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The new magnetic field optimisation procedure of the nEDM experiment - - PowerPoint PPT Presentation

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The new magnetic field optimisation procedure of the nEDM experiment at PSI Elise Wursten On behalf of the nEDM collaboration Probing Fundamental Symmetries with UCN workshop, Mainz April 11, 2016 Contents Introduction Magnetic

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Elise Wursten

On behalf of the nEDM collaboration

Probing Fundamental Symmetries with UCN workshop, Mainz April 11, 2016

The new magnetic field optimisation procedure of the nEDM experiment at PSI

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Contents

  • Introduction
  • Magnetic field knowledge
  • CsM
  • Field maps
  • Variometer
  • Optimisation procedure
  • Results
  • Homogeneity of 𝐢𝑨
  • Ramsey visibility of 2015
  • Conclusion

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Goal

To optimise the magnetic field such that we gain in nEDM sensitivity by improving the visibility of the Ramsey curve 𝛽 = 𝛽0 𝑓

βˆ’ π‘ˆ

π‘ˆ2

while keeping systematic effects under control.

𝛽0: Initial polarisation (86%) π‘ˆ2: Transverse depolarisation time

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Introduction

What do we know?

 The transverse depolarisation time π‘ˆ2 is mainly

dependent on the homogeneity of the longitudinal component 𝐢𝑨

 whereas systematic effects are related to the transverse

component squared of the magnetic field πΆπ‘ˆ

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So we want to homogenise 𝐢𝑨 while keeping πΆπ‘ˆ

2 small

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Introduction

What do we need?

οƒΌ Coils to trim the field

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Introduction

What do we need?

οƒΌ Coils to trim the field ? Vector information about the magnetic field shape

This would we easy if we had vector magnetometers, but we don’t have vector magnetometers… Or do we?

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Magnetic field knowledge

We have 16 Cs magnetometers installed above and below the precession chamber:

 Probe the field locally  Scalar sensors See talk M. Kasprzak

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Magnetic field knowledge

We have 16 Cs magnetometers installed above and below the precession chamber:

 Probe the field locally  Scalar sensors

𝐢 = 𝐢𝑨 + πΆπ‘ˆ

2

2𝐢𝑨 + β‹― β‰ˆ 𝐢𝑨 Homogenisation using only CsM was not really successful:

 No control over πΆπ‘ˆ

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Magnetic field knowledge

Field maps from mapping campaign in 2014:

 Vector fluxgate magnetometer mounted on a mapping

device

 Maps of main field 𝐢0, trimcoils,…

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Magnetic field knowledge

Field maps from mapping campaign in 2014:

 Vector fluxgate magnetometer mounted on a mapping

device

 Maps of main field 𝐢0, trimcoils,…

Homogenisation using only maps was not really successful:

 Accuracy is not high enough to get a reliable estimate of

𝐢0𝑨

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Magnetic field knowledge

Combine CsMs and field maps: variometer mode Apply a known transverse field additional to the main field and measure the response in the magnitude of the CsMs

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Magnetic field knowledge

Variometer mode:

B0

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Magnetic field knowledge

Variometer mode:

B0 BDC x-direction

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Magnetic field knowledge

Variometer mode:

B0 BDC x-direction

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Magnetic field knowledge

Variometer mode:

B0 BDC x-direction

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Magnetic field knowledge

Variometer mode:

B0 BDC x-direction

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Magnetic field knowledge

Variometer mode:

B0 BDC x-direction

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Magnetic field knowledge

Variometer mode:

B0 BDC y-direction

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Magnetic field knowledge

Variometer mode:

B0 BDC y-direction

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Magnetic field knowledge

Variometer mode:

B0 BDC y-direction

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Magnetic field knowledge

Variometer mode:

B0 BDC y-direction

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Magnetic field knowledge

Variometer mode:

B0 BDC

Fit function: Parabola!

y-direction

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Magnetic field knowledge

Fit function is a simple parabola Extract 𝐢0𝑦 and 𝐢0𝑧 from 𝐢0 βˆ™ 𝐢1 and 𝐢0 βˆ™ 𝐢2

  • Using 𝐢0𝑨 =

𝐢0 from CsM

  • 𝐢1 and 𝐢2 from field maps

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Magnetic field knowledge

Variometer mode

Precision:

  • Ranges from 5pT to tens of pT for 30s measurement time

Accuracy:

  • Limited by knowledge of the fields produced by the two coils
  • Absolute values could be off by tens of nT

πœ€πΆ0𝑦 β‰ˆ 𝐢0𝑨 πœ€πΆ1𝑨 𝐢1𝑦 β‰ˆ 1000 πœ€πΆ1𝑨 50 = 20 πœ€πΆ1𝑨

  • But differences (with common 𝐢0) are accurate up to a few %

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Magnetic field knowledge

Measure the field of the trimcoils: example BTC

Bx (nT) By (nT) Bz (nT)

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Optimisation procedure

Measure the field of each trimcoil with the variometer mode as in the previous example => response matrix

1.

Measure the instantaneous field

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Optimisation procedure

Measure the field of each trimcoil with the variometer mode as in the previous example => response matrix

1.

Measure the instantaneous field

2.

Minimise least squares function such that a) 𝐢𝑨 β†’ 𝐢 b) 𝐢𝑦 β†’ 0 and 𝐢𝑧 β†’ 0 c) and the trimcoil currents are regulated. Calculate πΆπ‘ˆ

2 based on the fluxgate maps of 2014

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Optimisation procedure

Measure the field of each trimcoil with the variometer mode as in the previous example => response matrix

1.

Measure the instantaneous field

2.

Minimise least squares function such that a) 𝐢𝑨 β†’ 𝐢 b) 𝐢𝑦 β†’ 0 and 𝐢𝑧 β†’ 0 c) and the trimcoil currents are regulated. Calculate πΆπ‘ˆ

2 based on the fluxgate maps of 2014

3.

Assign a large weight to the Bz term, fix the regularisation parameter and scan over (small) weights for the Bx and By

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Optimisation procedure

Measure the field of each trimcoil with the variometer mode as in the previous example => response matrix

1.

Measure the instantaneous field

2.

Minimise least squares function such that a) 𝐢𝑨 β†’ 𝐢 b) 𝐢𝑦 β†’ 0 and 𝐢𝑧 β†’ 0 c) and the trimcoil currents are regulated. Calculate πΆπ‘ˆ

2 based on the fluxgate maps of 2014

3.

Assign a large weight to the Bz term, fix the regularisation parameter and scan over (small) weights for the Bx and By

4.

Select a solution with low πΆπ‘ˆ

2 and small predicted spread in Bz.

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Results

Bz before Bz after

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Results

Visibility of nEDM runs of 2015:

2014 Typically between 0.45 and 0.6 2015 Typically between 0.7 and 0.8

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30%

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Conclusion

 Vector information from CsM in variometer mode  We have a successful routine to homogenise 𝐢𝑨 while

keeping πΆπ‘ˆ

2 under control  We report an increase of 30% in nEDM sensitivity!

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