Included here are data used to generate figures from the paper "Digital control of a superconducting qubit using a Josephson pulse generator at 3 K".Abstract: Scaling of quantum computers to fault-tolerant levels relies critically on the integration of energy-efficient, stable, and reproducible qubit control and readout electronics. In comparison to traditional semiconductor control electronics (TSCE) located at room temperature, the signals generated by Josephson junction (JJ) based rf sources benefit from small device sizes, low power dissipation, intrinsic calibration, superior reproducibility, and insensitivity to ambient fluctuations. Previous experiments to co-locate qubits and JJ-based control electronics resulted in quasiparticle poisoning of the qubit; degrading the qubit's coherence and lifetime. In this paper, we digitally control a 0.01~K transmon qubit with pulses from a Josephson pulse generator (JPG) located at the 3~K stage of a dilution refrigerator. We directly compare the qubit lifetime $T_1$, coherence time $T_2^*$, and thermal occupation $P_{th}$ when the qubit is controlled by the JPG circuit versus the TSCE setup. We find agreement to within the daily fluctuations on $\pm 0.5~\mu$s and $\pm 2~\mu$s for $T_1$ and $T_2^*$, respectively, and agreement to within the 1\% error for $P_{th}$. Additionally, we perform randomized benchmarking to measure an average JPG gate error of $2.1 imes 10^{-2}$. In combination with a small device size ($<25$~mm$^2$) and low on-chip power dissipation ($\ll 100~\mu$W), these results are an important step towards demonstrating the viability of using JJ-based control electronics located at temperature stages higher than the mixing chamber stage in highly-scaled superconducting quantum information systems

Datasets for the four published figures in the Paper "AC Metrology Applications of the Josephson Effect ". This paper is being submitted to Applied Physics Letters Special Topic, "Advances in Quantum Metrology,"https://publishing.aip.org/publications/journals/special-topics/apl/advances-in-quantum-metrology/ .Abstract of the paper:The performance of programmable voltage signals that exploit the quantum behavior of superconducting Josephson junctions continues to improve and enable new capabilities for applications in metrology, communications, and quantum control. We review advances in pulse-driven digital synthesis techniques with Josephson-junction-based devices. Unprecedented performance for synthesized voltage waveforms has been achieved at different frequencies, including rms amplitudes of 4 V at 1 kHz, 50 mV at 50 MHz, and 22 mV at 1.005 GHz. Josephson pulse generators have also successfully controlled and characterized superconducting qubits with a gate fidelity of 99.5%.

This bundle contains RPWS-HFR Quasi Thermal Noise (QTN) spectroscopy supplied CDF and plot files containing a time series of thermal plasma moments (density and temperature). QTN data products are generated only when the QTN analysis is applicable.

We present recent improvements within the growing field of Rydberg atom sensors. While initially started as a path towards absolute, independent measurements of electric fields, the research landscape has evolved into the realm of quantum sensors and receivers. We discuss the capabilities and limitations of Rydberg atom receivers, and we show how different atomic properties enhance or limit sensitivity and bandwidth.This data is for a review paper. Figures 6 (a) and 8 (a) and (b) are new data. The rest of the data is extracted from other NIST publications that have a data management plan. Related data are from the following papers.https://doi.org/10.1063/5.0069195https://doi.org/10.48550/arXiv.2402.00718https://doi.org/10.1116/5.0098057

