Parton shower matching and multijet merging at NLO

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1 Parton shower matching and multijet merging at NLO Institute for Particle Physics Phenomenology HP, 05/09/0 arxiv:.0, arxiv:88 arxiv: , arxiv: arxiv:08.85 Parton shower matching and multijet merging at NLO

2 MC@NLO NLO-merging Conclusions The SHERPA event generator framework JHEP0(009)007 Two multi-purpose Matrix Element (ME) generators AMEGIC JHEP0(00)044 COMIX JHEP(008)039 CS subtraction EPJC53(008)50 A Parton Shower (PS) generator CSSHOWER JHEP03(008)038 A multiple interaction simulation à la Pythia AMISIC hep-ph/0600 A cluster fragmentation module AHADIC EPJC36(004)38 A hadron and τ decay package HADRONS A higher order ED generator using YFS-resummation PHOTONS JHEP(008)08 Sherpa s traditional strength is the perturbative part of the event MEPS (CKKW), MC@NLO, MENLOPS, MEPS@NLO full analytic control mandatory for consistency/accuracy Parton shower matching and multijet merging at NLO

3 MC@NLO NLO-merging Conclusions The SHERPA event generator framework JHEP0(009)007 Two multi-purpose Matrix Element (ME) generators AMEGIC JHEP0(00)044 COMIX JHEP(008)039 CS subtraction EPJC53(008)50 A Parton Shower (PS) generator CSSHOWER JHEP03(008)038 A multiple interaction simulation à la Pythia AMISIC hep-ph/0600 A cluster fragmentation module AHADIC EPJC36(004)38 A hadron and τ decay package HADRONS A higher order ED generator using YFS-resummation PHOTONS JHEP(008)08 Sherpa s traditional strength is the perturbative part of the event MEPS (CKKW), MC@NLO, MENLOPS, MEPS@NLO full analytic control mandatory for consistency/accuracy Parton shower matching and multijet merging at NLO

4 O NLOPS = dφ B(A) B (Φ B ) (A) (t 0, µ ) O(Φ B ) dφ R R(Φ R ) i µ D (A) (Φ B, Φ ) dφ t 0 B(Φ B ) D (A) i (Φ R ) O(Φ R ) Frixione, Webber JHEP06(00)09 (A) (t, µ ) O(Φ R ) Höche, Krauss, MS, Siegert arxiv:.0 NLO weighted Born configuration B (A) = B Ṽ I dφ D (A) D (S) use D (A) i as resummation kernels (A) (t, t t ) = exp dφ t D (A) /B resummation phase space limited by µ = t max starting scale of parton shower evolution should be of the order of the hard resummation scale first implementation to allow to study µ uncertainty Parton shower matching and multijet merging at NLO 3

5 O NLOPS = dφ B(A) B (Φ B ) (A) (t 0, µ ) O(Φ B ) dφ R R(Φ R ) i µ D (A) (Φ B, Φ ) dφ t 0 B(Φ B ) D (A) i (Φ R ) O(Φ R ) Frixione, Webber JHEP06(00)09 (A) (t, µ ) O(Φ R ) Höche, Krauss, MS, Siegert arxiv:.0 NLO weighted Born configuration B (A) = B Ṽ I dφ D (A) D (S) use D (A) i as resummation kernels (A) (t, t t ) = exp dφ t D (A) /B resummation phase space limited by µ = t max starting scale of parton shower evolution should be of the order of the hard resummation scale first implementation to allow to study µ uncertainty Parton shower matching and multijet merging at NLO 3

6 O NLOPS = dφ B(A) B (Φ B ) (A) (t 0, µ ) O(Φ B ) dφ R R(Φ R ) i µ D (A) (Φ B, Φ ) dφ t 0 B(Φ B ) D (A) i (Φ R ) O(Φ R ) Frixione, Webber JHEP06(00)09 (A) (t, µ ) O(Φ R ) Höche, Krauss, MS, Siegert arxiv:.0 every term is well defined and NLO and NLL accuracy maintained if: D (A) = i D(A) i D (A) = i D(A) i is full colour correct in soft limit contains all spin correlations in collinear limit D (A) i and D (S) i have identical parton maps conventional parton showers need to be improved for that e.g. choose D (A) i = D (S) i up to phase space constraints Parton shower matching and multijet merging at NLO 3

