter43 , A. Bates47 , C. Bauer10 , Th. Bauer23 , A. Bay38 , I. Bediaga1 ,
K. Belous34 , I. Belyaev30,37 , E. Ben-Haim8 , M. Benayoun8 , G. Bencivenni18 , S. Benson46 , J. Benton42 , R. Bernet39 ,
M.-O. Bettler17 , M. van Beuzekom23 , A. Bien11 , S. Bifani12 , A. Bizzeti17,h , P.M. Bjørnstad50 , T. Blake49 ,
F. Blanc38 , C. Blanks49 , J. Blouw11 , S. Blusk52 , A. Bobrov33 , V. Bocci22 , A. Bondar33 , N. Bondar29 ,
W. Bonivento15 , S. Borghi47 , A. Borgia52 , T.J.V. Bowcock48 , C. Bozzi16 , T. Brambach9 , J. van den Brand24 ,
J. Bressieux38 , D. Brett50 , S. Brisbane51 , M. Britsch10 , T. Britton52 , N.H. Brook42 , H. Brown48 ,
A. Büchler-Germann39 , I. Burducea28 , A. Bursche39 , J. Buytaert37 , S. Cadeddu15 , J.M. Caicedo Carvajal37 ,
O. Callot7 , M. Calvi20,j , M. Calvo Gomez35,n , A. Camboni35 , P. Campana18,37 , A. Carbone14 , G. Carboni21,k ,
R. Cardinale19,i,37 , A. Cardini15 , L. Carson36 , K. Carvalho Akiba23 , G. Casse48 , M. Cattaneo37 , M. Charles51 ,
Ph. Charpentier37 , N. Chiapolini39 , K. Ciba37 , X. Cid Vidal36 , G. Ciezarek49 , P.E.L. Clarke46,37 , M. Clemencic37 ,
H.V. Cliff43 , J. Closier37 , C. Coca28 , V. Coco23 , J. Cogan6 , P. Collins37 , F. Constantin28 , G. Conti38 , A. Contu51 ,
A. Cook42 , M. Coombes42 , G. Corti37 , G.A. Cowan38 , R. Currie46 , B. D’Almagne7 , C. D’Ambrosio37 , P. David8 ,
I. De Bonis4 , S. De Capua21,k , M. De Cian39 , F. De Lorenzi12 , J.M. De Miranda1 , L. De Paula2 , P. De Simone18 ,
D. Decamp4 , M. Deckenhoff9 , H. Degaudenzi38,37 , M. Deissenroth11 , L. Del Buono8 , C. Deplano15 , O. Deschamps5 ,
F. Dettori15,d , J. Dickens43 , H. Dijkstra37 , P. Diniz Batista1 , S. Donleavy48 , F. Dordei11 , A. Dosil Suárez36 ,
D. Dossett44 , A. Dovbnya40 , F. Dupertuis38 , R. Dzhelyadin34 , C. Eames49 , S. Easo45 , U. Egede49 , V. Egorychev30 ,
S. Eidelman33 , D. van Eijk23 , F. Eisele11 , S. Eisenhardt46 , R. Ekelhof9 , L. Eklund47 , Ch. Elsasser39 ,
D.G. d’Enterria35,o , D. Esperante Pereira36 , L. Estève43 , A. Falabella16,e , E. Fanchini20,j , C. Färber11 , G. Fardell46 ,
C. Farinelli23 , S. Farry12 , V. Fave38 , V. Fernandez Albor36 , M. Ferro-Luzzi37 , S. Filippov32 , C. Fitzpatrick46 ,
M. Fontana10 , F. Fontanelli19,i , R. Forty37 , M. Frank37 , C. Frei37 , M. Frosini17,f,37 , S. Furcas20 ,
A. Gallas Torreira36 , D. Galli14,c , M. Gandelman2 , P. Gandini51 , Y. Gao3 , J-C. Garnier37 , J. Garofoli52 ,
J. Garra Tico43 , L. Garrido35 , C. Gaspar37 , N. Gauvin38 , M. Gersabeck37 , T. Gershon44,37 , Ph. Ghez4 , V. Gibson43 ,
V.V. Gligorov37 , C. Göbel54 , D. Golubkov30 , A. Golutvin49,30,37 , A. Gomes2 , H. Gordon51 ,
M. Grabalosa Gándara35 , R. Graciani Diaz35 , L.A. Granado Cardoso37 , E. Graugés35 , G. Graziani17 , A. Grecu28 ,
S. Gregson43 , B. Gui52 , E. Gushchin32 , Yu. Guz34 , T. Gys37 , G. Haefeli38 , C. Haen37 , S.C. Haines43 , T. Hampson42 ,
S. Hansmann-Menzemer11 , R. Harji49 , N. Harnew51 , J. Harrison50 , P.F. Harrison44 , J. He7 , V. Heijne23 ,
K. Hennessy48 , P. Henrard5 , J.A. Hernando Morata36 , E. van Herwijnen37 , E. Hicks48 , W. Hofmann10 ,
K. Holubyev11 , P. Hopchev4 , W. Hulsbergen23 , P. Hunt51 , T. Huse48 , R.S. Huston12 , D. Hutchcroft48 , D. Hynds47 ,
V. Iakovenko41 , P. Ilten12 , J. Imong42 , R. Jacobsson37 , A. Jaeger11 , M. Jahjah Hussein5 , E. Jans23 , F. Jansen23 ,
P. Jaton38 , B. Jean-Marie7 , F. Jing3 , M. John51 , D. Johnson51 , C.R. Jones43 , B. Jost37 , S. Kandybei40 ,
M. Karacson37 , T.M. Karbach9 , J. Keaveney12 , U. Kerzel37 , T. Ketel24 , A. Keune38 , B. Khanji6 , Y.M. Kim46 ,
M. Knecht38 , S. Koblitz37 , P. Koppenburg23 , A. Kozlinskiy23 , L. Kravchuk32 , K. Kreplin11 , M. Kreps44 ,
G. Krocker11 , P. Krokovny11 , F. Kruse9 , K. Kruzelecki37 , M. Kucharczyk20,25,37 , S. Kukulak25 , R. Kumar14,37 ,
T. Kvaratskheliya30,37 , V.N. La Thi38 , D. Lacarrere37 , G. Lafferty50 , A. Lai15 , D. Lambert46 , R.W. Lambert37 ,
E. Lanciotti37 , G. Lanfranchi18 , C. Langenbruch11 , T. Latham44 , R. Le Gac6 , J. van Leerdam23 , J.-P. Lees4 ,
