[PPT] - Slepton and bosino property determination in coanihilation SUSY PowerPoint Presentation

SLIDE 1

Slepton and bosino property determination in ˜ τ coanihilation SUSY DM models

Mikael Berggren1

1DESY, Hamburg

LCWS14, Belgrade, October 2014

Mikael Berggren (DESY) SUSY property determination LCWS, Oct 2014 1 / 24

SLIDE 2

Outline

This is a status report !!!

1

Outline

2

Studying SUSY in rich models

3

A bench-mark point: STC4 STC4 @ 500 GeV STC4 @ 500 GeV: Globaly STC4 @ 500 GeV: First light - ˜ eR STC4 @ 500 GeV: Full speed - sleptons STC4 @ 500 GeV: Full speed - ˜ τ1 and DM

4

Outlook & Conclusions

Mikael Berggren (DESY) SUSY property determination LCWS, Oct 2014 2 / 24

SLIDE 3

Studying SUSY in rich models

Aim of the study

Suppose SUSY is there and has a rich spectrum of sparticles accessible at the ILC. Then: Easy - wrt. things like ˜ H only, WIMP only: Lots to see. Hard - wrt. things like ˜ H only, WIMP only: Lots to Disentangle. Specifically: When data starts coming in, what is is first light ? How do we quickly determine a set of model parameters ? What is then the optimal use of beam-time in such a scenario ? And in a staged approach ? Spectrum in continuum vs. threshold-scans? Special points, eg. between ˜ τ1˜ τ2 and ˜ τ2˜ τ2 thresholds. Clean vs. high cross-section. What does it tell us about DM?

Mikael Berggren (DESY) SUSY property determination LCWS, Oct 2014 3 / 24

SLIDE 4

Studying SUSY in rich models

Aim of the study

Suppose SUSY is there and has a rich spectrum of sparticles accessible at the ILC. Then: Easy - wrt. things like ˜ H only, WIMP only: Lots to see. Hard - wrt. things like ˜ H only, WIMP only: Lots to Disentangle. Specifically: When data starts coming in, what is is first light ? How do we quickly determine a set of model parameters ? What is then the optimal use of beam-time in such a scenario ? And in a staged approach ? Spectrum in continuum vs. threshold-scans? Special points, eg. between ˜ τ1˜ τ2 and ˜ τ2˜ τ2 thresholds. Clean vs. high cross-section. What does it tell us about DM?

Mikael Berggren (DESY) SUSY property determination LCWS, Oct 2014 3 / 24

SLIDE 5

Studying SUSY in rich models

Aim of the study

Suppose SUSY is there and has a rich spectrum of sparticles accessible at the ILC. Then: Easy - wrt. things like ˜ H only, WIMP only: Lots to see. Hard - wrt. things like ˜ H only, WIMP only: Lots to Disentangle. Specifically: When data starts coming in, what is is first light ? How do we quickly determine a set of model parameters ? What is then the optimal use of beam-time in such a scenario ? And in a staged approach ? Spectrum in continuum vs. threshold-scans? Special points, eg. between ˜ τ1˜ τ2 and ˜ τ2˜ τ2 thresholds. Clean vs. high cross-section. What does it tell us about DM?

Mikael Berggren (DESY) SUSY property determination LCWS, Oct 2014 3 / 24

SLIDE 6

Studying SUSY in rich models

Aim of the study

Suppose SUSY is there and has a rich spectrum of sparticles accessible at the ILC. Then: Easy - wrt. things like ˜ H only, WIMP only: Lots to see. Hard - wrt. things like ˜ H only, WIMP only: Lots to Disentangle. Specifically: When data starts coming in, what is is first light ? How do we quickly determine a set of model parameters ? What is then the optimal use of beam-time in such a scenario ? And in a staged approach ? Spectrum in continuum vs. threshold-scans? Special points, eg. between ˜ τ1˜ τ2 and ˜ τ2˜ τ2 thresholds. Clean vs. high cross-section. What does it tell us about DM?

Mikael Berggren (DESY) SUSY property determination LCWS, Oct 2014 3 / 24

SLIDE 7

Studying SUSY in rich models

Aim of the study

Suppose SUSY is there and has a rich spectrum of sparticles accessible at the ILC. Then: Easy - wrt. things like ˜ H only, WIMP only: Lots to see. Hard - wrt. things like ˜ H only, WIMP only: Lots to Disentangle. Specifically: When data starts coming in, what is is first light ? How do we quickly determine a set of model parameters ? What is then the optimal use of beam-time in such a scenario ? And in a staged approach ? Spectrum in continuum vs. threshold-scans? Special points, eg. between ˜ τ1˜ τ2 and ˜ τ2˜ τ2 thresholds. Clean vs. high cross-section. What does it tell us about DM?

Mikael Berggren (DESY) SUSY property determination LCWS, Oct 2014 3 / 24

SLIDE 8

Studying SUSY in rich models

Aim of the study

Suppose SUSY is there and has a rich spectrum of sparticles accessible at the ILC. Then: Easy - wrt. things like ˜ H only, WIMP only: Lots to see. Hard - wrt. things like ˜ H only, WIMP only: Lots to Disentangle. Specifically: When data starts coming in, what is is first light ? How do we quickly determine a set of model parameters ? What is then the optimal use of beam-time in such a scenario ? And in a staged approach ? Spectrum in continuum vs. threshold-scans? Special points, eg. between ˜ τ1˜ τ2 and ˜ τ2˜ τ2 thresholds. Clean vs. high cross-section. What does it tell us about DM?

Mikael Berggren (DESY) SUSY property determination LCWS, Oct 2014 3 / 24

SLIDE 9

Studying SUSY in rich models

Aim of the study

Suppose SUSY is there and has a rich spectrum of sparticles accessible at the ILC. Then: Easy - wrt. things like ˜ H only, WIMP only: Lots to see. Hard - wrt. things like ˜ H only, WIMP only: Lots to Disentangle. Specifically: When data starts coming in, what is is first light ? How do we quickly determine a set of model parameters ? What is then the optimal use of beam-time in such a scenario ? And in a staged approach ? Spectrum in continuum vs. threshold-scans? Special points, eg. between ˜ τ1˜ τ2 and ˜ τ2˜ τ2 thresholds. Clean vs. high cross-section. What does it tell us about DM?

Mikael Berggren (DESY) SUSY property determination LCWS, Oct 2014 3 / 24

SLIDE 10

Studying SUSY in rich models

SUSY signatures and backgrounds

What we look for and like to measure is: NLSP pairs ⇔ Missing energy and momentum + pairs of the SM partner (˜ τ1 gives τ, ˜ e gives e, ˜ t gives t gives jet, ...)

Note:

Amount of missing stuff might span a wide range. Eg. small mass-difference between heavy sparticles gives large missing E, but little missing p. If NLSP is a bosino, SM partner is a IVB, possibly far off-shell. At small mass differences, the set of SM particles might be non-obvious.

Anything but NLSP pairs: Cascade decays: Still Missing energy and momentum, but id of SM particles can be mixed.

Mikael Berggren (DESY) SUSY property determination LCWS, Oct 2014 4 / 24

SLIDE 11

Studying SUSY in rich models

SUSY signatures and backgrounds

What we look for and like to measure is: NLSP pairs ⇔ Missing energy and momentum + pairs of the SM partner (˜ τ1 gives τ, ˜ e gives e, ˜ t gives t gives jet, ...)

Note:

Amount of missing stuff might span a wide range. Eg. small mass-difference between heavy sparticles gives large missing E, but little missing p. If NLSP is a bosino, SM partner is a IVB, possibly far off-shell. At small mass differences, the set of SM particles might be non-obvious.

Anything but NLSP pairs: Cascade decays: Still Missing energy and momentum, but id of SM particles can be mixed.

Mikael Berggren (DESY) SUSY property determination LCWS, Oct 2014 4 / 24

SLIDE 12

Studying SUSY in rich models

SUSY signatures and backgrounds

What we look for and like to measure is: NLSP pairs ⇔ Missing energy and momentum + pairs of the SM partner (˜ τ1 gives τ, ˜ e gives e, ˜ t gives t gives jet, ...)

Note:

Amount of missing stuff might span a wide range. Eg. small mass-difference between heavy sparticles gives large missing E, but little missing p. If NLSP is a bosino, SM partner is a IVB, possibly far off-shell. At small mass differences, the set of SM particles might be non-obvious.

Anything but NLSP pairs: Cascade decays: Still Missing energy and momentum, but id of SM particles can be mixed.

Mikael Berggren (DESY) SUSY property determination LCWS, Oct 2014 4 / 24

SLIDE 13

Studying SUSY in rich models

SUSY signatures and backgrounds

What we look for and like to measure is: NLSP pairs ⇔ Missing energy and momentum + pairs of the SM partner (˜ τ1 gives τ, ˜ e gives e, ˜ t gives t gives jet, ...)

Note:

Amount of missing stuff might span a wide range. Eg. small mass-difference between heavy sparticles gives large missing E, but little missing p. If NLSP is a bosino, SM partner is a IVB, possibly far off-shell. At small mass differences, the set of SM particles might be non-obvious.

Anything but NLSP pairs: Cascade decays: Still Missing energy and momentum, but id of SM particles can be mixed.

Mikael Berggren (DESY) SUSY property determination LCWS, Oct 2014 4 / 24

SLIDE 14

Studying SUSY in rich models

Bosino signatures

Depending on order of µ, M1, and M2, and on GUT-scale U(1)⊗SU(2) mass-unification: µ << M1, M2:

LSP and NLSP both higgsino, very low ∆M.

M2 < M1 << µ:

LSP Wino, NLSP is ˜ χ±

1 , and

is close.

M1 < M2 << µ:

LSP Bino, NLSP is near degenerate ˜ χ±

1 and ˜

χ0

2.

If GUT M1 − M2 relation, ∆M < MLSP.

50 100 150 200 250 300 350 400 450 500 50 100 150 200 250 300 350 400 450 500 Pairs and associated Only associated GUT M1-M2 relation ∆M=Mz ∆M=Mw ∆M=10 LEP

M(χ0 2 or χ+ 1) MLSP

Mikael Berggren (DESY) SUSY property determination LCWS, Oct 2014 5 / 24

SLIDE 15

Studying SUSY in rich models

SUSY signatures and backgrounds

Background from SM: Real missing energy + pair of SM-particles = di-boson production, with neutrinos:

WW → ℓνℓν ZZ → f¯ fνν

Fake missing energy + pair of SM-particles = γγ processes, ISR, single IVB.

e+e− →e+e−γγ → e+e−f¯ f, with both e+e− un-detected. e+e− →f¯ fγ, with γ un-detected.

Mikael Berggren (DESY) SUSY property determination LCWS, Oct 2014 6 / 24

SLIDE 16

Studying SUSY in rich models

SUSY signatures and backgrounds

Background from SM: Real missing energy + pair of SM-particles = di-boson production, with neutrinos:

WW → ℓνℓν ZZ → f¯ fνν

Fake missing energy + pair of SM-particles = γγ processes, ISR, single IVB.

e+e− →e+e−γγ → e+e−f¯ f, with both e+e− un-detected. e+e− →f¯ fγ, with γ un-detected.