7 Case study: Inclusive jet & dijet production Describe wealth of experimental data with a single sample (LHC@7TeV) MC@NLO di-jet production: Höche, MS arxiv:08.85 µ R/F = 4 H T, µ = p CT0 PDF (α s (m Z ) = ) hadron level calculation fully hadronised including MPI virtual MEs from BLACKHAT Giele, Glover, Kosower Nucl.Phys.B403(993) Bern et.al. arxiv:.3940 p j > 0 GeV, pj > 0 GeV Uncertainty estimates: µ variation MPI variation µ F, µ R variation µ R/F, µdef R/F µ, µ def MPI activity in tr. region ± 0% Parton shower matching and multijet merging at NLO 4

8 NLO-merging Conclusions Case study: Inclusive jet & dijet production Describe wealth of experimental data with a single sample (LHC@7TeV) MC@NLO di-jet production: Höche, MS arxiv:08.85 µ R/F = 4 H T, µ = p CT0 PDF (α s (m Z ) = ) hadron level calculation fully hadronised including MPI virtual MEs from BLACKHAT Giele, Glover, Kosower Nucl.Phys.B403(993) Bern et.al. arxiv:.3940 p j > 0 GeV, pj > 0 GeV Uncertainty estimates: µ R/F, µdef R/F µ, µ def MPI activity in tr. region ± 0% σ pb Inclusive jet multiplicity (anti-kt R=0.4) µr, µf variation µ variation MPI variation SherpaBlackHat ATLAS data Eur.Phys.J. C7 (0) 763 Sherpa MC@NLO µr = µf = 4 HT, µ = p Njet Parton shower matching and multijet merging at NLO 4

9 NLO-merging Conclusions Case study: Inclusive jet & dijet production dσ/dp pb/gev Jet transverse momenta (anti-kt R=0.4) ATLAS data Eur.Phys.J. C7 (0) 763 Sherpa MC@NLO µr = µf = 4 HT, µ = p µr, µf variation µ variation MPI variation st jet.4. Höche, MS arxiv:08.85 st jet nd jet th jet 0 3 SherpaBlackHat 3rd jet 0 nd jet rd jet 4th jet p GeV p GeV Parton shower matching and multijet merging at NLO 5

10 NLO-merging Conclusions Case study: Inclusive jet & dijet production R jets over jets ratio (anti-kt R=) µf, µr variation µ variation MPI variation SherpaBlackHat CMS data Phys. Lett. B 70 (0) 336 Sherpa MC@NLO µr = µf = 4 HT, µ = p 0. HT TeV 3-jet-over--jet ratio Höche, MS arxiv:08.85 determined from incl. sample -jet rate at NLONLL 3-jet rate at LOLL common scale choices varied simultaneously at large H T large MPI uncertainties better MPI physics needed (soft CD) similar description of related ATLAS observables Parton shower matching and multijet merging at NLO 6

11 NLO-merging Conclusions Case study: Inclusive jet & dijet production dσ/dm pb/tev Dijet invariant mass spectra in different rapidity ranges ATLAS data Phys. Rev. D86 (0) 040 Sherpa MC@NLO µr = µf = 4 HT, µ = p Sherpa MC@NLO µr = µf = 4 H(y) T, µ = p µr, µf variation µ variation MPI variation SherpaBlackHat 0 m TeV < y < < y < < y < < y < < y <.5.5 < y <.0.0 < y <.5 Höche, MS arxiv:08.85 < y <.0 y < 0 m GeV Parton shower matching and multijet merging at NLO 7

12 Case study: Inclusive jet & dijet production Try different scale µ R/F = 4 H(y) T with H (y) T = i jets p,i e 0.3 y boost y i with y boost = /n jets i jets y i reduces to µ R/F = p e 0.3y with y = y y for and captures real emission dynamics Ellis, Kunszt, Soper PRD40(989)88 better description of data at large rapidities, as expected description of most other observables worsened need proper description of forward physics (e.g. (B)FKL) < y < < y < < y < < y < < y <.5.5 < y <.0.0 < y <.5 Höche, MS arxiv:08.85 < y <.0 y < 0 m GeV Parton shower matching and multijet merging at NLO 7

13 Case study: Inclusive jet & dijet production Try different scale µ R/F = 4 H(y) T with H (y) T = i jets p,i e 0.3 y boost y i with y boost = /n jets i jets y i reduces to µ R/F = p e 0.3y with y = y y for and captures real emission dynamics Ellis, Kunszt, Soper PRD40(989)88 better description of data at large rapidities, as expected description of most other observables worsened need proper description of forward physics (e.g. (B)FKL) Höche, MS arxiv:08.85 st jet nd jet 3rd jet 4th jet p GeV Parton shower matching and multijet merging at NLO 7

