Superconducting thin-film electronics can offer low power consumption, fast operating speeds and interfacing capabilities with cryogenic systems such as single-photon detector arrays and quantum computing devices. However, the lack of a reliable superconducting two-terminal asymmetric device, analogous to a semiconducting diode, limits the development of power-handling circuits, which are fundamental for scaling up such technology. Here we report a robust superconducting diode with tunable polarity using the asymmetric vortex surface barrier in niobium nitride micro-bridges. The diode offers a 43

Efficiently simulating large circuits is crucial to the development of superconducting nanowire-based electronics. However, current simulation tools for this technology are not adapted to the scaling of circuit size and complexity. We focus on the multilayered heater-nanocryotron (hTron), a promising superconducting nanowire-based switch used in applications such as superconducting nanowire single-photon detector (SNSPD) readout. Previously, the hTron was modeled using traditional finite-element methods (FEM), which fall short in simulating systems at a larger scale. An empirical-based method would be better adapted to this task, enhancing both simulation speed and agreement with experimental data. In this work, we perform switching current and activation delay measurements on 17 hTron devices. We then develop a method for extracting physical fitting parameters used to characterize the devices. We build a SPICE behavioral model that reproduces the static and transient device behavior using these parameters, and validate it by comparing its performance to a model developed in prior work, showing an improvement in simulation time by several orders of magnitude. Our model provides circuit designers with a tool to help understand the hTron's behavior during all design stages, thus enabling broader use of the hTron across various new areas of application.

Nonequilibrium quasiparticle and phonon dynamics are central to the operation of superconducting devices. Superconducting detectors, such as superconducting nanowire single-photon detectors, transition-edge sensors, or microwave kinetic inductance detectors, perform best when a large quasiparticle population is generated in response to small perturbations. Conversely, for superconducting qubits and topologically protected Majorana fermions, even relatively small quasiparticle densities can lead to significant performance degradation. Hence, ideal materials for these devices would be less susceptible to quasiparticle poisoning. However, existing models of these devices often rely on approximations and phenomenology. Therefore, they lack a rigorous description of the underlying quasiparticle and phonon dynamics that are responsible for device performance. In this article, we combine kinetic equations with density functional theory to model the nonequilibrium quasiparticle and phonon dynamics of a thin superconducting film ab initio. To demonstrate the universality of our model, we illustrate two independent example applications: (1) we develop a theoretical model describing the detection of single photons in superconducting nanowires, and (2) we calculate the energy-relaxation rate of a transmon qubit due to the presence of excess quasiparticles. Our examples demonstrate from first principles that niobium nitride is well suited to be used for single-photon detection and that tantalum transmon qubits possess reduced sensitivity to quasiparticle poisoning relative to other materials, which is likely in part responsible for their longer coherence times. In contrast to previous models of superconducting devices, our ab initio approach makes predictions of device performance without experimental input and thus can be used to accelerate progress in device development. Moreover, by considering the full-bandwidth electron-phonon coupling, our approach can incorporate strong-coupling effects. Our methods effectively integrate ab initio materials modeling with nonequilibrium theory of superconductivity to perform practical modeling of superconducting devices, providing a comprehensive approach that connects fundamental theory with device-level applications.

The scaling of superconducting nanowire detectors to larger arrays is often limited by room-temperature-readout cabling. Cryogenic integrated circuits constructed from nanowire cryotrons, or nanocryotrons, can address this limitation by performing signal processing on chip. In this study, we characterize key performance metrics of the nanocryotron to elucidate its potential as a logical element in cryogenic integrated circuits and develop an electro-thermal model to connect material parameters with device performance. We find that the performance of the nanocryotron depends on the device geometry, and trade-offs are associated with optimizing the gain, jitter, and energy dissipation. We demonstrate that nanocryotrons fabricated on niobium nitride can achieve a grey zone less than 210 nA wide for a 5 ns long input pulse corresponding to a maximum achievable gain of 48 dB, an energy dissipation of less than 20 aJ per operation, and a jitter of less than 60 ps.

