DARK MATTER ON DEPARTMENT SCALE

Daniele Fantin (M. Merrifield, A. Green)University of Nottingham

Bologna, 2 April 2009

Summary

Dark Matter Candidates

Dark Matter Detection

State of art of N-body simulations

Alternative approaches (My research)

Daniele Fantin, University of Nottingham

Dark Matter Evidence

Daniele Fantin, University of Nottingham

Universe Energy Budget

Potential dark matter candidate

Optically dark: does not couple strongly with photons

Electrically neutral

Non-relativistic

Collisionless: in order to form extended halos

Stable: doesn’t decay on timescale shorter than age of the Universe

Daniele Fantin, University of Nottingham

Cold Dark Matter – Candidates

Non-baryonic matter

WIMPs (Weakly Interactive Massive Particles) (Lee & Weinberg, 77; Gunn et al, 78)

Neutralino (lightest supersymmetric particle )

Axions (Peccei & Quinn, 77; Weinberg, 78)

Daniele Fantin, University of Nottingham

Why WIMPs?Any stable WIMP in thermal equilibrium in the early Universewill have the right density at the present day to be the DM

Daniele Fantin, University of Nottingham

χ + χ ↔ U + Ū

1 32

1. High T: Efficient Creation/destruction

2. Destruction

3. Creation in overdense regions

Particle Colliders (LHC)

How can we detect WIMPs?

.

Generic signal: missing energy/momentumWon’t demonstrate the existence of DM

Daniele Fantin, University of Nottingham

Via products of annihilations (e.g. γ-rays, positrons, anti-protons,neutrinos) in high density regions.

Indirectly

Daniele Fantin, University of Nottingham

γ-rays: FERMI, HESS, MAGIC, VERITAS

Anti-matter: PAMELA,ATIC Neutrinos: IceCube, ANTARES

Dependence of signals on local dark matter distribution

Daniele Fantin, University of Nottingham

Via elastic scattering on detector nuclei in the lab.

χ+N χ+N

Solutions: go underground (mines)

Detect recoil energy via ionisation, scintillation and/or heat.

Problem: radioactivity

Directly

Daniele Fantin, University of Nottingham

ZEPLIN III

CDMSII DAMA

Daniele Fantin, University of Nottingham

The event rates in direct detection experiments depend on the DM density (and in some cases velocity) distribution.

Why is the DM Distribution important?

WIMP cross-section on proton

dR/dE ≈ σp ρχ ∫ f(v)/v dvvmin

∞

Differential event rate (per kg/day/KeV):

minimum WIMP speed whichcan cause a recoil of energy E.

WIMP speed distributionin rest frame of detector

local WIMP density

Daniele Fantin, University of Nottingham

To confirm the existence of DM we need to detect it .

WIMPs are a good dark matter candidate

They can be detected:

directly via elastic scattering in the lab

signals depend on ultra-local dark matter density and speed distribution

indirectly via annihilation products

signals depend on Milky Way density distribution in high density regions

Intro-Summary

Daniele Fantin, University of Nottingham

Event rate depends on dark matter distribution

The standard halo model:assumes Milky Way halo as isotropic, isothermal spherevelocity distribution is then Maxwellian

BUT “observed” and simulated halos are triaxial, anisotropic and contain substructure.

Halo Modelling

Moore et al, 04

Daniele Fantin, University of Nottingham

Actual predictions about f(v) based on very simple assumptions:

Maxwellian (Freese et al. 1988)

Multivariate Gaussian (Evans et al. 2000, Helmi et al. 2002)

Probably NOT valid in reality!!

Dark Matter Distribution

Daniele Fantin, University of Nottingham

How good is the assumption of a Maxwellian speed distribution?

Depends on the ultra-local (sub-mpc) WIMP distribution.