R. Lefèvre5 , A. Leflat31,37 , J. Lefrançois7 , O. Leroy6 , T. Lesiak25 , L. Li3 , L. Li Gioi5 , M. Lieng9 , M. Liles48 ,
R. Lindner37 , C. Linn11 , B. Liu3 , G. Liu37 , J.H. Lopes2 , E. Lopez Asamar35 , N. Lopez-March38 , J. Luisier38 ,
F. Machefert7 , I.V. Machikhiliyan4,30 , F. Maciuc10 , O. Maev29,37 , J. Magnin1 , S. Malde51 , R.M.D. Mamunur37 ,
G. Manca15,d , G. Mancinelli6 , N. Mangiafave43 , U. Marconi14 , R. Märki38 , J. Marks11 , G. Martellotti22 ,
A. Martens7 , L. Martin51 , A. Martı́n Sánchez7 , D. Martinez Santos37 , D. Martins Tostes1 , A. Massafferri1 ,
2
Z. Mathe12 , C. Matteuzzi20 , M. Matveev29 , E. Maurice6 , B. Maynard52 , A. Mazurov16,32,37 , G. McGregor50 ,
R. McNulty12 , C. Mclean14 , M. Meissner11 , M. Merk23 , J. Merkel9 , R. Messi21,k , S. Miglioranzi37 , D.A. Milanes13,37 ,
M.-N. Minard4 , J. Molina Rodriguez54 , S. Monteil5 , D. Moran12 , P. Morawski25 , R. Mountain52 , I. Mous23 ,
F. Muheim46 , K. Müller39 , R. Muresan28,38 , B. Muryn26 , M. Musy35 , J. Mylroie-Smith48 , P. Naik42 , T. Nakada38 ,
R. Nandakumar45 , J. Nardulli45 , I. Nasteva1 , M. Nedos9 , M. Needham46 , N. Neufeld37 , C. Nguyen-Mau38,p ,
M. Nicol7 , S. Nies9 , V. Niess5 , N. Nikitin31 , A. Oblakowska-Mucha26 , V. Obraztsov34 , S. Oggero23 , S. Ogilvy47 ,
O. Okhrimenko41 , R. Oldeman15,d , M. Orlandea28 , J.M. Otalora Goicochea2 , P. Owen49 , B. Pal52 , J. Palacios39 ,
M. Palutan18 , J. Panman37 , A. Papanestis45 , M. Pappagallo13,b , C. Parkes47,37 , C.J. Parkinson49 , G. Passaleva17 ,
G.D. Patel48 , M. Patel49 , S.K. Paterson49 , G.N. Patrick45 , C. Patrignani19,i , C. Pavel-Nicorescu28 ,
A. Pazos Alvarez36 , A. Pellegrino23 , G. Penso22,l , M. Pepe Altarelli37 , S. Perazzini14,c , D.L. Perego20,j ,
E. Perez Trigo36 , A. Pérez-Calero Yzquierdo35 , P. Perret5 , M. Perrin-Terrin6 , G. Pessina20 , A. Petrella16,37 ,
A. Petrolini19,i , B. Pie Valls35 , B. Pietrzyk4 , T. Pilar44 , D. Pinci22 , R. Plackett47 , S. Playfer46 , M. Plo Casasus36 ,
G. Polok25 , A. Poluektov44,33 , E. Polycarpo2 , D. Popov10 , B. Popovici28 , C. Potterat35 , A. Powell51 , T. du Pree23 ,
J. Prisciandaro38 , V. Pugatch41 , A. Puig Navarro35 , W. Qian52 , J.H. Rademacker42 , B. Rakotomiaramanana38 ,
M.S. Rangel2 , I. Raniuk40 , G. Raven24 , S. Redford51 , M.M. Reid44 , A.C. dos Reis1 , S. Ricciardi45 , K. Rinnert48 ,
D.A. Roa Romero5 , P. Robbe7 , E. Rodrigues47 , F. Rodrigues2 , P. Rodriguez Perez36 , G.J. Rogers43 , S. Roiser37 ,
V. Romanovsky34 , J. Rouvinet38 , T. Ruf37 , H. Ruiz35 , G. Sabatino21,k , J.J. Saborido Silva36 , N. Sagidova29 ,
P. Sail47 , B. Saitta15,d , C. Salzmann39 , M. Sannino19,i , R. Santacesaria22 , C. Santamarina Rios36 , R. Santinelli37 ,
E. Santovetti21,k , M. Sapunov6 , A. Sarti18,l , C. Satriano22,m , A. Satta21 , M. Savrie16,e , D. Savrina30 , P. Schaack49 ,
M. Schiller11 , S. Schleich9 , M. Schmelling10 , B. Schmidt37 , O. Schneider38 , A. Schopper37 , M.-H. Schune7 ,
R. Schwemmer37 , A. Sciubba18,l , M. Seco36 , A. Semennikov30 , K. Senderowska26 , I. Sepp49 , N. Serra39 , J. Serrano6 ,
P. Seyfert11 , B. Shao3 , M. Shapkin34 , I. Shapoval40,37 , P. Shatalov30 , Y. Shcheglov29 , T. Shears48 , L. Shekhtman33 ,
O. Shevchenko40 , V. Shevchenko30 , A. Shires49 , R. Silva Coutinho54 , H.P. Skottowe43 , T. Skwarnicki52 ,
A.C. Smith37 , N.A. Smith48 , K. Sobczak5 , F.J.P. Soler47 , A. Solomin42 , F. Soomro49 , B. Souza De Paula2 ,
B. Spaan9 , A. Sparkes46 , P. Spradlin47 , F. Stagni37 , S. Stahl11 , O. Steinkamp39 , S. Stoica28 , S. Stone52,37 ,
B. Storaci23 , M. Straticiuc28 , U. Straumann39 , N. Styles46 , V.K. Subbiah37 , S. Swientek9 , M. Szczekowski27 ,
P. Szczypka38 , T. Szumlak26 , S. T’Jampens4 , E. Teodorescu28 , F. Teubert37 , C. Thomas51,45 , E. Thomas37 ,
J. van Tilburg11 , V. Tisserand4 , M. Tobin39 , S. Topp-Joergensen51 , M.T. Tran38 , A. Tsaregorodtsev6 , N. Tuning23 ,
M. Ubeda Garcia37 , A. Ukleja27 , P. Urquijo52 , U. Uwer11 , V. Vagnoni14 , G. Valenti14 , R. Vazquez Gomez35 ,
P. Vazquez Regueiro36 , S. Vecchi16 , J.J. Velthuis42 , M. Veltri17,g , K. Vervink37 , B. Viaud7 , I. Videau7 , D. Vieira2 ,
