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Photonic integrated circuits (PICs) operating at cryogenic temperatures are fundamental building blocks required to achieve scalable quantum computing and cryogenic computing technologies 1 , 2 . Silicon PICs have matured for room-temperature applications, but their cryogenic performance is limited by the absence of efficient low-temperature electro-optic modulation. Here we demonstrate electro-optic switching and modulation from room temperature down to 4 K by using the Pockels effect in integrated barium titanate (BaTiO 3 ) devices 3 . We investigate the temperature dependence of the nonlinear optical properties of BaTiO 3 , showing an effective Pockels coefficient of 200 pm V −1 at 4 K. The fabricated devices show an electro-optic bandwidth of 30 GHz, ultralow-power tuning that is 10 9 times more efficient than thermal tuning, and high-speed data modulation at 20 Gbps. Our results demonstrate a missing component for cryogenic PICs, removing major roadblocks for the realization of cryogenic-compatible systems in the field of quantum computing, supercomputing and sensing, and for interfacing those systems with instrumentation at room temperature. The integration of barium titanate thin films with silicon-based waveguides enables the operation of efficient electro-optic switches and modulators at temperatures as low as 4 K, with potential applications in quantum computing and cryogenic computing technologies.

Photonics offers exciting opportunities for neuromorphic computing. This paper specifically reviews the prospects of integrated optical solutions for accelerating inference and training of artificial neural networks. Calculating the synaptic function, thereof, is computationally very expensive and does not scale well on state-of-the-art computing platforms. Analog signal processing, using linear and nonlinear properties of integrated optical devices, offers a path toward substantially improving performance and power efficiency of these artificial intelligence workloads. The ability of integrated photonics to operate at very high speeds opens opportunities for time-critical real-time applications, while chip-level integration paves the way to cost-effective manufacturing and assembly.

Neuromorphic systems are designed with careful consideration of the physical properties of the computational substrate they use. Specifically neuromorphic engineers often exploit physical phenomena to directly implement a desired functionality, enabled by ``the isomorphism between physical processes in different media'' (Douglas, 1995). This bottom-up design methodology could be described as matching computational primitives to physical phenomena. In this paper we propose a top-down counterpart to the bottom-up approach to neuromorphic design. Our top-down approach, termed `bias matching', is to match the inductive biases required in a learning system to the hardware constraints of its implementation; a well-known example is enforcing translation equivariance by tying weights (replacing vector-matrix multiplications with convolutions). We give numerous examples from the literature and explain how they can be understood from this perspective. Furthermore we propose novel network designs based on this approach in the context of collaborative filtering. Our simulation results underline our central conclusions: Additional hardware constraints can improve the predictions of a Machine Learning system and understanding the inductive biases that mediate these performance gains can be useful in finding applications for a given constraint.

A novel class of programmable integrated photonic circuits has emerged over the past years, strongly driven by approaches to tackle unsolved computing problems in the optical domain. Photonic neuromorphic and quantum computing are examples of optical systems implemented in complex photonic circuits, which are reconfigured before and during operation. However, a key building block to enable efficient reconfigurable optical network architectures is still missing: a non-volatile optical phase shifter. Here we demonstrate such an element—compatible with silicon photonics—based on the monolithic integration of BaTiO3 thin films with silicon waveguides. By manipulating ferroelectric domains in BaTiO3 with electrical control signals, we achieve analogue and non-volatile optical phase tuning with no absorption changes. We demonstrate an eight-level long-term-stable photonic device with non-destructive optical readout and switching energy as low as 4.6 pJ. With our results, an analogue non-volatile photonic element is added to the integrated photonics toolbox, enabling a new generation of power-efficient programmable photonic circuits.Researchers demonstrate a multilevel non-volatile phase shifter memory that is based on the monolithic integration of BaTiO3 thin films and silicon waveguides. By manipulating ferroelectric domains in BaTiO3 with electrical control signals, they achieve analogue and non-volatile optical phase tuning.

Integrated electrical and photonic circuits (PIC) operating at cryogenic temperatures are fundamental building blocks required to achieve scalable quantum computing, and cryogenic computing technologies. Optical interconnects offer better performance and thermal insulation than electrical wires and are imperative for true quantum communication. Silicon PICs have matured for room temperature applications but their cryogenic performance is limited by the absence of efficient low temperature electro-optic (EO) modulation. While detectors and lasers perform better at low temperature, cryogenic optical switching remains an unsolved challenge. Here we demonstrate EO switching and modulation from room temperature down to 4 K by using the Pockels effect in integrated barium titanate (BaTiO3)-based devices. We report the nonlinear optical (NLO) properties of BaTiO3 in a temperature range which has previously not been explored, showing an effective Pockels coefficient of 200 pm/V at 4 K. We demonstrate the largest EO bandwidth (30 GHz) of any cryogenic switch to date, ultra-low-power tuning which is 10^9 times more efficient than thermal tuning, and high-speed data modulation at 20 Gbps. Our results demonstrate a missing component for cryogenic PICs. It removes major roadblocks for the realisation of novel cryogenic-compatible systems in the field of quantum computing and supercomputing, and for interfacing those systems with the real world at room-temperature.

