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Diagnostics with Beamstrahlung Electrons and Photons

Diagnostics with Beamstrahlung Electrons and Photons. Christian Grah. WORKSHOP Machine-Detector Interface at the International Linear Collider SLAC, January 6-8, 2005, Session 5: Very Forward Region. Outline. Overview: Very Forward Calorimetry Beam diagnostics from beamstrahlung

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Diagnostics with Beamstrahlung Electrons and Photons

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  1. Diagnostics with Beamstrahlung Electrons and Photons Christian Grah WORKSHOP Machine-Detector Interface at the International Linear Collider SLAC, January 6-8, 2005, Session 5: Very Forward Region

  2. Outline • Overview: Very Forward Calorimetry • Beam diagnostics from beamstrahlung • analyzing pairs (BeamCal) • analyzing photons (PhotoCal) • Summary & outlook Ch.Grah: Beamdiagnostics

  3. Very Forward Region • BeamCal: • detection of electrons/photons at low angle • beam diagnostics from beamstrahlung electrons/positron pairs • shielding of Inner Detector • Photocal (not drawn ~ downstream) • beam diagnostics from beamstrahlung photons (LumiCal: 26 < q < 82 mrad) BeamCal: 4 < q < 28 mrad PhotoCal: 100 < q < 400 μrad(recent idea, not mentioned in TESLA TDR, distance to IP > 100m) Ch.Grah: Beamdiagnostics

  4. Beamstrahlung: Fast Beam Diagnostics e+ e- • e+e-pairs from beamstrahlung are deflected into the BeamCal • 15000 e+e- per BX 10 – 20 TeV • 10 MGy per year • “fast” => O(μs) • direct photons forq< 400 mrad Ch.Grah: Beamdiagnostics

  5. Beamstrahlung Pairs • Observables (examples): • total energy • first radial moment • thrust value • angular spread • E(ring ≥ 4) / Etot • E / N • left/right, up/down, forward/backward asymmetries GeV/mm2 detector: realistic segmentation, ideal resolution bunch by bunch resolution Ch.Grah: Beamdiagnostics

  6. Analysis Concept Taylor Matrix Observables Observables Δ BeamPar nom • Beam Parameters • determine collision • creation of beamstr. • creation of e+e- pairs • guinea-pig • Observables • characterize energy distributions in detectors • analysis program 1st order Taylor-Exp. Solve by matrix inversion (Moore-Penrose Inverse) = + * Ch.Grah: Beamdiagnostics

  7. Slopes parametrization (polynomial) 1 point = 1 bunch crossing by guinea-pig slope at nom. value  taylor coefficient i,j observable j [au] beam parameter i [au] Ch.Grah: Beamdiagnostics

  8. Results of 1-Parameter Analysis Ch.Grah: Beamdiagnostics

  9. Analysis Test with non-nominal bunches: e- e+ nom. bunch size x: 575nm 575nm 553nm bunch size y: 5nm 7nm 5nm bunch size z: 290μm 320μm 300μm Ch.Grah: Beamdiagnostics

  10. Photons from Beamstrahlung • Report on analysis done by Andrei Rybin (Protvino) • Beam parameters under investigation: • beam size σx, σy, σz • beam offset x,y • waist shift x,y • Observables • Eγ (left – right) along x • Eγ (up – down) along y • Eγ (forward – backward) along z Every beam parameter analyzed separately, all others were fixed to nominal value. Ch.Grah: Beamdiagnostics

  11. Photon Distribution and Selection • Photon selection:|angle x| > 0.2 mrad|angle y| > 0.1 mrad Etot=3366.83 TeV nominal setting (550 nm x 5 nm) Ch.Grah: Beamdiagnostics

  12. Vertical Beam Waist Variation vert. waist shift > 0 vert. waist shift < 0 nominell beam parameters Ch.Grah: Beamdiagnostics

  13. Results of Analysis Parameter nom. in phot. pairs • σx 553 nm 4.2 1.5 • σy 5.0 nm 0.1 0.2 • σz 300 μm 7.5 4.3 • beam offset x 0 nm 4.0 6.0 • beam offset y 0 nm 0.16 0.4 • vertical waist shift 360 μm 14 24 Ch.Grah: Beamdiagnostics

  14. Summary • Analyzing beamstrahlung grants access to many beam parameters. • Investigating the possibility of measuring the distribution of pairs from beamstrahlung with BeamCal. • Started to analyze photon distribution at lowest angles (~100 μrad) with PhotoCal. • Started to analyze impact of small crossing angle on photon distribution. • Started comparison CAIN & GuineaPIG and saw only minor differences. Ch.Grah: Beamdiagnostics

  15. Outlook • Closer look at realistic beam simulation (started). • Analyze impact of/on the detector: • energy resolution • precision of the position measurement. Ch.Grah: Beamdiagnostics

  16. Backup Slides Ch.Grah: Beamdiagnostics

  17. Multi Parameter Analysis σx Δσx σy Δσy σz Δσz 0.3 % 0.4 % 3.4 % 9.5 % 1.4 % 0.8 % 1.5 % 0.9 % 0.3 % 0.4 % 3.5 % 11 % 0.9 % 1.0 % 11 % 24 % 5.7 % 24 % 1.6 % 1.9 % 1.8 % 1.1 % 16 % 27 % 3.2 % 2.1 % Ch.Grah: Beamdiagnostics

  18. Full Analysis Ch.Grah: Beamdiagnostics

  19. Neural Network for Photon Analysis In use: Multi layer perceptron feed-forward network 2 input nodes 1 hidden layer with 5 nodes 1 output node 200 Epochs for learning hybrid linear BFGS learning method Ch.Grah: Beamdiagnostics

  20. Example: Reconstruction of σy • Reconstruction done by Neural Network: • training vs. error • Single bunch crossing: σ(σy)= 0.113 nm Ch.Grah: Beamdiagnostics

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