Mikael Berggren (DESY) SUSY property determination LCWS, Oct 2014 6 / 24

SLIDE 17

Studying SUSY in rich models

SUSY signatures and backgrounds

Background from SM: Real missing energy + pair of SM-particles = di-boson production, with neutrinos:

WW → ℓνℓν ZZ → f¯ fνν

Fake missing energy + pair of SM-particles = γγ processes, ISR, single IVB.

e+e− →e+e−γγ → e+e−f¯ f, with both e+e− un-detected. e+e− →f¯ fγ, with γ un-detected.

Mikael Berggren (DESY) SUSY property determination LCWS, Oct 2014 6 / 24

SLIDE 18

Studying SUSY in rich models

SUSY signatures and backgrounds

Background from SM: Real missing energy + pair of SM-particles = di-boson production, with neutrinos:

WW → ℓνℓν ZZ → f¯ fνν

Fake missing energy + pair of SM-particles = γγ processes, ISR, single IVB.

e+e− →e+e−γγ → e+e−f¯ f, with both e+e− un-detected. e+e− →f¯ fγ, with γ un-detected.

Mikael Berggren (DESY) SUSY property determination LCWS, Oct 2014 6 / 24

SLIDE 19

Studying SUSY in rich models

Observables:

Observable Gives If Edges (or average and ... not too far from width) Masses threshold Shape of spectrum Spin Angular distributions Mass, Spin Invariant mass distributions from full reconstruction Mass ... cascade decays Angular distributions from full reconstruction Spin, CP , ... masses known Un-polarised Cross-section in continuum Mass, coupling Polarised Cross-section Mass, coupling, in continuum mixing Decay product polarisation Mixing ... ˜ τ decays Threshold-scan Mass(es), Spin

Mikael Berggren (DESY) SUSY property determination LCWS, Oct 2014 7 / 24

SLIDE 20

Studying SUSY in rich models

Observables:

Observable Gives If Edges (or average and ... not too far from width) Masses threshold Shape of spectrum Spin Angular distributions Mass, Spin Invariant mass distributions from full reconstruction Mass ... cascade decays Angular distributions from full reconstruction Spin, CP , ... masses known Un-polarised Cross-section in continuum Mass, coupling Polarised Cross-section Mass, coupling, in continuum mixing Decay product polarisation Mixing ... ˜ τ decays Threshold-scan Mass(es), Spin

Ultimately Determine nature of DM and it’s properties

Mikael Berggren (DESY) SUSY property determination LCWS, Oct 2014 7 / 24

SLIDE 21

Studying SUSY in rich models

Observables: Pair-production, two-body decay

Consider e+e− →XX, followed by X → UY, where Y is a detectable (SM) particle. Then

EY max(min) = EBeam

2

1 −
MU

MX

2 1 +

(−)

1 −
MX

EBeam

2

, so that

MX = EBeam

1 − (∆/Σ)2

MU = EBeam

1 − (∆/Σ)2

1 − Σ/EBeam (∆ = EY max − EY min; Σ = EY max + EY min)

If the spectrum is flat (eg if X is a sfermion) between the end-points:

< EY >= (EY max + EY min)/2 and σEY =

(EY max − EY min)/12, which

gives

MU = EBeam

1 − 2<EY >

EBeam

1 −
6σ2

EY

<EY >

2

MX = EBeam

1 −
12σ2

EY

<EY >

2

Mikael Berggren (DESY) SUSY property determination LCWS, Oct 2014 8 / 24

SLIDE 22

Studying SUSY in rich models

Observables: Pair-production, two-body decay

Consider e+e− →XX, followed by X → UY, where Y is a detectable (SM) particle. Then

EY max(min) = EBeam

2

1 −
MU

MX

2 1 +

(−)

1 −
MX

EBeam

2

, so that

MX = EBeam

1 − (∆/Σ)2

MU = EBeam

1 − (∆/Σ)2

1 − Σ/EBeam (∆ = EY max − EY min; Σ = EY max + EY min)

If the spectrum is flat (eg if X is a sfermion) between the end-points:

< EY >= (EY max + EY min)/2 and σEY =

(EY max − EY min)/12, which

gives

MU = EBeam

1 − 2<EY >

EBeam

1 −
6σ2

EY

<EY >

2

MX = EBeam

1 −
12σ2

EY

<EY >

2

Mikael Berggren (DESY) SUSY property determination LCWS, Oct 2014 8 / 24

SLIDE 23

Studying SUSY in rich models

Observables: Pair-production, two-body decay

Consider e+e− →XX, followed by X → UY, where Y is a detectable (SM) particle. Then

EY max(min) = EBeam

2

1 −
MU

MX

2 1 +

(−)

1 −
MX

EBeam

2

, so that

MX = EBeam

1 − (∆/Σ)2

MU = EBeam

1 − (∆/Σ)2

1 − Σ/EBeam (∆ = EY max − EY min; Σ = EY max + EY min)

If the spectrum is flat (eg if X is a sfermion) between the end-points:

< EY >= (EY max + EY min)/2 and σEY =

(EY max − EY min)/12, which

gives

MU = EBeam

1 − 2<EY >

EBeam

1 −
6σ2

EY

<EY >

2

MX = EBeam

1 −
12σ2

EY

<EY >

2

Mikael Berggren (DESY) SUSY property determination LCWS, Oct 2014 8 / 24

SLIDE 24

Studying SUSY in rich models

Observables: Pair-production, two-body decay

Consider e+e− →XX, followed by X → UY, where Y is a detectable (SM) particle. Then

EY max(min) = EBeam

2

1 −
MU

MX

2 1 +

(−)

1 −
MX

EBeam

2

, so that

MX = EBeam

1 − (∆/Σ)2

MU = EBeam

1 − (∆/Σ)2

1 − Σ/EBeam (∆ = EY max − EY min; Σ = EY max + EY min)

If the spectrum is flat (eg if X is a sfermion) between the end-points:

< EY >= (EY max + EY min)/2 and σEY =

(EY max − EY min)/12, which

gives

MU = EBeam

1 − 2<EY >

EBeam

1 −
6σ2

EY

<EY >

2

MX = EBeam

1 −
12σ2

EY

<EY >

2

Mikael Berggren (DESY) SUSY property determination LCWS, Oct 2014 8 / 24

SLIDE 25

A bench-mark point: STC4

Example: STC4

STC4-8 11 parameters. Separate gluino Higgs, un-coloured, and coloured scalar parameters separate Parameters chosen to deliver all constraints (LHC, LEP , cosmology, low energy). At ECMS = 500 GeV: All sleptons available. No squarks. Lighter bosinos, up to ˜ χ0

3 (in e+e− →˜

χ0

1 ˜

χ0

3)

(See H. Baer, J. List, arXiv:1307:0782.)

Mikael Berggren (DESY) SUSY property determination LCWS, Oct 2014 9 / 24

SLIDE 26

A bench-mark point: STC4

Full STC4 mass-spectrum

200 400 600 800 1000 1200 1400 1600 1800 2000 2200 Mass / GeV

h0 A0 H0 H± ˜ qR ˜ qL ˜ g ˜ b1 ˜ t1 ˜ ℓR ˜ νL ˜ ℓL ˜ τ1 ˜ ντ ˜ τ2 ˜ χ0

1

˜ χ0

2

˜ χ±

1

˜ χ0

3

˜ χ0

4

˜ χ±

2

˜ b2 ˜ t2 Mikael Berggren (DESY) SUSY property determination LCWS, Oct 2014 10 / 24

SLIDE 27

A bench-mark point: STC4

Zoomed STC4 mass-spectrum

80 160 240 320 400 480 Mass / GeV

h0 A0 H0 H± ˜ t1 ˜ νL ˜ ℓL ˜ τ1 ˜ ντ ˜ χ0

1

˜ χ0

2

˜ χ±

1

˜ χ0

3

˜ χ0

4

˜ χ±

2

˜ ℓR ˜ τ2 Mikael Berggren (DESY) SUSY property determination LCWS, Oct 2014 11 / 24

SLIDE 28

A bench-mark point: STC4

Channels and observables at 250, 350 and 500 GeV

Channel Threshold Available at Can give ˜ τ1˜ τ1 212 250 M˜

τ1, ˜

τ1 nature, τ polarisation ˜ µR˜ µR 252 250+ + M˜

µR, M ˜ χ0

1, ˜

µR nature ˜ eR˜ eR 252 250+ + M˜

eR, M ˜ χ0

1, ˜

eR nature ˜ χ0

1 ˜

χ0

2 ∗)

302 350 + M ˜

χ0

2, M ˜

χ0

1, nature of ˜

χ0

1, ˜

χ0

2

˜ τ1˜ τ2

∗)

325 350 + M˜

τ2θmix ˜

τ ˜ eR˜ eL

∗)

339 350 + M˜

eL, ˜

χ0

1 mixing, ˜

eL nature ˜ ν˜ τ ˜ ν˜ τ 392 500 7 % visible BR (→ ˜ τ1W) ˜ χ±

1 ˜

χ±

1 ∗)

412 500 + M ˜

χ±

1 , nature of ˜

χ±

1

˜ eL˜ eL

∗)

416 500 + M˜

eL, M ˜ χ0

1, ˜

eL nature ˜ µL˜ µL

∗)

416 500 + M˜

µR, M ˜ χ0

1, ˜

µR nature ˜ τ2˜ τ2

∗)

438 500 + M˜

τ2, M ˜ χ0

1, ˜

τ2 nature, θmix ˜ τ ˜ χ0

1 ˜

χ0

3 ∗)

503 500+ + M ˜

χ0

3, M ˜

χ0

1, nature of ˜

χ0

1, ˜

χ0

3

*): Cascade decays. + invisible ˜ χ0

1 ˜

χ0

1, ˜

ν˜ e,˜ µ˜ ν˜ e,˜ µ.

Mikael Berggren (DESY) SUSY property determination LCWS, Oct 2014 12 / 24

SLIDE 29

A bench-mark point: STC4 STC4 @ 500 GeV

Features of STC4 @ 500 GeV

The ˜ τ1 is the NLSP . For ˜ τ1: Eτ,min = 2.3 GeV, Eτ,max = 45.5 GeV: γγ − background ⇔ pairs − background. For ˜ τ2: :Eτ,min = 52.4 GeV, Eτ,max = 150.0 GeV: WW → lνlν − background ⇔ Polarisation. For ˜ eRor ˜ µR: :El,min = 7.3 GeV, El,max = 99.2 GeV: Neither γγ nor WW → lνlν background severe. For pol=(1,-1): σ(˜ eR˜ eR) = 1.3 pb ! ˜ τ NLSP → τ:s in most SUSY decays → SUSY is background to SUSY. For pol=(-1,1): σ(˜ χ0

2 ˜

χ0

2) and σ(˜

χ+

1 ˜

χ−

1 ) = several hundred fb and

BR(X→ ˜ τ) > 70 %. For pol=(1,-1): σ(˜ χ0

2 ˜

χ0

2) and σ(˜

χ+

1 ˜

χ−

1 ) ≈ 0.

