1.1.

FIP Image Sensor Signal Flow

The FIP imaging system will feature a new kind of image sensor comprised of arrays of MKIDs or microwave superconducting quantum interference device (SQUID) multiplexed TES resonator elements (pixels). Arrays of the latter type of sensor are the current baseline for the instrument,¹ employing 7957 pixels to be exact. Currently, four groups of $\sim 2000\text{pixels}$ each are output from the image sensor as RF signals that are amplified by high electron-mobility transistor-based amplifiers. Each signal is 4 GHz in bandwidth and will be located from 4 to 8 GHz in RF frequency. The image sensor also requires detector bias signals, fluxramp modulation signals, and feedback signals to operate. The flow of input and output signals to and from the detector is shown in Fig. 2. The task of the FIP readout electronics subsystem is to acquire and process all four image sensor output signals and generate the feedback, bias, and fluxramp signals required for operation. If MKIDs are used in lieu of TES detectors, then the fluxramp modulation signals are not required.

Fig. 2

Detector input and output signals for the FIP instrument. All detector pixels are arranged in four groups of $\sim 2000$ each that are passed on to a HEMT amplifier. The signals occupy a 4 GHz bandwidth centered at 6-GHz RF. The detector array also requires a RF comb signal for feedback, as well as fluxramp modulation (only if TES detectors are used) and detector bias signals.

1.2.

MKID Signal Processing

MKIDs are a type of cryogenic superconducting photon detector first developed at the California Institute of Technology and NASA Jet Propulsion Laboratory in 2003⁴ (Fig. 3). These devices are used for high-sensitivity astronomical detection of electromagnetic frequencies ranging from the far-infrared to x-rays. Impinging photons incident on a strip of superconducting material break Cooper pairs and create excess quasiparticles. The kinetic inductance of the superconducting strip varies inversely with the density of Cooper pairs, and thus the kinetic inductance increases upon photon absorption. This inductance is combined with a capacitor to form a microwave resonator modeled as an equivalent LC tank circuit, with a resonant frequency that varies with the absorption of photons (Fig. 4). An imaging array is formed by connecting many thousands of resonators in parallel along a common transmission line. Since each resonator can be designed to have its own unique starting resonant frequency and corresponding bandwidth, the resonator is said to be frequency-division multiplexed as a result (Fig. 5). Therefore, resonator array readout is accomplished by tracking each resonator frequency response in the transmission line and mapping amplitude, phase, and frequency variation to the amount of kinetic inductance present and, hence, the properties of the incident photon.

Fig. 3

MKID device, highlighting the lithographically etched resonator arrays along a single feedline.

Fig. 4

When an incident photon interacts with the MKID device, the resonator frequency and phase responses are shifted. Measuring this shift is the job of the readout system, and the astrophysical image pixel to be read out is embedded in this shift information.

Fig. 5

Equivalent parallel LC circuit representation for a MKID array of $n$ resonators and its corresponding frequency response ($S_{21}$ parameter). Figure from Day et al.⁴

The prevailing technique for array readout digitally synthesizes a comb signal, feeds it to the array, and reads back the resulting signal for processing.⁵ The comb signal consists of a linear combination of sinusoidal tones that are individually set to the corresponding initial frequencies of each detector in the array. As kinetic inductance occurs as a result of incident photons, each sinusoid in the comb signal is modified by its corresponding detector. The resultant output signal is fed back to the electronics system, where its spectrum is estimated, and the modification of each sinusoidal element in the feedback comb signal is computed. Embedded in the output spectra of the instrument is the astrophysical image to be synthesized via ground processing.

1.3.

TES Signal Processing

A TES, developed in the 1940’s by Andrews et al.,⁶ is a very sensitive cryogenic energy detector made from a superconducting film held at its phase transition temperature. In this temperature region, a very small change in temperature leads to a very large change in film resistance. An incident photon heats this element, resulting in the resistance change. The superconducting element is inductively coupled to a SQUID resonator array, which is frequency division multiplexed similarly to MKID arrays. Inductively coupling TES devices to a microwave multiplexed SQUID array allows for thousands of TES devices to be utilized simultaneously and share a common RF feedline (Fig. 10).

