Basics of QCD: jets & jet substructure Gavin Salam (CERN) with extensive use of material by Matteo Cacciari and Gregory Soyez ICTP–SAIFR school on QCD and LHC physics July 2015, São Paulo, Brazil 1 JETS Collimated, energetic bunches of particles Gavin Salam (CERN) QCD basics 4 ICTP-SAIFR school, July 2015 2 Find all papers by ATLAS and CMS 850 records found Gavin Salam (CERN) QCD basics 4 ICTP-SAIFR school, July 2015 3 Pull out those that refer to one widely used jet-alg 538 records found > 60% of papers use jets! Gavin Salam (CERN) QCD basics 4 ICTP-SAIFR school, July 2015 4 Why do we see jets? [Introduction] [Background knowledge] Why do we see jets? Parton fragmentation Gluon emission Gluon emission: π+ dE dθdE d✓ quark αs ↵s ≫ 1 1 K E θ E ✓ L ! Z 0 π At low scales: perturbative + − K Non-perturbative − αs → 1 hadronisation π physics non ↵ 1 s ⇠ High-energy partons unavoidably lead to collimated bunches of hadrons Gavin Salam (CERN) Jets and jet substructure (1) June 2013 3 / 35 Gavin Salam (CERN) QCD basics 4 ICTP-SAIFR school, July 2015 5 Jet finding as a form of projection [Introduction] [Background knowledge] Jets as projections π π p φ K LO partons NLO partons parton shower hadron level Jet Def n Jet Def n Jet Def n Jet Def n jet 1 jet 2 jet 1 jet 2 jet 1 jet 2 jet 1 jet 2 ProjectionProjection to tojets jets should should bebe resilient resilient to to QCD QCD effects effects Gavin Salam (CERN) Jets and jet substructure (1) June 2013 8 / 35 Gavin Salam (CERN) QCD basics 4 ICTP-SAIFR school, July 2015 6 [Introduction]Reconstructing jets is an ambiguous task [Background knowledge] Seeing v. defining jets Jets are what we see. How many jets do you see? Clearly(?) 2 jets here Do you really want to ask yourself this question for 109 events? Gavin Salam (CERN) QCD basics 4 ICTP-SAIFR school, July 2015 7 Gavin Salam (CERN) Jets and jet substructure (1) June 2013 6 / 35 [Introduction]Reconstructing jets is an ambiguous task [Background knowledge] Seeing v. defining jets Jets are what we see. How many jets do you see? Clearly(?)2 2clear jets here jets Do you really want to ask yourself this question for 109 events? Gavin Salam (CERN) QCD basics 4 ICTP-SAIFR school, July 2015 7 Gavin Salam (CERN) Jets and jet substructure (1) June 2013 6 / 35 [Introduction]Reconstructing jets is an ambiguous task [Background knowledge] Seeing v. defining jets Jets are what we see. How many jets do you see? Clearly(?)2 2clear jets here jets 3 jets? Do you really want to ask yourself this question for 109 events? Gavin Salam (CERN) QCD basics 4 ICTP-SAIFR school, July 2015 7 Gavin Salam (CERN) Jets and jet substructure (1) June 2013 6 / 35 [Introduction]Reconstructing jets is an ambiguous task [Background knowledge] Seeing v. defining jets Jets are what we see. How many jets do you see? Clearly(?)2 2clear jets here jets 3 jets? Do you reallyor 4 want jets? to ask yourself this question for 109 events? Gavin Salam (CERN) QCD basics 4 ICTP-SAIFR school, July 2015 8 Gavin Salam (CERN) Jets and jet substructure (1) June 2013 6 / 35 Gavin Salam (CERN) QCD basics 4 ICTP-SAIFR school, July 2015 9 Make a choice: specify a jet definition jet definition {pi} {jk} particles, jets 4-momenta, calorimeter towers, .... • Which particles do you put together into a same jet? • How do you recombine their momenta (4-momentum sum is the obvious choice, right?) “Jet [definitions] are legal contracts between theorists and experimentalists’’ -- MJ Tannenbaum They’re also a way of organising the information in an event 1000’s of particles per events, up to 20.000,000 events per second Gavin Salam (CERN) QCD basics 4 ICTP-SAIFR school, July 2015 10 Jet definitions date back to the late 1970s Sterman and Weinberg, Phys. Rev. Lett. 39, 1436 (1977): Gavin Salam (CERN) QCD basics 4 ICTP-SAIFR school, July 2015 11 [Theory v. experiment] Key[Cone algorithms] requirement: infraredConsequences and ofcollinear collinear unsafety safety Collinear Safe Collinear Unsafe jet 1 jet 1 jet 1 jet 1 jet 2 n n n n αs x (−∞ ) αs x (+∞ ) αs x (−∞ ) αs x (+∞ ) Infinities cancel Infinities do not cancel Invalidates perturbation theory Jets lecture 2 (Gavin Salam) CERN Academic Training March/April 2011 9 / 28 Gavin Salam (CERN) QCD basics 4 ICTP-SAIFR school, July 2015 12 hadron-collider kt