X. Vilasis-Cardona35,n , J. Visniakov36 , A. Vollhardt39 , D. Voong42 , A. Vorobyev29 , H. Voss10 , K. Wacker9 ,
S. Wandernoth11 , J. Wang52 , D.R. Ward43 , A.D. Webber50 , D. Websdale49 , M. Whitehead44 , D. Wiedner11 ,
L. Wiggers23 , G. Wilkinson51 , M.P. Williams44,45 , M. Williams49 , F.F. Wilson45 , J. Wishahi9 , M. Witek25,37 ,
W. Witzeling37 , S.A. Wotton43 , K. Wyllie37 , Y. Xie46 , F. Xing51 , Z. Yang3 , R. Young46 , O. Yushchenko34 ,
M. Zavertyaev10,a , F. Zhang3 , L. Zhang52 , W.C. Zhang12 , Y. Zhang3 , A. Zhelezov11 , L. Zhong3 , E. Zverev31 ,
A. Zvyagin 37 .
1 Centro
Brasileiro de Pesquisas Fı́sicas (CBPF), Rio de Janeiro, Brazil
Federal do Rio de Janeiro (UFRJ), Rio de Janeiro, Brazil
3 Center for High Energy Physics, Tsinghua University, Beijing, China
4 LAPP, Université de Savoie, CNRS/IN2P3, Annecy-Le-Vieux, France
5 Clermont Université, Université Blaise Pascal, CNRS/IN2P3, LPC, Clermont-Ferrand, France
6 CPPM, Aix-Marseille Université, CNRS/IN2P3, Marseille, France
7 LAL, Université Paris-Sud, CNRS/IN2P3, Orsay, France
8 LPNHE, Université Pierre et Marie Curie, Université Paris Diderot, CNRS/IN2P3, Paris, France
9 Fakultät Physik, Technische Universität Dortmund, Dortmund, Germany
10 Max-Planck-Institut für Kernphysik (MPIK), Heidelberg, Germany
11 Physikalisches Institut, Ruprecht-Karls-Universität Heidelberg, Heidelberg, Germany
12 School of Physics, University College Dublin, Dublin, Ireland
13 Sezione INFN di Bari, Bari, Italy
14 Sezione INFN di Bologna, Bologna, Italy
15 Sezione INFN di Cagliari, Cagliari, Italy
16 Sezione INFN di Ferrara, Ferrara, Italy
17 Sezione INFN di Firenze, Firenze, Italy
18 Laboratori Nazionali dell’INFN di Frascati, Frascati, Italy
19 Sezione INFN di Genova, Genova, Italy
20 Sezione INFN di Milano Bicocca, Milano, Italy
21 Sezione INFN di Roma Tor Vergata, Roma, Italy
2 Universidade
3
22 Sezione INFN di Roma La Sapienza, Roma, Italy
National Institute for Subatomic Physics, Amsterdam, Netherlands
24 Nikhef National Institute for Subatomic Physics and Vrije Universiteit, Amsterdam, Netherlands
25 Henryk Niewodniczanski Institute of Nuclear Physics Polish Academy of Sciences, Cracow, Poland
26 Faculty of Physics & Applied Computer Science, Cracow, Poland
27 Soltan Institute for Nuclear Studies, Warsaw, Poland
28 Horia Hulubei National Institute of Physics and Nuclear Engineering, Bucharest-Magurele, Romania
29 Petersburg Nuclear Physics Institute (PNPI), Gatchina, Russia
30 Institute of Theoretical and Experimental Physics (ITEP), Moscow, Russia
31 Institute of Nuclear Physics, Moscow State University (SINP MSU), Moscow, Russia
32 Institute for Nuclear Research of the Russian Academy of Sciences (INR RAN), Moscow, Russia
33 Budker Institute of Nuclear Physics (SB RAS) and Novosibirsk State University, Novosibirsk, Russia
34 Institute for High Energy Physics (IHEP), Protvino, Russia
35 Universitat de Barcelona, Barcelona, Spain
36 Universidad de Santiago de Compostela, Santiago de Compostela, Spain
37 European Organization for Nuclear Research (CERN), Geneva, Switzerland
38 Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
39 Physik-Institut, Universität Zürich, Zürich, Switzerland
40 NSC Kharkiv Institute of Physics and Technology (NSC KIPT), Kharkiv, Ukraine
41 Institute for Nuclear Research of the National Academy of Sciences (KINR), Kyiv, Ukraine
42 H.H. Wills Physics Laboratory, University of Bristol, Bristol, United Kingdom
43 Cavendish Laboratory, University of Cambridge, Cambridge, United Kingdom
44 Department of Physics, University of Warwick, Coventry, United Kingdom
45 STFC Rutherford Appleton Laboratory, Didcot, United Kingdom
46 School of Physics and Astronomy, University of Edinburgh, Edinburgh, United Kingdom
47 School of Physics and Astronomy, University of Glasgow, Glasgow, United Kingdom
48 Oliver Lodge Laboratory, University of Liverpool, Liverpool, United Kingdom
49 Imperial College London, London, United Kingdom
50 School of Physics and Astronomy, University of Manchester, Manchester, United Kingdom
51 Department of Physics, University of Oxford, Oxford, United Kingdom
52 Syracuse University, Syracuse, NY, United States
53 CC-IN2P3, CNRS/IN2P3, Lyon-Villeurbanne, France, associated member
54 Pontifı́cia Universidade Católica do Rio de Janeiro (PUC-Rio), Rio de Janeiro, Brazil, associated to 2
23 Nikhef
a P.N.
Lebedev Physical Institute, Russian Academy of Science (LPI RAS), Moscow, Russia
b Università di Bari, Bari, Italy
c Università di Bologna, Bologna, Italy
d Università di Cagliari, Cagliari, Italy
e Università di Ferrara, Ferrara, Italy
f Università di Firenze, Firenze, Italy
g Università di Urbino, Urbino, Italy
h Università di Modena e Reggio Emilia, Modena, Italy
i Università di Genova, Genova, Italy
j Università di Milano Bicocca, Milano, Italy
k Università di Roma Tor Vergata, Roma, Italy
l Università di Roma La Sapienza, Roma, Italy
m Università della Basilicata, Potenza, Italy
n LIFAELS, La Salle, Universitat Ramon Llull, Barcelona, Spain
o Institució Catalana de Recerca i Estudis Avançats (ICREA), Barcelona, Spain
p Hanoi University of Science, Hanoi, Viet Nam
A model-independent search for direct CP violation in the Cabibbo suppressed decay D+ →
K K + π + in a sample of approximately 370,000 decays is carried out. The data were collected by the
LHCb experiment in 2010 and correspond to an integrated luminosity of 35 pb−1 . The normalized
Dalitz plot distributions for D+ and D− are compared using four different binning schemes that are
sensitive to different manifestations of CP violation. No evidence for CP asymmetry is found.
−
PACS numbers: 13.25.Ft, 11.30.Er, 14.40.Lb
I.
INTRODUCTION
To date CP violation (CPV) has been observed only
in decays of neutral K and B mesons. All observations
are consistent with CPV being generated by the phase in
the Cabibbo-Kobayashi-Maskawa (CKM) matrix [1, 2] of
the Standard Model (SM). In the charm sector, CKM dynamics can produce direct CP asymmetries in Cabibbo
suppressed D± decays of the order of 10−3 or less [3].
Asymmetries of up to around 1% can be generated by
new physics (NP) [4, 5]. In most extensions of the SM,
asymmetries arise in processes with loop diagrams. However, in some cases CPV could occur even at tree level,
for example in models with charged Higgs exchange.
In decays of hadrons, CPV can be observed when
two different amplitudes with non-zero relative weak
4
and strong phases contribute coherently to a final state.
Three-body decays are dominated by intermediate resonant states, and the requirement of a non-zero relative
strong phase is fulfilled by the phases of the resonances.
In two-body decays, CPV leads to an asymmetry in the
partial widths. In three-body decays, the interference
between resonances in the two-dimensional phase space
can lead to observable asymmetries which vary across the
Dalitz plot.
CP -violating phase differences of 10◦ or less do not,
in general, lead to large asymmetries in integrated decay
rates, but they could have clear signatures in the Dalitz
plot, as we will show in Sect. III. This means that a twodimensional search should have higher sensitivity than an
integrated measurement. In addition, the distribution
of an asymmetry across phase space could hint at the
underlying dynamics.