Improving the scalability, reproducibility, and operating temperature of superconducting nanowire single photon detectors (SNSPDs) has been a major research goal since the devices were first proposed. The recent innovation of helium-ion irradiation as a postprocessing technique for SNSPDs could enable high detection efficiencies to be more easily reproducible, but is still poorly understood. In addition, fabricating detectors at micron-wide scales from high-T-c materials could improve scalability and operating temperature, respectively. At the same time, fabrication of successful devices in wide wires and from higher-T-c materials like magnesium diboride has proven challenging. In this work, we compare helium ion irradiation in niobium nitride and magnesium diboride detectors with different material stacks in order to better understand the mechanics of irradiation and practical implications of encapsulating layers on effective dose. We examine the effects of experimental effective dose tests and compare these results to the damage per ion predicted by simulations in corresponding material stacks. In both materials, irradiation results in an increase in count rate, though for niobium nitride this increase has not fully saturated even at the highest tested dose of 2.6 x 10(17 )ions/cm(2), while for resist-encapsulated magnesium diboride even the lowest tested dose of 1 x 10(15) ions/cm(2) appears higher than optimal. Our results demonstrate the general applicability of helium ion irradiation to vastly different devices and material stacks, albeit with differing optimal doses, and show the reproducibility and effectiveness of this postprocessing technique in significantly improving SNSPD efficiency.

This work presents an analysis of the first mmWaves-operating Cross-sectional Lame Mode Resonators (CLMRs), investigating the intrinsic quality factor limit of the technology. By leveraging the Finite Element Modeling-simulated energy distributions in the piezoelectric and metal layer, an accurate matching of theoretical and experimental quality factor is achieved, thus identifying the main source of CLMR performance degradation in the 20 to 35 GHz frequency range. Furthermore, excellent quality factors are recorded, achieving the largest frequency and quality factor product (f(s) center dot Q = 14.4 THz) ever demonstrated on sputtered thin-films and among the largest ever reported for the microacoustic technology. In conclusion, the present results explore the feasibility of enabling mmWaves-operating CLMRs to extend the use cases of the microacoustic technology to a virtually new spectrum territory, while outlining design trade-offs aiming to maximize their quality factors.

Decreasing the number of cables that bring heat into the cryocooler is a critical issue for all cryoelectronic devices. Especially, arrays of superconducting nanowire single-photon detectors (SNSPDs) could require more than $10^6$ readout lines. Performing signal processing operations at low temperatures could be a solution. Nanocryotrons, superconducting nanowire three-terminal devices, are good candidates for integrating sensing and electronics on the same technological platform as SNSPDs in photon-counting applications. In this work, we demonstrated that it is possible to read out, process, encode, and store the output of SNSPDs using exclusively superconducting nanowires. In particular, we present the design and development of a nanocryotron ripple counter that detects input voltage spikes and converts the number of pulses to an $N$-digit value. The counting base can be tuned from 2 to higher values, enabling higher maximum counts without enlarging the circuit. As a proof-of-principle, we first experimentally demonstrated the building block of the counter, an integer-$N$ frequency divider with $N$ ranging from 2 to 5. Then, we demonstrated photon-counting operations at 405\,nm and 1550\,nm by coupling an SNSPD with a 2-digit nanocryotron counter partially integrated on-chip. The 2-digit counter operated in either base 2 or base 3 with a bit error rate lower than $2 \times 10^{-4}$ and a maximum count rate of $45 \times 10^6\,$s$^{-1}$. We simulated circuit architectures for integrated readout of the counter state, and we evaluated the capabilities of reading out an SNSPD megapixel array that would collect up to $10^{12}$ counts per second. The results of this work, combined with our recent publications on a nanocryotron shift register and logic gates, pave the way for the development of nanocryotron processors, from which multiple superconducting platforms may benefit.

We present a design for a superconducting nanowire binary shift register, which stores digital states in the form of circulating supercurrents in high-kinetic-inductance loops. Adjacent superconducting loops are connected with nanocryotrons, three-terminal electrothermal switches, and fed with an alternating two-phase clock to synchronously transfer the digital state between the loops. A two-loop serial-input shift register was fabricated with thin-film NbN and a bit error rate of less than 10−4 was achieved, when operated at a maximum clock frequency of 83 MHz and in an out-of-plane magnetic field of up to 6 mT. A shift register based on this technology offers an integrated solution for low-power readout of superconducting nanowire single photon detector arrays and is capable of interfacing directly with room-temperature electronics and operating unshielded in high magnetic field environments.

The development of superconducting electronics based on nanocryotrons has been limited so far to few-device circuits, in part due to the lack of standard and robust logic cells. Here, we introduce and experimentally demonstrate designs for a set of nanocryotron-based building blocks that can be configured and combined to implement memory and logic functions. The devices were fabricated by patterning a single superconducting layer of niobium nitride and measured in liquid helium on a wide range of operating points. The tests show $10^{-4}$ bit error rates with above $20\,\%$ margins up to $50\,$MHz and the possibility of operating under the effect of a perpendicular $36\,$mT magnetic field, with $30\,\%$ margins at $10\,$MHz. Additionally, we designed and measured an equivalent delay flip-flop made of two memory cells to show the possibility of combining multiple building blocks to make larger circuits. These blocks may constitute a solid foundation for the development of nanocryotron logic circuits and finite-state machines with potential applications in the integrated processing and control of superconducting nanowire single-photon detectors.