14 NLO-merging Conclusions Case study: Inclusive jet & dijet production Gap Fraction Inclusive jet transverse momenta in different rapidity ranges 0 Leading dijet selection ATLAS data JHEP 09 (0) 053 Sherpa MC@NLO.5 Höche, MS arxiv: GeV < p < 70 GeV 8 µr = µf = 4 HT, µ = p µf, µr variation µ variation MPI variation.5 0 GeV < p < 40 GeV 6 4 SherpaBlackHat 40 GeV < p < 70 GeV 6 0 GeV < p < 40 GeV 5 80 GeV < p < 0 GeV 4 50 GeV < p < 80 GeV 3 0 GeV < p < 50 GeV 90 GeV < p < 0 GeV 70 GeV < p < 90 GeV y.5 80 GeV < p < 0 GeV.5 50 GeV < p < 80 GeV GeV < p < 50 GeV 90 GeV < p < 0 GeV.5 70 GeV < p < 90 GeV y Parton shower matching and multijet merging at NLO 8

15 NLO-merging Conclusions Case study: Inclusive jet & dijet production Gap Fraction Inclusive jet transverse momenta in different rapidity ranges 0 Forward-backward selection ATLAS data JHEP 09 (0) 053 Sherpa MC@NLO.5 40 GeV < p < 70 GeV Höche, MS arxiv: µr = µf = 4 HT, µ = p µf, µr variation µ variation MPI variation.5 0 GeV < p < 40 GeV 6 4 SherpaBlackHat 40 GeV < p < 70 GeV 6 0 GeV < p < 40 GeV 5 80 GeV < p < 0 GeV 4 50 GeV < p < 80 GeV 3 0 GeV < p < 50 GeV 90 GeV < p < 0 GeV 70 GeV < p < 90 GeV y.5 80 GeV < p < 0 GeV.5 50 GeV < p < 80 GeV GeV < p < 50 GeV 90 GeV < p < 0 GeV.5 70 GeV < p < 90 GeV y Parton shower matching and multijet merging at NLO 9

16 Case study: Inclusive jet & dijet production small- y region small uncertainty on additional jet production large- y region all uncertainties sizable GeV < p < 70 GeV Höche, MS arxiv: GeV < p < 40 GeV small- p region dominated by perturbative uncertainties small- p region non-perturbative uncertainties as large as perturbative uncertainties Reduction of theoretical uncertainty necessitates better understanding of soft CD and nonfactorisable contributions GeV < p < 0 GeV 50 GeV < p < 80 GeV 0 GeV < p < 50 GeV 90 GeV < p < 0 GeV 70 GeV < p < 90 GeV y Parton shower matching and multijet merging at NLO 9

17 NLO-merging Conclusions Case study: Inclusive jet & dijet production de/dη GeV Forward energy flow in dijet events, p jets > 0 GeV CMS data JHEP (0) 48 Sherpa MC@NLO µr = µf = 4 HT, µ = p SherpaBlackHat µf, µr variation µ variation MPI variation η Forward energy flow Höche, MS arxiv:08.85 energy flow in rapidity interval per event with a central back-to-back di-jet pair normalisation reduces µ R/F and µ dependence dominated by MPI modeling uncertainty Parton shower matching and multijet merging at NLO 0

18 NLO merging LO merging: LO accuracy for n n max -jet processes preserve LL accuracy of the parton shower NLO merging: NLO accuracy for n n max -jet processes preserve LL accuracy of the parton shower Catani, Krauss, Kuhn, Webber JHEP(00)063 Lönnblad JHEP05(00)046 Höche, Krauss, Schumann, Siegert JHEP05(009)053 Hamilton, Richardson, Tully JHEP(009)038 Lönnblad, Prestel JHEP03(0)09 Lavesson, Lönnblad JHEP(008)070 Höche, Krauss, MS, Siegert arxiv: Gehrmann, Höche, Krauss, MS, Siegert arxiv: Parton shower matching and multijet merging at NLO

19 NLO merging O MEPS@NLO = dφ n B(A) n (A) n (t 0, µ ) O n µ t 0 dφ n R n D (A) dφ n B(A) n (A) Dn dφ n B n Höche, Krauss, MS, Siegert arxiv: Gehrmann, Höche, Krauss, MS, Siegert arxiv: (A) n (t n, µ ) Θ( cut ) O n Θ( cut ) (PS) n (t n, µ ) O n B n B n µ t n dφ K n (PS) n (t n, µ ) Θ( cut ) tn (A) (A) n (t Dn 0, t n ) O n dφ (A) n t 0 B (t n, t n ) O n n dφ n R n D (A) n (PS) n (t n, t n ) (PS) n (t n, µ ) Θ( cut ) O n Parton shower matching and multijet merging at NLO