At present, no theoretical tools for computing decay
fractions and relative phases of resonant modes in D decays have been applied to multibody D+ decay modes,
and no predictions have been made for how asymmetries
might vary across their Dalitz plots. A full Dalitz plot
analysis of large data samples could, in principle, measure small phase differences. However, rigorous control
of the much larger strong phases would be required. For
this to be achieved, better understanding of the amplitudes, especially in the scalar sector, will be needed, and
effects like three-body final state interactions should be
taken into account.
This paper describes a model-independent search for
direct CPV in the Cabibbo suppressed decay D+ →
K − K + π + in a binned Dalitz plot.1 A direct comparison
between the D+ and the D− Dalitz plots is made on a
bin-by-bin basis. The data sample used is approximately
35 pb−1 collected in 2010
√ by the LHCb experiment at a
centre of mass energy of s = 7 TeV. This data set corresponds to nearly 10 and 20 times more signal events than
used in previous studies of this channel performed by the
BABAR [6] and CLEO-c [7] collaborations, respectively.
It is comparable to the dataset used in a more recent
search for CPV in D+ → φπ + decays at BELLE [8].
The strategy is as follows. For each bin in the Dalitz
plot, a local CP asymmetry variable is defined [9, 10],
N i (D+ ) − αN i (D− )
i
SCP
=p
,
N i (D+ ) + α2 N i (D− )
Ntot (D+ )
,
Ntot (D− )
(1)
where N i (D+ ) and N i (D− ) are the numbers of D± candidates in the ith bin and α is the ratio between the
total D+ and D− yields. The parameter α accounts for
global asymmetries, i.e. those that are constant across
the Dalitz plot.
1
α=
Throughout this paper charge conjugation is implied, unless otherwise stated.
In the absence of Dalitz plot dependent asymmetries,
i
the SCP
values are distributed according to a Gaussian
distribution with zero mean and unit width. CPV signals
are, therefore, deviations from this behaviour. The nu+
merical comparison between the DP
and the D− Dalitz
i
plots is made with a χ2 test (χ2 = (SCP
)2 ). The number of degrees of freedom is the number of bins minus one
(due to the constraint of the overall D+ /D− normalization). The p-value that results from this test is defined
as the probability of obtaining, for a given number of degrees of freedom and under the assumption of no CPV,
a χ2 that is at least as high as the value observed [11].
It measures the degree to which we are confident that
the differences between the D+ and D− Dalitz plots are
driven only by statistical fluctuations.
If CPV is observed, the p-value from this test could be
converted into a significance for a signal using Gaussian
statistics. However, in the event that no CPV is found,
there is no model-independent mechanism for setting limits on CPV within this procedure. In this case, the results
can be compared to simulation studies in which an artificial CP asymmetry is introduced into an assumed amplitude model for the decay. Since such simulations are
clearly model-dependent, they are only used as a guide
to the sensitivity of the method, and not in the determination of the p-values that constitute the results of the
analysis.
The technique relies on careful accounting for local
asymmetries that could be induced by sources such as,
the difference in the K–nucleon inelastic cross-section,
differences in the reconstruction or trigger efficiencies,
left-right detector asymmetries, etc. These effects are investigated in the two control channels D+ → K − π + π +
and Ds+ → K − K + π + .
The optimum sensitivity is obtained with bins of nearly
the same size as the area over which the asymmetry extends in the Dalitz plot. Since this is a search for new
and therefore unknown phenomena, it is necessary to be
sensitive to effects restricted to small areas as well as
those that extend over a large region of the Dalitz plot.
Therefore two types of binning scheme are employed.
The first type is simply a uniform grid of equally sized
bins. The second type takes into account the fact that the
D+ → K − K + π + Dalitz plot is dominated by the φπ +
and K ∗ (892)0 K + resonances, so the event distribution
is highly non-uniform. This “adaptive binning” scheme
uses smaller bins where the density of events is high, aiming for a uniform bin population. In each scheme, different numbers of bins are used in our search for localized
asymmetries.
The paper is organized as follows. In Sect. II, a description of the LHCb experiment and of the data selection
is presented. In Sect. III, the methods and the binnings
are discussed in detail. The study of the control channels
and of possible asymmetries generated by detector effects
or backgrounds is presented in Sect. IV. The results of
our search are given in Sect. V, and the conclusions in
Sect. VI.
5
II.
DETECTOR, DATASET AND SELECTION
The LHCb detector [12] is a single-arm forward spectrometer with the main purpose of measuring CPV and
rare decays of hadrons containing b and c quarks. A vertex locator (VELO) determines with high precision the
positions of the vertices of primary pp collisions (PVs)
and the decay vertices of long-lived particles. The tracking system also includes a large area silicon strip detector located in front of a dipole magnet with an integrated field of around 4 Tm, and a combination of silicon
strip detectors and straw drift chambers placed behind
the magnet. Charged hadron identification is achieved
with two ring-imaging Cherenkov (RICH) detectors. The
calorimeter system consists of a preshower, a scintillator pad detector, an electromagnetic calorimeter and a
hadronic calorimeter. It identifies high transverse energy (ET ) hadron, electron and photon candidates and
provides information for the trigger. Five muon stations composed of multi-wire proportional chambers and
triple-GEMs (gas electron multipliers) provide fast information for the trigger and muon identification capability.
The LHCb trigger consists of two levels. The first,
hardware-based level selects leptonic and hadronic final
states with high tranverse momentum, using the subset
of the detectors that are able to reduce the rate at which
the whole detector is read out to a maximum of 1 MHz.
The second level, the High Level Trigger (HLT), is subdivided into two software stages that can use the information from all parts of the detector. The first stage,
HLT1, performs a partial reconstruction of the event,
reducing the rate further and allowing the next stage,
HLT2, to fully reconstruct the individual channels. At
each stage, several selections designed for specific types
of decay exist. As luminosity increased throughout 2010
several changes in the trigger were required. To match
these, the datasets for signal and control modes are divided into three parts according to the trigger, samples
1, 2 and 3, which correspond to integrated luminosities
of approximately 3, 5 and 28 pb−1 respectively. The
magnet polarity was changed several times during data
taking.
The majority of the signal decays come via the
hadronic hardware trigger, which has an ET threshold
that varied between 2.6 and 3.6 GeV in 2010. In the
HLT1, most candidates also come from the hadronic selections which retain events with at least one high transverse momentum (pT ) track that is displaced from the
PV. In the HLT2, dedicated charm triggers select most
of the signal. However, the signal yield for these channels
can be increased by using other trigger selections, such as
those for decays of the form B → DX. To maintain the
necessary control of Dalitz plot-dependent asymmetries,
only events from selections which have been measured
not to introduce charge asymmetries into the Dalitz plot
of the D+ → K − π + π + control mode are accepted.
The signal ( D+ → K − K + π + ) and control (D+ →
− + +
K π π and Ds+ → K − K + π + ) mode candidates are
selected using the same criteria, which are chosen to maximize the statistical significance of the signal. Moreover,
care is taken to use selection cuts that do not have a low
efficiency in any part of the Dalitz plot, as this would reduce the sensitivity in these areas. The selection criteria
are the same regardless of the trigger conditions.
The event selection starts by requiring at least one PV
with a minimum of five charged tracks to exist. To control CPU consumption each event must also have fewer
than 350 reconstructed tracks. The particle identification
system constructs a relative log-likelihood for pion and
kaon hypotheses, DLLKπ , and we require DLLKπ > 7
for kaons and < 3 for pions. Three particles with appro+
priate charges are combined to form the D(s)
candidates.