algorithm Two parameters, R and pt,min (These are the two parameters in essentially every widely used hadron-collider jet algorithm) ∆R2 d =min(p2 ,p2 ) ij , ∆R2 =(y y )2 +(φ φ )2 ij ti tj R2 ij i − j i − j Sequential recombination algorithm 1. Find smallest of dij, diB 2. If ij, recombine them 3. If iB, call i a jet and remove from list of particles 4. repeat from step 1 until no particles left Inclusive kt algorithm Only use jets with pt > pt,min S.D. Ellis & Soper, 1993 Catani, Dokshitzer, Seymour & Webber, 1993 Gavin Salam (CERN) QCD basics 4 ICTP-SAIFR school, July 2015 13 Sequential recombination variants Cambridge/Aachen: the simplest of hadron-collider algorithms • Recombine pair of objects closest in ΔRij • Repeat until all ΔRij > R — remaining objects are jets Dokshitzer, Leder, Moretti, Webber ’97 (Cambridge): more involved e+e− form Wobisch & Wengler ’99 (Aachen): simple inclusive hadron-collider form One still applies a pt,min cut to the jets, as for inclusive kt C/A privileges the collinear divergence of QCD; it ‘ignores’ the soft one Gavin Salam (CERN) QCD basics 4 ICTP-SAIFR school, July 2015 14 anti-kt Anti-kt: formulated similarly to inclusive kt, but with 2 1 ∆Rij 1 dij = 2 2 2 ,diB = 2 max(pti,ptj) R pti Cacciari, GPS & Soyez ’08 [+Delsart unpublished] Anti-kt privileges the collinear divergence of QCD and disfavours clustering between pairs of soft particles Most pairwise clusterings involve at least one hard particle Gavin Salam (CERN) QCD basics 4 ICTP-SAIFR school, July 2015 15 Anti-kt in action 2 Clustering grows 1 ∆Rij 1 dij = 2 2 2 ,diB = 2 around hard cores max(pti,ptj) R pti Gavin Salam (CERN) QCD basics 4 ICTP-SAIFR school, July 2015 16 Anti-kt in action 2 Clustering grows 1 ∆Rij 1 dij = 2 2 2 ,diB = 2 around hard cores max(pti,ptj) R pti Gavin Salam (CERN) QCD basics 4 ICTP-SAIFR school, July 2015 16 Anti-kt in action 2 Clustering grows 1 ∆Rij 1 dij = 2 2 2 ,diB = 2 around hard cores max(pti,ptj) R pti Gavin Salam (CERN) QCD basics 4 ICTP-SAIFR school, July 2015 16 Anti-kt in action 2 Clustering grows 1 ∆Rij 1 dij = 2 2 2 ,diB = 2 around hard cores max(pti,ptj) R pti Gavin Salam (CERN) QCD basics 4 ICTP-SAIFR school, July 2015 16 Anti-kt in action 2 Clustering grows 1 ∆Rij 1 dij = 2 2 2 ,diB = 2 around hard cores max(pti,ptj) R pti Gavin Salam (CERN) QCD basics 4 ICTP-SAIFR school, July 2015 16 Anti-kt in action 2 Clustering grows 1 ∆Rij 1 dij = 2 2 2 ,diB = 2 around hard cores max(pti,ptj) R pti Gavin Salam (CERN) QCD basics 4 ICTP-SAIFR school, July 2015 16 Anti-kt in action 2 Clustering grows 1 ∆Rij 1 dij = 2 2 2 ,diB = 2 around hard cores max(pti,ptj) R pti Gavin Salam (CERN) QCD basics 4 ICTP-SAIFR school, July 2015 16 Anti-kt in action 2 Clustering grows 1 ∆Rij 1 dij = 2 2 2 ,diB = 2 around hard cores max(pti,ptj) R pti Gavin Salam (CERN) QCD basics 4 ICTP-SAIFR school, July 2015 16 Anti-kt in action 2 Clustering grows 1 ∆Rij 1 dij = 2 2 2 ,diB = 2 around hard cores max(pti,ptj) R pti Gavin Salam (CERN) QCD basics 4 ICTP-SAIFR school, July 2015 16 Anti-kt in action 2 Clustering grows 1 ∆Rij 1 dij = 2 2 2 ,diB = 2 around hard cores max(pti,ptj) R pti Gavin Salam (CERN) QCD basics 4 ICTP-SAIFR school, July 2015 16 Anti-kt in action 2 Clustering grows 1 ∆Rij 1 dij = 2 2 2 ,diB = 2 around hard cores max(pti,ptj) R pti Gavin Salam (CERN) QCD basics 4 ICTP-SAIFR school, July 2015 16 Anti-kt in action 2 Clustering grows 1 ∆Rij 1 dij = 2 2 2 ,diB = 2 around hard cores max(pti,ptj) R pti Gavin Salam (CERN) QCD basics 4 ICTP-SAIFR school, July 2015 16 Anti-kt in action 2 Clustering grows 1 ∆Rij 1 dij = 2 2 2 ,diB = 2 around hard cores max(pti,ptj) R pti Gavin Salam (CERN) QCD basics 4 ICTP-SAIFR school, July 2015 16 Anti-kt in action 2 Clustering grows 1 ∆Rij 1 dij = 2 2 2 ,diB = 2 around hard cores max(pti,ptj) R pti Gavin Salam (CERN) QCD basics 4 ICTP-SAIFR school, July 2015 16 Anti-kt in action 2 Clustering grows 1 ∆Rij 1 dij = 2 2 2 ,diB = 2 around hard cores max(pti,ptj) R pti Gavin Salam (CERN) QCD basics 4 ICTP-SAIFR school, July 2015 16 Anti-kt in action 2 Clustering grows 1 ∆Rij 1 dij = 2 2 2 ,diB = 2 around hard cores max(pti,ptj) R pti Anti-kt gives circular jets (“cone-like”) in a way that’s infrared safe Gavin Salam (CERN) QCD basics 4 ICTP-SAIFR school, July 2015 16 Linearity: kt v.