Neutralino Dark Matter and Bayesian Statistics Leszek Roszkowski - - PowerPoint PPT Presentation

Neutralino Dark Matter and Bayesian Statistics

Leszek Roszkowski Astro–Particle Theory and Cosmology Group Sheffield, England

with Roberto Ruiz de Austri and Roberto Trotta hep-ph/0602028 → JHEP06, hep-ph/0611173→ JHEP07 arXiv:0705.2012→ JHEP07 arXiv:0707.0622 (with R.R., R.T. and J. Silk) and arXiv:0809.3792 (with R.R., R.T., F . Feroz and M. Hobson) and in preparation with R.R, R.T, T. Varley and S. Tsai

new tool: SuperBayes package, available from www.superbayes.org

• L. Roszkowski, GGI, 9 Feb ’09 – p.1

Dark Matter Programme at GGI

• L. Roszkowski, GGI, 9 Feb ’09 – p.2

Dark Matter Programme at GGI

venue: Galileo Galilei Institute, Florence dates: May - June 2010

• rganizers: H. Baer, L. Covi,
• L. Roszkowski and P

. Ullio

• L. Roszkowski, GGI, 9 Feb ’09 – p.2

Cosmology After WMAP...

Post WMAP-5yr

(April 08) ...+ACBAR+CBI+SN+LSS+... Ωi = ρi/ρcrit Hubble H0 = 100 h km/ s/ Mpc

• L. Roszkowski, GGI, 9 Feb ’09 – p.3

Cosmology After WMAP...

Post WMAP-5yr

(April 08) ...+ACBAR+CBI+SN+LSS+... Ωi = ρi/ρcrit Hubble H0 = 100 h km/ s/ Mpc assume simplest ΛCDM model

matter Ωmh2 = 0.1378 ± 0.0043 baryons Ωbh2 = 0.02263 ± 0.00060 ⇒ ΩCDMh2 = 0.1152 ± 0.0042 h = 0.696 ± 0.017 ΩΛ = 0.715 ± 0.20 . . .

CMB (WMAP , ACBAR, CBI,...) LSS (2dF , SDSS, Lyman-α)

• L. Roszkowski, GGI, 9 Feb ’09 – p.3

Cosmology After WMAP...

Post WMAP-5yr

(April 08) ...+ACBAR+CBI+SN+LSS+... Ωi = ρi/ρcrit Hubble H0 = 100 h km/ s/ Mpc assume simplest ΛCDM model

matter Ωmh2 = 0.1378 ± 0.0043 baryons Ωbh2 = 0.02263 ± 0.00060 ⇒ ΩCDMh2 = 0.1152 ± 0.0042 h = 0.696 ± 0.017 ΩΛ = 0.715 ± 0.20 . . .

CMB (WMAP , ACBAR, CBI,...) LSS (2dF , SDSS, Lyman-α)

concordance model works well main components: dark energy and dark matter

• L. Roszkowski, GGI, 9 Feb ’09 – p.3

Cosmic Pie

• L. Roszkowski, GGI, 9 Feb ’09 – p.4

Outline

• L. Roszkowski, GGI, 9 Feb ’09 – p.5

Outline

DM candidates and particle physics models

• L. Roszkowski, GGI, 9 Feb ’09 – p.5

Outline

DM candidates and particle physics models SUSY neutralino - most popular candidate

• L. Roszkowski, GGI, 9 Feb ’09 – p.5

Outline

DM candidates and particle physics models SUSY neutralino - most popular candidate SUSY models: Constrained MSSM, Non-Universal Higgs Model (NUHM)

• L. Roszkowski, GGI, 9 Feb ’09 – p.5

Outline

DM candidates and particle physics models SUSY neutralino - most popular candidate SUSY models: Constrained MSSM, Non-Universal Higgs Model (NUHM) predictions for direct detection

• L. Roszkowski, GGI, 9 Feb ’09 – p.5

Outline

DM candidates and particle physics models SUSY neutralino - most popular candidate SUSY models: Constrained MSSM, Non-Universal Higgs Model (NUHM) predictions for direct detection indirect detection halo models

• L. Roszkowski, GGI, 9 Feb ’09 – p.5

Outline

DM candidates and particle physics models SUSY neutralino - most popular candidate SUSY models: Constrained MSSM, Non-Universal Higgs Model (NUHM) predictions for direct detection indirect detection halo models predictions for Fermi predictions for Pamela

• L. Roszkowski, GGI, 9 Feb ’09 – p.5

Outline

DM candidates and particle physics models SUSY neutralino - most popular candidate SUSY models: Constrained MSSM, Non-Universal Higgs Model (NUHM) predictions for direct detection indirect detection halo models predictions for Fermi predictions for Pamela summary

• L. Roszkowski, GGI, 9 Feb ’09 – p.5

DM: The Big Picture

∗ – not invented to solve the DM problem

well–motivated∗ particle candidates with Ω ∼ 0.1

• L. Roszkowski, GGI, 9 Feb ’09 – p.6

DM: The Big Picture

L.R. (2000), hep-ph/0404052

neutrino ν – hot DM neutralino χ “generic” WIMP axion a axino a gravitino G

vast ranges of interactions and masses different production mechanisms in the early Universe (thermal, non-thermal) axino, gravitino could be either CDM or WDM (or both) need to go beyond the Standard Model

• L. Roszkowski, GGI, 9 Feb ’09 – p.6

To SUSY or not to SUSY?

SUSY - by far the most popular and developed framework

gauge couplings “run” with energy

• L. Roszkowski, GGI, 9 Feb ’09 – p.7

Neutralino of SUSY – Prime Suspect

• L. Roszkowski, GGI, 9 Feb ’09 – p.8

Neutralino of SUSY – Prime Suspect

neutralino χ = lightest mass eigenstate

• f neutral gauginos e

B (bino), f W0

3 (wino) and neutral higgsinos f

H0

t , f

H0

b

Majorana fermion (χc = χ)

most popular candidate

• L. Roszkowski, GGI, 9 Feb ’09 – p.8

Neutralino of SUSY – Prime Suspect

neutralino χ = lightest mass eigenstate

• f neutral gauginos e

B (bino), f W0

3 (wino) and neutral higgsinos f

H0

t , f

H0

b

Majorana fermion (χc = χ)

most popular candidate part of a well-defined and well-motivated framework of SUSY calculable relic density: Ωχh2 ∼ 0.1 from freeze-out (...more like 10−4 − 103)

stable with some discrete symmetry (e.g., R-parity or baryon parity) testable with today’s experiments (DD, ID, LHC) ...no obviously superior competitor (both to SUSY and to χ) exists

• L. Roszkowski, GGI, 9 Feb ’09 – p.8

Neutralino of SUSY – Prime Suspect

neutralino χ = lightest mass eigenstate

• f neutral gauginos e

B (bino), f W0

3 (wino) and neutral higgsinos f

H0

t , f

H0

b

Majorana fermion (χc = χ)

most popular candidate part of a well-defined and well-motivated framework of SUSY calculable relic density: Ωχh2 ∼ 0.1 from freeze-out (...more like 10−4 − 103)

stable with some discrete symmetry (e.g., R-parity or baryon parity) testable with today’s experiments (DD, ID, LHC) ...no obviously superior competitor (both to SUSY and to χ) exists Don’t forget: multitude of SUSY-based models: general MSSM, CMSSM, split SUSY, MNMSSM, SO(10) GUTs, string inspired models, etc, etc neutralino properties often differ widely from model to model

