Fig 18 - uploaded by Oleg Mukhanov
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Superconductor first-order band-pass sigma-delta ADC based on microstrip resonator [69]. (a) Schematic of sigma-delta band-pass modulator. (b) 6.3 mm 2 6.3 mm test ADC chip incorporating the band-pass modulator and digital data buffers with 4065 Josephson junctions.
Source publication
Ultrafast switching speed, low power, natural quantization of magnetic flux, quantum accuracy, and low noise of cryogenic superconductor circuits enable fast and accurate data conversion between the analog and digital domains. Based on rapid single-flux quantum (RSFQ) logic, these integrated circuits are capable of achieving performance levels unat...
Citations
... Substantial progress is superconductor RSFQ Analog to Digital Converters (ADCs) [20][21][22][23][24] enables the development of superconductor broadband receivers with direct signal digitizing and subsequent digital extraction of sub-bands with programmable band location and bandwidth [25,26] in VHF to X bands [27][28][29][30] and even in K band [31]. Figure 1 presents the general concept of such a digital-rf broadband receiver (based on ideas from [26]). ...
... Among possible candidates for a cryogenic ADC, superconducting ADCs [22], [23] are inherently cryogenic and offer high speed at a low power consumption but are incompatible with the integration in a cryo-CMOS system on chip (SoC). A cryogenic FPGA-based ADC has demonstrated a sampling rate of 1.2 GS/s and offers great flexibility [24], but its power efficiency is much lower than RT CMOS ADCs, e.g., [25]. ...
This article presents a two-times interleaved, loop-unrolled SAR analog-to-digital converter (ADC) operational from 300 down to 4.2 K. The 6–8-bit resolution and the sampling speed up to 1 GS/s are targeted at digitizing the multi-channel frequency-multiplexed input in a spin-qubit reflectometry readout for quantum computing. To optimize the circuit for the altered device behavior at cryogenic temperatures, a modified common-mode switching scheme is adopted as well as a flexible calibration. The design is implemented in 40-nm CMOS technology and achieves 36.2-dB signal to noise and distortion ratio (SNDR) for Nyquist input at 4.2 K while maintaining a Walden figure of merit (FOMW) of 200 pJ/conv-step (for a 10.8-mW power consumption), including the clock receiver, and 15 pJ/conv-step (for a 0.8-mW power consumption) for just the core ADC. With these specifications, the ADC can support the simultaneous readout of 20 qubit channels with a power consumption of 0.5 mW/qubit, thus advancing toward the full integration of the cryogenic readout for future large-scale quantum processors.
... RSFQ has had success in decimation filters for mixed-signal applications 7,8 where scale is modest and bit rates are high, but scale is limited due to DC power delivery to a current draw of 1 A per 1000 gates, and by the timing uncertainty of free-running pulses. Energy efficient SFQ (eSFQ/ERSFQ) 9,10 and dynamic SFQ (DSFQ) 11 variants have these same limitations. ...
Superconducting digital pulse-conserving logic and Josephson static random access memory (JSRAM) memory together enable scalable circuits with energy efficiency 100× beyond leading-node CMOS. Circuit designs support high throughput and low latency when implemented in an advanced fabrication stack with high-critical-current-density Josephson junctions of 1000 μA/μm2. Pulse-conserving logic produces one single-flux-quantum output for each input and includes a three-input, three-output gate producing logical or3, majority3, and and3. Gate macros using dual-rail data encoding eliminate inversion latency and produce efficient implementations of all standard logic functions. A full adder using 70 Josephson junctions has a carry-out latency of 5 ps corresponding to an effective 12 levels of logic at 30 GHz. JSRAM memory uses single-flux-quantum signals throughout an active array to achieve throughput at the same clock rate as the logic. The unit cell has eight Josephson junctions, a signal propagation latency of 1 ps, and a footprint of 2 μm2. Projected density of JSRAM is 4 MB/cm2, and computational density of pulse-conserving logic is on par with leading node CMOS accounting for power densities and clock rates.
... RSFQ has had success in decimation filters for mixedsignal applications 7,8 where scale is modest and bit rates are high, but scale is limited by a DC current draw of 1 A per 1,000 gates, and by the timing uncertainty of free-running pulses. Energy Efficient SFQ (eSFQ/ERSFQ) 9,10 and Dynamic SFQ (DSFQ) 11 variants have these same limitations. ...
