Dataset for multiple publishable figures in the paper entitled "Quasi-continuous voltage standard using sinusoidal and pulse-driven Josephson junction arrays" submitted to Meas. Sci. and Tech. journal. Figure 3. (a) Pattern of pulses used to generate a dc voltage of 0.2 V, (b) difference from the nominal of the voltage measured using the K3458A versus dc bias current for different RF power biases.Figure 4. PD JJA voltage difference from nominal, measured with a K3458A, versus dc bias current for different pulse patterns and repetition frequencies.Figure 5. (a) Current-voltage characteristic of the CWD JJA and (b) the RF power-voltage characteristic of the PD JJA. The error bars show the Type-A uncertainty (k=1) of the measurement of five measurements.Figure 6. Current-voltage characteristic of the CWD JJAs. The error bars show the Type-A uncertainty (k=1) of the measurement.Figure 7. Allan deviation for 0 V. See text for details.Figure 8. Current-voltage characteristic of the CWD JJAs. The error bars show the Type-A uncertainty (k=1) of the measurement.Figure 9. Allan deviation at 1 V.

Delta-sigma algorithms are used to determine the desired sequence of quantum-based voltage pulses used by the Josephson Arbitrary Waveform Synthesizer (JAWS) to create calculable voltage waveforms. This data set contains a comparison (Fig 1. of the CPEM 2024 abstract) of a 1 kHz pulse pattern with rms amplitude of 2 mV without post-processing and with post-processing which modifies the problematic pulse pattern to remove incorrect pulses at the 0.75 ms pattern wrap point. In the time-domain, the pulse patterns are low-pass filtered at 30 MHz and the residuals relative to the 1 kHz ac signal are also shown. This data set also contains spectra which show the pulse patterns' voltage relative to the fundamental in the frequency domain.

The abstract of the paper [1] is:This paper describes differential sampling measurements of an ac source and a Josephson arbitrary waveform synthesizer (JAWS).A new iterative approach for aligning the phases of the JAWS and the source waveforms was implemented to minimize the differential voltage at the digitizer. A type-A uncertainty of 45 nV/V after 10 min was measured for a commercial ac source at 1 V rms amplitude and 1 kHz.[1] "Differential Measurements of an AC Source with a Josephson Arbitrary Waveform Synthesizer"submitted to Conference on Precision Electromagnetic Measurements (CPEM) 2024; will be published and available on IEEE website at a later date.Data for figures 2 to 4 of the manuscript.Files included in this publication: Fig 2 FFT of the digitizer signal.csv Figure 2 Fig. 2. 1 kHz component of the FFT of the digitizer signal (amplitude and phase) for Delta_V1=Source-JAWS1 and Delta_V2=Source-JAWS2 over 3.5 hours Five columns: The first column is the time (x-axis), the second column is the amplitude in volt of the first measured difference voltage (shown as black solid circle in Fig. 2), the third column is the phase in degree of the first measured difference voltage (shown as black open circle in Fig. 2), the fourth column is the amplitude in volt of the second measured difference voltage (shown as red solid circle in Fig. 2), the fifth column is the phase in degree of the second measured difference voltage (shown as red open circle in Fig. 2). Format: CSV Fig 3 Source rms amplitude and environment data.csv Figure 3 Fig. 3. Room environment conditions recorded (temperature, atmospheric pressure, and relative humidity) and Reconstructed rms amplitude for the source at 1 kHz. Five columns: The first column is the time (x-axis), the second column is the reconstructed amplitude in volt - 1 V (shown as blue solid circle in Fig. 3 bottom), the third column is the temperature in degree C (shown as orange solid square in Fig. 3 top), the fourth column is the atomsepheric pressure in hecto Pascal (shown as green open triangle in Fig. 3 top), the fifth column is the relative humidity in percent (shown as puple open circle in Fig. 2). Format: CSV Fig 4 Allan variance.csv Figure 4 Fig. 4. Allan deviation of the source amplitude measured at 1 V and 1 kHz. Five columns: The first column is the time (x-axis), the second column is the calculated Allan Deviation in volt (shown as blue solid circle in Fig. 4), the third column is the fit on the results, representing the white noise with slope -0.5 (shown as black dash line in Fig. 4), the fourth column is the is the time (x-axis) for the 1/f noise floor plot and the fifth column is the 1/f noise floor (shown as a black solid line in Fig. 4) Format: CSV

Rydberg atom-based receivers of modulated radio frequency (RF) fields are promising systems for measurements. These systems are self-calibrating, widely tunable, nearly transparent to RF fields, and can be electrically small. However, the instantaneous bandwidth of current Rydberg atom receivers is typically less than 1 MHz. Using two-photon electromagnetically induced transparency (EIT) to observe the 56D5/2 Rydberg state in cesium, we measure modulation sidebands on each tooth in a probe optical frequency comb that spans the D2 F=4-F'=5 transition resulting from transmission modulation of the probe beam. This transmission modulation occurs from changes in susceptibility of the room temperature cesium vapor as two RF fields impinge on the atoms. A strong RF local oscillator is resonant with the 56D-57P state and mixes with a weak RF signal field detuned from the RF LO by an intermediate frequency. Using a self-heterodyned electro-optic comb setup, we separate positive and negative sideband amplitudes and compare to an equivalent comb-free system. These data report EIT measurement with the comb system, local spectra around two comb teeth - one within and one outside the EIT line, and normalized minimum detectable RF signal field as a function of RF intermediate frequency used to evaluate the instantaneous bandwidth of the single frequency, positive sideband, and negative sideband datasets.