The corresponding tracks are required to have a good
fit quality (χ2 /ndf < 5), pT > 250 MeV/c, momentum
p > 2000 MeV/c and the scalar sum of their pT above
2800 MeV/c. Because a typical D+ travels for around
8 mm before decaying, the final state tracks should not
point to the PV. The smallest displacement from each
track to the PV is computed, and a χ2 (χ2IP ), formed by
using the hypothesis that this distance is equal to zero,
is required to be greater than 4 for each track. The three
daughters should be produced at a common origin, the
charm decay vertex, with vertex fit χ2 /ndf < 10.
This ‘secondary’ vertex must be well separated from
any PV, thus a flight distance variable (χ2FD ) is constructed. The secondary vertex is required to have
χ2FD > 100, and to be downstream of the PV. The pT
+
of the D(s)
candidate must be greater than 1000 MeV/c,
and its reconstructed trajectory is required to originate
from the PV (χ2IP < 12).
In order to quantify the signal yields (S), a simultaneous fit to the invariant mass distribution of the D+ and
D− samples is performed. A double Gaussian is used for
the K − K + π + signal, whilst the background (B) is described by a quadratic component and a single Gaussian
for the small contamination from D∗+ → D0 (K − K + )π +
above the Ds+ peak. The fitted mass spectrum for samples 1 and 3 combined is shown in Fig. 1, giving the
yields shown in Table I. A weighted mean of the widths
of the two Gaussian contributions to the mass peaks is
used to determine the overall widths, σ, as 6.35 MeV/c2
for D+ → K − K + π + , 7.05 MeV/c2 for Ds+ → K − K + π + ,
and 8.0 MeV/c2 for D+ → K − π + π + . These values are
used to define signal mass windows of approximately 2σ
in which the Dalitz plots are constructed. The purities,
defined as S/(B + S) within these mass regions, are also
shown in Table I for samples 1 and 3 in the different
decay modes.
For sample 2, the yield cannot be taken directly from
the fit, because there is a mass cut in the HLT2 line that
accepts the majority of the signal, selecting events in a
±25 MeV/c2 window around the nominal value. However, another HLT2 line with a looser mass cut that
is otherwise identical to the main HLT2 line exists, although only one event in 100 is retained. In this line the
purity is found to be the same in sample 2 as in sample
15000
40000
Events / ( 0.48 MeV/c2)
Events / ( 0.28 MeV/c2)
6
(a)
LHCb
lower
upper
10000
20000
lower
middle
upper
5000
+
D
0
1800
(b)
LHCb
+
+
D
1850
1900
mK-π+π+ (MeV/c2)
0
1800
1850
Ds
1900
1950
2000
mK-K+π+ (MeV/c2)
m2K-K+ (GeV2/c 4)
FIG. 1. Fitted mass spectra of (a) K − π + π + and (b) K − K + π + candidates from samples 1 and 3, D+ and D− combined. The
signal mass windows and sidebands defined in the text are labelled.
3
LHCb
2.5
103
102
2
1.5
10
TABLE I. Yield (S) and purity for samples 1 and 3 after
the final selection. The purity is estimated in the 2σ mass
window.
Decay
D+ → K − K + π+
Ds+ → K − K + π +
D+ → K − π+ π+
Yield
Purity
Sample 1+3
Sample 1 Sample 3
(3.284 ± 0.006) × 105
88%
92%
(4.615 ± 0.012) × 105
89%
92%
(3.3777 ± 0.0037) × 106
98%
98%
1
0.5
1
1.5
m2K-π+
2
4
2
1
(GeV /c )
FIG. 2. Dalitz plot of the D+ → K − K + π + decay for selected candidates in the signal window. The vertical K ∗ (892)0
and horizontal φ(1020) contributions are clearly visible in the
data.
3. The yield in sample 2 is then inferred as the total
(S + B) in all allowed triggers in the mass window times
the purity in sample 3. Thus the overall yield of signal
D+ → K − K + π + candidates in the three samples within
the mass window is approximately 370,000. The total
number of candidates (S + B) in each decay mode used
in the analysis are given in Table II. The Dalitz plot of
data in the D+ window is shown in Fig. 2.
Within the 2σ D+ → K − K + π + mass window, about
8.6% of events are background. Apart from random
three-body track combinations, charm backgrounds and
two-body resonances plus one track are expected. Charm
reflections appear when a particle is wrongly identified in
a true charm three-body decay and/or a track in a fourbody charm decay is lost. The main three-body reflection in the K − K + π + spectrum is the Cabibbo-favoured
TABLE II. Number of candidates (S + B) in the signal windows shown in Fig. 1 after the final selection, for use in the
subsequent analysis.
sample 1
D+ → K − K + π + 84,667
Ds+ → K − K + π + 126,206
D+ → K − π + π + 858,356
sample 2
65,781
91,664
687,197
sample 3 Total
253,446 403,894
346,068 563,938
2,294,315 3,839,868
D+ → K − π + π + , where the incorrect assignment of the
kaon mass to the pion leads to a distribution that partially overlaps with the Ds+ → K − K + π + signal region,
but not with D+ → K − K + π + . The four body, Cabibbofavoured mode D0 → K − π + π − π + where a π + is lost
and the π − is misidentified as a K − will appear broadly
distributed in K − K + π + mass, but its resonances could
create structures in the Dalitz plot. Similarly, K ∗ (892)0
and φ resonances from the PV misreconstructed with a
random track forming a three-body vertex will also appear.
7
TABLE III. The CLEO-c amplitude model “B” [7] used in the simulation studies. The uncertainties are statistical, experimental
systematic and model systematic respectively.
Resonance
K ∗ (892)0
K ∗0 (1430)0
κ(800)
K ∗2 (1430)0
φ(1020)
a0 (1450)0
φ(1680)
III.
Amplitude
1 (fixed)
4.56 ± 0.13+0.10+0.42
−0.01−0.39
2.30 ± 0.13+0.01+0.52
−0.11−0.29
7.6 ± 0.8+0.5+2.4
−0.6−4.8
+0.001+0.025
1.166 ± 0.015−0.009−0.009
+0.09+0.92
1.50 ± 0.10−0.06−0.33
1.86 ± 0.20+0.02+0.62
−0.08−0.77
METHODS AND BINNINGS
Monte Carlo pseudo-experiments are used to verify
that we can detect CPV with the strategy outlined in
Sect. I without producing fake signals, and to devise and
test suitable binning schemes for the Dalitz plot. They
are also used to quantify our sensitivity to possible manifestations of CPV, where we define the sensitivity to a
given level of CPV as the probability of observing it with
3σ significance.
For the D+ → K − K + π + Dalitz plot model, the result
of the CLEO-c analysis (fit B) [7] is used. The amplitudes and phases of the resonances used in this model
are reproduced in Table III. For simplicity, only resonant
modes with fit fractions greater than 2% are included
in the pseudo-experiments. The fit fraction for a resonance is defined as the integral of its squared amplitude
over the Dalitz plot divided by the integral of the square
of the overall complex amplitude. An efficiency function is determined from a two-dimensional second order
polynomial fit to the Dalitz plot distribution of triggered
events that survive the selection cuts in the GEANTbased [13] LHCb Monte Carlo simulation for nonresonant
D+ → K − K + π + . A simple model for the background
is inferred from the Dalitz plots of the sidebands of the
D+ → K − K + π + signal. It is composed of random combinations of K − , K + , and π + tracks, φ resonances with
π + tracks, and K ∗ (892)0 resonances with K + tracks.