• L. Roszkowski, GGI, 9 Feb ’09 – p.8

Neutralino of SUSY – Prime Suspect

neutralino χ = lightest mass eigenstate

• f neutral gauginos e

B (bino), f W0

3 (wino) and neutral higgsinos f

H0

t , f

H0

b

Majorana fermion (χc = χ)

most popular candidate part of a well-defined and well-motivated framework of SUSY calculable relic density: Ωχh2 ∼ 0.1 from freeze-out (...more like 10−4 − 103)

stable with some discrete symmetry (e.g., R-parity or baryon parity) testable with today’s experiments (DD, ID, LHC) ...no obviously superior competitor (both to SUSY and to χ) exists Don’t forget: multitude of SUSY-based models: general MSSM, CMSSM, split SUSY, MNMSSM, SO(10) GUTs, string inspired models, etc, etc neutralino properties often differ widely from model to model

neutralino = stable, weakly interacting, massive ⇒ WIMP

• L. Roszkowski, GGI, 9 Feb ’09 – p.8

SUSY Models

Two basic approaches:

• L. Roszkowski, GGI, 9 Feb ’09 – p.9

SUSY Models

Two basic approaches: general MSSM

• L. Roszkowski, GGI, 9 Feb ’09 – p.9

SUSY Models

Two basic approaches: general MSSM unification based:

• L. Roszkowski, GGI, 9 Feb ’09 – p.9

SUSY Models

Two basic approaches: general MSSM unification based: Constrained MSSM (CMSSM)

• L. Roszkowski, GGI, 9 Feb ’09 – p.9

SUSY Models

Two basic approaches: general MSSM unification based: Constrained MSSM (CMSSM) Non-unified Higgs mass (NUHM)

• L. Roszkowski, GGI, 9 Feb ’09 – p.9

SUSY Models

Two basic approaches: general MSSM unification based: Constrained MSSM (CMSSM) Non-unified Higgs mass (NUHM) SO(10)–GUT . . .

• L. Roszkowski, GGI, 9 Feb ’09 – p.9

Strategies for WIMP Detection

• L. Roszkowski, GGI, 9 Feb ’09 – p.10

Strategies for WIMP Detection

direct detection (DD): measure WIMPs scattering off a target

go underground to beat cosmic ray bgnd

• L. Roszkowski, GGI, 9 Feb ’09 – p.10

Strategies for WIMP Detection

direct detection (DD): measure WIMPs scattering off a target

go underground to beat cosmic ray bgnd

indirect detection (ID):

• L. Roszkowski, GGI, 9 Feb ’09 – p.10

Strategies for WIMP Detection

direct detection (DD): measure WIMPs scattering off a target

go underground to beat cosmic ray bgnd

indirect detection (ID): HE neutrinos from the Sun (or Earth)

WIMPs get trapped in Sun’s core, start pair annihilating, only ν’s escape

• L. Roszkowski, GGI, 9 Feb ’09 – p.10

Strategies for WIMP Detection

direct detection (DD): measure WIMPs scattering off a target

go underground to beat cosmic ray bgnd

indirect detection (ID): HE neutrinos from the Sun (or Earth)

WIMPs get trapped in Sun’s core, start pair annihilating, only ν’s escape

antimatter (e+, ¯ p, ¯ D) from WIMP pair-annihilation in the MW halo

from within a few kpc

• L. Roszkowski, GGI, 9 Feb ’09 – p.10

Strategies for WIMP Detection

direct detection (DD): measure WIMPs scattering off a target

go underground to beat cosmic ray bgnd

indirect detection (ID): HE neutrinos from the Sun (or Earth)

WIMPs get trapped in Sun’s core, start pair annihilating, only ν’s escape

antimatter (e+, ¯ p, ¯ D) from WIMP pair-annihilation in the MW halo

from within a few kpc

gamma rays from WIMP pair-annihilation in the Galactic center

depending on DM distribution in the GC

• L. Roszkowski, GGI, 9 Feb ’09 – p.10

Strategies for WIMP Detection

direct detection (DD): measure WIMPs scattering off a target

go underground to beat cosmic ray bgnd

indirect detection (ID): HE neutrinos from the Sun (or Earth)

WIMPs get trapped in Sun’s core, start pair annihilating, only ν’s escape

antimatter (e+, ¯ p, ¯ D) from WIMP pair-annihilation in the MW halo

from within a few kpc

gamma rays from WIMP pair-annihilation in the Galactic center

depending on DM distribution in the GC

• ther ideas: traces of WIMP annihilation in dwarf galaxies, in

rich clusters, etc

more speculative

• L. Roszkowski, GGI, 9 Feb ’09 – p.10

MSSM: Expectations for σSI

p

general MSSM µ > 0 Kim, Nihei, LR & Ruiz de Austri (02) σSI

p – WIMP–proton SI elastic scatt. c.s.

(elastic c.s. for χp → χp at zero momentum transfer)

• L. Roszkowski, GGI, 9 Feb ’09 – p.11

MSSM: Expectations for σSI

p

general MSSM µ > 0 Kim, Nihei, LR & Ruiz de Austri (02) σSI

p – WIMP–proton SI elastic scatt. c.s.

(elastic c.s. for χp → χp at zero momentum transfer)

⇒ MSSM: vast ranges! Lacks real predictive power!

• L. Roszkowski, GGI, 9 Feb ’09 – p.11

Add grand unification...

• L. Roszkowski, GGI, 9 Feb ’09 – p.12

Constrained MSSM (CMSSM)

Kane, Kolda, LR, Wells (1993) ...“benchmark framework” for the LHC (...e.g., mSUGRA)

• L. Roszkowski, GGI, 9 Feb ’09 – p.13

Constrained MSSM (CMSSM)

Kane, Kolda, LR, Wells (1993) ...“benchmark framework” for the LHC (...e.g., mSUGRA) At MGUT ≃ 2 × 1016 GeV: gauginos M1 = M2 = me

g = m1/2

scalars m2

e qi = m2 e li = m2 Hb = m2 Ht = m2

3–linear soft terms Ab = At = A0

• L. Roszkowski, GGI, 9 Feb ’09 – p.13

Constrained MSSM (CMSSM)

Kane, Kolda, LR, Wells (1993) ...“benchmark framework” for the LHC (...e.g., mSUGRA) At MGUT ≃ 2 × 1016 GeV: gauginos M1 = M2 = me

g = m1/2

scalars m2

e qi = m2 e li = m2 Hb = m2 Ht = m2

3–linear soft terms Ab = At = A0 radiative EWSB µ2 =

m2

Hb −m2 Ht tan2 β

tan2 β−1

− m2

Z

2

• L. Roszkowski, GGI, 9 Feb ’09 – p.13

Constrained MSSM (CMSSM)