This data is provided as a supplement to NIST Technical Note 2159 Laboratory Method for Recording AWS-3 LTE Waveforms available at https://doi.org/10.6028/NIST.TN.2159. In particular, the data provided here are a compressed version of all the IQ recordings discussed in the report, with diagnostic information. The data is structured as a compressed archive, Data.zip, for each experimental configuration and capture repeat, resulting in 112 compressed archives organized by directory structure. The compressed archive, Data.zip, contains six files: IQ.csv, configuration.csv, diagnostic.csv, UE_diagnostic_spectrogram.csv, IQ_spectrogram.csv and IQ_spectrogram.png. - IQ.csv Description: Measured IQ at a sampling rate of 61.44 MS / s Contents: I and Q as signed integers, relative units- configuration.csv Description: The experimental configuration under which the IQ recording was made. Corresponds to a row in Table 4.1: Test Configurations of the technote. Contents: Scheduler_Awareness, Scheduler_Allocation, PowerControl_PUSCH, PowerControl_PUCCH,Scheduler_RBMask, P0_PUSCH, P0_PUCCH, alpha, UTG_NumUEs, UTG_ULRate, UTG_TrafficType, UTG_UERSRP, DUT_UE_ULRate, DUT_UE_TrafficType, UT_UE2_ULRate, DUT_UE2_TrafficType - diagnostic.csv Description: UE Diagnostic information with a time-axis in ms based on system subframes. Contents: Elapsed time (ms), Total Tx Power (dBm), Resource Block Start, Number of Resource Blocks, MCS Index - UE_diagnostic_spectrogram.csv Description: The UE diagnostic report of power and resource block allocation organized into physical resource blocks with a time-axis in ms based on system subframes. Contents: Elapsed time (ms), 0 ? max physical resource blocks in shared channel with a power in mw. - IQ_spectrogram.csv Description: IQ data organized into physical resource blocks with a time axis aligned to the diagnostic information. Contents: Elapsed time (ms), 0 ? 199 resource blocks with a relative power. - IQ_spectrogram.png Description: Plot of 140 ms of spectrogram, max relative power versus frequency and mean relative power, corresponds to appendix B of technote. Contents: Single image

This data is provided as a supplement to NIST Technical Note 2159 Laboratory Method for Recording AWS-3 LTE Waveforms available at https://doi.org/10.6028/NIST.TN.2159. In particular, the data provided here are a compressed version of all the IQ recordings discussed in the report, with diagnostic information. The data is structured as a compressed archive, Data.zip, for each experimental configuration and capture repeat, resulting in 112 compressed archives organized by directory structure. The compressed archive, Data.zip, contains six files: IQ.csv, configuration.csv, diagnostic.csv, UE_diagnostic_spectrogram.csv, IQ_spectrogram.csv and IQ_spectrogram.png. - IQ.csv Description: Measured IQ at a sampling rate of 61.44 MS / s Contents: I and Q as signed integers, relative units- configuration.csv Description: The experimental configuration under which the IQ recording was made. Corresponds to a row in Table 4.1: Test Configurations of the technote. Contents: Scheduler_Awareness, Scheduler_Allocation, PowerControl_PUSCH, PowerControl_PUCCH,Scheduler_RBMask, P0_PUSCH, P0_PUCCH, alpha, UTG_NumUEs, UTG_ULRate, UTG_TrafficType, UTG_UERSRP, DUT_UE_ULRate, DUT_UE_TrafficType, UT_UE2_ULRate, DUT_UE2_TrafficType - diagnostic.csv Description: UE Diagnostic information with a time-axis in ms based on system subframes. Contents: Elapsed time (ms), Total Tx Power (dBm), Resource Block Start, Number of Resource Blocks, MCS Index - UE_diagnostic_spectrogram.csv Description: The UE diagnostic report of power and resource block allocation organized into physical resource blocks with a time-axis in ms based on system subframes. Contents: Elapsed time (ms), 0 ? max physical resource blocks in shared channel with a power in mw. - IQ_spectrogram.csv Description: IQ data organized into physical resource blocks with a time axis aligned to the diagnostic information. Contents: Elapsed time (ms), 0 ? 199 resource blocks with a relative power. - IQ_spectrogram.png Description: Plot of 140 ms of spectrogram, max relative power versus frequency and mean relative power, corresponds to appendix B of technote. Contents: Single image

This project produces synthetic datasets of spectrum sharing simulation results (I/Q data, metadata, and KPIs).

Included here are figures and other relevant data from the paper "Characterizing Interconnects to 325 GHz". Abstract: We developed an interconnect characterization procedure that first embeds the interconnect into the error boxes of a multiline thru-reflect-line calibration and subsequently de-embeds the interconnect with a multi-tiered calibration. We experimentally validated our method with distributed contactless interconnects in the form of broadside coupled coplanar waveguides as a test case. We find excellent agreement between experiment, full-wave simulations, and a distributed model of contactless interconnects. This work provides a rigorous method to accurately characterize interconnects when conventional approaches are not applicable.