Automation in quantum logic experiments with cold molecular ions

TL;DR

This work addresses the bottlenecks of manual, timing-critical workflows in quantum-logic experiments with molecular ions by delivering a fully automated control system that coordinates crystal loading, dark-ion recognition, ion reduction, mass/state identification, and spectroscopy. It leverages a modular, distributed architecture with two primary modules (loading and measurement), real-time image analysis, and the Sinara/ARTIQ framework for nanosecond-level control, enabling unsupervised operation over extended periods. The system delivers significant gains in experimental throughput—up to about tenfold in cycles and eightfold in loaded molecules—through adaptive feedback, robust error handling, and comprehensive logging. The approach provides a scalable blueprint for similar molecular-ion experiments, with future improvements anticipated in laser stability, autonomous micromotion compensation, and potential machine-learning enhancements to further boost efficiency and reliability.

Abstract

Modern experiments with cold molecular ions have reached a high degree of complexity requiring frequent sample preparation, state initialization and protocol execution while demanding precise control over multiple devices and laser sources. To maintain a high experimental duty cycle and robust measurement conditions, automation becomes essential. We present a fully automated control system for the preparation of trapped state-selected molecular ions and subsequent quantum logic-based experiments. Adaptive feedback routines based on real-time image analysis introduce and identify single molecular ions in atomic-ion Coulomb crystals. By appropriate manipulation of the trapping potentials, excess atomic ions are released from the trap to produce dual-species two-ion strings, here Ca$^+-$N$_2^+$. After mass and state identification of the molecular ion, nanosecond-level synchronization of laser pulses employing the Sinara/ARTIQ framework and real-time data analysis enable quantum-logic-spectroscopic measurements. The present automated control system enables robust, unsupervised operation over extended periods resulting in an increase of the number of experimentation cycles by about a factor of ten compared to manual operation and a factor of about eight in loaded molecules in typical practical situations. The modular, distributed design of the system provides a scalable blueprint for similar molecular-ion experiments.

Figures (5)

• Figure 1: a) Experimental setup consisting of a molecular-beam machine and an ultrahigh-vacuum chamber containing the ion trap and a Ca oven. A piezo valve produces a beam of neutral N$_2$ molecules which passes through skimmers and a gate valve to reach the ion trap. Laser beams: blue: photoionization of Ca (423 nm, 375 nm), coherent manipulation and cooling of Ca$^+$ (729 nm, 397 nm, 866 nm, 854 nm); green: photoionization of N$_2$ (212 nm, 255 nm), spectroscopy of N$_2^+$ (4.5 $\mu$m); red: state detection of N$_2^+$. b) Generation of a Ca$^+$-N$_2^+$ two-ion string: A small Coulomb crystal of Ca$^+$ ions is prepared in the trap. After generation and sympathetic cooling of a single N$_2^+$ ion, the 3D crystal is transformed into a string to more easily detect the single dark molecular ion. Following reduction of the crystal to a two-ion string, the mass of the molecular ion is measured by resonant motional excitation. c) Quantum-logic spectroscopy scheme: a travelling optical lattice exerts an optical dipole force on N$_2^+$ to cause motional excitation of the ion string depending on its internal state. See text for details.
• Figure 2: a) The control system comprises an ion-loading module (green) and a measurement module (blue), each controlling a set of hardware components (gray) via software routines for designated tasks. Subroutines (red) such as wavemeter readout and laser relocking support the routines. Communication between different components of the control system (dotted lines) is carried out via TCP/IP. b) The control logic executes routines sequentially, only proceeding if a routine terminated successfully and restarting the cycle otherwise.
• Figure 3: Camera images (panels a, e) and corresponding fluorescence-intensity profiles (panels b, d) before and after loading a single N$_2^+$ ion. Shaded areas in (b) and (d) indicate the standard deviation over an average of multiple frames. Vertical red and blue lines designate peak markers, dashed gray lines the peak-finding thresholds. The detector panel (c) visualizes the dark-ion detection algorithm. Purple lines indicate the difference in the inter-ion distances and gray vertical lines mark thresholds $\pm T_i$ for each gap. See text for details.
• Figure 4: Stability diagram of the ion trap indicating configurations used during measurements (blue), ion loading (green), ion counting (yellow), and crystal reduction (red) for Ca$^+$ (diamonds) and N$_2^+$ (stars).
• Figure 5: a) Rabi flop on a motional sideband of the in-phase motional mode for N$_2^+$ in its rovibrational ground state (blue trace) and in an excited state (red trace). A background measurement before applying the lattice lasers (green trace) serves to discriminate systematic errors. Solid lines represent fits of the data Sinhal20a. b) In subsequent QLS measurements, only data points around the time of maximum contrast in the Rabi flop are taken, averaged to a single value and compared with each other yielding the following outcomes of the state-detection measurements during the spectroscopy protocol: (i) successful spectroscopic excitation experiment from the ground state, (ii) no spectroscopic excitation detected, (iii) loss of ion during the sequence. See text for details.