Kane, Kolda, LR, Wells (1993) ...“benchmark framework” for the LHC (...e.g., mSUGRA) At MGUT ≃ 2 × 1016 GeV: gauginos M1 = M2 = me

g = m1/2

scalars m2

e qi = m2 e li = m2 Hb = m2 Ht = m2

3–linear soft terms Ab = At = A0 radiative EWSB µ2 =

m2

Hb −m2 Ht tan2 β

tan2 β−1

− m2

Z

2

4+1 independent parameters:

m1/2, m0, A0, tan β, sgn(µ)

• L. Roszkowski, GGI, 9 Feb ’09 – p.13

Constrained MSSM (CMSSM)

Kane, Kolda, LR, Wells (1993) ...“benchmark framework” for the LHC (...e.g., mSUGRA) At MGUT ≃ 2 × 1016 GeV: gauginos M1 = M2 = me

g = m1/2

scalars m2

e qi = m2 e li = m2 Hb = m2 Ht = m2

3–linear soft terms Ab = At = A0 radiative EWSB µ2 =

m2

Hb −m2 Ht tan2 β

tan2 β−1

− m2

Z

2

4+1 independent parameters:

m1/2, m0, A0, tan β, sgn(µ)

well developed machinery to compute masses and couplings

• L. Roszkowski, GGI, 9 Feb ’09 – p.13

Constrained MSSM (CMSSM)

Kane, Kolda, LR, Wells (1993) ...“benchmark framework” for the LHC (...e.g., mSUGRA) At MGUT ≃ 2 × 1016 GeV: gauginos M1 = M2 = me

g = m1/2

scalars m2

e qi = m2 e li = m2 Hb = m2 Ht = m2

3–linear soft terms Ab = At = A0 radiative EWSB µ2 =

m2

Hb −m2 Ht tan2 β

tan2 β−1

− m2

Z

2

4+1 independent parameters:

m1/2, m0, A0, tan β, sgn(µ)

well developed machinery to compute masses and couplings neutralino χ mostly bino

• L. Roszkowski, GGI, 9 Feb ’09 – p.13

Constrained MSSM (CMSSM)

Kane, Kolda, LR, Wells (1993) ...“benchmark framework” for the LHC (...e.g., mSUGRA) At MGUT ≃ 2 × 1016 GeV: gauginos M1 = M2 = me

g = m1/2

scalars m2

e qi = m2 e li = m2 Hb = m2 Ht = m2

3–linear soft terms Ab = At = A0 radiative EWSB µ2 =

m2

Hb −m2 Ht tan2 β

tan2 β−1

− m2

Z

2

4+1 independent parameters:

m1/2, m0, A0, tan β, sgn(µ)

well developed machinery to compute masses and couplings neutralino χ mostly bino some useful mass relations: bino: mχ ≃ 0.4m1/2 gluino e g: me

g ≃ 2.7m1/2

supersymmetric tau (stau) e τ1: me

τ1 ≃

q 0.15m2

1/2 + m2

• L. Roszkowski, GGI, 9 Feb ’09 – p.13

Earlier analyses of CMSSM

very many papers

• L. Roszkowski, GGI, 9 Feb ’09 – p.14

Earlier analyses of CMSSM

very many papers Until recently usual approach has been to: do fixed-grid scans of m1/2 and m0 for fixed tan β and A0 apply constraints from LEP , BR( ¯ B → Xsγ), Ωχh2, EWSB, charged LSP , etc impose rigid (in/out) 1σ or 2σ ranges

• L. Roszkowski, GGI, 9 Feb ’09 – p.14

Earlier analyses of CMSSM

very many papers Until recently usual approach has been to: do fixed-grid scans of m1/2 and m0 for fixed tan β and A0 apply constraints from LEP , BR( ¯ B → Xsγ), Ωχh2, EWSB, charged LSP , etc impose rigid (in/out) 1σ or 2σ ranges

• btain narrow “allowed” regions

hep-ph/0404052

• L. Roszkowski, GGI, 9 Feb ’09 – p.14

Earlier analyses of CMSSM

very many papers Until recently usual approach has been to: do fixed-grid scans of m1/2 and m0 for fixed tan β and A0 apply constraints from LEP , BR( ¯ B → Xsγ), Ωχh2, EWSB, charged LSP , etc impose rigid (in/out) 1σ or 2σ ranges

• btain narrow “allowed” regions

Shortcomings: hard to compare relative impact of various constraints, hard to include TH + residual SM errors, etc. full scan of PS not feasible impossible to assess relative impact of var- ious constraints hep-ph/0404052

• L. Roszkowski, GGI, 9 Feb ’09 – p.14

Earlier analyses of CMSSM

very many papers Until recently usual approach has been to: do fixed-grid scans of m1/2 and m0 for fixed tan β and A0 apply constraints from LEP , BR( ¯ B → Xsγ), Ωχh2, EWSB, charged LSP , etc impose rigid (in/out) 1σ or 2σ ranges

• btain narrow “allowed” regions

Shortcomings: hard to compare relative impact of various constraints, hard to include TH + residual SM errors, etc. full scan of PS not feasible impossible to assess relative impact of var- ious constraints hep-ph/0404052

results in over-simplified predictions

• L. Roszkowski, GGI, 9 Feb ’09 – p.14

Bayesian Analysis of the CMSSM

Apply to the CMSSM:

new development, led by 2 groups

• L. Roszkowski, GGI, 9 Feb ’09 – p.15

Bayesian Analysis of the CMSSM

Apply to the CMSSM:

new development, led by 2 groups

m = (θ, ψ) – model’s all relevant parameters

• L. Roszkowski, GGI, 9 Feb ’09 – p.15

Bayesian Analysis of the CMSSM

Apply to the CMSSM:

new development, led by 2 groups

m = (θ, ψ) – model’s all relevant parameters CMSSM parameters θ = m1/2, m0, A0, tan β , fix sgn(µ) relevant SM param’s ψ = Mt, mb(mb)MS, αMS

s

, αem(MZ)MS

• L. Roszkowski, GGI, 9 Feb ’09 – p.15

Bayesian Analysis of the CMSSM

Apply to the CMSSM:

new development, led by 2 groups

m = (θ, ψ) – model’s all relevant parameters CMSSM parameters θ = m1/2, m0, A0, tan β , fix sgn(µ) relevant SM param’s ψ = Mt, mb(mb)MS, αMS

s

, αem(MZ)MS ξ = (ξ1, ξ2, . . . , ξm): set of derived variables (observables): ξ(m)

• L. Roszkowski, GGI, 9 Feb ’09 – p.15

Bayesian Analysis of the CMSSM

Apply to the CMSSM:

new development, led by 2 groups

m = (θ, ψ) – model’s all relevant parameters CMSSM parameters θ = m1/2, m0, A0, tan β , fix sgn(µ) relevant SM param’s ψ = Mt, mb(mb)MS, αMS

s

, αem(MZ)MS ξ = (ξ1, ξ2, . . . , ξm): set of derived variables (observables): ξ(m) d: data (ΩCDMh2, b → sγ, mh, etc)