20 NLO merging O MEPS@NLO = dφ n B(A) n (A) n (t 0, µ ) O n µ t 0 dφ n R n D (A) dφ n B(A) n (A) Dn dφ n B n Höche, Krauss, MS, Siegert arxiv: Gehrmann, Höche, Krauss, MS, Siegert arxiv: (A) n (t n, µ ) Θ( cut ) O n Θ( cut ) (PS) n (t n, µ ) O n B n B n µ t n dφ K n (PS) n (t n, µ ) Θ( cut ) tn (A) (A) n (t Dn 0, t n ) O n dφ (A) n t 0 B (t n, t n ) O n n dφ n R n D (A) n (PS) n (t n, t n ) (PS) n (t n, µ ) Θ( cut ) O n Parton shower matching and multijet merging at NLO

21 NLO merging O MEPS@NLO = dφ n B(A) n (A) n (t 0, µ ) O n µ t 0 dφ n R n D (A) dφ n B(A) n (A) Dn dφ n B n Höche, Krauss, MS, Siegert arxiv: Gehrmann, Höche, Krauss, MS, Siegert arxiv: (A) n (t n, µ ) Θ( cut ) O n Θ( cut ) (PS) n (t n, µ ) O n B n B n µ t n dφ K n (PS) n (t n, µ ) Θ( cut ) tn (A) (A) n (t Dn 0, t n ) O n dφ (A) n t 0 B (t n, t n ) O n n dφ n R n D (A) n (PS) n (t n, t n ) (PS) n (t n, µ ) Θ( cut ) O n Parton shower matching and multijet merging at NLO

22 NLO merging O MEPS@NLO = dφ n B(A) n (A) n (t 0, µ ) O n µ t 0 dφ n R n D (A) dφ n B(A) n (A) Dn dφ n B n Höche, Krauss, MS, Siegert arxiv: Gehrmann, Höche, Krauss, MS, Siegert arxiv: (A) n (t n, µ ) Θ( cut ) O n Θ( cut ) (PS) n (t n, µ ) O n B n B n µ t n dφ K n (PS) n (t n, µ ) Θ( cut ) tn (A) (A) n (t Dn 0, t n ) O n dφ (A) n t 0 B (t n, t n ) O n n dφ n R n D (A) n (PS) n (t n, t n ) (PS) n (t n, µ ) Θ( cut ) O n Parton shower matching and multijet merging at NLO

23 NLO merging O MEPS@NLO = dφ n B(A) n (A) n (t 0, µ ) O n µ t 0 dφ n R n D (A) dφ n B(A) n (A) Dn dφ n B n Höche, Krauss, MS, Siegert arxiv: Gehrmann, Höche, Krauss, MS, Siegert arxiv: (A) n (t n, µ ) Θ( cut ) O n Θ( cut ) (PS) n (t n, µ ) O n B n B n µ t n dφ K n (PS) n (t n, µ ) Θ( cut ) tn (A) (A) n (t Dn 0, t n ) O n dφ (A) n t 0 B (t n, t n ) O n n dφ n R n D (A) n (PS) n (t n, t n ) (PS) n (t n, µ ) Θ( cut ) O n Parton shower matching and multijet merging at NLO

24 NLO merging O MEPS@NLO = dφ n B(A) n (A) n (t 0, µ ) O n µ t 0 dφ n R n D (A) dφ n B(A) n (A) Dn dφ n B n Höche, Krauss, MS, Siegert arxiv: Gehrmann, Höche, Krauss, MS, Siegert arxiv: (A) n (t n, µ ) Θ( cut ) O n Θ( cut ) (PS) n (t n, µ ) O n B n B n µ t n dφ K n (PS) n (t n, µ ) Θ( cut ) tn (A) (A) n (t Dn 0, t n ) O n dφ (A) n t 0 B (t n, t n ) O n n dφ n R n D (A) n (PS) n (t n, t n ) (PS) n (t n, µ ) Θ( cut ) O n Parton shower matching and multijet merging at NLO

