Rapid Single flux quantum (RSFQ) confluence buffer is widely used in complex superconductive digital circuits. In this work, we have improved the currently used confluence buffer and obtained a more soundly designed confluence buffer. In simulations, improvements in the bias margins of 11 % and the global margins of 10%, compared to the previously used confluence buffer, were achieved. Global margins are very important in estimating a process error range allowed in fabrications. We used two circuit simulation tools, WRspice and Julia, to design and optimize the confluence buffer. We used Xic to obtain a mask layout. We fabricated the improved circuits by using Nb technology. The test results at low frequency showed that the improved confluence buffer operated correctly and had a very wide main bias margin of +/-43% enhanced from +/-26% of the previously used confluence buffer.
Rapid Single flux quantum (RSFQ) confluence buffer is widely used in complex superconductive digital circuits. In this work, we have improved the currently used confluence buffer and obtained a more soundly designed confluence buffer. In simulations, improvements in the bias margins of 11 % and the global margins of 10%, compared to the previously used confluence buffer, were achieved. Global margins are very important in estimating a process error range allowed in fabrications. We used two circuit simulation tools, WRspice and Julia, to design and optimize the confluence buffer. We used Xic to obtain a mask layout. We fabricated the improved circuits by using Nb technology. The test results at low frequency showed that the improved confluence buffer operated correctly and had a very wide main bias margin of +/-43% enhanced from +/-26% of the previously used confluence buffer.
There are several simulation programs in studying superconductor RSFQ (Rapid Single flux Quantum) electronic devices, which include WRspice, WinS, PSCAN, and JSIM. Even though different research groups use different simulation programs, it is not well known about which program gives the simulation results closer to the measurement values. In this work, we used both WRspice and WinS to simulate RSFQ OR gate and to compare the results from the different simulations. This comparison would help in deciding which program is better in the RSFQ circuit design. In the confluence buffer, which is the one of the main components of the DR gate, the measured bias margins were , while the margins from the simulations were from WRspice and it 53.1% from WinS. However, with the actual fabricated circuit parameters WRspice gave . In WinS the circuit did not operate. We concluded that WRspice is more reliable.
We has designed, fabricated, and measured a Single flux quantum (SFQ) toggle flip-flop (TFF). The TFF is widely used in superconductive digital electronics circuits. Many digital devices, such as frequency counter, counting ADC and program counter be used TFF Specially, a program counter may be constructed based on TFF We have designed the newly TFF and obtained high bias margins on test. In this work, we used two circuit simulation tools, WRspice and Julia, as circuit optimization tools. We used XIC for a layout tool. Newly designed TFF had minimum bias margins of +/- and maximum bias margins of +/-(enhanced from +/- ). The designed circuits were fabricated by using Nb technology The test results showed that the re-optimized TFF operated correctly on 100kHz and had a very wide bias margins of +/- .
Several novel circuits of the rapid single-flux-quantum (RSFQ) family of Josephson-junction digital devices have been designed, fabricated using a 2.5- mu m 1000-A/cm/sup 2/ Nb trilayer technology, and tested at low frequencies. Numerical simulation and measurements have shown that these circuits have considerably wider parameter margins, due to application of several novel design methods. The authors have also carried out an experiment to measure the rate of errors in a simple RSFQ circuit including an inverter, confluence buffer, and Josephson transmission line. Near the middle of the parameter window at 4.2 K, the error probability was definitely lower than 3*10/sup -15/ per logic operation, despite experimentation with rudimentary shielding and filtering.>
Some basic cells in the rapid single-flux quantum (RSFQ) family of superconductive logic circuits were studied. An input stage, a buffer, and an OR gate were simulated and laid out for a standard niobium-based fabrication process. The resulting circuits perform properly for clock speeds up to 1 GHz. For the simpler circuits tested, the measured margins are wide, consistent with simulations, and not very dependent on clock speed. However, margin decreases with increased circuit complexity. The input stage converts a rising edge into an SFQ pulse, which has a small amplitude and narrow width in time. On the present circuits, these pulses are about 200 mu V in amplitude and 10 ps in width. To facilitate measurement, the authors have chosen as the output an asymmetrical superconducting quantum interference device (SQUID) consisting of two Josephson junctions. It converts SFQ pulses into 2.5 mV latching output levels on chip. By inductively coupling SFQ pulses into the SQUID loop, DC current isolation between the RSFQ circuit-under-test and the output stage is provided. The SQUID was optimized for 2 GHz operations.>
We report on the fabrication and the operation of all-NbN rapid single flux quantum (RSFQ) circuits. The NbN integrated circuit consists of NbN/AlN/NbN tunnel junctions, Mo resistors, sputtered SiO/sub 2/ insulating layers, and 400-nm-thick NbN ground plane and wiring layer. The circuits were fabricated with the minimum junction size of 2 /spl mu/m/spl times/2 /spl mu/m and the alignment margin of +/-0.5 /spl mu/m. We designed RSFQ logic cells under critical current density of 2.5 kA/cm/sup 2/, sheet resistance of 2 /spl Omega/ and sheet inductance of 1.4 pH. We experimentally investigated dc bias margin of the fabricated RSFQ cells at 9 K. We observed relatively large dc bias margin of more than +/-25% for a pulse splitter, a confluence buffer and an RS flip-flop, while the dc bias margin of a T flip-flop was less than +/-5%. We succeeded to demonstrate the operation of 16-bit concurrent flow shift register at 9 K.
Abstract As a member of the superconducting integrated circuit family, energy-efficient rapid single flux quantum (ERSFQ) circuit combines low-power consumption with high frequency, showing promise for application in high-energy efficient neuromorphic computing and traditional high-performance computing. Previous studies have demonstrated that there are typically two energy dissipation states in working ERSFQ circuits: energy-efficient SFQ state (E-state) and resistive-biased SFQ state (R-state). These states occur at different biasing current ranges, and the sum of the bias margin of these two states is close to the margin of rapid single flux quantum (RSFQ) circuits of the same design. For ultra-low-power applications, the bias current margin of the R-state must be excluded, leading to a substantially narrower bias margin in ERSFQ circuits than in their RSFQ counterparts. In our previous research, we proposed the feeding pulse method to increase the bias current margin by extending the lower boundary of the E-state through the injection of feeding pulses into the feeding Josephson transmission line (FJTL). In this study, we further investigated the current distribution mechanism in ERSFQ circuits and, based on this, proposed a method of optimizing design of the FJTL to redirect excess current to the FJTL, so as to expand the upper boundary of the E-state’s bias current margin. We tested an ERSFQ 8-bit shift register of the ERSFQ by applying methods proposed in this work together with the feeding pulses method proposed before. The results demonstrated that the bias current margin of the E-state expanded from (94%, 98%) to (56%, 116%), corresponding to a 14-times increase, with both the lower and upper boundary successfully extended. Our research addresses the issue of limited current bias margin in ERSFQ circuits during actual operation, providing a more robust ERSFQ technology for future applications in neural networks and high-performance computing.