The CLEO-c Dalitz plot analysis has large uncertainties,
as do the background and efficiency simulations (due to
limited numbers of MC events), so the method is tested
on a range of different Dalitz plot models.
Pseudo-experiments with large numbers of events are
used to investigate how CPV would be observed in the
Dalitz plot. These experiments are simple “toy” simulations that produce points in the Dalitz plot according
to the probability density function determined from the
CLEO-c amplitude model with no representation of the
proton-proton collision, detector, or trigger. Figure 3(a)
i
illustrates the values of SCP
observed with 8 × 107 events
and no CPV. This dataset is approximately 50 times
larger than the data sample under study. The resulting χ2 /ndf is 253.4/218, giving a p-value for consistency
with no CPV of 5.0%. This test shows that the method
Relative phase
0 (fixed)
70 ± 6+1+16
−6−23
− 87 ± 6+2+15
−3−10
171 ± 4+0+24
−2−11
−163 ± 3+1+14
−1−5
116 ± 2+1+7
−1−14
−112 ± 6+3+19
−4−12
Fit fraction
25.7 ± 0.5+0.4+0.1
−0.3−1.2
18.8 ± 1.2+0.6+3.2
−0.1−3.4
7.0 ± 0.8+0.0+3.5
−0.6−1.9
1.7 ± 0.4+0.3+1.2
−0.2−0.7
27.8 ± 0.4+0.1+0.2
−0.3−0.4
4.6 ± 0.6+0.5+7.2
−0.3−1.8
0.51 ± 0.11+0.01+0.37
−0.04−0.15
by itself is very unlikely to yield false positive results.
Figure 3(b) shows an example test using 5 × 107 events
with a CP violating phase difference of 4◦ between the
amplitudes for the φ(1020)π + component in D+ and D−
decays. The p-value in this case is less than 10−100 . The
CPV effect is clearly visible, and is spread over a broad
area of the plot, changing sign from left to right. This
sign change means the CPV causes only a 0.1% difference in the total decay rate between D+ and D− . This
illustrates the strength of our method, as the asymmetry would be much more difficult to detect in a measurement that was integrated over the Dalitz plot. Even with
no systematic uncertainties, to see a 0.1% asymmetry at
the 3σ level would require 2.25 × 106 events. With the
method and much smaller dataset used here we would
observe this signal at the 3σ level with 76% probability,
as shown in Table IV below.
The sensitivity to a particular manifestation of CPV
depends on the choice of binning. The fact that the CP violating region in most of the pseudo-experiments covers
a broad area of the Dalitz plot suggests that the optimal
number of bins for this type of asymmetry is low. Each
bin adds a degree of freedom without changing the χ2
value for consistency with no CPV. However, if CP asymmetries change sign within a bin, they will not be seen.
Similarly, the sensitivity is reduced if only a small part
of a large bin has any CPV in it. To avoid effects due
to excessive fluctuations, bins that contain fewer than 50
candidates are not used anywhere in the analysis. Such
bins are very rare.
The binnings are chosen to reflect the highly nonuniform structure of the Dalitz plot. A simple adaptive binning algorithm was devised to define binnings of
approximately equal population without separating D+
and D− . Two binnings that are found to have good
sensitivity to the simulated asymmetries contain 25 bins
(“Adaptive I”) arranged as shown in Fig. 4(a), and 106
bins (“Adaptive II”) arranged as shown in Fig. 4(b). For
Adaptive I, a simulation of the relative value of the strong
phase across the Dalitz plot in the CLEO-c amplitude
model is used to refine the results of the algorithm: if
the strong phase varies significantly across a bin, CP
asymmetries are more likely to change sign. Therefore
the bin boundaries are adjusted to minimise changes in
LHCb
(a)
2
2.5
1
0
2
15
SCP
3
m2K-K+ (GeV2/c 4)
3
SCP
m2K-K+ (GeV2/c 4)
8
3
LHCb
(b)
10
2.5
5
0
2
-5
-1
1.5
1.5
-10
-2
1
0.5
1
1.5
2
1
-3
0.5
m2K-π+ (GeV2/c 4)
1
1.5
2
-15
m2K-π+ (GeV2/c 4)
3
LHCb
2.5
(a)
103
102
2
1.5
m2K-K+ (GeV2/c 4)
m2K-K+ (GeV2/c 4)
FIG. 3. SCP across the Dalitz plot in a Monte Carlo pseudo-experiment with a large number of events with (a) no CPV and
(b) a 4◦ CPV in the φπ phase. Note the difference in colour scale between (a) and (b).
3
LHCb
2.5
(b)
103
102
2
1.5
10
1
10
1
0.5
1
1.5
2
1
0.5
m2K-π+ (GeV2/c 4)
1
1.5
2
1
m2K-π+ (GeV2/c 4)
FIG. 4. Layout of the (a) “Adaptive I” and (b) “Adaptive II” binnings on the Dalitz plot of data.
the strong phase within bins. The model-dependence of
this simulation could, in principle, influence the binning
and therefore the sensitivity to CPV, but it cannot introduce model-dependence into the final results as no artificial signal could result purely from the choice of binning.
Two further binning schemes, “Uniform I” and “Uniform
II”, are defined. These use regular arrays of rectangular
bins of equal size.
The adaptive binnings are used to determine the sensitivity to several manifestations of CPV. With 200 test
experiments of approximately the same size as the signal sample in data, including no asymmetries, no CP violating signals are observed at the 3σ level with Adaptive I or Adaptive II. The expectation is 0.3.
With the chosen binnings, a number of sets of 100
pseudo-experiments with different CP -violating asymmetries are produced. The probability of observing a given
signal in either the φ(1020) or κ(800) resonances with
3σ significance is calculated in samples of the same size
as the dataset. The results are given in Table IV. The
CPV shows up both in the χ2 /ndf and in the width of
the fitted SCP distribution.
For comparison, the asymmetries in the φ phase and
κ magnitude measured by the CLEO collaboration us◦
ing the same amplitude model were (6 ± 6+0+6
−2−2 ) and
+6+2
2
(−12 ± 12−1−10 )%, where the uncertainties are statistical, systematic and model-dependent, respectively. Table IV suggests that, assuming their model, we would be
at least 95% confident of detecting the central values of
these asymmetries.
The sensitivity of the results to variations in the Dalitz
plot model and the background is investigated, and example results for the CP asymmetry in the φ(1020) phase
are shown in Table V. In this table, models A and B
are taken from the CLEO paper, model B2 includes an
f0 (980) contribution that accounts for approximately 8%
2
The conventions used in the CLEO paper to define asymmetry
are different, so the asymmetries in Table II of [7] have been
multiplied by two in order to be comparable with those given
above.
9
TABLE IV. Results from sets of 100 pseudo-experiments with different CP asymmetries and Adaptive I and II binnings. p(3σ)
is the probability of a 3σ observation of CPV. hSi is the mean significance with which CPV is observed.
