Iain Sedgwick ^1* Cornelia Beatrix Wunderer ^2,3* Jiaguo Zhang ^4*

• ¹ Rutherford Appleton Laboratory, Didcot, United Kingdom
• ² German Electron Synchrotron, Helmholtz Association of German Research Centres (HZ), Hamburg, Hamburg, Germany
• ³ Center for Free-Electron Laser Science (CFEL), Hamburg, Hamburg, Germany
• ⁴ Paul Scherrer Institut (PSI), Villigen, Switzerland

The dramatic improvement in photon sources such as Free Electron Lasers (FELs) and Diffraction-Limited Storage Rings (DSLRs) over the last two decades has significantly expanded the range of science that is possible at these facilities. In order to take full advantage, detectors with similarly advanced capabilities are needed. Developing such detectors, however, is extremely challenging; they typically take a decade to deploy and often require several iterations, necessitating considerable resources. Their integration in experiments is also not trivial. As a result, many experiments are still detector limited, as described by Gruner et al.. Therefore, we have solicited papers on progress in this field. This editorial includes an overview of key challenges reported by the authors and new technologies they described that help overcome them. Of course, many other developments are underway; here, we largely focus on those submitted by the authors. The development of new detectors for photon science presents several challenges. The first is to meet the well-documented (1, 2) performance increase of new FELs and DLSRs. Second, photon science detectors must accommodate a wide range of experimental operating modes (Gruner et al., Andresen et al., Armstrong et al.). Even within a single facility, detectors supporting a variety of applications are required (Graafsma et al.). They are also frequently adapted for experiments for which they were not originally optimized, and are increasingly fitted with multiple sensor types to address the need for wider X-ray energy ranges. Designing with all these possible cases in mind is difficult and time-consuming -and can lead to compromise solutions not optimised for any one experiment.The range of requirements is not entirely open-ended, as some specifications have practical limits, and advancements in radiation sources can even lead to detector consolidation. For instance, at higher photon energies, there is a sensible limit to pixel size related to absorption length of secondary particles (Frojdh et al.), and the increasing brilliance of DLSRs requires event or frame rates comparable to the CW-pulse repetition rates of future FELs, suggesting that similar detectors may be suitable for both (Graafsma et al.).Despite this convergence in frame rate requirements, however, specific needs do persist for much higher frame rates (GHz) for burst imaging (Gruner et al.) and much slower, low-noise imaging (sub-Hz) for RIXS (Andresen et al.). This, and the fact that high repetition-rate CW operation at some facilities remains a long-term project, suggests requirements will remain divergent at least in the near future.The increase in performance of modern detectors also poses challenges for downstream systems. Multimegapixel detectors with MHz frame rates generate vast quantities of data. This needs not just to be captured but calibrated and stored for many years. The calibration itself is a major task, since for some detectors the number of parameters can exceed 10 9 (Sztuk et al.). The associated difficulty can be strongly impacted by decisions taken at the detector development stage many years earlier (Pennicard et al.). The need for reproducibility of calibrations years later further adds to the complexity, since it must also be possible to apply more advanced calibrations as the understanding of an installed detector improves whilst still re-producing older results (Schmidt et al.).A "gold standard" would be an integrating sensor with single-photon resolution which could convert to photon counts and compress to the Poisson limit for ultimate data reduction with zero science loss (Frojdhet al., Pennicard et al.).When addressing these challenges, it's crucial to identify the primary bottleneck in the system, which could be anywhere from sensor to data transfer. If this bottleneck cannot be mitigated, optimizing other parts of the system for higher performance may be inefficient or unnecessary. The need for detectors to span an energy regime from 10 1 to 10 5 eV pushes both hard and soft X-ray sensor developments. For hard X-rays, in addition to GaAs, Ge, and CdTe, research into the manufacture and use Cutting-edge commercial designs and even other scientific fields use much smaller nodes (3) than the 65 nm and 110 nm used here. However, Commercial effort focuses on reducing the cost per transistor whereas for large area detector applications, the cost per area is most important, and this tends to increase as the node shrinks (4). This may eventually limit what node is used for large-area applications. In addition, Frontiers while smaller nodes are superior for digital circuitry, for analog circuits larger nodes have advantages as well. Older nodes may continue to be employed, or the use of chiplets to best match cost and performance may become more common.New CMOS functionalities beyond node size also allow improved performance. However, these are sometimes not available for small-batch developments. A prominent example is 3-D integration, which has been commercially common for many years but has only been sporadically employed for photon science.Whether such technologies will permit higher-performing detectors in the future will likely be a question of access.Advances can also be made when commercial detector systems in other fields turn out to be suitable for photon science use. In some cases, in particular in terms of cost and time, these constitute a viable or even better alternative to custom-developed systems.Handling the vast amount of data produced by modern detectors is a particularly critical area, discussed in greater detail in the next section. Data reduction and processing is a vast field which, even 10-15 years ago, was -at least in photon science -firmly linked to "data analysis" which occurred long after data was first recorded. Since then, source ), but it is clear that ML will become increasingly common.From a detector developers' viewpoint, the key point to realize is that the complexity of data processing and calibration depends largely on the detector design (Pennicard et al.). ASIC design decisions in particular, often among the first taken in the system design, can have a significant impact on the complexity of later data reduction processes. With ever-increasing raw data volumes, a system that delivers the most science content per recorded Gigabyte in a variety of scientific contexts is likely to become the most sought-after. Furthermore, simplifying system integration is also critical, and this is treated in the next section.