Readout of TES devices, once multiplexed by microwave SQUID resonators, are read out similarly to MKIDs. The common element between MKID and microwave SQUIDS is the use of a comb signal to excite the microwave resonator array and the use of a spectrometer to measure the resultant spectrum of the comb signal. Compared with MKIDs, TES devices require additional linearization. This is accomplished by means of flux ramp modulation. In this technique, a secondary set of signals are sent to the TES devices so that their responses can be linearized, whereas the primary set of signals are the individual sinusoidal components of the comb signal that address each microwave SQUID resonator element. In this paper, the terminology TES implies frequency-domain SQUID multiplexed variety of TES detectors (Fig. 6).

Fig. 6

Microwave-multiplexed TES schematic. Figure from Becker et al.⁷

3.1.

Frequency Plan

Design of the FIP detector readout electronics system starts with careful consideration of the frequency plan, i.e., the arrangement of the detector signals in the microwave frequency range and the plan for how they arrive at the digital system for subsequent processing. Currently, both TES and MKID detector array designs under consideration for FIP will be designed to operate in the 4 to 8 GHz RF frequency range. This requires all signal processing to synthesize and acquire signals in this range. The Xilinx RFSoC is aptly suited for this task since it has an array of on-chip RF-Sampling ADCs and DACs that sample up to two Nyquist zones and operate at 4 GSPS.

However, the Nyquist bandwidth of each on-chip data converter on the RFSoC under consideration is a maximum of 2 GHz for the ADCs and 3 GHz for the DACs. This means that the entire 4-GHz bandwidth of either the MKID or TES detector array requires 2 DACs and 2 ADCs each for processing. One RFSoC chip therefore is capable of processing 16 GHz of bandwidth; therefore four different groups of 4 GHz detector arrays can be read out simultaneously using only one device. To capture the full 4 GHz of any detector group, while minimizing the amount of required RF analog electronics required for operating in the 4 to 8 GHz band, the bands must be split before interfacing to the RFSoC.

The scheme to accomplish this is shown in Fig. 9. Currently, a group of roughly 2000 microwave resonators (baseline TES or MKIDs) occupy 4 GHz of bandwidth and are presented to the readout system over a single transmission line following a HEMT amplification stage.¹ The full band signal needs to be downconverted and split into two separate 2 GHz-wide bands to be acquired by the on-chip ADCs of the RFSoC. Depending on which Nyquist zone the resulting 2-GHz signal lands—either first or second, a single ADC channel of the RFSoC acquires it since all channels operate at 4 GHz.

Fig. 9

Detector array frequency plan. The detector resonators live within the 4- to 8-GHz RF bandpass frequency in (a). This signal is downconverted to baseband (0 to 4 GHz), rejecting the image frequency in (b). In (c) through (f), second-Nyquist zone sampling is employed to further downconvert and acquire each signal portion, filtering out image signals along the way.

FIP outputs four 4 GHz signals, therefore eight ADC channels are required, and the RFSoC has exactly this many ADC inputs to accommodate this. Similarly, the RFSoC has complimentary DACs that can operate at 6 GHz, and they can be used to synthesize the excitation signals that the MKIDs and TES arrays require for readout.

The functional block diagram for the FIP detector readout subsystem is given in Fig. 10. Reading the signal flow from left to right, the TES array (and similarly, the MKID array) produces the RF electrical signals that are captured by all subsequent electronics.

Fig. 10

FIP detector subsystem functional block diagram. Four RF signals corresponding to $\sim 8000$ resonators (TES or MKID) interface the input of the system and are processed. Simultaneously, the detector comb signals are synthesized digitally and are fed back via four output RF signals. Two additional sets of outputs consist of flux ramp modulation signals required only for TES detectors for linearizing the array and detector bias currents. Detector array spectra as well as any pertinent system monitoring telemetry are output to the spacecraft computer.

The baseline concept for FIP’s image sensor consists of 7957 TES elements, configured as a rectangular array ($109\times 73$), and output over four RF transmission lines, with each being 4 GHz in bandwidth and living in the 4- to 8-GHz RF frequency range. As a result, these four RF signals need to be connected to corresponding HEMT amplifiers and transmitted downstream for readout. The required bandwidth of the FIP detector array is near 16 GHz to cover all TES elements.