25 NLO merging O MEPS@NLO = dφ n B(A) n (A) n (t 0, µ ) O n µ t 0 dφ n R n D (A) dφ n B(A) n (A) Dn dφ n B n Höche, Krauss, MS, Siegert arxiv: Gehrmann, Höche, Krauss, MS, Siegert arxiv: (A) n (t n, µ ) Θ( cut ) O n Θ( cut ) (PS) n (t n, µ ) O n B n B n µ t n dφ K n (PS) n (t n, µ ) Θ( cut ) tn (A) (A) n (t Dn 0, t n ) O n dφ (A) n t 0 B (t n, t n ) O n n dφ n R n D (A) n (PS) n (t n, t n ) (PS) n (t n, µ ) Θ( cut ) O n Parton shower matching and multijet merging at NLO

26 NLO merging Generation of MC counterterm B n B n µ t n dφ K n same form as exponent of Sudakov form factor (PS) n (t n, µ ) truncated parton shower on n-parton configuration underlying n -parton event no emission retain n -parton event as is first emission at t with > cut, multiply event weight with B n/ B (A) n, restart evolution at t, do not apply emission kinematics 3 treat every subsequent emission as in standard truncated vetoed shower generates B n B n µ t n dφ K n (PS) n (t n, µ ) identify O(α s ) counterterm with the emitted emission Parton shower matching and multijet merging at NLO 3

27 NLO merging Renormalisation scales: determined by clustering using PS probabilities and taking the respective nodal values t i α s (µ R )k = k α s (t i ) i= change of scales µ R µ R in MEs necessitates one-loop counter term ( ) α s ( µ R) k α s( µ R ) k β 0 ln t i π µ R Factorisation scale: µ F determined from core n-jet process change of scales µ F µ F in MEs necessitates one-loop counter term ( B n (Φ n ) α s( µ R ) log µ n ) F dz π µ F x a z P ac(z) f c (x a /z, µ F )... c=q,g i= Parton shower matching and multijet merging at NLO 4

28 NLO-merging Conclusions Results: e e hadrons /σ dσ/dln(y3) /σ dσ/dln(y45) Durham jet resolution 3 (E CMS = 9. GeV) ALEPH data MePs@Nlo MePs@Nlo µ/...µ MEnloPS MEnloPS µ/...µ Mc@Nlo ln(y3) Durham jet resolution 5 4 (E CMS = 9. GeV) ALEPH data MePs@Nlo MePs@Nlo µ/...µ MEnloPS MEnloPS µ/...µ Mc@Nlo ln(y45) /σ dσ/dln(y34) /σ dσ/dln(y56) Durham jet resolution 4 3 (E CMS = 9. GeV) ALEPH data MePs@Nlo MePs@Nlo µ/...µ MEnloPS MEnloPS µ/...µ Mc@Nlo ln(y34) Durham jet resolution 6 5 (E CMS = 9. GeV) ALEPH data MePs@Nlo MePs@Nlo µ/...µ MEnloPS MEnloPS µ/...µ Mc@Nlo ln(y56) ee hadrons NLO; LO) Jet resolutions (Durham measure) MEPS@NLO vs MENLOPS at y dominated by hadr. effects needs retuning much improved ren. scale dependence ALEPH data EPJC35(004) Parton shower matching and multijet merging at NLO 5

29 NLO-merging Conclusions Results: e e hadrons ALEPH data EPJC35(004) Thrust (E CMS = 9. GeV) Sphericity (E CMS = 9. GeV) /σ dσ/dt ALEPH data MePs@Nlo MePs@Nlo µ/...µ MEnloPS MEnloPS µ/...µ Mc@Nlo /σ dσ/ds ALEPH data MePs@Nlo MePs@Nlo µ/...µ MEnloPS MEnloPS µ/...µ Mc@Nlo T S Parton shower matching and multijet merging at NLO 6

30 NLO-merging Conclusions Results: pp Wjets Inclusive Jet Multiplicity σ(w Njet jets) pb p jet > 30GeV ATLAS data MePs@Nlo MePs@Nlo µ/...µ MEnloPS MEnloPS µ/...µ Mc@Nlo p jet > 0GeV ( 0) pp W jets NLO; LO) µ R/F, µ def scale uncertainty much reduced NLO dependece for pp W 0,, jets LO dependence for pp W 3,4 jets cut = 30 GeV Njet good data description ATLAS data Phys.Rev.D85(0)0900 Parton shower matching and multijet merging at NLO 7

