How to use a radiation monitor to reduce LISA noise levels
Diana Shaul1, Henrique Araújo1, Daniel Hollington1, Alberto Lobo2, Markus Schulte1, Tim Sumner1, Simon Waschke1, Peter Wass3
1 Imperial College London; 2ICE/CSIC and IEEC; 3University of Trento
High energy cosmic ray and solar particle fluxes will charge up the LISA test masses (TMs). This charge will result in spurious electromagnetic
forces acting on the TMs, disturbing their geodesic motion. The primary approach to minimise the impact of these forces is to discharge the TMs
using the photoelectric effect. Unfortunately, the flux and energy spectrum of these high energy particles varies over time and therefore it is not
easy to match charging and discharging rates, which would minimise the disturbances induced by charging. The gravitational reference sensor
(GRS) can be used to measure the average charge accumulated, but not the shorter term variations in the charging rate. A radiation monitor (RM)
can enable tracking of these changes.
We describe how a RM could be used to reduce the charging disturbances for LISA and the plans for use of the RM on LISA Pathfinder (LPF),
including an approach that could enable acceleration noise associated with charging to be effectively subtracted.
2.3 Minimum Aims for RM on LPF
1. INTRODUCTION
1.1 Charging Disturbances
•
Charge on the TM leads to Coulomb and Lorentz forces from interactions with
GRS conducting surfaces and IMF, respectively.
• These forces give rise to different types of disturbance:
1. Acceleration noise, due to fluctuations in e.g. voltage [1]
2. Modification of the effective stiffness describing TM-S/C coupling, due
to position dependence of Coulomb forces [1]
3. Coherent Fourier components, due to time dependence of the amount of
charge on the TM [2,3]
•
•
•
•
•
Establish Monte Carlo (GEANT [4, 5, 12], FLUKA [13, 14, 15]) TM and RM
charging simulation accuracy
Establish approximate GCR and SEP transfer functions between RM and TM
charge
Establish/limit PSD of GCR flux and investigate whether there are any
periodicities in the GCR flux in the LISA frequency band.
Establish the SEP flux enhancements distributions (temporal and fluence)
seen by RM
Demonstrate the closed loop charge control process and estimate gain factor
1.2 The Incident Flux
2.4 Additional Aim for LISA: Derive TM
charging rate and shot noise using RM
•
•
•
•
•
•
TM charging characteristics (net charging rate and charging shot noise)
depend on the incident particle flux and its energy spectrum [4]
Higher energy particles => higher charge multiplicity events => more noise
and higher net charging rates, compared with lower energy particles [4]
Solar Energetic Particle (SEP) energy spectra are softer than Galactic Cosmic
Ray (GCR) spectra => A given particle flux will result in different TM charging
characteristics, dependent on the proportion of SEP and GCR particles. [4]
The charging disturbances will also depend on the variability of the
incident flux over time. This may give rise to sharp or gradual changes or
periodicities in the charging rate, potentially resulting in spectral leakage,
modulation of the coherent Fourier components and the masking of true
signals in the LISA bandwidth.
Variations in flux:
• Solar Cycle: 11 year period; 50% difference in charging rate between solar
minimum and maximum [4, 5]; Gradual and sharp changes possible [6]
• Solar rotation: ~ 27 day period; ~ 1 – 5 % GCR flux modulation [6]
• Jovian synodic year: 13 months; <5% TM charging rate modulation [7]
• SEPs: ~ 1 day–1 week; ~100-70000% (rare) TM charging rate increase [4]
• Forbush Decreases: ~days; ~ few – 35% GCR flux modulation. [6]
• Other GCR modulations: ~<few% in ~mins – week [8, 9]; Periodic
fluctuations(?) [7, 10]
•
•
Accurate measurement of RM-TM transfer function for net charging rate and
charging noise could enable not only the coherent Fourier components but
also charging shot noise to be effectively subtracted from the science data, as
the RM would enable their independent and continuous measurement.
This is an ambitious aim as there is a high level of ambiguity in the transfer
function measurement. This is because it must be calibrated using the 2 direct
measurements of the TM charging rate and shot noise, compared with the RM
singles rate and the multi-channel coincidence deposited energy spectrum.
To break the degeneracy, multiple measurements are needed in as diverse
solar conditions as possible. On LPF, there is no real-time feedback between
RM and GRS and hence this calibration may be limited due to the difficulty in
predicting when a SEP will occur. However it should be possible for LISA.
2.4.1 Steps
•
•
•
Start with a RM-TM transfer function derived from Monte Carlo models
Recalibrate RM-TM transfer function in flight based on direct TM charging
rate/noise measurements
Ambiguity => iterate with each new direct TM measurement
1. Measurements = Synchronised GRS TM charging rate
(noise) measurement with UV lamps off and acquisition of
RM coincidence spectra
2. Scale the RM coincidence spectrum using the average RM
singles rate over the same period.