The detector array configuration of the FIP instrument maps to a single RFSoC device with the addition of a little RF processing to subdivide the total bandwidth into eight 2 GHz sections. The four detector signals are passed to a set of mixers that downconvert and split each 4 GHz signal into a pair of 2 GHz signals as shown in Fig. 11, which are interfaced to two RFSoC RF input channels at a time. All input signals are digitized in parallel. The RFSoC FPGA portion computes all spectra and generates the variable-frequency comb function that is sent back to the detector array. Detector bias and fluxramp modulation signals are also generated by the RFSoC and are sent to the detector array. The RFSoC also contains two different multicore processors on-chip, which can carry out all necessary software functions in the signal processing chain. These functions include input signal calibration, interfacing the instrument to the spacecraft via SpaceWire, tone tracking algorithm implementation,⁵ and general-purpose board functions such as telemetry and health monitoring, limit checking, and any signal processing intelligence that is too cumbersome to implement in FPGA logic.

Fig. 11

Each of the four RF input signals $x_k(t)$ are mixed down to baseband using a 2-GHz LO and subsequently lowpass filtered to 4 GHz. The resulting signal is split into upper and lower spectral halves, which are acquired for subsequent signal processing, according to the frequency plan.

Utilization of the RFSoC, or any ASIC that has RF-Sampling data converters, simplifies the required radio-frequency and intermediate-frequency circuitry. For FIP, only a single RF-to-baseband downconversion stage is required, along with a two-channel RF filterbank with gain and filtering stages. The RF-to-baseband downconversion stage also incorporates any AC-coupling and anti-alias filtering required for interfacing the RFSoC input. Similarly, the RFSoC output stage requires baseband-to-RF upconversion, gain, and RF-combining circuitry.

3.2.

Digital Spectrometer

A digital filter bank is a collection of related digital filters that share either a common input or a common output signal.⁸ There are two types of filterbanks—synthesis and analysis. An analysis filterbank is used as the spectrometer processor for the FIP instrument in much the same way that the same type of filter bank was used in the Soil Moisture Active Passive Mission, launched in 2015.⁹

The filterbank consists of a polyphase finite-impulse response filter that is used to shape every frequency bin of the spectrometer. The polyphase filter employs a 50% overlap factor so that each analysis bin overlaps adjacent bins and no signal droop occurs between frequency bins. A standard fast Fourier transform is then applied to the polyphase-filtered data stream, averaged, and transmitted to the command and data-handling subsystem. The filterbank spectrometer operates in real-time, over the entire 4-GHz bandwidth of signal originating from each of HEMT amplifiers.

The digital spectrometer used for FIP signal processing is highly parallelized. The first level of parallelization is due to the detector array signals themselves being fed into eight parallel RF input ports of the RFSoC. All 7957 pixels, occupying a total of 16 GHz of bandwidth, are fed into 8 on-chip ADCs that are all sampling at 4 GSPS. The second level of parallelization comes from the ADCs themselves. The embedded data converters must demultiplex the high-speed 4 GSPS 12-bit data stream into 16 parallel streams of data clocked at the FPGA fabric rate of 250 MSPS. Since data are not re-interleaved, all algorithms that operate on the data must be developed to operate on the parallel data stream. Using the polyphase filterbank approach⁸ in Chapter 4, parallel processing is straightforward, linear, and identical for every ADC input stream. Implementation of the polyphase filterbank spectrometer, comb function generation, and array signal processing functions are shown in Fig. 12.

Fig. 12

Implementation of the polyphase filterbank spectrometer, comb function generation, and array signal processing functions implemented on the Xilinx RFSoC processor.

Currently, a hand-coded very high-speed integrated-circuit hardware description language (VHDL) implementation of our 50% weighted-overlap and add filterbank, with 1024 frequency bins per every 2 GHz of spectrum, utilizes 52% of the total logic of the RFSoC. This design is not yet optimized to use the majority of the DSP48 macros on the device; therefore, this utilization figure will decrease. Currently, our composite filterbank spectrometers, which is split into eight independent filterbank spectrometers, covers a total of 8192 frequency bins. This number will increase as the VHDL is optimized for performance.

3.3.

FIP Data Rate

The primary output data product of the FIP instrument is a vector of 7957 12-bit numbers corresponding to the comb frequency amplitudes that are modified by the TES or MKID resonators. The signal processor produces 300 of these per second to maintain a 150-Hz scientific bandwidth. Therefore, the output data rate is the product of these quantities, or 7957 amplitudes × 300 Hz readout × 12 bits/amplitude = 28.7 Mbps. A 12-bit resolution, corresponding to a 72-dB dynamic range for each detector value, is sufficient to capture the detector’s photon noise-limited dynamic range.