31 NLO-merging Conclusions Results: pp Wjets dσ/dp pb/gev 0 3 First Jet p W jet ( ) W jets ( 0.) W 3 jets ( 0.0) ATLAS data MePs@Nlo MePs@Nlo µ/...µ MEnloPS MEnloPS µ/...µ Mc@Nlo pp W jets NLO; LO) µ R/F, µ def scale uncertainty much reduced NLO dependece for pp W 0,, jets LO dependence for pp W 3,4 jets cut = 30 GeV good data description ATLAS data Phys.Rev.D85(0) Parton shower matching and multijet merging at NLO 7

32 NLO-merging Conclusions Results: pp Wjets ATLAS data Phys.Rev.D85(0)0900 R Distance of Leading Jets Azimuthal Distance of Leading Jets dσ/d R pb ATLAS data MePs@Nlo MePs@Nlo µ/...µ MEnloPS MEnloPS µ/...µ Mc@Nlo dσ/d φ pb ATLAS data MePs@Nlo MePs@Nlo µ/...µ MEnloPS MEnloPS µ/...µ Mc@Nlo R(First Jet, Second Jet) φ(first Jet, Second Jet) Parton shower matching and multijet merging at NLO 8

33 Conclusions SHERPA s MC@NLO formulation allows full evaluation of perturbative uncertainties (µ F, µ R, µ ) MC@NLO can be easily combined with MEPS MENLOPS MC@NLO is a necessary input for NLO merging MEPS@NLO MEPS@NLO gives full benefits of NLO calculations (scale dependences, normalisations) while also retaining full (N)LL accuracy of parton shower will be included in next major release Current release: SHERPA better description of perturbative CD is only part of the story to achieve higher precission for (hard) collider observables Parton shower matching and multijet merging at NLO 9

34 Thank you for your attention! Parton shower matching and multijet merging at NLO 0

35 NLO-merging Conclusions Case study: Inclusive jet & dijet production Dijet azimuthal decorrelation in various p lead bins Höche, MS arxiv:08.85 /σ dσ/d φ pb CMS data Phys. Rev. Lett. 06 (0) 003 Sherpa MC@NLO µr = µf = 4 HT, µ = p µr, µf variation µ variation MPI variation GeV < p lead 00 GeV < p lead < 300 GeV SherpaBlackHat GeV < p lead < 00 GeV 0 GeV < p lead < 40 GeV 80 GeV < p lead < 0 GeV φ φ Parton shower matching and multijet merging at NLO

36 NLO-merging Conclusions Case study: Inclusive jet & dijet production dσ/dp pb/gev Inclusive jet transverse momenta in different rapidity ranges SherpaBlackHat ATLAS data Phys. Rev. D86 (0) 040 Sherpa MC@NLO µr = µf = 4 HT, µ = p Sherpa MC@NLO µr = µf = 4 H(y) T, µ = p µr, µf variation µ variation MPI variation p GeV Höche, MS arxiv:08.85 y < < y < 3 < y <. 3. < y <. 3. < y < < y < < y < p GeV Parton shower matching and multijet merging at NLO

37 NLO-merging Conclusions Case study: Inclusive jet & dijet production /N dn/dln(τ,c) pb Central transverse thrust in different leading jet p ranges.4. CMS data Phys. Rev. Lett. 06 (0) 003 Sherpa MC@NLO µr = µf = 4 HT, µ = p µr, µf variation µ variation MPI variation Höche, MS arxiv: GeV < p jet GeV < p jet GeV < p jet < 00 GeV GeV < p jet < 00 GeV GeV < p jet < 5 GeV 0. SherpaBlackHat ln(τ,c) GeV < p jet < 5 GeV ln(τ,c) Parton shower matching and multijet merging at NLO 3

38 NLO-merging Conclusions Case study: Inclusive jet & dijet production /N dn/dln(t m,c) pb Central transverse thrust minor in different leading jet p ranges.4. CMS data Phys. Rev. Lett. 06 (0) 003 Sherpa MC@NLO µr = µf = 4 HT, µ = p µr, µf variation µ variation MPI variation Höche, MS arxiv: GeV < p jet GeV < p jet GeV < p jet < 00 GeV GeV < p jet < 00 GeV GeV < p jet < 5 GeV 0. SherpaBlackHat ln(t m,c) GeV < p jet < 5 GeV ln(t m,c) Parton shower matching and multijet merging at NLO 4

Study of the Higgs boson coupling to the top quark and of the b jet identification with the ATLAS experiment at the Large Hadron Collider.

Study of the Higgs boson coupling to the top quark and of the b jet identification with the ATLAS experiment at the Large Hadron Collider. Calvet Thomas CPPM, ATLAS group PhD day 25 novembre 2015 2 The