Which depends on how well-mixed the tidal debris from disrupted sub-halos is.

i) Ultra-local WIMP distribution is smooth, consisting of large number of streams. [Helmi, White & Springel,02; Vogelsberger et al,08]

ii) Ultra-local WIMP distribution consists of a finite number of streams [Stiff & Widrow,01 ; Moore et al., 04; Fantin, Merrifield & Green,08]

Daniele Fantin, University of Nottingham

First cosmological simulationable to resolve the building bricks of massive MW-like DM halo (10¹²M⊙) at z=0

Presence in the Phase S ofunderdense elongated streams formed by material removed from accreted subhalos

Substructures: Via Lactea - GHALO

Diemand et al, 08

800 kpc

40 kpc

Daniele Fantin, University of Nottingham

4 generations of substructures

Smooth emission from the main halo

Smooth emission from the subhalos

Substructures: AQUARIUS

Springel et al, 08

Daniele Fantin, University of Nottingham

Name Authors CodeParticle

mass(M⊙)

Softening(pc)

Number ofhalos

simulated

Aquarius Springel et al.

GADGET3(TreePM)

1.7 x 10³ 21 6

GHALO Stadel et al. PKDGRAV2 1.0 x 10³ 61 5

Via Lactea2 Diemand etal.

PKDGRAV2 4.0 x 10³ 40 1

Recent simulations of Milky Way-like halos

Daniele Fantin, University of Nottingham

Substructures

DistributionAbundanceMass ProfileAnnihilation signal

Phase-space distribution of DM

DM Halos: Open Questions

Daniele Fantin, University of Nottingham

The smallest halos resolved in sim are close to 10⁵ M⊙, while the mass of the smallest WIMP microhalos 10⁻⁶ M⊙ (Green et al., 2004)

Resolution in simulations ~ 100 pc, while the expected scales probed by direct detection experiments are 0.1-1 mpc

NEW APPROACHES REQUIRED!!!

Sim-Summary/Conclusions

Daniele Fantin, University of Nottingham

Method based on reverse integration process

Collision head-on between unbound system of particles and a galaxy

No numerical integration

First model of the ultra-fine structure of the DM halo in the solar neighbourhood

My Research

Daniele Fantin, University of Nottingham

Realistic gravity

Results in a single timestep

Orbits history can be calculated analytically

No numerical integration: quick

Exploration of parameter space with very high resolution

Positive Aspects

Daniele Fantin, University of Nottingham

No detailed quantitative/realistic comparison with Milky Way

Isochrone potential

Negative Aspects

Daniele Fantin, University of Nottingham

i. Set the IC for the satellite and the time in the past t0

at which it was at that locationii. Set the present-day PS coordinates of the detector

locationiii. Evolve analytically these coords. backwards in timeiv. Assume for the merging halo a Gaussian distributionv. Evaluate the initial PS density due to the satellite for

this PS locationvi. Repeat for a grid of v to map out the full velocity

distribution within the detector

Main Steps

Daniele Fantin, University of Nottingham

Evolution at t = 1.23 Gyr

Look at the difference in resolution!!!

Results

Daniele Fantin, University of Nottingham

fx

vx

fx

vx

fx

vx

t =13.6 Gyr (MW’s age):

Single Merger: Distribution Function

Halo perturbed Whole series of

peaks

Daniele Fantin, University of Nottingham

Distribution Function Evolution

Daniele Fantin, University of Nottingham

Fantin et al, 08

cosθ

v

Diagnostic for Directional Detectors

Cos θ = vy/v

Smooth background+

Evident features

Daniele Fantin, University of Nottingham

Fantin et al, 08

Many mergers at each timestep

Add to each merger a signal

Analysis of the final signal

Multiple Merger

cosθ

vDaniele Fantin, University of Nottingham

Merger Tree

• Merger tree of a MW-like halo

• Add f(v) at different z

• Look for the final velocity/angle distribution

Daniele Fantin, University of Nottingham

Multiple Merger: Angle Distribution

Daniele Fantin, University of NottinghamM(M⊙)

Time(Gyr)

10⁶

10⁸

10¹⁰

13.6 1.36 7.35 136

Merger Tree

Daniele Fantin, University of Nottingham

132

1. Relations between velocity components

2. Presence of shell structure

3. Presence of escape velocity

Fantin et al, in prep.

• Event rate in direct detection of DM depends on the Ultra-local spatial(velocity) distribution

• In this case N-body simulation cannot help us• New approaches are necessary to investigate • Presence of “features” in the velocity

distribution coming from merging events• Work is still ongoing

Final Summary

Daniele Fantin, University of Nottingham

Daniele Fantin, University of Nottingham

Any Question?