• L. Roszkowski, GGI, 9 Feb ’09 – p.15

Bayesian Analysis of the CMSSM

Apply to the CMSSM:

new development, led by 2 groups

m = (θ, ψ) – model’s all relevant parameters CMSSM parameters θ = m1/2, m0, A0, tan β , fix sgn(µ) relevant SM param’s ψ = Mt, mb(mb)MS, αMS

s

, αem(MZ)MS ξ = (ξ1, ξ2, . . . , ξm): set of derived variables (observables): ξ(m) d: data (ΩCDMh2, b → sγ, mh, etc) Bayes’ theorem: posterior pdf p(θ, ψ|d) = p(d|ξ)π(θ,ψ)

p(d)

posterior =

likelihood × prior normalization factor

p(d|ξ) = L: likelihood π(θ, ψ): prior pdf p(d): evidence (normalization factor)

• L. Roszkowski, GGI, 9 Feb ’09 – p.15

Bayesian Analysis of the CMSSM

Apply to the CMSSM:

new development, led by 2 groups

m = (θ, ψ) – model’s all relevant parameters CMSSM parameters θ = m1/2, m0, A0, tan β , fix sgn(µ) relevant SM param’s ψ = Mt, mb(mb)MS, αMS

s

, αem(MZ)MS ξ = (ξ1, ξ2, . . . , ξm): set of derived variables (observables): ξ(m) d: data (ΩCDMh2, b → sγ, mh, etc) Bayes’ theorem: posterior pdf p(θ, ψ|d) = p(d|ξ)π(θ,ψ)

p(d)

posterior =

likelihood × prior normalization factor

p(d|ξ) = L: likelihood π(θ, ψ): prior pdf p(d): evidence (normalization factor) usually marginalize over SM (nuisance) parameters ψ ⇒ p(θ|d)

• L. Roszkowski, GGI, 9 Feb ’09 – p.15

Impact of varying SM parameters

• L. Roszkowski, GGI, 9 Feb ’09 – p.16

Impact of varying SM parameters

fix tan β, A0 + all SM param’s

tanβ=50 A0=0 m1/2 (GeV) m0 (GeV)

500 1000 1500 2000 500 1000 1500 2000 2500 3000 3500 4000

Relative probability density

0.2 0.4 0.6 0.8 1

• L. Roszkowski, GGI, 9 Feb ’09 – p.16

Impact of varying SM parameters

fix tan β, A0 + all SM param’s

tanβ=50 A0=0 m1/2 (GeV) m0 (GeV)

500 1000 1500 2000 500 1000 1500 2000 2500 3000 3500 4000

Relative probability density

0.2 0.4 0.6 0.8 1

vary Mt

Mt varied

tanβ=50 A0=0

m1/2 (GeV) m0 (GeV)

500 1000 1500 2000 500 1000 1500 2000 2500 3000 3500 4000

Relative probability density

0.2 0.4 0.6 0.8 1

• L. Roszkowski, GGI, 9 Feb ’09 – p.16

Impact of varying SM parameters

fix tan β, A0 + all SM param’s

tanβ=50 A0=0 m1/2 (GeV) m0 (GeV)

500 1000 1500 2000 500 1000 1500 2000 2500 3000 3500 4000

Relative probability density

0.2 0.4 0.6 0.8 1

vary αs

αs varied

tanβ=50 A0=0

m1/2 (GeV) m0 (GeV)

500 1000 1500 2000 500 1000 1500 2000 2500 3000 3500 4000

Relative probability density

0.2 0.4 0.6 0.8 1

• L. Roszkowski, GGI, 9 Feb ’09 – p.16

Impact of varying SM parameters

fix tan β, A0 + all SM param’s

tanβ=50 A0=0 m1/2 (GeV) m0 (GeV)

500 1000 1500 2000 500 1000 1500 2000 2500 3000 3500 4000

Relative probability density

0.2 0.4 0.6 0.8 1

vary αs

αs varied

tanβ=50 A0=0

m1/2 (GeV) m0 (GeV)

500 1000 1500 2000 500 1000 1500 2000 2500 3000 3500 4000

Relative probability density

0.2 0.4 0.6 0.8 1

residual errors in SM parameters ⇒ strong impact on favoured SUSY ranges

effect of varying A0, tan β also substantial

• L. Roszkowski, GGI, 9 Feb ’09 – p.16

CMSSM: Prospects for direct detection

CMSSM: Constrained MSSM Bayesian analysis, flat priors, MCMC

• L. Roszkowski, GGI, 9 Feb ’09 – p.17

CMSSM: Prospects for direct detection

CMSSM: Constrained MSSM Bayesian analysis, flat priors, MCMC

mχ (TeV) Log[σp

SI (pb)]

CDMS−II EDELWEISS−I XENON−10 ZEPLIN−III

CMSSM, µ > 0

Roszkowski, Ruiz & Trotta (2007)

0.2 0.4 0.6 0.8 1 −11 −10 −9 −8 −7 −6 −5 −4

internal (external): 68% (95%) region

• L. Roszkowski, GGI, 9 Feb ’09 – p.17

CMSSM: Prospects for direct detection

CMSSM: Constrained MSSM Bayesian analysis, flat priors, MCMC

mχ (TeV) Log[σp

SI (pb)]

CDMS−II EDELWEISS−I XENON−10 ZEPLIN−III

CMSSM, µ > 0

Roszkowski, Ruiz & Trotta (2007)

0.2 0.4 0.6 0.8 1 −11 −10 −9 −8 −7 −6 −5 −4

internal (external): 68% (95%) region

XENON-10 (June 07) and CDMS-II (Feb 08): σSI

p

∼ < 10−7 pb:

also Zeplin–III

⇒ already explore 68% region

(large m0 ≫ m1/2 ⇒ heavy squarks) largely beyond LHC reach

• L. Roszkowski, GGI, 9 Feb ’09 – p.17

CMSSM: Prospects for direct detection

CMSSM: Constrained MSSM Bayesian analysis, flat priors, MCMC

mχ (TeV) Log[σp

SI (pb)]

CDMS−II EDELWEISS−I XENON−10 ZEPLIN−III

CMSSM, µ > 0

Roszkowski, Ruiz & Trotta (2007)

0.2 0.4 0.6 0.8 1 −11 −10 −9 −8 −7 −6 −5 −4

internal (external): 68% (95%) region

XENON-10 (June 07) and CDMS-II (Feb 08): σSI

p

∼ < 10−7 pb:

also Zeplin–III

⇒ already explore 68% region

(large m0 ≫ m1/2 ⇒ heavy squarks) largely beyond LHC reach

m1/2 (TeV) m0 (TeV)

CMSSM µ>0

Roszkowski, Ruiz & Trotta (2007)

0.5 1 1.5 2 0.5 1 1.5 2 2.5 3 3.5 4

LHC

• L. Roszkowski, GGI, 9 Feb ’09 – p.17

CMSSM: Prospects for direct detection

CMSSM: Constrained MSSM Bayesian analysis, flat priors, MCMC

mχ (TeV) Log[σp

SI (pb)]