Mikael Berggren (DESY) SUSY property determination LCWS, Oct 2014 13 / 24

SLIDE 30

A bench-mark point: STC4 STC4 @ 500 GeV

Features of STC4 @ 500 GeV

The ˜ τ1 is the NLSP . For ˜ τ1: Eτ,min = 2.3 GeV, Eτ,max = 45.5 GeV: γγ − background ⇔ pairs − background. For ˜ τ2: :Eτ,min = 52.4 GeV, Eτ,max = 150.0 GeV: WW → lνlν − background ⇔ Polarisation. For ˜ eRor ˜ µR: :El,min = 7.3 GeV, El,max = 99.2 GeV: Neither γγ nor WW → lνlν background severe. For pol=(1,-1): σ(˜ eR˜ eR) = 1.3 pb ! ˜ τ NLSP → τ:s in most SUSY decays → SUSY is background to SUSY. For pol=(-1,1): σ(˜ χ0

2 ˜

χ0

2) and σ(˜

χ+

1 ˜

χ−

1 ) = several hundred fb and

BR(X→ ˜ τ) > 70 %. For pol=(1,-1): σ(˜ χ0

2 ˜

χ0

2) and σ(˜

χ+

1 ˜

χ−

1 ) ≈ 0.

Mikael Berggren (DESY) SUSY property determination LCWS, Oct 2014 13 / 24

SLIDE 31

A bench-mark point: STC4 STC4 @ 500 GeV

Features of STC4 @ 500 GeV

The ˜ τ1 is the NLSP . For ˜ τ1: Eτ,min = 2.3 GeV, Eτ,max = 45.5 GeV: γγ − background ⇔ pairs − background. For ˜ τ2: :Eτ,min = 52.4 GeV, Eτ,max = 150.0 GeV: WW → lνlν − background ⇔ Polarisation. For ˜ eRor ˜ µR: :El,min = 7.3 GeV, El,max = 99.2 GeV: Neither γγ nor WW → lνlν background severe. For pol=(1,-1): σ(˜ eR˜ eR) = 1.3 pb ! ˜ τ NLSP → τ:s in most SUSY decays → SUSY is background to SUSY. For pol=(-1,1): σ(˜ χ0

2 ˜

χ0

2) and σ(˜

χ+

1 ˜

χ−

1 ) = several hundred fb and

BR(X→ ˜ τ) > 70 %. For pol=(1,-1): σ(˜ χ0

2 ˜

χ0

2) and σ(˜

χ+

1 ˜

χ−

1 ) ≈ 0.

Mikael Berggren (DESY) SUSY property determination LCWS, Oct 2014 13 / 24

SLIDE 32

A bench-mark point: STC4 STC4 @ 500 GeV

Features of STC4 @ 500 GeV

The ˜ τ1 is the NLSP . For ˜ τ1: Eτ,min = 2.3 GeV, Eτ,max = 45.5 GeV: γγ − background ⇔ pairs − background. For ˜ τ2: :Eτ,min = 52.4 GeV, Eτ,max = 150.0 GeV: WW → lνlν − background ⇔ Polarisation. For ˜ eRor ˜ µR: :El,min = 7.3 GeV, El,max = 99.2 GeV: Neither γγ nor WW → lνlν background severe. For pol=(1,-1): σ(˜ eR˜ eR) = 1.3 pb ! ˜ τ NLSP → τ:s in most SUSY decays → SUSY is background to SUSY. For pol=(-1,1): σ(˜ χ0

2 ˜

χ0

2) and σ(˜

χ+

1 ˜

χ−

1 ) = several hundred fb and

BR(X→ ˜ τ) > 70 %. For pol=(1,-1): σ(˜ χ0

2 ˜

χ0

2) and σ(˜

χ+

1 ˜

χ−

1 ) ≈ 0.

Mikael Berggren (DESY) SUSY property determination LCWS, Oct 2014 13 / 24

SLIDE 33

A bench-mark point: STC4 STC4 @ 500 GeV

STC4 @ 500 GeV

Strategy: Global preselection to reduce SM, while efficiency for all signals stays above ∼ 90 %. The further select for all sleptons (˜ eR,˜ eL, ˜ µR, ˜ µL, ˜ τ1). Next step: specific selections for ˜ eR and ˜ µR, for ˜ eL and ˜ µL, and for ˜ τ1. Last step: add particle id to separate ˜ e and ˜ µ, special cuts for ˜ τ1. Check results both for RL and LR beam-polarisation. In the following, a mix of new results from STC4+SGV@DBD and SPS1a’+FullSim@LOI will be shown

Mikael Berggren (DESY) SUSY property determination LCWS, Oct 2014 14 / 24

SLIDE 34

A bench-mark point: STC4 STC4 @ 500 GeV

STC4 @ 500 GeV

Strategy: Global preselection to reduce SM, while efficiency for all signals stays above ∼ 90 %. The further select for all sleptons (˜ eR,˜ eL, ˜ µR, ˜ µL, ˜ τ1). Next step: specific selections for ˜ eR and ˜ µR, for ˜ eL and ˜ µL, and for ˜ τ1. Last step: add particle id to separate ˜ e and ˜ µ, special cuts for ˜ τ1. Check results both for RL and LR beam-polarisation. In the following, a mix of new results from STC4+SGV@DBD and SPS1a’+FullSim@LOI will be shown

Mikael Berggren (DESY) SUSY property determination LCWS, Oct 2014 14 / 24

SLIDE 35

A bench-mark point: STC4 STC4 @ 500 GeV: Globaly

STC4 global

After a few very general cuts: Missing energy > 100 Less than 10 charged tracks | cos θPtot| < 0.95 Exactly two τ-jets Visible mass < 300 GeV θacop between 0.15 and 3.1

10 4 10 5 25 50 75 100 125 150 175 200 225 250 ECMS=500 GeV, Pol=+0.8,-0.3

Ejet(GeV) Jets/2 GeV

Magenta: γγ, Blue: 3f, Red: Rest of SM, Green: SUSY.

Mikael Berggren (DESY) SUSY property determination LCWS, Oct 2014 15 / 24

SLIDE 36

A bench-mark point: STC4 STC4 @ 500 GeV: First light - ˜ eR

STC4 early discovery: ˜ eR

Early discovery channel: crossection in the pb-range. Few simple cuts. Simple observable: Evis: Peak and width gives M˜ eR and M˜

χ0

1.

See the signal appearing after

1 fb−1 5 fb−1 25 fb−1 100 fb−1 250 fb−1

Mikael Berggren (DESY) SUSY property determination LCWS, Oct 2014 16 / 24

SLIDE 37

A bench-mark point: STC4 STC4 @ 500 GeV: First light - ˜ eR

STC4 early discovery: ˜ eR

Early discovery channel: crossection in the pb-range. Few simple cuts. Simple observable: Evis: Peak and width gives M˜ eR and M˜

χ0

1.

See the signal appearing after

1 fb−1 5 fb−1 25 fb−1 100 fb−1 250 fb−1

50 100 150 200 250 300 350 400 10 20 30 40 50 60 70 80 Visible Energy @ 1 fb-1

Mikael Berggren (DESY) SUSY property determination LCWS, Oct 2014 16 / 24

SLIDE 38

A bench-mark point: STC4 STC4 @ 500 GeV: First light - ˜ eR

STC4 early discovery: ˜ eR

Early discovery channel: crossection in the pb-range. Few simple cuts. Simple observable: Evis: Peak and width gives M˜ eR and M˜

χ0

1.

See the signal appearing after

1 fb−1 5 fb−1 25 fb−1 100 fb−1 250 fb−1

50 100 150 200 250 300 350 400 50 100 150 200 250 300

Visible Energy @ 5 fb-1

Mikael Berggren (DESY) SUSY property determination LCWS, Oct 2014 16 / 24

SLIDE 39

A bench-mark point: STC4 STC4 @ 500 GeV: First light - ˜ eR

STC4 early discovery: ˜ eR

Early discovery channel: crossection in the pb-range. Few simple cuts. Simple observable: Evis: Peak and width gives M˜ eR and M˜

χ0

1.

See the signal appearing after

1 fb−1 5 fb−1 25 fb−1 100 fb−1 250 fb−1

50 100 150 200 250 300 350 400 200 400 600 800 1000 1200 1400

Visible Energy @ 25 fb-1

Mikael Berggren (DESY) SUSY property determination LCWS, Oct 2014 16 / 24

SLIDE 40

A bench-mark point: STC4 STC4 @ 500 GeV: First light - ˜ eR

STC4 early discovery: ˜ eR

Early discovery channel: crossection in the pb-range. Few simple cuts. Simple observable: Evis: Peak and width gives M˜ eR and M˜

χ0

1.

See the signal appearing after

1 fb−1 5 fb−1 25 fb−1 100 fb−1 250 fb−1

50 100 150 200 250 300 350 400 1000 2000 3000 4000 5000 6000

Visible Energy @ 100 fb-1

Mikael Berggren (DESY) SUSY property determination LCWS, Oct 2014 16 / 24

SLIDE 41

A bench-mark point: STC4 STC4 @ 500 GeV: First light - ˜ eR

STC4 early discovery: ˜ eR

Early discovery channel: crossection in the pb-range. Few simple cuts. Simple observable: Evis: Peak and width gives M˜ eR and M˜

χ0

1.

See the signal appearing after

1 fb−1 5 fb−1 25 fb−1 100 fb−1 250 fb−1

50 100 150 200 250 300 350 400 2000 4000 6000 8000 10000 12000 14000

Visible Energy @ 250 fb-1

Mikael Berggren (DESY) SUSY property determination LCWS, Oct 2014 16 / 24

SLIDE 42

A bench-mark point: STC4 STC4 @ 500 GeV: Full speed - sleptons

STC4 sleptons @ 500 GeV:˜ e, ˜ µ

Selections for ˜ µ and ˜ e:

Correct charge. PT wrt. beam and one ℓ wrt the other. Tag and probe, ie. accept

ne jet if the other is “in the

box”.

Further selections for R:

Cuts on polar angle and angle between leptons.

Ejet, beam-pol 80%,-30%... ... or beam-pol -80%,30%. Further selections for L (LR):

qjet cos θjet Mvis = MZ

Mikael Berggren (DESY) SUSY property determination LCWS, Oct 2014 17 / 24

SLIDE 43

A bench-mark point: STC4 STC4 @ 500 GeV: Full speed - sleptons

STC4 sleptons @ 500 GeV:˜ e, ˜ µ

Selections for ˜ µ and ˜ e:

Correct charge. PT wrt. beam and one ℓ wrt the other. Tag and probe, ie. accept

ne jet if the other is “in the

box”.