CPV
no CPV
6◦ in φ(1020) phase
5◦ in φ(1020) phase
4◦ in φ(1020) phase
3◦ in φ(1020) phase
2◦ in φ(1020) phase
6.3% in κ(800) magnitude
11% in κ(800) magnitude
Adaptive I
p(3σ)
hSi
0
0.84σ
99%
7.0σ
97%
5.5σ
76%
3.8σ
38%
2.8σ
5%
1.6σ
16%
1.9σ
83%
4.2σ
Adaptive II
p(3σ)
hSi
1%
0.84σ
98%
5.2σ
79%
3.8σ
41%
2.7σ
12%
1.9σ
2%
1.2σ
24%
2.2σ
95%
5.6σ
TABLE V. Results from sets of 100 pseudo-experiments with 4◦ CPV in the φ(1020) phase and different Dalitz plot models.
p(3σ) is the probability of a 3σ observation of CPV. hSi is the mean significance with which CPV is observed. The sample size
is comparable to that seen in data.
Model
B (baseline)
A
B2 (add f0 (980))
B3 (vary K ∗0 (1430)0 magn.)
B4 (vary K ∗0 (1430)0 phase)
of events, and models B3 and B4 are variations of the
K ∗0 (1430)0 amplitude and phase within their uncertainties. As expected, the sensitivity to CPV in the resonances of an amplitude model depends quite strongly on
the details of the model. This provides further justification for our model-independent approach. However, a
reasonable level of sensitivity is retained in all the cases
we tested. Thus, when taken together, the studies show
that the method works well. It does not yield fake signals,
and should be sensitive to any large CPV that varies significantly across the Dalitz plot even if it does not occur
precisely in the way investigated here.
IV.
CONTROL MODES
It is possible that asymmetries exist in the data that
do not result from CPV, for example due to production,
backgrounds, instrumental effects such as left-right differences in detection efficiency, or momentum-dependent
differences in the interaction cross-sections of the daughter particles with detector material. Our sensitivity to
such asymmetries is investigated in the two Cabibbo
favoured control channels, where there is no large CPV
predicted. The D+ → K − π + π + control mode has an
order of magnitude more candidates than the Cabibbosuppressed signal mode, and is more sensitive to detector effects since there is no cancellation between K + and
K − reconstruction efficiencies. Conversely, the Ds+ →
Adaptive I
p(3σ)
hSi
76%
3.8σ
84%
4.3σ
53%
3.2σ
82%
4.0σ
73%
3.7σ
Adaptive II
p(3σ)
hSi
41%
2.7σ
47%
2.9σ
24%
2.2σ
41%
2.8σ
38%
2.7σ
K − K + π + control mode is very similar to our signal mode
in terms of resonant structure, number of candidates,
kinematics, detector effects, and backgrounds.
The control modes and their mass sidebands defined
in Fig. 1 are tested for asymmetries using the method
described in the previous section. Adaptive and uniform
binning schemes are defined for D+ → K − π + π + and
Ds+ → K − K + π + . They are applied to samples 1–3 and
each magnet polarity separately. In the final results, the
asymmetries measured in data taken with positive and
negative magnet polarity are combined in order to cancel
left-right detector asymmetries. The precise number of
bins chosen is arbitrary, but care is taken to use a wide
range of tests with binnings that reflect the size of the
dataset for the decay mode under study.
For D+ → K − π + π + , five different sets of bins in each
scheme are used. A very low p-value would indicate a
local asymmetry. One test with 25 adaptive bins in one
of the subsamples (with negative magnet polarity) has
a p-value of 0.1%, but when combined with the positive
polarity sample the p-value increases to 1.7%. All other
tests yield p-values ranging from 1–98%. Some example
results are given in Table VI. A typical distribution of
the SCP values with a Gaussian fit is shown in Fig. 5(a)
for a test with 900 uniform bins. The fitted values of
the mean and width are consistent with one and zero
respectively, suggesting that the differences between the
D+ and the D− Dalitz plots are driven only by statistical
fluctuations.
140
(a)
LHCb
120
Number of bins (0.5)
Number of bins (0.4)
10
100
80
60
25
(b)
LHCb
20
15
10
40
5
20
0
30
-4
-2
0
2
0
-4
4
-2
0
2
4
SCP
SCP
2
1.02
1.8
0.70
-1.38
1.6
(a)
LHCb
0.12 0.69
-2.33
-1.74
-1.09
2500
0.31
2000
1.00
1 0.64
2.62 -0.24
0.49 0.05
0.48 -0.04 1.80
1000
-0.45
0.66
-0.46
-0.96
-1.13
-1.71
0.70
0.4
1
1.5
2
3.5
104
Zone C
(b)
LHCb
3
103
2.5
102
2
1500
0.8
0.6
3500
3000
1.4
1.2
4000
m2K-K+ (GeV2/c 4)
m2K-π+, max (GeV2/c 4)
FIG. 5. (a) Distribution of SCP values from D+ → K − π + π + from a test with 900 uniform bins. The mean of the fitted
Gaussian distribution is 0.015 ± 0.034 and the width is 0.996 ± 0.023. (b) Distribution of SCP values from Ds+ → K − K + π +
with 129 bins. The fitted mean is −0.011 ± 0.084 and the width is 0.958 ± 0.060.
2.5
3
500
0
m2K-π+, min (GeV2/c 4)
1.5
10
Zone C
Zone B
1
Zone A
0.5
1
1.5
2
m2K-π+
1
2
4
(GeV /c )
FIG. 6. Dalitz plots of (a) D+ → K − π + π + , showing the 25-bin adaptive scheme with the SCP values, and (b) Ds+ → K − K + π + ,
showing the three regions referred to in the text. The higher and lower K − π + invariant mass combinations are plotted in (a)
as there are identical pions in the final state.
TABLE VI. Results (p-values, in %) from tests with the
D+ → K − π + π + control channel using the uniform and adaptive binning schemes. The values correspond to tests performed on the whole dataset in the mass windows defined in
Sect. II.
Uniform
Adaptive
1300 bins 900 bins 400 bins 100 bins 25 bins
73.8
17.7
72.6
54.6
1.7
81.7
57.4
65.8
30.0
11.8
For the Ds+ → K − K + π + mode a different procedure
is followed due to the smaller sample size and to the high
density of events along the φ and the K ∗ (892)0 bands.
The Dalitz plot is divided into three zones, as shown in
Fig. 6. Each zone is further divided into 300, 100 and 30
bins of same size. The results are given in Table VII. In
addition, a test is performed on the whole Dalitz plot us-
TABLE VII. Results (p-values, in %) from tests with the
Ds+ → K − K + π + control channel using the uniform binning
scheme. The values correspond to tests performed separately
on Zones A-C, with samples 1-3 and both magnet polarities
combined.
bins Zone A Zone B Zone C
300 20.1
25.3
14.5
100 41.7
84.6
89.5
30 66.0
62.5
24.6
ing 129 bins chosen by the adaptive algorithm, and a version of the 25-bin scheme outlined in Sect. III scaled by
the ratio of the available phase space in the two modes.
These tests yield p-values of 71.5% and 34.3% respectively.