Neuromorphic computing would benefit from the utilization of improved customized hardware. However, the translation of neuromorphic algorithms to hardware is not easily accomplished. In particular, building superconducting neuromorphic systems requires expertise in both superconducting physics and theoretical neuroscience, which makes such design particularly challenging. In this work, we aim to bridge this gap by presenting a tool and methodology to translate algorithmic parameters into circuit specifications. We first show the correspondence between theoretical neuroscience models and the dynamics of our circuit topologies. We then apply this tool to solve a linear system and implement Boolean logic gates by creating spiking neural networks with our superconducting nanowire-based hardware.

As the limits of traditional von Neumann computing come into view, the brain's ability to communicate vast quantities of information using low-power spikes has become an increasing source of inspiration for alternative architectures. Key to the success of these largescale neural networks is a power-efficient spiking element that is scalable and easily interfaced with traditional control electronics. In this work, we present a spiking element fabricated from superconducting nanowires that has pulse energies on the order of ~10 aJ. We demonstrate that the device reproduces essential characteristics of biological neurons, such as a refractory period and a firing threshold. Through simulations using experimentally measured device parameters, we show how nanowire-based networks may be used for inference in image recognition, and that the probabilistic nature of nanowire switching may be exploited for modeling biological processes and for applications that rely on stochasticity.

We report on the first implementation of a long-range wake-up receiver (WuRx) enabled by an aggressively scaled 100 nm thick aluminum nitride transducer that occupies an area of only $100\ \mu \mathrm{m}\ \times\ 100\ \mu \mathrm{m}$ . This piezoelectric Nanoscale Ultrasound Transducer (pNUT) offers the same sensitivity and characteristic impedance of its microscale counterparts but enables “dust-like” WuRx because of its dramatically reduced size. We validate this concept by synthesizing a WuRx using a pNUT and off-the-shelf electronic components forming a voltage amplifier, an envelope detector and a comparator (Fig. 1). We demonstrate robust data transfer over a range of 0.5 m when operating with a 40 kHz carrier signal modulated at 250Hz. Based on these measurements we extrapolate the device performance at resonance to show that communication over> 10m is possible without increasing the WuRx area.

Information processing with very low power consumption and innovative computing paradigms are required for the development of modern technologies in which real-time elaboration of data is needed. Natural spiking neural networks are being explored for their speed and energy-efficiency. In these systems, spikes generated by neurons take the information, and synapses act as local memories and connections between neurons, allowing networks to learn and adapt to external stimuli. Superconducting electronics for its intrinsic low energy dissipation is the perfect candidate for building bio-inspired neuronal systems. It has already been proposed a structure that mimics the spiking behavior of the neuron and can be based on two different superconducting devices, which are able to generate low-power pulses: (1) Josephson junctions; and (2) NbN nanowires. The former are widely used for their high operation speed and low power consumption. The latter are typically exploited for single-photon detectors (SNSPDs), but recently are emerging as a platform for new electronics, thanks to their ability to interface with high-impedance environments. This work mainly focuses on the design, optimization, and characterization of the nanowire-based elements necessary for the realization of a spiking neural network. The spiking behavior of nanowire neurons has been demonstrated experimentally, but further work is needed to improve the controllability of their properties. An artificial synapse has not yet been fabricated and tested, but it has been designed, exploiting the presence of kinetic inductance, a particular effect of NbN nanowires (inductive synapse). It is able to reproduce some characteristics of its biological counterpart, like the variable connection strength, but still presents some lacks for the creation of large and versatile networks. A new structure developed to improves the performances of the inductive synapse is here proposed (nTron synapse), introducing the nano-cryotrons (nTron and hTron): nanowire-based comparators with tunable gain, that use the formation of a localized Joule-heated hotspot to modulate the current flow in a superconducting channel. SPICE models of all the exploited superconducting devices were created, starting from experimental data and the existing model of SNSPDs, to facilitate a correct design of the nTron synapse and find limitations of the network. Moreover, fundamental elements of the neurons and nTron synapses like (1) large kinetic inductors, (2) shunted nanowires, and (3) nTrons, were fabricated and tested. Electrical simulations were also performed to study in depth a possible integration of nanowire neurons with Josephson junction neurons. Merging the two technologies could be useful to increase the overall performances of the network, but it generates also some problems, that are here analyzed.