Further selections for R:

Cuts on polar angle and angle between leptons.

Ejet, beam-pol 80%,-30%... ... or beam-pol -80%,30%. Further selections for L (LR):

qjet cos θjet Mvis = MZ

Mikael Berggren (DESY) SUSY property determination LCWS, Oct 2014 17 / 24

SLIDE 44

A bench-mark point: STC4 STC4 @ 500 GeV: Full speed - sleptons

STC4 sleptons @ 500 GeV:˜ e, ˜ µ

Selections for ˜ µ and ˜ e:

Correct charge. PT wrt. beam and one ℓ wrt the other. Tag and probe, ie. accept

ne jet if the other is “in the

box”.

Further selections for R:

Cuts on polar angle and angle between leptons.

Ejet, beam-pol 80%,-30%... ... or beam-pol -80%,30%. Further selections for L (LR):

qjet cos θjet Mvis = MZ

1000 2000 3000 4000 5000 20 40 60 80 100 120

Ejet (GeV) Jets/1 GeV

Selectrons R 1000 2000 3000 4000 5000 20 40 60 80 100 120

Ejet (GeV) Jets/1 GeV

Smuons R

Mikael Berggren (DESY) SUSY property determination LCWS, Oct 2014 17 / 24

SLIDE 45

A bench-mark point: STC4 STC4 @ 500 GeV: Full speed - sleptons

STC4 sleptons @ 500 GeV:˜ e, ˜ µ

Selections for ˜ µ and ˜ e:

Correct charge. PT wrt. beam and one ℓ wrt the other. Tag and probe, ie. accept

ne jet if the other is “in the

box”.

Further selections for R:

Cuts on polar angle and angle between leptons.

Ejet, beam-pol 80%,-30%... ... or beam-pol -80%,30%. Further selections for L (LR):

qjet cos θjet Mvis = MZ

1000 2000 3000 4000 5000 20 40 60 80 100 120

Ejet (GeV) Jets/1 GeV

Selectrons R 1000 2000 3000 4000 5000 20 40 60 80 100 120

Ejet (GeV) Jets/1 GeV

Smuons R

Mikael Berggren (DESY) SUSY property determination LCWS, Oct 2014 17 / 24

SLIDE 46

A bench-mark point: STC4 STC4 @ 500 GeV: Full speed - sleptons

STC4 sleptons @ 500 GeV:˜ e, ˜ µ

Selections for ˜ µ and ˜ e:

Correct charge. PT wrt. beam and one ℓ wrt the other. Tag and probe, ie. accept

ne jet if the other is “in the

box”.

Further selections for R:

Cuts on polar angle and angle between leptons.

Ejet, beam-pol 80%,-30%... ... or beam-pol -80%,30%. Further selections for L (LR):

qjet cos θjet Mvis = MZ

1000 2000 3000 4000 5000 20 40 60 80 100 120 140 160

Ejet (GeV) Jets/1 GeV

Selectrons L 1000 2000 3000 4000 5000 20 40 60 80 100 120 140 160

Ejet (GeV) Jets/1 GeV

Smuons L

Mikael Berggren (DESY) SUSY property determination LCWS, Oct 2014 17 / 24

SLIDE 47

A bench-mark point: STC4 STC4 @ 500 GeV: Full speed - sleptons

STC4 sleptons @ 500 GeV:˜ e, ˜ µ

Selections for ˜ µ and ˜ e:

Correct charge. PT wrt. beam and one ℓ wrt the other. Tag and probe, ie. accept

ne jet if the other is “in the

box”.

Further selections for R:

Cuts on polar angle and angle between leptons.

Ejet, beam-pol 80%,-30%... ... or beam-pol -80%,30%. Further selections for L (LR):

qjet cos θjet Mvis = MZ

200 400 600 800 1000 1200 20 40 60 80 100 120 140 160

Ejet (GeV) Jets/1 GeV

Selectrons L 200 400 600 800 1000 1200 20 40 60 80 100 120 140 160

Ejet (GeV) Jets/1 GeV

Smuons L

Mikael Berggren (DESY) SUSY property determination LCWS, Oct 2014 17 / 24

SLIDE 48

A bench-mark point: STC4 STC4 @ 500 GeV: Full speed - sleptons

Masses from ˜ e, ˜ µ in the continuum

In R[Emin, Emax], the MVB exists and is min(max)(Eℓ) (!) In presence of background this won’t work. Try to mitigate the effect of extreme cases:

Exclude highest/lowest x%, and/or Subdivide in sub-samples and average.

Also calculate masses using mean and s.d. of entire spectrum and compare.

Mikael Berggren (DESY) SUSY property determination LCWS, Oct 2014 18 / 24

SLIDE 49

A bench-mark point: STC4 STC4 @ 500 GeV: Full speed - sleptons

Masses from ˜ e, ˜ µ in the continuum

In R[Emin, Emax], the MVB exists and is min(max)(Eℓ) (!) In presence of background this won’t work. Try to mitigate the effect of extreme cases:

Exclude highest/lowest x%, and/or Subdivide in sub-samples and average.

Also calculate masses using mean and s.d. of entire spectrum and compare.

1000 2000 3000 4000 5000 20 40 60 80 100 120

Ejet (GeV) Jets/1 GeV

Selectrons R Mikael Berggren (DESY) SUSY property determination LCWS, Oct 2014 18 / 24

SLIDE 50

A bench-mark point: STC4 STC4 @ 500 GeV: Full speed - sleptons

Masses from ˜ e, ˜ µ in the continuum

In R[Emin, Emax], the MVB exists and is min(max)(Eℓ) (!) In presence of background this won’t work. Try to mitigate the effect of extreme cases:

Exclude highest/lowest x%, and/or Subdivide in sub-samples and average.

Also calculate masses using mean and s.d. of entire spectrum and compare.

1000 2000 3000 4000 5000 20 40 60 80 100 120

Ejet (GeV) Jets/1 GeV

Selectrons R Mikael Berggren (DESY) SUSY property determination LCWS, Oct 2014 18 / 24

SLIDE 51

A bench-mark point: STC4 STC4 @ 500 GeV: Full speed - sleptons

Masses from ˜ e, ˜ µ in the continuum

In R[Emin, Emax], the MVB exists and is min(max)(Eℓ) (!) In presence of background this won’t work. Try to mitigate the effect of extreme cases:

Exclude highest/lowest x%, and/or Subdivide in sub-samples and average.

Also calculate masses using mean and s.d. of entire spectrum and compare.

LSP 0.05 0.1 0.15 0.2 0.25 0.3 0.35 100 101 102 103 104 105 106 107 108 109 110

Mseen

Rel. freq.

From edges From full spect Mikael Berggren (DESY) SUSY property determination LCWS, Oct 2014 18 / 24

SLIDE 52

A bench-mark point: STC4 STC4 @ 500 GeV: Full speed - sleptons

Masses from ˜ e, ˜ µ in the continuum

In R[Emin, Emax], the MVB exists and is min(max)(Eℓ) (!) In presence of background this won’t work. Try to mitigate the effect of extreme cases:

Exclude highest/lowest x%, and/or Subdivide in sub-samples and average.

Also calculate masses using mean and s.d. of entire spectrum and compare.

Slepton 0.05 0.1 0.15 0.2 0.25 0.3 133 134 135 136 137 138 139 140 141 142 143

Mseen

Rel. freq.

From edges From full spect Mikael Berggren (DESY) SUSY property determination LCWS, Oct 2014 18 / 24

SLIDE 53

A bench-mark point: STC4 STC4 @ 500 GeV: Full speed - sleptons

Masses from ˜ e, ˜ µ in the continuum

In R[Emin, Emax], the MVB exists and is min(max)(Eℓ) (!) In presence of background this won’t work. Try to mitigate the effect of extreme cases:

Exclude highest/lowest x%, and/or Subdivide in sub-samples and average.

Also calculate masses using mean and s.d. of entire spectrum and compare.

Slepton 0.05 0.1 0.15 0.2 0.25 0.3 133 134 135 136 137 138 139 140 141 142 143

Mseen

Rel. freq.

From edges From full spect

Results from edges (ECMS=500, 500 fb−1 @ [+0.8,-0.3]) M˜ eR = 135.01 ± 0.19 GeV/c2 M˜

χ0

1 = 101.51 ± 0.14 GeV/c2

Results for full spectrum (ECMS=500, 500 fb−1 @ [+0.8,-0.3]) M˜ eR = 140.90 ± 0.33GeV/c2 M˜

χ0

1 = 107.61 ± 0.23 GeV/c2 Mikael Berggren (DESY) SUSY property determination LCWS, Oct 2014 18 / 24

SLIDE 54

A bench-mark point: STC4 STC4 @ 500 GeV: Full speed - sleptons

˜ µR threshold scan

From these spectra, we can estimate M˜ eR, M˜ µR and M˜

χ0

1 to <

0.2 GeV.

Mikael Berggren (DESY) SUSY property determination LCWS, Oct 2014 19 / 24

SLIDE 55

A bench-mark point: STC4 STC4 @ 500 GeV: Full speed - sleptons

˜ µR threshold scan

From these spectra, we can estimate M˜ eR, M˜ µR and M˜

χ0

1 to <

0.2 GeV. So: Next step is M˜ µR from threshold: 10 points, 10 fb−1/point. Luminosity ∝ ECMS, so this is ⇔ 170 fb−1 @ ECMS=500 GeV. Error on M˜ µR = 197 MeV ⇒ more studies needed to see if the continuum can match this.

Mikael Berggren (DESY) SUSY property determination LCWS, Oct 2014 19 / 24

SLIDE 56

A bench-mark point: STC4 STC4 @ 500 GeV: Full speed - sleptons

˜ µR threshold scan

From these spectra, we can estimate M˜ eR, M˜ µR and M˜

χ0

1 to <

0.2 GeV. So: Next step is M˜ µR from threshold: 10 points, 10 fb−1/point. Luminosity ∝ ECMS, so this is ⇔ 170 fb−1 @ ECMS=500 GeV. Error on M˜ µR = 197 MeV ⇒ more studies needed to see if the continuum can match this.

1 2 3 4 5 6 7 8 9 272 274 276 278 280 282 √s [GeV] σ(e+e-→µ ˜ Rµ ˜ R) [fb] data 10 fb-1 / point fit to data : δMµ ˜ = 197 MeV Mµ ˜ = 135.4 ± 0.2 GeV Mµ ˜ = 135.28 GeV Mikael Berggren (DESY) SUSY property determination LCWS, Oct 2014 19 / 24

SLIDE 57

A bench-mark point: STC4 STC4 @ 500 GeV: Full speed - sleptons

˜ µR threshold scan

From these spectra, we can estimate M˜ eR, M˜ µR and M˜

χ0

1 to <

0.2 GeV. So: Next step is M˜ µR from threshold: 10 points, 10 fb−1/point. Luminosity ∝ ECMS, so this is ⇔ 170 fb−1 @ ECMS=500 GeV. Error on M˜ µR = 197 MeV ⇒ more studies needed to see if the continuum can match this.