CDMS−II EDELWEISS−I XENON−10 ZEPLIN−III

CMSSM, µ > 0

Roszkowski, Ruiz & Trotta (2007)

0.2 0.4 0.6 0.8 1 −11 −10 −9 −8 −7 −6 −5 −4

internal (external): 68% (95%) region

XENON-10 (June 07) and CDMS-II (Feb 08): σSI

p

∼ < 10−7 pb:

also Zeplin–III

⇒ already explore 68% region

(large m0 ≫ m1/2 ⇒ heavy squarks) largely beyond LHC reach

m1/2 (TeV) m0 (TeV)

CMSSM µ>0

Roszkowski, Ruiz & Trotta (2007)

0.5 1 1.5 2 0.5 1 1.5 2 2.5 3 3.5 4

LHC

⇒ DD: prospects look very good

• L. Roszkowski, GGI, 9 Feb ’09 – p.17

Impact of priors

• L. Roszkowski, GGI, 9 Feb ’09 – p.18

Impact of priors

flat in m0, m1/2

mχ (GeV) log(σp

SI) (pb)

Trotta et al (2008) CMSSM, µ>0, flat priors

CDMS−II XENON−10 ZEPLIN−II

200 400 600 800 −11 −10 −9 −8 −7 −6 −5

• L. Roszkowski, GGI, 9 Feb ’09 – p.18

Impact of priors

flat in m0, m1/2

mχ (GeV) log(σp

SI) (pb)

Trotta et al (2008) CMSSM, µ>0, flat priors

CDMS−II XENON−10 ZEPLIN−II

200 400 600 800 −11 −10 −9 −8 −7 −6 −5

flat in log(m0), log(m1/2)

mχ (GeV) log(σp

SI) (pb)

Trotta et al (2008) CMSSM, µ>0, log priors

CDMS−II XENON−10 ZEPLIN−II

200 400 600 800 −11 −10 −9 −8 −7 −6 −5

• L. Roszkowski, GGI, 9 Feb ’09 – p.18

Impact of priors

flat in m0, m1/2

mχ (GeV) log(σp

SI) (pb)

Trotta et al (2008) CMSSM, µ>0, flat priors

CDMS−II XENON−10 ZEPLIN−II

200 400 600 800 −11 −10 −9 −8 −7 −6 −5

flat in log(m0), log(m1/2)

mχ (GeV) log(σp

SI) (pb)

Trotta et al (2008) CMSSM, µ>0, log priors

CDMS−II XENON−10 ZEPLIN−II

200 400 600 800 −11 −10 −9 −8 −7 −6 −5

still strong prior dependence (data not yet constraining enough) both priors: most regions above some 10−10 pb ⇒ good news for DM expt LHC reach: mχ ∼ < 400 − 500 GeV ⇒ additional vital info

• L. Roszkowski, GGI, 9 Feb ’09 – p.18

Non-Universal Higgs Mass

(NUHM) ...many papers (Ellis et al, Munoz, et al, Baer et al.)

• L. Roszkowski, GGI, 9 Feb ’09 – p.19

Non-Universal Higgs Mass

(NUHM) ...many papers (Ellis et al, Munoz, et al, Baer et al.)

At MGUT ≃ 2 × 1016 GeV: disunify Higgs soft masses from other scalars gauginos M1 = M2 = me

g = m1/2

(c.f. MSSM)

squarks, sleptons m2

e qi = m2 e li = m2

Higgs doublets m2

Hd, m2 Hu

3–linear soft terms Ab = At = A0

• L. Roszkowski, GGI, 9 Feb ’09 – p.19

Non-Universal Higgs Mass

(NUHM) ...many papers (Ellis et al, Munoz, et al, Baer et al.)

At MGUT ≃ 2 × 1016 GeV: disunify Higgs soft masses from other scalars gauginos M1 = M2 = me

g = m1/2

(c.f. MSSM)

squarks, sleptons m2

e qi = m2 e li = m2

Higgs doublets m2

Hd, m2 Hu

3–linear soft terms Ab = At = A0 radiative EWSB µ2 =

“ m2

Hd+Σ(1) d

” −(m2

Hu +Σ(1) u ) tan2 β

tan2 β−1

− m2

Z

2

• L. Roszkowski, GGI, 9 Feb ’09 – p.19

Non-Universal Higgs Mass

(NUHM) ...many papers (Ellis et al, Munoz, et al, Baer et al.)

At MGUT ≃ 2 × 1016 GeV: disunify Higgs soft masses from other scalars gauginos M1 = M2 = me

g = m1/2

(c.f. MSSM)

squarks, sleptons m2

e qi = m2 e li = m2

Higgs doublets m2

Hd, m2 Hu

3–linear soft terms Ab = At = A0 radiative EWSB µ2 =

“ m2

Hd+Σ(1) d

” −(m2

Hu +Σ(1) u ) tan2 β

tan2 β−1

− m2

Z

2

6+1 parameters: tan β, m1/2, m0, mHu, mHd, A0, sgn(µ)

• L. Roszkowski, GGI, 9 Feb ’09 – p.19

Non-Universal Higgs Mass

(NUHM) ...many papers (Ellis et al, Munoz, et al, Baer et al.)

At MGUT ≃ 2 × 1016 GeV: disunify Higgs soft masses from other scalars gauginos M1 = M2 = me

g = m1/2

(c.f. MSSM)

squarks, sleptons m2

e qi = m2 e li = m2

Higgs doublets m2

Hd, m2 Hu

3–linear soft terms Ab = At = A0 radiative EWSB µ2 =

“ m2

Hd+Σ(1) d

” −(m2

Hu +Σ(1) u ) tan2 β

tan2 β−1

− m2

Z

2

6+1 parameters: tan β, m1/2, m0, mHu, mHd, A0, sgn(µ) two more parameters than in CMSSM surprisingly rich phenomenological difference with CMSSM

• L. Roszkowski, GGI, 9 Feb ’09 – p.19

NUHM: DM Searches

Bayesian posterior probability maps spin-independent c.s.