These data files contain the data for the measured transition frequencies shown in Table I and the traces in Figure 3 of the publication "Frequency-comb spectroscopy on pure quantum states of a single molecular ion," accessible at https://arxiv.org/abs/1911.12808. In this publication we use generally applicable quantum-logic techniques to prepare a trapped molecular ion in a single quantum state, drive terahertz rotational transitions with an optical frequency comb, and read out the molecular state non-destructively, leaving the molecule ready for further manipulation. One file contains data For Table 1. In the measurement of rotational transition frequencies, the intensities of the comb beams are varied to characterize the effect of AC Stark shift, while the intensity ratio between the sigma and pi polarized beams are kept at close to 2. The average intensity of the sigma-polarized comb beam is quantified by measuring the resultant Stark shift, fSS_sigma, on the 729 nm transition of the Ca+ ion, with the Ca+ ion where the CaH+ ion would be during rotational spectroscopy experiments. The other file contains data for Figure 3, (a) Spectra for the J = 4 to 2 transition: 40CaH+ is prepared in J = 2, followed by a pulse train from the comb Raman beams probing the J = 2 to J = 4 transition. After the probe pulse train, projective measurements of both initial and final states are performed and the state occupation probability is determined. The probe time is ~1.6 ms. The frequency shows the offset of the Raman difference frequency from the resonant value. (b) Rabi flopping on the J = 4 to J = 2 transition: Starting in J = 4, with the comb Raman pulse detuning set to resonance, the state of the 40CaH+ ion is driven coherently to J = 2 by a pulse train of variable duration from the comb Raman beams. The center wavelength of the frequency comb was ~800 nm for these spectra and Rabi flopping traces. The error bars stand for ±1 standard deviation.

On-resonance Rydberg atom-based radio-frequency (RF) electric field sensing methods remain limited by the narrow frequency signal detection bands available by resonant transitions. The use ofan additional RF tuner field to dress or shift a target Rydberg state can be used to return a detuned signal field to resonance and thus dramatically extend the frequency range available for resonantsensing. Here we compare three distinct tuning schemes based on adjacent Rydberg transitions, which are shown to have distinct tuning characteristics and can be tuned with mechanisms based onthe tuning field frequency or field strength. We further show that a two-photon Raman feature can be used as an effective tuning mechanism separate from conventional Autler-Townes splitting. Wecompare our tuning schemes to AC Stark effect-based broadband RF field sensing and show that although the sensitivity is diminished as we tune away from a resonant state, it nevertheless can beused in configurations where there is a low density of Rydberg states, which would result in a weak AC Stark effect.

Theoretical calculation, simulation and experimental measurement data from the paper "Bound-state-in-continuum guided modes in a multilayer electro-optically active photonic integrated circuit platform," Optica 11, 706-713 (2024). https://doi.org/10.1364/OPTICA.516044.Abstract: In many physical systems, the interaction with an open environment leads to energy dissipation and reduced coherence, making it challenging to control these systems effectively. In the context of wave phenomena, such lossy interactions can be specifically controlled to isolate the system, a condition known as a bound-state-in-continuum (BIC). Despite the recent advances in engineered BICs for photonic waveguiding, practical implementations are still largely polarization- and geometry-specific, and the underlying principles remain to be systematically explored. Here, we theoretically and experimentally study low loss BIC photonic waveguiding within a two-layer heterogeneous electro-optically active integrated photonic platform. We show that coupling to the slab wave continuum can be selectively suppressed for guided modes with different polarizations and spatial structure. We demonstrate a low-loss same-polarization quasi-BIC guided mode enabling a high extinction Mach-Zehnder electro-optic amplitude modulator within a single Si3N4 ridge waveguide integrated with an extended LiNbO3 slab layer. By elucidating the broad BIC waveguiding principles and demonstrating them in an industry-relevant photonic configuration, this work may inspire innovative approaches to photonic applications such as switching and filtering. The broader impact of this work extends beyond photonics, influencing research in other wave dynamics disciplines, including microwave and acoustics.

Although Rydberg atom-based electric field sensing provides key advantages over traditional antenna-based detection, it remains limited by the need for a local oscillator (LO) for low-field and phase resolved detection. In this work, we demonstrate the general applicability of closed-loop quantum interferometric schemes for Rydberg field sensing, which eliminate the need for an LO. We reveal that the quantum-interferometrically defined phase and frequency of our scheme provides an internal reference that enables LO-free full 360 degree-resolved phase sensitivity. This internal reference can further be used analogously to a traditional LO for atom-based down-mixing to an intermediate frequency for lock-in-based phase detection, which we demonstrate by demodulating a four phase-state signal broadcast on the atoms.

This software package performs joint quantum state and measurement tomography. The software is provided as Python source code. A description of the algorithms used is in "Joint Quantum State and Measurement Tomography with Incomplete Measurements" https://arxiv.org/abs/1803.08245Included are three example scripts that simulate data for one or two trapped ion systems with either symmetric or asymmetric measurements:- analysis_scripts/paper_simulations.py: produces all data and histograms shown in related publication with seed = 0. Also provides an example of symmetric measurements.- analysis_scripts/asym_simulations.py: produces simulated data from asymmetric measurements by similar methods as in previous script.- analysis_scripts/load_tutorial/load_simulations.py: gives an example of loading data with asymmetric measurements.