1 2 3 4 5 6 7 8 9 272 274 276 278 280 282 √s [GeV] σ(e+e-→µ ˜ Rµ ˜ R) [fb] data 10 fb-1 / point fit to data : δMµ ˜ = 197 MeV Mµ ˜ = 135.4 ± 0.2 GeV Mµ ˜ = 135.28 GeV Mikael Berggren (DESY) SUSY property determination LCWS, Oct 2014 19 / 24

SLIDE 58

A bench-mark point: STC4 STC4 @ 500 GeV: Full speed - ˜ τ1 and DM

STC4 sleptons @ 500 GeV:˜ τ1

Selections for ˜ τ1: Correct charge. PT wrt. beam and one τ wrt the other. Mjet < Mτ Evis < 120 GeV,Mvis ∈ [20, 87] GeV. Cuts on polar angle and angle between leptons. Little energy below 30 deg, or not in τ-jet. At least one τ-jet should be hadronic. Anti-γγ likelihood.

100 200 300 400 500 600 10 20 30 40 50 60 70

Ejet (GeV) Jets/1 GeV

Mikael Berggren (DESY) SUSY property determination LCWS, Oct 2014 20 / 24

SLIDE 59

A bench-mark point: STC4 STC4 @ 500 GeV: Full speed - ˜ τ1 and DM

Fitting the ˜ τ mass from end-point (SPS1a’)

Results for old analysis of SPS1a’ (See Phys.Rev.D82:055016,2010). Only the upper end-point is relevant. Background subtraction:

˜ τ1: Important SUSY background,but region above 45 GeV is signal free. Fit exponential and extrapolate. ˜ τ2: ∼ no SUSY background above 45 GeV. Take background from SM-only simulation and fit exponential.

Fit line to (data-background fit).

Mikael Berggren (DESY) SUSY property determination LCWS, Oct 2014 21 / 24

SLIDE 60

A bench-mark point: STC4 STC4 @ 500 GeV: Full speed - ˜ τ1 and DM

Fitting the ˜ τ mass from end-point (SPS1a’)

Results for old analysis of SPS1a’ (See Phys.Rev.D82:055016,2010). Only the upper end-point is relevant. Background subtraction:

˜ τ1: Important SUSY background,but region above 45 GeV is signal free. Fit exponential and extrapolate. ˜ τ2: ∼ no SUSY background above 45 GeV. Take background from SM-only simulation and fit exponential.

Fit line to (data-background fit).

[GeV]

jet

E 20 40 60 jets/0.7 Gev 1 10

2

10

3

10 Mikael Berggren (DESY) SUSY property determination LCWS, Oct 2014 21 / 24

SLIDE 61

A bench-mark point: STC4 STC4 @ 500 GeV: Full speed - ˜ τ1 and DM

Fitting the ˜ τ mass from end-point (SPS1a’)

Results for old analysis of SPS1a’ (See Phys.Rev.D82:055016,2010). Only the upper end-point is relevant. Background subtraction:

˜ τ1: Important SUSY background,but region above 45 GeV is signal free. Fit exponential and extrapolate. ˜ τ2: ∼ no SUSY background above 45 GeV. Take background from SM-only simulation and fit exponential.

Fit line to (data-background fit).

[GeV]

jet

E 50 100 150 jets/1.8 GeV 200 400 600 800

Mikael Berggren (DESY) SUSY property determination LCWS, Oct 2014 21 / 24

SLIDE 62

A bench-mark point: STC4 STC4 @ 500 GeV: Full speed - ˜ τ1 and DM

Fitting the ˜ τ mass from end-point (SPS1a’)

Results for old analysis of SPS1a’ (See Phys.Rev.D82:055016,2010). Only the upper end-point is relevant. Background subtraction:

˜ τ1: Important SUSY background,but region above 45 GeV is signal free. Fit exponential and extrapolate. ˜ τ2: ∼ no SUSY background above 45 GeV. Take background from SM-only simulation and fit exponential.

Fit line to (data-background fit).

[GeV]

jet

E 50 100 150 jets/1.8 GeV 200 400 600 800

Mikael Berggren (DESY) SUSY property determination LCWS, Oct 2014 21 / 24

SLIDE 63

A bench-mark point: STC4 STC4 @ 500 GeV: Full speed - ˜ τ1 and DM

Fitting the ˜ τ mass from end-point (SPS1a’)

Results for old analysis of SPS1a’ (See Phys.Rev.D82:055016,2010). Only the upper end-point is relevant. Background subtraction:

˜ τ1: Important SUSY background,but region above 45 GeV is signal free. Fit exponential and extrapolate. ˜ τ2: ∼ no SUSY background above 45 GeV. Take background from SM-only simulation and fit exponential.

Fit line to (data-background fit).

[GeV]

jet

E 50 100 150 jets/1.8 GeV 200 400 600 800

Results for ˜ τ1 M˜ τ1 = 107.73+0.03

−0.05GeV/c2 ⊕ 1.3∆(M˜ χ0

1) The error from M˜

χ0

1 largely

dominates Results for ˜ τ2 M˜ τ2 = 183+11

−5 GeV/c2 ⊕ 18∆(M˜ χ0

1) The error from the endpoint largely

dominates

Mikael Berggren (DESY) SUSY property determination LCWS, Oct 2014 21 / 24

SLIDE 64

A bench-mark point: STC4 STC4 @ 500 GeV: Full speed - ˜ τ1 and DM

Fitting the ˜ τ mass from end-point (SPS1a’)

Results for old analysis of SPS1a’ (See Phys.Rev.D82:055016,2010). Only the upper end-point is relevant. Background subtraction:

˜ τ1: Important SUSY background,but region above 45 GeV is signal free. Fit exponential and extrapolate. ˜ τ2: ∼ no SUSY background above 45 GeV. Take background from SM-only simulation and fit exponential.

Fit line to (data-background fit).

[GeV]

jet

E 50 100 150 jets/1.8 GeV 200 400 600 800

Results from cross-section for ˜ τ1 ∆(Nsignal)/Nsignal = 3.1% → ∆(M˜ τ1) = 3.2GeV/c2 Results from cross-section for ˜ τ2 ∆(Nsignal)/Nsignal = 4.2% → ∆(M˜ τ2) = 3.6GeV/c2 End-point + Cross-section → ∆(M˜

χ0

1) = 1.7GeV/c2 Mikael Berggren (DESY) SUSY property determination LCWS, Oct 2014 21 / 24

SLIDE 65

A bench-mark point: STC4 STC4 @ 500 GeV: Full speed - ˜ τ1 and DM

Fitting the ˜ τ mass from end-point (SPS1a’)

Results for old analysis of SPS1a’ (See Phys.Rev.D82:055016,2010). Only the upper end-point is relevant. Background subtraction:

˜ τ1: Important SUSY background,but region above 45 GeV is signal free. Fit exponential and extrapolate. ˜ τ2: ∼ no SUSY background above 45 GeV. Take background from SM-only simulation and fit exponential.

Fit line to (data-background fit).

[GeV]

jet

E 50 100 150 jets/1.8 GeV 200 400 600 800

Also: τ polarisation in ˜ τ1 decays ∆(Pτ)/Pτ = 9 %.

Mikael Berggren (DESY) SUSY property determination LCWS, Oct 2014 21 / 24

SLIDE 66

A bench-mark point: STC4 STC4 @ 500 GeV: Full speed - ˜ τ1 and DM

Fitting masses from cascades (SPS1a’)

Nice channel: e+e− →˜ χ0

2 ˜

χ0

2,

˜ χ0

2 → ˜

µRµ or → ˜ eRe) BR= few %. Can be fully kinematically constrained at ILC ⇒ even lower uncertainties on M˜ µR and M˜ eR: ∼ 25 MeV. Also decays to ˜ τ1τ can be constrained as good as, or better than a threshold scan.

Mikael Berggren (DESY) SUSY property determination LCWS, Oct 2014 22 / 24

SLIDE 67

A bench-mark point: STC4 STC4 @ 500 GeV: Full speed - ˜ τ1 and DM

Fitting masses from cascades (SPS1a’)

Nice channel: e+e− →˜ χ0

2 ˜

χ0

2,

˜ χ0

2 → ˜

µRµ or → ˜ eRe) BR= few %. Can be fully kinematically constrained at ILC ⇒ even lower uncertainties on M˜ µR and M˜ eR: ∼ 25 MeV. Also decays to ˜ τ1τ can be constrained as good as, or better than a threshold scan.

25 50 75 100 125 150 175 200 100 120 140 160 180 200

Mslepton [GeV/c2]

Mikael Berggren (DESY) SUSY property determination LCWS, Oct 2014 22 / 24

SLIDE 68

A bench-mark point: STC4 STC4 @ 500 GeV: Full speed - ˜ τ1 and DM

Fitting masses from cascades (SPS1a’)

Nice channel: e+e− →˜ χ0

2 ˜

χ0

2,

˜ χ0

2 → ˜

µRµ or → ˜ eRe) BR= few %. Can be fully kinematically constrained at ILC ⇒ even lower uncertainties on M˜ µR and M˜ eR: ∼ 25 MeV. Also decays to ˜ τ1τ can be constrained as good as, or better than a threshold scan.

5 10 15 20 25 30 144.2 144.3 144.4 144.5 144.6 144.7 144.8 144.9 145 145.1 145.2 Constant 25.56 Mean 144.7 Sigma 0.8335E-01

Mslepton [GeV/c2]

Mikael Berggren (DESY) SUSY property determination LCWS, Oct 2014 22 / 24

SLIDE 69

A bench-mark point: STC4 STC4 @ 500 GeV: Full speed - ˜ τ1 and DM

Fitting masses from cascades (SPS1a’)

Nice channel: e+e− →˜ χ0

2 ˜

χ0

2,

˜ χ0

2 → ˜

µRµ or → ˜ eRe) BR= few %. Can be fully kinematically constrained at ILC ⇒ even lower uncertainties on M˜ µR and M˜ eR: ∼ 25 MeV. Also decays to ˜ τ1τ can be constrained as good as, or better than a threshold scan.