• L. Roszkowski, GGI, 9 Feb ’09 – p.20

NUHM: DM Searches

Bayesian posterior probability maps spin-independent c.s. flat prior

mχ (TeV) Log[σp

SI (pb)]

ZEPLIN−II EDELWEISS−I XENON−10 ZEPLIN−III CDMS−II

NUHM, µ > 0 flat prior

Roszkowski, Ruiz, Trotta, Tsai & Varley (2009)

0.5 1 1.5 −11 −10 −9 −8 −7 −6 −5 −4

large region at mχ ∼ 1 TeV

• L. Roszkowski, GGI, 9 Feb ’09 – p.20

NUHM: DM Searches

Bayesian posterior probability maps spin-independent c.s. flat prior

mχ (TeV) Log[σp

SI (pb)]

ZEPLIN−II EDELWEISS−I XENON−10 ZEPLIN−III CDMS−II

NUHM, µ > 0 flat prior

Roszkowski, Ruiz, Trotta, Tsai & Varley (2009)

0.5 1 1.5 −11 −10 −9 −8 −7 −6 −5 −4

large region at mχ ∼ 1 TeV log prior in m1/2, m0

mχ (TeV) Log[σp

SI (pb)]

ZEPLIN−II EDELWEISS−I XENON−10 ZEPLIN−III CDMS−II

NUHM, µ > 0 log prior

Roszkowski, Ruiz, Trotta, Tsai & Varley (2009)

0.5 1 1.5 −11 −10 −9 −8 −7 −6 −5 −4

big shift towards smaller mχ

• L. Roszkowski, GGI, 9 Feb ’09 – p.20

NUHM: DM Searches

Bayesian posterior probability maps spin-independent c.s. flat prior

mχ (TeV) Log[σp

SI (pb)]

ZEPLIN−II EDELWEISS−I XENON−10 ZEPLIN−III CDMS−II

NUHM, µ > 0 flat prior

Roszkowski, Ruiz, Trotta, Tsai & Varley (2009)

0.5 1 1.5 −11 −10 −9 −8 −7 −6 −5 −4

large region at mχ ∼ 1 TeV log prior in m1/2, m0

mχ (TeV) Log[σp

SI (pb)]

ZEPLIN−II EDELWEISS−I XENON−10 ZEPLIN−III CDMS−II

NUHM, µ > 0 log prior

Roszkowski, Ruiz, Trotta, Tsai & Varley (2009)

0.5 1 1.5 −11 −10 −9 −8 −7 −6 −5 −4

big shift towards smaller mχ

⇒ NUHM: new higgsino LSP region at mχ ∼ 1 TeV ⇒ large prior dependence

• L. Roszkowski, GGI, 9 Feb ’09 – p.20

Indirect detection

• L. Roszkowski, GGI, 9 Feb ’09 – p.21

Indirect detection

look for traces of WIMP annihilation in the MW halo detection prospects often strongly depend on astrophysical uncertainties

• L. Roszkowski, GGI, 9 Feb ’09 – p.21

Indirect detection

look for traces of WIMP annihilation in the MW halo detection prospects often strongly depend on astrophysical uncertainties dark halo models?

• verdense regions (clumps)?
• L. Roszkowski, GGI, 9 Feb ’09 – p.21

Indirect detection

look for traces of WIMP annihilation in the MW halo detection prospects often strongly depend on astrophysical uncertainties dark halo models?

• verdense regions (clumps)?

DM density profile near Galactic center?

• L. Roszkowski, GGI, 9 Feb ’09 – p.21

CDM Halo Models

...not a settled matter

• L. Roszkowski, GGI, 9 Feb ’09 – p.22

CDM Halo Models

...not a settled matter fitting DM halo with a semi-heuristic formula:

ρDM(r) = ρc/ r

a

γ 1 + r

a

α(β−γ)/α

α, β, γ - adjustable parameters ρc = ρ0 ` r0

a

´γ h 1 + “

R0 a

”αi(β−γ)/α , ρ0 ∼ 0.3 GeV/ cm3 - DM density at r0 a - scale radius - from num. sim’s or to match observations

• L. Roszkowski, GGI, 9 Feb ’09 – p.22

CDM Halo Models

...not a settled matter fitting DM halo with a semi-heuristic formula:

ρDM(r) = ρc/ r

a

γ 1 + r

a

α(β−γ)/α

α, β, γ - adjustable parameters ρc = ρ0 ` r0

a

´γ h 1 + “

R0 a

”αi(β−γ)/α , ρ0 ∼ 0.3 GeV/ cm3 - DM density at r0 a - scale radius - from num. sim’s or to match observations

• adiabatic compression due to baryon concentration in the GC:

likely effect: central cusp becames steeper: “model” ⇒ “model-c”

• L. Roszkowski, GGI, 9 Feb ’09 – p.22

CDM Halo Models

...not a settled matter fitting DM halo with a semi-heuristic formula:

ρDM(r) = ρc/ r

a

γ 1 + r

a

α(β−γ)/α

α, β, γ - adjustable parameters ρc = ρ0 ` r0

a

´γ h 1 + “

R0 a

”αi(β−γ)/α , ρ0 ∼ 0.3 GeV/ cm3 - DM density at r0 a - scale radius - from num. sim’s or to match observations

• adiabatic compression due to baryon concentration in the GC:

likely effect: central cusp becames steeper: “model” ⇒ “model-c” some most popular models: halo model a r0 (α, β, γ) small r large r ( kpc) ( kpc) r ∝ r−γ r ∝ r−β isothermal cored 3.5 8.5 (2, 2, 0) flat r−2 NFW 20.0 8.0 (1, 3, 1) r−1 r−3 NFW-c 20.0 8.0 (1.5, 3, 1.5) r−1.5 r−3 Moore 28.0 8.0 (1, 3, 1.5) r−1.5 r−3 Moore-c 28.0 8.0 (0.8, 2.7, 1.65) r−1.65 r−2.7

• L. Roszkowski, GGI, 9 Feb ’09 – p.22

CDM Halo Models

...not a settled matter fitting DM halo with a semi-heuristic formula:

ρDM(r) = ρc/ r

a

γ 1 + r

a

α(β−γ)/α

α, β, γ - adjustable parameters ρc = ρ0 ` r0

a

´γ h 1 + “

R0 a

”αi(β−γ)/α , ρ0 ∼ 0.3 GeV/ cm3 - DM density at r0 a - scale radius - from num. sim’s or to match observations

• adiabatic compression due to baryon concentration in the GC:

likely effect: central cusp becames steeper: “model” ⇒ “model-c” some most popular models: halo model a r0 (α, β, γ) small r large r ( kpc) ( kpc) r ∝ r−γ r ∝ r−β isothermal cored 3.5 8.5 (2, 2, 0) flat r−2 NFW 20.0 8.0 (1, 3, 1) r−1 r−3 NFW-c 20.0 8.0 (1.5, 3, 1.5) r−1.5 r−3 Moore 28.0 8.0 (1, 3, 1.5) r−1.5 r−3 Moore-c 28.0 8.0 (0.8, 2.7, 1.65) r−1.65 r−2.7 Many open questions: clumps??, central cusp??, spherical or tri–axial??,. . .

• L. Roszkowski, GGI, 9 Feb ’09 – p.22

Our Milky Way

example of a reasonable model (Klypin, et al., 2001)

• L. Roszkowski, GGI, 9 Feb ’09 – p.23

Our Milky Way

example of a reasonable model (Klypin, et al., 2001) based on NFW model with angular mom. exchange between baryons and DM DM dominates only at large r, well beyond the solar radius DM likely to be subdominant in the inner regions if no exchange of angular mom.: more DM in the center (but problem with fast rotating bar?)

