We have characterized and mapped the electrical cross talk (ECT) of a frequency division multiplexing (FDM) system with a transition edge sensor (TES) bolometer array, which is intended for space applications. By adding a small modulation at 120 Hz to the AC bias voltage of one bolometer and measuring the cross talk response in the current noise spectra of the others simultaneously, we have for the first time mapped the ECT level of 61 pixels with a nominal frequency spacing of 32 kHz in a 61 × 61 matrix and a carrier frequency ranging from 1 MHz to 4 MHz. We find that about 94% of the pixels show an ECT level of less than 0.4%. Only the adjacent pixels reach this level, and the ECT for the rest of the pixels is less than 0.1%. We also observe higher ECT levels, up to 10%, between some of the pixels, which have bundled long, parallel coplanar wires connecting TES bolometers to inductor-capacitor filters. In this case, the high mutual inductances dominate. To mitigate this source of ECT, the coplanar wires should be replaced by microstrip wires in the array. Our study suggests that an FDM system can have a relatively low ECT level, e.g., around 0.4% if the frequency spacing is 30 kHz. Our results successfully demonstrate a low electrical cross talk for a space FDM technology.

@en

Understanding and predicting surface movement is important both technically and for social reasons. The shallow processes contributing to subsidence include construction works, peat oxidation, clay compaction, and groundwater withdrawal; deep causes are hydrocarbon and salt production. We describe an inversion procedure we have devised to disentangle the deep and shallow causes of surface movement. It employs a Bayesian inversion scheme, using forward models and other ‘a priori’ information about shallow and deep compaction. Parameter estimation thus takes place at two different depths, thereby disentangling the deep and shallow compaction processes responsible for surface movement. The uncertainty in the surface measurements and ‘a priori’ estimates is naturally incorporated. Furthermore, spatial and temporal correlations can be taken into account through inclusion of the covariance matrix. The inversion scheme is demonstrated for two synthetic cases. The first combines a compacting gas field and a compacting shallow peat layer. We demonstrate that assumptions on the shape of the subsidence bowl are not necessary. We also show how neglecting either deep or shallow causes of subsidence can produce spurious results. The advantage of using the ‘a priori’ estimates of the compaction and the covariance matrix obtained by Monte Carlo simulations is demonstrated with a second synthetic example involving two polders and different depths of their water table. A robust solution is obtained for each polder unit, while a simpler (and faster) ‘a priori’ estimate based on the expected average clay thickness fails to reproduce the actual compaction. Monte Carlo simulations can also be applied to compaction in depleting gas reservoirs. Information on spatial correlations is often available, even when the absolute values of the ‘a priori’ compaction data are quite uncertain. Explicitly incorporating such ‘a priori’ known spatial correlations improves the result significantly.@en