3. Split the RM to TM charging noise transformation matrix
into n segments, where n is the total number of direct TM
charging rate (noise) measurements. The optimum
positions of the segments will be derived using MC models.
4. Introduce n coefficients in the transformation matrix and
solve for these coefficients, using the scaled coincidence
spectra and direct TM charging measurements.
5. Repeat each time another suitable TM charging
measurement is made to iteratively improve the
transformation matrix.
6. To optimally improve this matrix, measurements should be
made in as different solar conditions as possible.
1.3 Charge Management
1. Charge measurement: Apply dither voltages to opposing electrodes and
measure resultant TM displacement => average charging rate. Accuracy
depends on the dither voltage amplitude, dither frequency, degree of
freedom, and integration time. Typically, an accuracy of 104e is reached in
~1 hour. This measurement does not give information on the charging
shot noise nor the short term variability in the average charging rate.
2. TM Discharge: Use UV light to discharge via the photoelectric effect.
Nominal science mode: closed loop control to match charging and
discharging rates as closely as possible, to minimise disturbances. [11]
2. THE RADIATION MONITOR
Schematic illustrating calibration of RM-TM transfer function
2.4.2 Direct measurement: TM charging rate, shot noise
•
2.1 Aims
•
•
•
•
•
•
Independent monitor of incident particle fluxes
2 Silicon PIN diodes in
Minimise/track disturbances due to charging
telescopic arrangement,
Help to manage disturbances
Match charging/discharging rates
Identify “DC” changes/coherent Fourier components
Subtract Fourier components and charging noise
Data : Coincidence
spectrum, 10 mins
integration
Singles rates, 10 secs
integration
2.2 LPF RM Design
(see e.g. [12] for more details)
•
•
•
•
•
Shielding to mimic TM shielding
Telescopic arrangement to enable SEP and GCR spectral discrimination
within ~1hr for events registering in both diodes
Minimum isotropic count rate >7c/s, set to ensure: recognise small changes
in flux associated with e.g. SEPs; RM shot noise ~ TM charging shot noise;
detect periodic modulation in flux before exceeds LISA noise
Maximum count rate: large SEP: ~1500 c/s (isotropic), ~ 100 (coincident)
Nominal time bin counter <30s (LPF: 1 mHz ≤ f ≤ 30 mHz)
References:
[1]
[2]
[3]
[4]
[5]
[6]
[7]
[8]
The TM charging rate and shot noise may both be measured by applying a
dither voltage to opposing electrodes and measuring the resultant TM
Accuracy of
Minimum
Maximum
Rough guide to LPF requirements for
measurement (e/s)
integration
integration
displacement. [16] sensitivity and integration time for
direct TM measurements in different
solar conditions
GCR, solar
quiet
Small SEP
Large SEP
Small
Forbush
Decrease or
similar GCR
decrease
Large
Forbush
Decrease
Solar
Rotation
Example measurement
accuracy for 1 day
integration and dither
voltage of 1V
Effective
charging
rate (noise)
0.6
Net
charging
rate
0.1
time (hours)
time (hours)
4
24x14
10
5000
1.5
10
5000
0.1
1
1
3.5
5
7
4
10.5
1
0.1
24
0.3
0.03
24x3.5
24x13
N.B. It still needs to be confirmed whether the LPF RM spectral
resolution is sufficient to distinguish variations in GCR spectrum
during mission lifetime.
2.5 RM improvements for LISA
•
•
•
•
Electron monitor to track flux changes due to Jovian flux/early SEP warning
Multiple, distributed RMs on LISA S/C to a/c for anisotropies in flux during
SEP events, Forbush decreases etc..
Real-time, on-board feedback between RM and GRS to: calibrate RM; match
charging and discharging rates; to benefit from early SEP warning
Improved spectral discrimination
Shaul DNA et al., Class. Quantum Grav. 22, S297 (2005).
Shaul DNA et al., International Journal of Modern Physics D 14, 51 (2005).
Shaul DNA et al., Class. Quantum Grav. 21, S647 (2004).
Araújo HM et al., Astroparticle Physics 22, 451 (2005).
Wass PJ et al., Class. Quantum Grav. 22, S311 (2005).
Jursa AS (ed.), Handbook of geophysics and the space environment, 4th edn., Air Force Geophysics Laboratory (1985).
Shaul DNA et al., 6th International LISA Symposium, AIP Conf. Proc. 873, 172 (2006).
Blake JB et al., in preparation (2008).
[9]
[10]
[11]
[12]
[13]
[14]
[15]
[16]
Quenby J., et al., JGR, in publication (2008)
Starodubtsev et al., Ann. Geophys 24, 779 (2006).
Shaul DNA et al., International Journal of Modern Physics D, in publication (2008).
Wass PJ, PhD thesis (2007).
Vocca, H., et al., Class. Quantum Grav. 22, S319 (2005).
Vocca, H., et al., Class. Quantum Grav. 21, S665 (2004).
Grimani, C. et al., Class. Quantum Grav. 22, S327 (2005).
Weber, W., Private Communication (2007).