• L. Roszkowski, GGI, 9 Feb ’09 – p.23

Halo models

10

−3

10

−2

10

−1

10 10

1

10

2

10

−3

10

−2

10

−1

10 10

1

10

2

10

3

DM density (GeV/cm3) Radius (kpc)

Klypin et al Moore NFW isothermal

• L. Roszkowski, GGI, 9 Feb ’09 – p.24

Halo models

10

−3

10

−2

10

−1

10 10

1

10

2

10

−3

10

−2

10

−1

10 10

1

10

2

10

3

DM density (GeV/cm3) Radius (kpc)

Klypin et al Moore NFW isothermal

steeper inner profie r−1.8 ⇒ stronger DM annihilation at small r

• L. Roszkowski, GGI, 9 Feb ’09 – p.24

Diffuse GRs from the GC

use Fermi/GLAST parameters Bayesian posterior probability maps

• L. Roszkowski, GGI, 9 Feb ’09 – p.25

Diffuse GRs from the GC

use Fermi/GLAST parameters Bayesian posterior probability maps CMSSM, flat priors

• L. Roszkowski, GGI, 9 Feb ’09 – p.25

Diffuse GRs from the GC

use Fermi/GLAST parameters Bayesian posterior probability maps CMSSM, flat priors NUHM, flat priors

mχ (TeV) Log[Φγ (cm−2s−1)]

Fermi/GLAST reach (1yr)

Φγ from GC

NUHM, µ > 0 flat prior ∆ Ω = 10−5 sr Ethr = 10 GeV K l y p i n

NFW isothermal

Roszkowski, Ruiz, Trotta, Tsai & Varley (2009)

0.5 1 1.5 2 −16 −14 −12 −10 −8 −6

• L. Roszkowski, GGI, 9 Feb ’09 – p.25

Diffuse GRs from the GC

use Fermi/GLAST parameters Bayesian posterior probability maps CMSSM, flat priors NUHM, flat priors

mχ (TeV) Log[Φγ (cm−2s−1)]

Fermi/GLAST reach (1yr)

Φγ from GC

NUHM, µ > 0 flat prior ∆ Ω = 10−5 sr Ethr = 10 GeV K l y p i n

NFW isothermal

Roszkowski, Ruiz, Trotta, Tsai & Varley (2009)

0.5 1 1.5 2 −16 −14 −12 −10 −8 −6

⇒ WIMP signal at Fermi/GLAST: outcome depends on halo cuspiness at GC

• L. Roszkowski, GGI, 9 Feb ’09 – p.25

Impact of Priors

use Fermi/GLAST parameters Bayesian posterior probability maps

• L. Roszkowski, GGI, 9 Feb ’09 – p.26

Impact of Priors

use Fermi/GLAST parameters Bayesian posterior probability maps NUHM, flat priors

mχ (TeV) Log[Φγ (cm−2s−1)]

Fermi/GLAST reach (1yr)

Φγ from GC

NUHM, µ > 0 flat prior ∆ Ω = 10−5 sr Ethr = 10 GeV K l y p i n

NFW isothermal

Roszkowski, Ruiz, Trotta, Tsai & Varley (2009)

0.5 1 1.5 2 −16 −14 −12 −10 −8 −6

• L. Roszkowski, GGI, 9 Feb ’09 – p.26

Impact of Priors

use Fermi/GLAST parameters Bayesian posterior probability maps NUHM, flat priors

mχ (TeV) Log[Φγ (cm−2s−1)]

Fermi/GLAST reach (1yr)

Φγ from GC

NUHM, µ > 0 flat prior ∆ Ω = 10−5 sr Ethr = 10 GeV K l y p i n

NFW isothermal

Roszkowski, Ruiz, Trotta, Tsai & Varley (2009)

0.5 1 1.5 2 −16 −14 −12 −10 −8 −6

NUHM, log priors

mχ (TeV) Log[Φγ (cm−2s−1)]

Fermi/GLAST reach (1yr)

Φγ from GC

NUHM, µ > 0 log prior ∆ Ω = 10−5 sr Ethr = 10 GeV K l y p i n

NFW isothermal

Roszkowski, Ruiz, Trotta, Tsai & Varley (2009)

0.5 1 1.5 2 −16 −14 −12 −10 −8 −6

• L. Roszkowski, GGI, 9 Feb ’09 – p.26

Impact of Priors

use Fermi/GLAST parameters Bayesian posterior probability maps NUHM, flat priors

mχ (TeV) Log[Φγ (cm−2s−1)]

Fermi/GLAST reach (1yr)

Φγ from GC

NUHM, µ > 0 flat prior ∆ Ω = 10−5 sr Ethr = 10 GeV K l y p i n

NFW isothermal

Roszkowski, Ruiz, Trotta, Tsai & Varley (2009)

0.5 1 1.5 2 −16 −14 −12 −10 −8 −6

NUHM, log priors

mχ (TeV) Log[Φγ (cm−2s−1)]

Fermi/GLAST reach (1yr)

Φγ from GC

NUHM, µ > 0 log prior ∆ Ω = 10−5 sr Ethr = 10 GeV K l y p i n

NFW isothermal

Roszkowski, Ruiz, Trotta, Tsai & Varley (2009)

0.5 1 1.5 2 −16 −14 −12 −10 −8 −6

log prior: ⇒ sqeeze towards lower mass (as expected) ⇒ higher fluxes

• L. Roszkowski, GGI, 9 Feb ’09 – p.26

e+ data from PAMELA

• L. Roszkowski, GGI, 9 Feb ’09 – p.27

e+ data from PAMELA

PAMELA satelite (since 2007)

• L. Roszkowski, GGI, 9 Feb ’09 – p.27

e+ data from PAMELA

PAMELA satelite (since 2007) e+/(e+ + e−) difficult measurement

• O. Adriani et al., arXiv:0810.4995
• L. Roszkowski, GGI, 9 Feb ’09 – p.27

e+ data from PAMELA

PAMELA satelite (since 2007) e+/(e+ + e−) difficult measurement puzzling: growth at large e+ new physics? DM? pulsars?

• O. Adriani et al., arXiv:0810.4995
• L. Roszkowski, GGI, 9 Feb ’09 – p.27

e+ data from PAMELA

PAMELA satelite (since 2007) e+/(e+ + e−) difficult measurement puzzling: growth at large e+ new physics? DM? pulsars? wave of (wild?) theoretical specu- lations

• O. Adriani et al., arXiv:0810.4995
• L. Roszkowski, GGI, 9 Feb ’09 – p.27

e+ data from PAMELA

PAMELA satelite (since 2007) e+/(e+ + e−) difficult measurement puzzling: growth at large e+ new physics? DM? pulsars? wave of (wild?) theoretical specu- lations

• O. Adriani et al., arXiv:0810.4995

...analysis to be cross-checked, result to be verified by AMS

• L. Roszkowski, GGI, 9 Feb ’09 – p.27

Positron flux and PAMELA

• L. Roszkowski, GGI, 9 Feb ’09 – p.28

Positron flux and PAMELA

e+’s from DM annihilations propagate in interstellar magnetic field K(ǫ) = 2.1 × 1028ǫ0.6 cm2 sec−1 ǫ = Ee+/1 GeV much less dependence on halo model loose energy via inverse Compton scattering b(ǫ) = ǫ2 τE ≈ 10−16ǫ2 sec−1 τE = 1016 sec−1 diffusion zone: infinite slab of height L = 4 kpc, free escape BC’s