2.5 5 7.5 10 12.5 15 17.5 20 22.5 100 120 140 160 180 200

Mstau [GeV/c2]

f)

Mikael Berggren (DESY) SUSY property determination LCWS, Oct 2014 22 / 24

SLIDE 70

A bench-mark point: STC4 STC4 @ 500 GeV: Full speed - ˜ τ1 and DM

STC4 sleptons @ 500 GeV:˜ τ1 and DM

In ˜ τ-coannihilation scenarios, Precise determination of the ˜ τ sector ⇒ Predict relic density with sufficient precision ⇒ Test whether the ˜ χ0

1 is indeed

the dominant DM. Studied by Fittino (similar model, with ˜ χ0

1 and ˜

τ1 identical to STC4). Fit with 18 free parameters, and predict ΩCDMh2

Mikael Berggren (DESY) SUSY property determination LCWS, Oct 2014 23 / 24

SLIDE 71

A bench-mark point: STC4 STC4 @ 500 GeV: Full speed - ˜ τ1 and DM

STC4 sleptons @ 500 GeV:˜ τ1 and DM

In ˜ τ-coannihilation scenarios, Precise determination of the ˜ τ sector ⇒ Predict relic density with sufficient precision ⇒ Test whether the ˜ χ0

1 is indeed

the dominant DM. Studied by Fittino (similar model, with ˜ χ0

1 and ˜

τ1 identical to STC4). Fit with 18 free parameters, and predict ΩCDMh2

Mikael Berggren (DESY) SUSY property determination LCWS, Oct 2014 23 / 24

SLIDE 72

A bench-mark point: STC4 STC4 @ 500 GeV: Full speed - ˜ τ1 and DM

STC4 sleptons @ 500 GeV:˜ τ1 and DM

In ˜ τ-coannihilation scenarios, Precise determination of the ˜ τ sector ⇒ Predict relic density with sufficient precision ⇒ Test whether the ˜ χ0

1 is indeed

the dominant DM. Studied by Fittino (similar model, with ˜ χ0

1 and ˜

τ1 identical to STC4). Fit with 18 free parameters, and predict ΩCDMh2

Mikael Berggren (DESY) SUSY property determination LCWS, Oct 2014 23 / 24

SLIDE 73

A bench-mark point: STC4 STC4 @ 500 GeV: Full speed - ˜ τ1 and DM

STC4 sleptons @ 500 GeV:˜ τ1 and DM

In ˜ τ-coannihilation scenarios, Precise determination of the ˜ τ sector ⇒ Predict relic density with sufficient precision ⇒ Test whether the ˜ χ0

1 is indeed

the dominant DM. Studied by Fittino (similar model, with ˜ χ0

1 and ˜

τ1 identical to STC4). Fit with 18 free parameters, and predict ΩCDMh2

Mikael Berggren (DESY) SUSY property determination LCWS, Oct 2014 23 / 24

SLIDE 74

A bench-mark point: STC4 STC4 @ 500 GeV: Full speed - ˜ τ1 and DM

STC4 sleptons @ 500 GeV:˜ τ1 and DM

In ˜ τ-coannihilation scenarios, Precise determination of the ˜ τ sector ⇒ Predict relic density with sufficient precision ⇒ Test whether the ˜ χ0

1 is indeed

the dominant DM. Studied by Fittino (similar model, with ˜ χ0

1 and ˜

τ1 identical to STC4). Fit with 18 free parameters, and predict ΩCDMh2

(measured)

2

h

DM

(predicted)/

2

h

DM

0.2

0.4 0.6 0.8 1 1.2 Toy fits 50 100 150 200 250 300 350 400 450

0.00098 ± = 0.99995

LE+LHC+ILC mSUGRA:

0.00208 ± = 1.00009

LE+LHC+ILC MSSM18:

0.07131 ± = 0.97286

LE+LHC MSSM18:
1

±

2

h

DM

WMAP
1

±

2

h

DM

Planck

0.992 0.994 0.996 0.998 1 1.002 1.004 1.006 1.008 20 40 60 80 100 120

Mikael Berggren (DESY) SUSY property determination LCWS, Oct 2014 23 / 24

SLIDE 75

Outlook & Conclusions

If STCx is realised, We could have extremely precise information on DM:

Is it SUSY ? Is it only SUSY?

In any case: would open up, not only precission SUSY at ILC (“ILC is the LEP of SUSY”), but also new branch of cosmology... To get extremely precise information: Specific reconstruction methods for e, µ, τ and bosinos (comming). Make a coherent study of all channels, at all ECMS stages.

Also channels not studied in SPS1a’ Exploit more complex decay cascades.

Revisit the many-parameter fit w/ fittino.

Mikael Berggren (DESY) SUSY property determination LCWS, Oct 2014 24 / 24

SLIDE 76

Outlook & Conclusions

If STCx is realised, We could have extremely precise information on DM:

Is it SUSY ? Is it only SUSY?

In any case: would open up, not only precission SUSY at ILC (“ILC is the LEP of SUSY”), but also new branch of cosmology... To get extremely precise information: Specific reconstruction methods for e, µ, τ and bosinos (comming). Make a coherent study of all channels, at all ECMS stages.

Also channels not studied in SPS1a’ Exploit more complex decay cascades.

Revisit the many-parameter fit w/ fittino.

Mikael Berggren (DESY) SUSY property determination LCWS, Oct 2014 24 / 24

SLIDE 77

Outlook & Conclusions

If STCx is realised, We could have extremely precise information on DM:

Is it SUSY ? Is it only SUSY?

In any case: would open up, not only precission SUSY at ILC (“ILC is the LEP of SUSY”), but also new branch of cosmology... To get extremely precise information: Specific reconstruction methods for e, µ, τ and bosinos (comming). Make a coherent study of all channels, at all ECMS stages.

Also channels not studied in SPS1a’ Exploit more complex decay cascades.

Revisit the many-parameter fit w/ fittino.

Mikael Berggren (DESY) SUSY property determination LCWS, Oct 2014 24 / 24

SLIDE 78

Outlook & Conclusions

If STCx is realised, We could have extremely precise information on DM:

Is it SUSY ? Is it only SUSY?

In any case: would open up, not only precission SUSY at ILC (“ILC is the LEP of SUSY”), but also new branch of cosmology... To get extremely precise information: Specific reconstruction methods for e, µ, τ and bosinos (comming). Make a coherent study of all channels, at all ECMS stages.

Also channels not studied in SPS1a’ Exploit more complex decay cascades.

Revisit the many-parameter fit w/ fittino.

Mikael Berggren (DESY) SUSY property determination LCWS, Oct 2014 24 / 24

SLIDE 79

Outlook & Conclusions

If STCx is realised, We could have extremely precise information on DM:

Is it SUSY ? Is it only SUSY?

In any case: would open up, not only precission SUSY at ILC (“ILC is the LEP of SUSY”), but also new branch of cosmology... To get extremely precise information: Specific reconstruction methods for e, µ, τ and bosinos (comming). Make a coherent study of all channels, at all ECMS stages.

Also channels not studied in SPS1a’ Exploit more complex decay cascades.

Revisit the many-parameter fit w/ fittino.

Mikael Berggren (DESY) SUSY property determination LCWS, Oct 2014 24 / 24

SLIDE 80

Outlook & Conclusions

If STCx is realised, We could have extremely precise information on DM:

Is it SUSY ? Is it only SUSY?

In any case: would open up, not only precission SUSY at ILC (“ILC is the LEP of SUSY”), but also new branch of cosmology... To get extremely precise information: Specific reconstruction methods for e, µ, τ and bosinos (comming). Make a coherent study of all channels, at all ECMS stages.

Also channels not studied in SPS1a’ Exploit more complex decay cascades.

Revisit the many-parameter fit w/ fittino.

Mikael Berggren (DESY) SUSY property determination LCWS, Oct 2014 24 / 24

SLIDE 81

Outlook & Conclusions

If STCx is realised, We could have extremely precise information on DM:

Is it SUSY ? Is it only SUSY?

In any case: would open up, not only precission SUSY at ILC (“ILC is the LEP of SUSY”), but also new branch of cosmology... To get extremely precise information: Specific reconstruction methods for e, µ, τ and bosinos (comming). Make a coherent study of all channels, at all ECMS stages.

Also channels not studied in SPS1a’ Exploit more complex decay cascades.

Revisit the many-parameter fit w/ fittino.

Mikael Berggren (DESY) SUSY property determination LCWS, Oct 2014 24 / 24

SLIDE 82

Outlook & Conclusions

If STCx is realised, We could have extremely precise information on DM:

Is it SUSY ? Is it only SUSY?

In any case: would open up, not only precission SUSY at ILC (“ILC is the LEP of SUSY”), but also new branch of cosmology... To get extremely precise information: Specific reconstruction methods for e, µ, τ and bosinos (comming). Make a coherent study of all channels, at all ECMS stages.

Also channels not studied in SPS1a’ Exploit more complex decay cascades.

Revisit the many-parameter fit w/ fittino.

Mikael Berggren (DESY) SUSY property determination LCWS, Oct 2014 24 / 24

SLIDE 83

Outlook & Conclusions

Thank You !

SLIDE 84

Backup

BACKUP

BACKUP SLIDES

SLIDE 85

Backup

Observables: Pair-production, two-body decay (less text)

So, there are two SUSY parameters, and two independent

bservables in the spectrum.

Any pair of observables can be chosen, edges, average, standard deviation, width, ... Which choice is the best depends on the situation. Just a bit of algebra to extract the two SUSY masses. Note that if Ebeam >> MX, there is just one observable (low edge becomes 0, width becomes average/2), so one should not operate too far above threshold ! Note that there are two decays in each event: two measurements per event. Also note that there are not enough measurements to make a constrained fit, even assuming that the two SUSY particles in the two decays are the same: (2 × 4 unknown components of 4-momentum (=8)) - ( total E and p conservation (=4) + 2 equal-mass constraints) = 2 remaining unknowns.

SLIDE 86

Backup

Observables: Pair-production, two-body decay (less text)

So, there are two SUSY parameters, and two independent

bservables in the spectrum.

Any pair of observables can be chosen, edges, average, standard deviation, width, ... Which choice is the best depends on the situation. Just a bit of algebra to extract the two SUSY masses. Note that if Ebeam >> MX, there is just one observable (low edge becomes 0, width becomes average/2), so one should not operate too far above threshold ! Note that there are two decays in each event: two measurements per event. Also note that there are not enough measurements to make a constrained fit, even assuming that the two SUSY particles in the two decays are the same: (2 × 4 unknown components of 4-momentum (=8)) - ( total E and p conservation (=4) + 2 equal-mass constraints) = 2 remaining unknowns.

SLIDE 87

Backup

Observables: Pair-production, two-body decay (less text)

So, there are two SUSY parameters, and two independent

bservables in the spectrum.

Any pair of observables can be chosen, edges, average, standard deviation, width, ... Which choice is the best depends on the situation. Just a bit of algebra to extract the two SUSY masses. Note that if Ebeam >> MX, there is just one observable (low edge becomes 0, width becomes average/2), so one should not operate too far above threshold ! Note that there are two decays in each event: two measurements per event. Also note that there are not enough measurements to make a constrained fit, even assuming that the two SUSY particles in the two decays are the same: (2 × 4 unknown components of 4-momentum (=8)) - ( total E and p conservation (=4) + 2 equal-mass constraints) = 2 remaining unknowns.

SLIDE 88

Backup

Observables: Pair-production, two-body decay (less text)

So, there are two SUSY parameters, and two independent

bservables in the spectrum.

