Measuring the dark matter mass in spite of astrophysical - - PowerPoint PPT Presentation

measuring the dark matter mass in spite of astrophysical
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Measuring the dark matter mass in spite of astrophysical - - PowerPoint PPT Presentation

Measuring the dark matter mass in spite of astrophysical uncertainties Bradley J Kavanagh University of Nottingham Based on work with Anne Green and Mattia Fornasa: B J Kavanagh and A M Green, PRL 111 (2013) 031302 [arXiv:1303.6868] B J


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Measuring the dark matter mass – in spite of astrophysical uncertainties

Bradley J Kavanagh University of Nottingham

Based on work with Anne Green and Mattia Fornasa: B J Kavanagh and A M Green, PRL 111 (2013) 031302 [arXiv:1303.6868] B J Kavanagh, PRD 89 (2014) 085026 [arXiv:1312.1852] M Fornasa, A M Green and B J Kavanagh (2014) [arXiv:1407.XXXX] Astroparticle Physics 2014, Amsterdam 23/06/2014

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Speed distribution uncertainties

SHM SHM + 30% dark disk Stream

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Possible approaches

  • Incorporate uncertainties in SHM parameters
  • Attempt to measure from the data (assuming a

particular value for )

  • Write as a large number of steps and optimise

the step heights

  • Write down a general parametrisation for and fit

the parameters to data

Peter [arXiv:1103.5145] Strigari & Trotta [arXiv:0906.5361] Fox, Liu & Weiner [arXiv:1011.1915] Frandsen et al. [arXiv:1111.0292] Feldstein & Kahlhoefer [arXiv:1403.4606] See talk by Felix Kahlhoefer this afternoon

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A general parametrisation

N=6

Polynomial basis functions Parameters

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Impact of uncertainties

Generate mock data for 3 future experiments (Xe, Ar, Ge), for a stream distribution function. Reconstruct assuming: (correct) stream distribution (incorrect) SHM distribution

Best fit Benchmark

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Impact of uncertainties

Generate mock data for 3 future experiments (Xe, Ar, Ge), for a stream distribution function. Reconstruct assuming: (correct) stream distribution using our parametrisation

Best fit Benchmark

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The cross-section degeneracy

Minimum WIMP speed accessible with Xenon for and

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WIMP mass reconstruction

  • Wide range of input WIMP

masses

  • Range of input speed

distributions

  • Finite backgrounds and

energy resolution

  • Data including Poisson

noise

Ideal experiments Finite B/G and energy resolution

WIMP mass accurately reconstructed for :

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Incorporating IceCube

WIMP capture rate in the Sun due to species i: WIMP capture rate in the Sun due to species i: Low speed WIMPs preferentially captured NB: Need to include SD scattering

ER = [5, 45] keV

“down-scatter rate” IceCube detector is sensitive to neutrinos from annihilating WIMPs captured in the Sun

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Reconstruction without IceCube

Benchmark: , annihilation to , SHM + dark disk distribution , Reconstructed using polynomial parametrisation (N=6)

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Benchmark: ,

Reconstruction with IceCube

annihilation to , SHM + dark disk distribution , Reconstructed using polynomial parametrisation (N=6)

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Reconstructing the speed distribution

Reconstructed using polynomial parametrisation... Without IceCube data With IceCube data Benchmark is: , SHM + dark disk distribution

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Conclusions

  • Astrophysical uncertainties are important in direct

detection analysis

  • We propose a new parametrisation:
  • WIMP mass can be recovered from direct detection

experiments with no assumptions about the speed distribution

  • Including IceCube data means the WIMP mass, SI and

SD cross sections and speed distribution can all be reconstructed

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Back-up slides

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Number of basis functions

Double-peak distribution function

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Choice of basis function

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Reconstructing the speed distribution

Reconstructed using polynomial parametrisation... With IceCube data Benchmark is: , SHM distribution