• L. Roszkowski, GGI, 9 Feb ’09 – p.28

SUSY: Positron flux

Bayesian posterior probability maps BF=1

• L. Roszkowski, GGI, 9 Feb ’09 – p.29

SUSY: Positron flux

Bayesian posterior probability maps BF=1 CMSSM, flat priors, NFW

Roszkowski, Ruiz, Silk & Trotta (2008)

Φe+/(Φe++Φe−)

PAMELA 08 HEAT 00 HEAT 94+95 CAPRICE 94

Ee+ (GeV)

NFW profile, BF = 1 CMSSM, µ > 0

95% 68%

Moore+ac NFW+ac NFW

0.1 1 10 100 400 10

−8

10

−7

10

−6

10

−5

10

−4

10

−3

10

−2

10

−1

• L. Roszkowski, GGI, 9 Feb ’09 – p.29

SUSY: Positron flux

Bayesian posterior probability maps BF=1 CMSSM, flat priors, NFW

Roszkowski, Ruiz, Silk & Trotta (2008)

Φe+/(Φe++Φe−)

PAMELA 08 HEAT 00 HEAT 94+95 CAPRICE 94

Ee+ (GeV)

NFW profile, BF = 1 CMSSM, µ > 0

95% 68%

Moore+ac NFW+ac NFW

0.1 1 10 100 400 10

−8

10

−7

10

−6

10

−5

10

−4

10

−3

10

−2

10

−1

NUHM, flat priors, NFW

10

−1

10 10

1

10

2

10

−5

10

−4

10

−3

10

−2

10

−1

10

Roszkowski, Ruiz, Trotta, Tsai & Varley (2009)

Φe+/(Φe++Φe−) Ee+ (GeV)

0.62< mχ /TeV <1.1 (68% range)

b g n d .

CAPRICE 94 HEAT 94+95 HEAT 00 PAMELA

NUHM, µ >0 NFW, BF=1 flat prior

mχ (GeV) 200 400 600 800 1000 1200

• L. Roszkowski, GGI, 9 Feb ’09 – p.29

SUSY: Positron flux

Bayesian posterior probability maps BF=1 CMSSM, flat priors, NFW

Roszkowski, Ruiz, Silk & Trotta (2008)

Φe+/(Φe++Φe−)

PAMELA 08 HEAT 00 HEAT 94+95 CAPRICE 94

Ee+ (GeV)

NFW profile, BF = 1 CMSSM, µ > 0

95% 68%

Moore+ac NFW+ac NFW

0.1 1 10 100 400 10

−8

10

−7

10

−6

10

−5

10

−4

10

−3

10

−2

10

−1

NUHM, flat priors, NFW

10

−1

10 10

1

10

2

10

−5

10

−4

10

−3

10

−2

10

−1

10

Roszkowski, Ruiz, Trotta, Tsai & Varley (2009)

Φe+/(Φe++Φe−) Ee+ (GeV)

0.62< mχ /TeV <1.1 (68% range)

b g n d .

CAPRICE 94 HEAT 94+95 HEAT 00 PAMELA

NUHM, µ >0 NFW, BF=1 flat prior

mχ (GeV) 200 400 600 800 1000 1200

⇒ CMSSM, NUHM: inconsistent with PAMELA e+ claim

...even for unrealistically large boost factors (flux scales linearly with boost factor)

• L. Roszkowski, GGI, 9 Feb ’09 – p.29

The great tragedy of Science – the slying of a beautiful hypothesis by an ugly fact

T.H. Huxley

• L. Roszkowski, GGI, 9 Feb ’09 – p.30

One should never believe any experiment until it has been confirmed by theory

• A. Eddington
• L. Roszkowski, GGI, 9 Feb ’09 – p.30

Summary

unified SUSY models remain by far most attractive and well-motivated candidates for “new physics” SUSY neutralino remain by far most attractive and well-motivated candidate for dark matter

• L. Roszkowski, GGI, 9 Feb ’09 – p.31

Summary

unified SUSY models remain by far most attractive and well-motivated candidates for “new physics” SUSY neutralino remain by far most attractive and well-motivated candidate for dark matter very good prospects for discovery in DM direct searches & LHC

• L. Roszkowski, GGI, 9 Feb ’09 – p.31

Summary

unified SUSY models remain by far most attractive and well-motivated candidates for “new physics” SUSY neutralino remain by far most attractive and well-motivated candidate for dark matter very good prospects for discovery in DM direct searches & LHC direct detection: σSI

p

≃ 10−9±1 pb

already partially probed by current detectors... ...to be almost completely covered by planned 1-tonne detectors

• L. Roszkowski, GGI, 9 Feb ’09 – p.31

Summary

unified SUSY models remain by far most attractive and well-motivated candidates for “new physics” SUSY neutralino remain by far most attractive and well-motivated candidate for dark matter very good prospects for discovery in DM direct searches & LHC direct detection: σSI

p

≃ 10−9±1 pb

already partially probed by current detectors... ...to be almost completely covered by planned 1-tonne detectors

indirect detection generally somewhat less promising

...but large halo model dependence

• L. Roszkowski, GGI, 9 Feb ’09 – p.31

Summary

unified SUSY models remain by far most attractive and well-motivated candidates for “new physics” SUSY neutralino remain by far most attractive and well-motivated candidate for dark matter very good prospects for discovery in DM direct searches & LHC direct detection: σSI

p

≃ 10−9±1 pb

already partially probed by current detectors... ...to be almost completely covered by planned 1-tonne detectors

indirect detection generally somewhat less promising

...but large halo model dependence

Fermi/GLAST should see diffuse γ radiation from Galactic center

...if DM halo cuspy enough

• L. Roszkowski, GGI, 9 Feb ’09 – p.31

Summary

unified SUSY models remain by far most attractive and well-motivated candidates for “new physics” SUSY neutralino remain by far most attractive and well-motivated candidate for dark matter very good prospects for discovery in DM direct searches & LHC direct detection: σSI

p

≃ 10−9±1 pb

already partially probed by current detectors... ...to be almost completely covered by planned 1-tonne detectors

indirect detection generally somewhat less promising

...but large halo model dependence

Fermi/GLAST should see diffuse γ radiation from Galactic center

...if DM halo cuspy enough

PAMELA e+ result inconsistent with neutralino DM in unified SUSY

...astrophysical explanation (pulsars)? ...proton rejection poorer than assumed?

• L. Roszkowski, GGI, 9 Feb ’09 – p.31

when looking for truth...

• L. Roszkowski, GGI, 9 Feb ’09 – p.32

when looking for truth... look no further than (Bayesian) statistics

• L. Roszkowski, GGI, 9 Feb ’09 – p.32

Backup...

• L. Roszkowski, GGI, 9 Feb ’09 – p.33

• M. Schubnell
• L. Roszkowski, GGI, 9 Feb ’09 – p.34

• M. Schubnell

Pamela e+ excess consistent with mis-identifying 3 in 10,000 protons as positrons

• L. Roszkowski, GGI, 9 Feb ’09 – p.34