Any pair of observables can be chosen, edges, average, standard deviation, width, ... Which choice is the best depends on the situation. Just a bit of algebra to extract the two SUSY masses. Note that if Ebeam >> MX, there is just one observable (low edge becomes 0, width becomes average/2), so one should not operate too far above threshold ! Note that there are two decays in each event: two measurements per event. Also note that there are not enough measurements to make a constrained fit, even assuming that the two SUSY particles in the two decays are the same: (2 × 4 unknown components of 4-momentum (=8)) - ( total E and p conservation (=4) + 2 equal-mass constraints) = 2 remaining unknowns.

SLIDE 89

Backup

Observables: Pair-production, two-body decay

However: If the masses are known from other measurements, there are enough constraints. Then the events can be completely reconstructed ... ... and the angular distributions both in production and decay can be measured. From this the spins can be determined, which is essential to determine that what we are seeing is SUSY. Furthermore: Looking at more complicated decays, such as cascade decays, there are enough constraints if some (but not all) masses are known. Allows to reconstruct eg. the slepton mass in ˜ χ0

2 → ˜

ℓℓ → ℓℓ˜ χ0

1 if

chargino and LSP masses are known. Order-of-magnitude better mass resolution.

SLIDE 90

Backup

Observables: Pair-production, two-body decay

However: If the masses are known from other measurements, there are enough constraints. Then the events can be completely reconstructed ... ... and the angular distributions both in production and decay can be measured. From this the spins can be determined, which is essential to determine that what we are seeing is SUSY. Furthermore: Looking at more complicated decays, such as cascade decays, there are enough constraints if some (but not all) masses are known. Allows to reconstruct eg. the slepton mass in ˜ χ0

2 → ˜

ℓℓ → ℓℓ˜ χ0

1 if

chargino and LSP masses are known. Order-of-magnitude better mass resolution.

SLIDE 91

Backup

Observables: Pair-production, two-body decay

However: If the masses are known from other measurements, there are enough constraints. Then the events can be completely reconstructed ... ... and the angular distributions both in production and decay can be measured. From this the spins can be determined, which is essential to determine that what we are seeing is SUSY. Furthermore: Looking at more complicated decays, such as cascade decays, there are enough constraints if some (but not all) masses are known. Allows to reconstruct eg. the slepton mass in ˜ χ0

2 → ˜

ℓℓ → ℓℓ˜ χ0

1 if

chargino and LSP masses are known. Order-of-magnitude better mass resolution.

25 50 75 100 125 150 175 200 100 120 140 160 180 200

Mslepton [GeV/c2]

d)

SLIDE 92

Backup

Observables

But this is not all ! The cross-section in e+e− →XX close to threshold depends both

n coupling, spin and kinematics (= β).

The distribution of the angle between the two SM-particles depends on β, in a complicated, but calculable way. The cross-section is different for L and R SUSY particles. So checking how much the cross-section changes when switching beam-polarisations measures mixing. Measure the helicity of the SM particle → properties of the particles in the decay, ie. in addition to the produced X, also the invisible U. In one case this is possible: In ˜ τ → τ ˜ χ0

1 → Xντ ˜

χ0

1.

SLIDE 93

Backup

Observables

But this is not all ! The cross-section in e+e− →XX close to threshold depends both

n coupling, spin and kinematics (= β).

The distribution of the angle between the two SM-particles depends on β, in a complicated, but calculable way. The cross-section is different for L and R SUSY particles. So checking how much the cross-section changes when switching beam-polarisations measures mixing. Measure the helicity of the SM particle → properties of the particles in the decay, ie. in addition to the produced X, also the invisible U. In one case this is possible: In ˜ τ → τ ˜ χ0

1 → Xντ ˜

χ0

1.

SLIDE 94

Backup

Observables

But this is not all ! The cross-section in e+e− →XX close to threshold depends both

n coupling, spin and kinematics (= β).

The distribution of the angle between the two SM-particles depends on β, in a complicated, but calculable way. The cross-section is different for L and R SUSY particles. So checking how much the cross-section changes when switching beam-polarisations measures mixing. Measure the helicity of the SM particle → properties of the particles in the decay, ie. in addition to the produced X, also the invisible U. In one case this is possible: In ˜ τ → τ ˜ χ0

1 → Xντ ˜

χ0

1.

SLIDE 95

Backup

Observables

But this is not all ! The cross-section in e+e− →XX close to threshold depends both

n coupling, spin and kinematics (= β).

The distribution of the angle between the two SM-particles depends on β, in a complicated, but calculable way. The cross-section is different for L and R SUSY particles. So checking how much the cross-section changes when switching beam-polarisations measures mixing. Measure the helicity of the SM particle → properties of the particles in the decay, ie. in addition to the produced X, also the invisible U. In one case this is possible: In ˜ τ → τ ˜ χ0

1 → Xντ ˜

χ0

1.

SLIDE 96

Backup ˜ τ channels

Extracting the ˜ τ properties

See Phys.Rev.D82:055016,2010 Use polarisation (0.8,-0.22) to reduce bosino background. From decay kinematics: M˜

τ from M˜ χ0

1 and end-point of spectrum = Eτ,max.

Other end-point hidden in γγ background:Must get M˜

χ0

1 from other

sources. (˜

µ , ˜ e, ...) From cross-section: σ˜ τ = A(θ˜ τ , Pbeam) × β3/s, so M˜

τ = Ebeam

1 − (σs/A)2/3: no M˜

χ0

1 !

From decay spectra: Pτ from exclusive decay-mode(s): handle on mixing angles θ˜ τ and θ˜ χ0

1

SLIDE 97

Backup ˜ τ channels

Topology selection

Take over SPS1a’ ˜ τ analysis principle ˜ ℓ properties: Only two particles (possibly τ:s:s) in the final state. Large missing energy and momentum. High Acolinearity, with little correlation to the energy of the τ decay-products. Central production. No forward-backward asymmetry. + anti γγ cuts. Select this by: Exactly two jets. Nch < 10 Vanishing total charge. Charge of each jet = ± 1, Mjet < 2.5 GeV/c2, Evis significantly less than ECMS. Mmiss significantly less than MCMS. No particle with momentum close to Ebeam.

SLIDE 98

Backup ˜ τ channels

Topology selection

Take over SPS1a’ ˜ τ analysis principle ˜ ℓ properties: Only two particles (possibly τ:s:s) in the final state. Large missing energy and momentum. High Acolinearity, with little correlation to the energy of the τ decay-products. Central production. No forward-backward asymmetry. + anti γγ cuts. Select this by: Exactly two jets. Nch < 10 Vanishing total charge. Charge of each jet = ± 1, Mjet < 2.5 GeV/c2, Evis significantly less than ECMS. Mmiss significantly less than MCMS. No particle with momentum close to Ebeam.

SLIDE 99

Backup ˜ τ channels

Topology selection

Take over SPS1a’ ˜ τ analysis principle ˜ ℓ properties: Only two particles (possibly τ:s:s) in the final state. Large missing energy and momentum. High Acolinearity, with little correlation to the energy of the τ decay-products. Central production. No forward-backward asymmetry. + anti γγ cuts. Select this by: Exactly two jets. Nch < 10 Vanishing total charge. Charge of each jet = ± 1, Mjet < 2.5 GeV/c2, Evis significantly less than ECMS. Mmiss significantly less than MCMS. No particle with momentum close to Ebeam.

SLIDE 100

Backup ˜ τ channels

˜ τ1and ˜ τ2further selections

˜ τ1:

(Ejet1 + Ejet2) sin θacop < 30 GeV.

˜ τ2:

Other side jet not e or µ Most energetic jet not e or µ Cut on Signal-SM LR of f(qjet1 cos θjet1, qjet2 cos θjet2)

Efficiency 15 (22) %

[GeV]

to 2nd jet

pt

10 20 30

[GeV]

to 1st jet

pt

10 20 30 b)

SLIDE 101

Backup ˜ τ channels

˜ τ1and ˜ τ2further selections

˜ τ1:

(Ejet1 + Ejet2) sin θacop < 30 GeV.

˜ τ2:

Other side jet not e or µ Most energetic jet not e or µ Cut on Signal-SM LR of f(qjet1 cos θjet1, qjet2 cos θjet2)

Efficiency 15 (22) %

[GeV]

to 2nd jet

pt

10 20 30

[GeV]

to 1st jet

pt

10 20 30

a)

0.5 1 1.5 2 2.5 3 3.5 4

SLIDE 102

Backup ˜ τ channels

˜ τ1and ˜ τ2further selections

˜ τ1:

(Ejet1 + Ejet2) sin θacop < 30 GeV.

˜ τ2:

Other side jet not e or µ Most energetic jet not e or µ Cut on Signal-SM LR of f(qjet1 cos θjet1, qjet2 cos θjet2)

Efficiency 15 (22) %

b)

),jet 1 θ qcos(

−1 −0.5 0.5 1

),jet 2 θ qcos(

−1 −0.5 0.5 1 2 4 6 8 10 12

SLIDE 103

Backup ˜ τ channels

˜ τ1and ˜ τ2further selections

˜ τ1:

(Ejet1 + Ejet2) sin θacop < 30 GeV.

˜ τ2:

Other side jet not e or µ Most energetic jet not e or µ Cut on Signal-SM LR of f(qjet1 cos θjet1, qjet2 cos θjet2)

Efficiency 15 (22) %

a)

),jet 1 θ qcos(

−1 −0.5 0.5 1

),jet 2 θ qcos(

−1 −0.5 0.5 1 20 40 60 80 100 120 140 160 180

SLIDE 104

Backup ˜ τ channels

˜ τ1and ˜ τ2further selections

˜ τ1:

(Ejet1 + Ejet2) sin θacop < 30 GeV.

˜ τ2:

Other side jet not e or µ Most energetic jet not e or µ Cut on Signal-SM LR of f(qjet1 cos θjet1, qjet2 cos θjet2)

Efficiency 15 (22) % Likelihood ratio

0.2 0.4 0.6 0.8 1 1.2 1.4

events

100 200 300

d)

SLIDE 105

Backup ˜ τ channels

˜ τ1and ˜ τ2further selections

˜ τ1:

(Ejet1 + Ejet2) sin θacop < 30 GeV.

˜ τ2:

Other side jet not e or µ Most energetic jet not e or µ Cut on Signal-SM LR of f(qjet1 cos θjet1, qjet2 cos θjet2)

Efficiency 15 (22) %

c)

),jet 1 θ qcos(

−1 −0.5 0.5 1

),jet 2 θ qcos(

−1 −0.5 0.5 1

SLIDE 106

Backup ˜ τ channels

˜ τ1and ˜ τ2further selections

˜ τ1:

(Ejet1 + Ejet2) sin θacop < 30 GeV.