Other possible sources of local charge asymmetry in the
11
TABLE VIII. Results (p-values, in %) from tests with the
D+ → K − π + π + and Ds+ → K − K + π + samples divided according to the impact parameter with respect to the primary
vertex. The tests are performed using the adaptive binning
scheme with 25 bins.
D+ → K − π+ π+
Ds+ → K − K + π +
χ2IP < 6 χ2IP > 6
8.5
88.9
52.0
30.6
signal region are the charm contamination of the background, and asymmetries from CPV in misreconstructed
B decays. In order to investigate the first possibility,
similar tests are carried out in the mass sidebands of the
+
D(s)
→ K − K + π + signal (illustrated in Fig. 1). There is
no evidence for asymmetries in the background.
From a simulation of the decay D+ → K − π + π + the
level of secondary charm (B → DX) in our selected sample is found to be 4.5%. The main discriminating variable to distinguish between prompt and secondary charm
is the impact parameter (IP) of the D with respect to the
primary vertex. Given the long B lifetime, the IP distribution of secondary charm candidates is shifted towards
larger values compared to that of prompt D+ mesons.
The effect of secondary charm is investigated by dividing the data set according to the value of the candidate
IP significance (χ2IP ). The subsample with events having
larger χ2IP are likely to be richer in secondary charm. The
results are shown in Table VIII. No anomalous effects are
seen in the high χ2IP sample, so contamination from secondary charm with CPV does not affect our results for
studies with our current level of sensitivity.
The analysis on the two control modes and on the
sidebands in the final states K − K + π + and K − π + π +
gives results from all tests that are fully consistent with
no asymmetry. Therefore, any asymmetry observed in
D+ → K − K + π + is likely to be a real physics effect.
V.
RESULTS
The signal sample with which we search for CP violation consists of 403,894 candidates selected within the
K − K + π + mass window from 1856.7 to 1882.1 MeV/c2 ,
as described in Sect. II. There are 200,336 and 203,558
D+ and D− candidates respectively. This implies a normalization factor α = Ntot (D+ )/Ntot (D− ) = 0.984 ±
0.003, to be used in Eq. 1.
The strategy for looking for signs of localized CPV is
discussed in the previous sections. In the absence of local
asymmetries in the control channels D+ → K − π + π + and
Ds+ → K − K + π + and in the sidebands of the K − K + π +
mass spectrum, we investigate the signal sample under
different binning choices.
First, the adaptive binning is used with 25 and 106
bins in the Dalitz plot as illustrated in Fig. 4. Then
CPV is investigated with uniform binnings, using 200
and 530 bins of equal size. For each of these binning
i
choices, the significance SCP
of the difference in D+ and
−
D population is computed
each bin i, as defined in
P for
i
Eq. 1. The χ2 /ndf = i (SCP
)2 /ndf is calculated and
i
the p-value is obtained. The distributions of SCP
are
fitted to Gaussian functions.
The p-values are shown in Table IX. The Dalitz plot
i
distributions of SCP
are shown in Fig. 7. In Fig. 8 the disi
tributions of SCP and the corresponding Gaussian fits for
the different binnings are shown. The p-values obtained
indicate no evidence for CPV. This is corroborated by
i
the good fits of the SCP
distributions to Gaussians, with
means and widths consistent with 0 and 1, respectively.
As further checks, many other binnings are tested.
The number of bins in the adaptive and uniform binning schemes is varied from 28 to 106 and from 21 to
530 respectively. The samples are separated according
to the magnet polarity and the same studies are repeated. In all cases the p-values are consistent with no
CPV, with values ranging from 4% to 99%. We conclude
that there is no evidence for CPV in our data sample of
D+ → K − K + π+ .
VI.
CONCLUSION
Due to the rich structure of their Dalitz plots, three
body charm decays are sensitive to CP violating phases
within and beyond the Standard Model. Here, a modelindependent search for direct CP violation is performed
in the Cabibbo suppressed decay D+ → K − K + π + with
35 pb−1 of data collected by the LHCb experiment, and
no evidence for CPV is found. Several binnings are used
to compare normalised D+ and D− Dalitz plot distributions. This technique is validated with large numbers of simulated pseudo-experiments and with Cabibbo
favoured control channels from the data: no false positive
signals are seen. To our knowledge this is the first time
a search for CPV is performed using adaptive bins which
reflect the structure of the Dalitz plot.
Monte Carlo simulations illustrate that large localised
asymmetries can occur without causing detectable differences in integrated decay rates. The technique used here
is shown to be sensitive to such asymmetries. Assuming
the decay model, efficiency parameterisation and background model described in Sect. III we would be 90%
confident of seeing a CP violating difference of either 5◦
in the phase of the φπ + or 11% in the magnitude of the
κ(800)K + with 3σ significance. Since we find no evidence
of CPV, effects of this size are unlikely to exist.
VII.
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 ad-
12
TABLE IX. Fitted means and widths, χ2 /ndf and p-values for consistency with no CPV for the D+ → K − K + π + decay mode
with four different binnings.
LHCb
2.5
(a)
2
1
2
0
-1
1.5
χ2 /ndf p-value (%)
32.0/24
12.7
123.4/105
10.6
191.3/198
82.1
519.5/529
60.5
3
SCP
3
3
m2K-K+ (GeV2/c 4)
Fitted width
1.13 ± 0.16
1.078 ± 0.074
0.929 ± 0.051
1.011 ± 0.034
SCP
3
LHCb
2.5
(b)
2
1
2
0
-1
1.5
-2
-2
1
1
1.5
m2K-K+ (GeV2/c 4)
m2K-π+
2
4
2
-3
1
3
LHCb
(c)
2
1
2
1.5
m2K-π+
(GeV /c )
3
2.5
0.5
0
m2K-K+ (GeV2/c 4)
1
SCP
0.5
2
4
2
(GeV /c )
3
3
LHCb
(d)
2
2.5
1
0
2
-1
1.5
-3
SCP
m2K-K+ (GeV2/c 4)
Binning
Fitted mean
Adaptive I
0.01 ± 0.23
Adaptive II −0.024 ± 0.010
Uniform I −0.043 ± 0.073
Uniform II −0.039 ± 0.045
-1
1.5
-2
1
0.5
1
1.5
m2K-π+
2
2
-3
4
(GeV /c )
-2
1
0.5
1
1.5
m2K-π+
2
4
2
-3
(GeV /c )
i
FIG. 7. Distribution of SCP
in the Dalitz plot for (a) “Adaptive I”, (b) “Adaptive II”, (c) “Uniform I” and (d) “Uniform II”.
In (c) and (d) bins at the edges are not shown if the number of entries is not above a threshold of 50 (see Sect. III).
ministrative staff at CERN and at the LHCb institutes, and acknowledge support from the National Agencies: CAPES, CNPq, FAPERJ and FINEP (Brazil);
CERN; NSFC (China); CNRS/IN2P3 (France); BMBF,
DFG, HGF and MPG (Germany); SFI (Ireland); INFN
(Italy); FOM and NWO (Netherlands); SCSR (Poland);
ANCS (Romania); MinES of Russia and Rosatom (Russia); MICINN, XuntaGal and GENCAT (Spain); SNSF
and SER (Switzerland); NAS Ukraine (Ukraine); STFC
(United Kingdom); NSF (USA). We also acknowledge
the support received from the ERC under FP7 and the
Region Auvergne.
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