Superconducting digital Pulse-Conserving Logic (PCL) and Josephson SRAM (JSRAM) memory together enable scalable circuits with energy efficiency 100x beyond leading-node CMOS. Circuit designs support high throughput and low latency when implemented in an advanced fabrication stack with high-critical-current-density Josephson junctions of 1000$\mu$A/$\mu$m$^2$. Pulse-conserving logic produces one single-flux-quantum output for each input, and includes a three-input, three-output gate producing logical or3, majority3 and and3. Gate macros using dual-rail data encoding eliminate inversion latency and produce efficient implementations of all standard logic functions. A full adder using 70 Josephson junctions has a carry-out latency of 5ps corresponding to an effective 12 levels of logic at 30 GHz. JSRAM (Josephson SRAM) memory uses single-flux-quantum signals throughout an active array to achieve throughput at the same clock rate as the logic. The unit cell has eight Josephson junctions, signal propagation latency of 1ps, and a footprint of 2$\mu$m$^2$. Projected density of JSRAM is 4 MB/cm$^2$, and computational density of pulse-conserving logic is on par with leading node CMOS accounting for power densities and clock rates.
... There have been several reports on superconducting ADCs with promising figures of merit. [101][102][103] However, this is still an evolving field of research and there is a strong need for further research exploration and scrutiny. ...
The revolution in artificial intelligence (AI) brings up an enormous storage and data processing requirement. Large power consumption and hardware overhead have become the main challenges for building next-generation AI hardware. To mitigate this, neuromorphic computing has drawn immense attention due to its excellent capability for data processing with very low power consumption. While relentless research has been underway for years to minimize the power consumption in neuromorphic hardware, we are still a long way off from reaching the energy efficiency of the human brain. Furthermore, design complexity and process variation hinder the large-scale implementation of current neuromorphic platforms. Recently, the concept of implementing neuromorphic computing systems in cryogenic temperature has garnered intense interest thanks to their excellent speed and power metric. Several cryogenic devices can be engineered to work as neuromorphic primitives with ultra-low demand for power. Here, we comprehensively review the cryogenic neuromorphic hardware. We classify the existing cryogenic neuromorphic hardware into several hierarchical categories and sketch a comparative analysis based on key performance metrics. Our analysis concisely describes the operation of the associated circuit topology and outlines the advantages and challenges encountered by the state-of-the-art technology platforms. Finally, we provide insight to circumvent these challenges for the future progression of research.
... VoIP act differently in many aspects from conventional PSTN. Signals are converted to digital before sending and are done by Analog to Digital converter (A/D) [21]. Reverse procedure is applied on the receiver to gather [21]. ...
... Signals are converted to digital before sending and are done by Analog to Digital converter (A/D) [21]. Reverse procedure is applied on the receiver to gather [21]. ...
Today, applications of real-time multimedia require heavily use of networks resources in which it affects the network performance. So, Quality of Service (QoS) of such networks is highly needed to be investigated and improved. VoWLAN is a VoIP system over Wi-Fi which offers a significantly extended operational range.
In this thesis, we analyse the performance of Deficit Round Robin (DRR), Fair Queue (FQ), DropTail (FIFO), Stochastic Fair Queue (SFQ), and Random Early Discard (RED) queuing management schemes for VoIP over SCTP 802.11n in Wi-Fi n using NS2 network simulator based on QoS (throughput, delay, and jitter) to obtain a better call quality for the users. In the used simulator, we generate SCTP VoIP traffic over Wi-Fi n and measure the impact of each node with applying different queue management schemes. The results of our simulation showed that the Drop Tail and RED queuing schemes performed better than other queue management schemes, in which both give high throughput, less delay and less jitter.
... Superconducting receivers and superconducting analogueto-digital converters are the most common applications of SCs in the field of electronics. Low loss and compact structures are the most common properties of these elements [63,64]. ...
More than a century after the discovery of superconductors (SCs), numerous studies have been accomplished to take the advantage of SCs in physics, power engineering, quantum computing, electronics, communications, aviation, health care, and defence-related applications. However, there are still challenges that hinder the full-scale commercialization of SCs, such as the high cost of superconducting wires/tapes, technical issues related to AC losses, the structure of superconducting devices, the complexity and high cost of the cooling systems, the critical temperature, and manufacturing related issues. In the current century, massive advancements have been achieved on artificial intelligence (AI) techniques by offering disruptive solutions to handle engineering problems. Consequently, AI techniques can be implemented to tackle those challenges facing superconductivity and act as a shortcut towards full commercialization of SCs and their applications. AI approaches are capable of providing fast, efficient, and accurate solutions for the technical, manufacturing, and economic problems with a high level of complexity and nonlinearity in the field of superconductivity. In this paper, concept of AI and the widely used algorithms are first given. Then a critical topical review is presented for those conducted studies that used AI methods for improvement, design, condition monitoring, fault detection and location of superconducting apparatuses in large scale power applications, as well as the prediction of critical temperature and the structure of new SCs, and any other related applications. The topical review are presented in three main categories, AI for large-scale superconducting applications, AI for superconducting materials, and AI for physics of superconductors. In addition, the challenges to apply AI techniques to the superconductivity and its applications are given. Eventually, future trends on how to integrate AI techniques with superconductivity towards the commercialization are discussed.