˜ τ2:

Other side jet not e or µ Most energetic jet not e or µ Cut on Signal-SM LR of f(qjet1 cos θjet1, qjet2 cos θjet2)

Efficiency 15 (22) %

SLIDE 107

Backup Channels with µ:s

˜ µ channels

Use “normal” polarisation (-0.8,0.22). ˜ µL˜ µL → µµ˜ χ0

1 ˜

χ0

1

˜ χ0

1 ˜

χ0

2 → µ˜

µR ˜ χ0

1 → µµ˜

χ0

1 ˜

χ0

1

Momentum of µ:s Emiss Mµµ

energy [GeV] µ 50 100 150 200 250 )

1

Yield (500 fb 2000 4000 6000 8000 10000 12000

1) × Standard Model Background ( 10) × SUSY background( 100) × (

1

χ µ µ → µ µ ∼ →

2

χ

1

χ →

e

+

e 10) × (

1

χ µ

1

χ µ →

L

µ

∼

+ L

µ ∼ →

e

+

e

SLIDE 108

Backup Channels with µ:s

˜ µ channels

Use “normal” polarisation (-0.8,0.22). ˜ µL˜ µL → µµ˜ χ0

1 ˜

χ0

1

˜ χ0

1 ˜

χ0

2 → µ˜

µR ˜ χ0

1 → µµ˜

χ0

1 ˜

χ0

1

Momentum of µ:s Emiss Mµµ

[GeV]

miss

E 50 100 150 200 250 300 350 400 450 500 )

1

Yield (500 fb 1000 2000 3000 4000 5000 6000 7000 8000 9000

1) × Standard Model Background ( 10) × SUSY background( 100) × (

1

χ µ µ → µ µ ∼ →

2

χ

1

χ →

e

+

e 10) × (

1

χ µ

1

χ µ →

L

µ

∼

+ L

µ ∼ →

e

+

e

SLIDE 109

Backup Channels with µ:s

˜ µ channels

Use “normal” polarisation (-0.8,0.22). ˜ µL˜ µL → µµ˜ χ0

1 ˜

χ0

1

˜ χ0

1 ˜

χ0

2 → µ˜

µR ˜ χ0

1 → µµ˜

χ0

1 ˜

χ0

1

Momentum of µ:s Emiss Mµµ

[GeV]

µ µ

m 50 100 150 200 250 300 350 400 450 500 )

1

Yield (500 fb 2000 4000 6000 8000 10000 12000 14000 16000

1) × Standard Model Background ( 10) × SUSY background( 100) × (

1

χ µ µ → µ µ ∼ →

2

χ

1

χ →

e

+

e 10) × (

1

χ µ

1

χ µ →

L

µ

∼

+ L

µ ∼ →

e

+

e

SLIDE 110

Backup Channels with µ:s

˜ µL˜ µL

Selections θmissingp ∈ [0.1π; 0.9π] Emiss ∈ [200, 430]GeV Mµµ / ∈ [80.100]GeV and > 30 GeV/c2 Masses from edges. Beam-energy spread dominates error. ∆(M˜

χ0

1) = 920MeV/c2

∆(M˜ µL) = 100MeV/c2

/ ndf = 8.39 / 14

2

χ

Amplitude(A) 3.51 ± 43.97 Edge (E) 0.2 ± 151.5 Slope (S) 0.1233 ± 0.3775 Background (B) 1.53 ± 15.17

energy [GeV] µ 146 148 150 152 154 156 )

1

Yield (500 fb 10 20 30 40 50 60 70 / ndf = 8.39 / 14

2

χ

Amplitude(A) 3.51 ± 43.97 Edge (E) 0.2 ± 151.5 Slope (S) 0.1233 ± 0.3775 Background (B) 1.53 ± 15.17 B+A/(1+exp((x-E)/S)) Signal / ndf

2

χ 29.73 / 26 Amplitude(A) 2.94 ± 48.92 Edge (E) 0.04 ± 32.25 Slope (S) 1.10605 ± 0.03249 Background (B) 1.65 ± 38.21

energy [GeV] µ 26 28 30 32 34 36 38 40 42 )

1

Yield (500 fb 20 30 40 50 60 70 80 90 100 110

/ ndf

2

χ 29.73 / 26 Amplitude(A) 2.94 ± 48.92 Edge (E) 0.04 ± 32.25 Slope (S) 1.10605 ± 0.03249 Background (B) 1.65 ± 38.21 B+A/(1+exp(x-E)/S) signal

SLIDE 111

Backup Channels with µ:s

˜ µL˜ µL

Selections θmissingp ∈ [0.1π; 0.9π] Emiss ∈ [200, 430]GeV Mµµ / ∈ [80.100]GeV and > 30 GeV/c2 Masses from edges. Beam-energy spread dominates error. ∆(M˜

χ0

1) = 920MeV/c2

∆(M˜ µL) = 100MeV/c2

/ ndf = 8.39 / 14

2

χ

Amplitude(A) 3.51 ± 43.97 Edge (E) 0.2 ± 151.5 Slope (S) 0.1233 ± 0.3775 Background (B) 1.53 ± 15.17

energy [GeV] µ 146 148 150 152 154 156 )

1

Yield (500 fb 10 20 30 40 50 60 70 / ndf = 8.39 / 14

2

χ

Amplitude(A) 3.51 ± 43.97 Edge (E) 0.2 ± 151.5 Slope (S) 0.1233 ± 0.3775 Background (B) 1.53 ± 15.17 B+A/(1+exp((x-E)/S)) Signal / ndf

2

χ 29.73 / 26 Amplitude(A) 2.94 ± 48.92 Edge (E) 0.04 ± 32.25 Slope (S) 1.10605 ± 0.03249 Background (B) 1.65 ± 38.21

energy [GeV] µ 26 28 30 32 34 36 38 40 42 )

1

Yield (500 fb 20 30 40 50 60 70 80 90 100 110

/ ndf

2

χ 29.73 / 26 Amplitude(A) 2.94 ± 48.92 Edge (E) 0.04 ± 32.25 Slope (S) 1.10605 ± 0.03249 Background (B) 1.65 ± 38.21 B+A/(1+exp(x-E)/S) signal

SLIDE 112

Backup Channels with µ:s

˜ χ0

1 ˜

χ0

2

Selections θmissingp ∈ [0.2π; 0.8π] pTmiss > 40GeV/c β of µ system > 0.6. Emiss ∈ [355, 395]GeV Masses from edges. Beam-energy spread dominates error. ∆(M˜

χ0

2) = 1.38GeV/c2

Invariant Mass [GeV] 40 50 60 70 80 90 100 110 )

1

Yield (500 fb 100 200 300 400 500

Standard Model Background SUSY background

1

χ µ µ → µ µ ∼ →

2

χ Total signal / ndf = 20.57 / 26

2

χ

Background(B) 2.93 ± 55.22 Edge (E) 0.0 ± 82.5 Width (S) 0.402 ± 1.747 Signal Amplitude (A) 5.8 ± 47.1 Signal Tail (T) 0.0785 ± 0.2713 Background Exp (BE) 0.0647 ± 0.9554 Background Slope (BS) 5.61 ±

79.82

Invariant Mass [GeV] 40 50 60 70 80 90 )

1

Yield (500 fb 20 40 60 80 100 120 140

/ ndf = 20.57 / 26

2

χ

Background(B) 2.93 ± 55.22 Edge (E) 0.0 ± 82.5 Width (S) 0.402 ± 1.747 Signal Amplitude (A) 5.8 ± 47.1 Signal Tail (T) 0.0785 ± 0.2713 Background Exp (BE) 0.0647 ± 0.9554 Background Slope (BS) 5.61 ±

79.82

Standard Model Background SUSY background

1

χ µ µ → µ µ ∼ →

2

χ Total signal

SLIDE 113

Backup Channels with µ:s

˜ χ0

1 ˜

χ0

2

Selections θmissingp ∈ [0.2π; 0.8π] pTmiss > 40GeV/c β of µ system > 0.6. Emiss ∈ [355, 395]GeV Masses from edges. Beam-energy spread dominates error. ∆(M˜

χ0

2) = 1.38GeV/c2

Invariant Mass [GeV] 40 50 60 70 80 90 100 110 )

1

Yield (500 fb 100 200 300 400 500

Standard Model Background SUSY background

1

χ µ µ → µ µ ∼ →

2

χ Total signal / ndf = 20.57 / 26

2

χ

Background(B) 2.93 ± 55.22 Edge (E) 0.0 ± 82.5 Width (S) 0.402 ± 1.747 Signal Amplitude (A) 5.8 ± 47.1 Signal Tail (T) 0.0785 ± 0.2713 Background Exp (BE) 0.0647 ± 0.9554 Background Slope (BS) 5.61 ±

79.82

Invariant Mass [GeV] 40 50 60 70 80 90 )

1

Yield (500 fb 20 40 60 80 100 120 140

/ ndf = 20.57 / 26

2

χ

Background(B) 2.93 ± 55.22 Edge (E) 0.0 ± 82.5 Width (S) 0.402 ± 1.747 Signal Amplitude (A) 5.8 ± 47.1 Signal Tail (T) 0.0785 ± 0.2713 Background Exp (BE) 0.0647 ± 0.9554 Background Slope (BS) 5.61 ±

79.82

Standard Model Background SUSY background

1

χ µ µ → µ µ ∼ →

2

χ Total signal

SLIDE 114

Backup Channels with µ:s

˜ µR threshold scan

From these spectra, we can estimate M˜ eR, M˜ µR and M˜

χ0

1 to <

1 GeV.

SLIDE 115

Backup Channels with µ:s

˜ µR threshold scan

From these spectra, we can estimate M˜ eR, M˜ µR and M˜

χ0

1 to <

1 GeV. So: Next step is M˜ µR from threshold: 10 points, 10 fb−1/point. Luminousity ∝ ECMS, so this is ⇔ 170 fb−1 @ ECMS=500 GeV. Error on M˜ µR = 197 MeV

SLIDE 116

Backup Channels with µ:s

˜ µR threshold scan

From these spectra, we can estimate M˜ eR, M˜ µR and M˜

χ0

1 to <

1 GeV. So: Next step is M˜ µR from threshold: 10 points, 10 fb−1/point. Luminousity ∝ ECMS, so this is ⇔ 170 fb−1 @ ECMS=500 GeV. Error on M˜ µR = 197 MeV

1 2 3 4 5 6 7 8 9 272 274 276 278 280 282 √s [GeV] σ(e+e-→µ ˜ Rµ ˜ R) [fb] data 10 fb-1 / point fit to data : δMµ ˜ = 197 MeV Mµ ˜ = 135.4 ± 0.2 GeV Mµ ˜ = 135.28 GeV

SLIDE 117

Backup Channels with µ:s

˜ µR threshold scan

From these spectra, we can estimate M˜ eR, M˜ µR and M˜

χ0

1 to <

1 GeV. So: Next step is M˜ µR from threshold: 10 points, 10 fb−1/point. Luminousity ∝ ECMS, so this is ⇔ 170 fb−1 @ ECMS=500 GeV. Error on M˜ µR = 197 MeV

1 2 3 4 5 6 7 8 9 272 274 276 278 280 282 √s [GeV] σ(e+e-→µ ˜ Rµ ˜ R) [fb] data 10 fb-1 / point fit to data : δMµ ˜ = 197 MeV Mµ ˜ = 135.4 ± 0.2 GeV Mµ ˜ = 135.28 GeV