Early JWST observations have uncovered a population of red sources that might represent a previously overlooked phase of supermassive black hole growth 1 – 3 . One of the most intriguing examples is an extremely red, point-like object that was found to be triply imaged by the strong lensing cluster Abell 2744 (ref.  4 ). Here we present deep JWST/NIRSpec observations of this object, Abell2744-QSO1. The spectroscopy confirms that the three images are of the same object, and that it is a highly reddened ( A V  ≃ 3) broad emission line active galactic nucleus at a redshift of z spec  = 7.0451 ± 0.0005. From the width of Hβ (full width at half-maximum = 2,800 ± 250 km s −1 ), we derive a black hole mass of M BH = 4 − 1 + 2 × 1 0 7 M ⊙ . We infer a very high ratio of black-hole-to-galaxy mass of at least 3%, an order of magnitude more than that seen in local galaxies 5 and possibly as high as 100%. The lack of strong metal lines in the spectrum together with the high bolometric luminosity ( L bol  = (1.1 ± 0.3) × 10 45  erg s −1 ) indicate that we are seeing the black hole in a phase of rapid growth, accreting at 30% of the Eddington limit. The rapid growth and high black-hole-to-galaxy mass ratio of Abell2744-QSO1 suggest that it may represent the missing link between black hole seeds 6 and one of the first luminous quasars 7 . JWST/NIRSpec observations of Abell2744-QSO1 show a high black-hole-to-host mass ratio in the early Universe, which indicates that we are seeing the black hole in a phase of rapid growth, accreting at 30% of the Eddington limit.

Genes underneath signals from genome-wide association studies (GWAS) for kidney function are promising targets for functional studies, but prioritizing variants and genes is challenging. By GWAS meta-analysis for creatinine-based estimated glomerular filtration rate (eGFR) from the Chronic Kidney Disease Genetics Consortium and UK Biobank (n = 1,201,909), we expand the number of eGFRcrea loci (424 loci, 201 novel; 9.8% eGFRcrea variance explained by 634 independent signal variants). Our increased sample size in fine-mapping (n = 1,004,040, European) more than doubles the number of signals with resolved fine-mapping (99% credible sets down to 1 variant for 44 signals, ≤5 variants for 138 signals). Cystatin-based eGFR and/or blood urea nitrogen association support 348 loci (n = 460,826 and 852,678, respectively). Our customizable tool for Gene PrioritiSation reveals 23 compelling genes including mechanistic insights and enables navigation through genes and variants likely relevant for kidney function in human to help select targets for experimental follow-up. Identifying causal variants and genes in genome-wide association studies remains a challenge, an issue that is ameliorated with larger sample sizes. Here the authors meta-analyze kidney function genome-wide association studies to identify new loci and fine-map loci to home in on variants and genes involved in kidney function.

Social media platforms are fundamentally disrupting public communication in two ways. First, non-journalistic actors, such as social media influencers, now have easier access to audiences, increasing the range of epistemic authorities. Second, established news outlets are increasingly reliant on platforms, pressuring them to adapt to the demands of social media. This platformization threatens the quality of public communication and citizens’ realization of their epistemic rights. Drawing on these concerns, this article offers a holistic approach to systematically analyze and practically govern epistemic threats to news quality in the platform-driven hybrid news ecosystem by developing a comprehensive three-stage framework that distinguishes between the production, distribution, and reception of news quality. News quality needs not only to be produced (input) but also to be made visible on platforms (throughput) and processed by audiences (output) in order to contribute to an informed public discourse. Focusing on the EU, the article then discusses current regulatory shortcomings and the need for additional measures to safeguard news quality along its three dimensions.

The identification of sources driving cosmic reionization, a major phase transition from neutral hydrogen to ionized plasma around 600–800 Myr after the Big Bang 1 – 3 , has been a matter of debate 4 . Some models suggest that high ionizing emissivity and escape fractions ( f esc ) from quasars support their role in driving cosmic reionization 5 , 6 . Others propose that the high f esc values from bright galaxies generate sufficient ionizing radiation to drive this process 7 . Finally, a few studies suggest that the number density of faint galaxies, when combined with a stellar-mass-dependent model of ionizing efficiency and f esc , can effectively dominate cosmic reionization 8 , 9 . However, so far, comprehensive spectroscopic studies of low-mass galaxies have not been done because of their extreme faintness. Here we report an analysis of eight ultra-faint galaxies (in a very small field) during the epoch of reionization with absolute magnitudes between M UV  ≈ −17 mag and −15 mag (down to 0.005 L ⋆ (refs.  10 , 11 )). We find that faint galaxies during the first thousand million years of the Universe produce ionizing photons with log[ ξ ion  (Hz erg −1 )] = 25.80 ± 0.14, a factor of 4 higher than commonly assumed values 12 . If this field is representative of the large-scale distribution of faint galaxies, the rate of ionizing photons exceeds that needed for reionization, even for escape fractions of the order of 5%. An analysis of eight ultra-faint galaxies during the epoch of reionization with absolute magnitudes between −17 mag and −15  mag shows that most of the photons that reionized the Universe come from dwarf galaxies.