... The possibilities of (i) designing specialized area-efficient cryogenic ADCs or (ii) to avert the need for ADCs by implementing a fully analog neuromorphic system are yet to be thoroughly tested/validated. There have been several reports on superconducting ADCs with promising figures-of-merit [94]- [96]. However, this is still an evolving field of research and there is a strong need for further exploration. ...
The revolution in artificial intelligence (AI) brings up an enormous storage and data processing requirement. Large power consumption and hardware overhead have become the main challenges for building next-generation AI hardware. Therefore, it is imperative to look for a new architecture capable of circumventing these bottlenecks of conventional von Neumann architecture. Since the human brain is the most compact and energy-efficient intelligent device known, it was intuitive to attempt to build an architecture that could mimic our brain, and so the chase for neuromorphic computing began. While relentless research has been underway for years to minimize the power consumption in neuromorphic hardware, we are still a long way off from reaching the energy efficiency of the human brain. Besides, design complexity, process variation, etc. hinder the large-scale implementation of current neuromorphic platforms. Recently, the concept of implementing neuromorphic computing systems in cryogenic temperature has garnered immense attention. Several cryogenic devices can be engineered to work as neuromorphic primitives with ultra-low demand for power. Cryogenic electronics has therefore become a promising exploratory platform for an energy-efficient and bio-realistic neuromorphic system. Here we provide a comprehensive overview of the reported cryogenic neuromorphic hardware. We carefully classify the existing cryogenic neuromorphic hardware into different categories and draw a comparative analysis based on several performance metrics. Finally, we explore the future research prospects to circumvent the challenges associated with the current technologies.
... It is considered to be especially suitable for "cold electronics" operating in the gradient between room temperature and temperature of cryogenic payloads like quantum computers, quantum internet, or scalable sensors [6]. Since the 1980s, superconducting circuits have been consistently developed reaching a fairly mature level at the end of the 1990s, showing an implementation of digital and mixedsignal devices [7][8][9]. ...
In this work, we briefly overview various options for Josephson junctions, which should be scalable down to nanometer range for utilization in nanoscale digital superconducting technology. Such junctions should possess high values of critical current, Ic, and normal state resistance, RN. Another requirement is the high reproducibility of the junction parameters across a wafer in a fabrication process. We argue that superconductor-normal metal-superconductor (SN-N-NS) Josephson junction of “variable thickness bridge” geometry is a promising choice to meet these requirements. Theoretical analysis of the SN-N-NS junction is performed in the case where the distance between the S electrodes is comparable to the coherence length of the N material. The restriction on the junction geometrical parameters providing the existence of superconductivity in the S electrodes is derived for the current flowing through the junction of an order of Ic. The junction heating, as well as available mechanisms for the heat removal, is analyzed. The obtained results show that a SN-N-NS junction with a high (submillivolt) value of IcRN product can be fabricated from a broadly utilized combination of materials like Nb/Cu using well-established technological processes. The junction area can be scaled down to that of semiconductor transistors fabricated in the frame of a 40-nm process.
... In certain applications, the stability of the oscillation frequency of the SFQ oscillators is important. For instance, in SFQ-based analog-to-digital converters [10,11] and timeto-digital converters [12,13], the accuracy of conversion is influenced by the frequency stability of the SFQ clock pulse trains. Furthermore, in random number generation using SFQ circuits, the quality of the generated random number train depends on the frequency stability of the input SFQ pulse train [14][15][16]. ...
We demonstrate the frequency synchronization of multiple single-flux quantum (SFQ) oscillators with different oscillation frequencies. To synchronize these SFQ oscillators, a common constant bias current is supplied to the SFQ oscillators without any bias resistors. When an SFQ oscillator oscillates at a frequency of f , the average voltage across the Josephson junction comprising the SFQ oscillator is f Φ 0 , where Φ 0 is the flux quantum in the superconductor. The bias currents supplied to the SFQ oscillators are redistributed to eliminate the average voltage difference output from the SFQ oscillators. As a result, the oscillation frequencies of all the SFQ oscillators are synchronized. Simulation results indicate that SFQ oscillators with an oscillation frequency difference of more than 50 GHz can be synchronized. We experimentally demonstrate the frequency synchronization of two SFQ oscillators composed of circular Josephson transmission lines. Frequency synchronization is expected to contribute toward the development of a low-power stable clock source stabilizing SFQ circuit operation.
