Identifying and calibrating quantitative dynamical models for physical quantum systems is important for a variety of applications. Here we present a closed-loop Bayesian learning algorithm for estimating multiple unknown parameters in a dynamical model, using optimized experimental "probe" controls and measurement. The estimation algorithm is based on a Bayesian particle filter, and is designed to autonomously choose informationally optimized probe experiments with which to compare to model predictions. We demonstrate the performance of the algorithm in both simulated calibration tasks and in an experimental single-qubit ion-trap system. Experimentally, we find that, with 60 times fewer samples, we exceed the precision of conventional calibration methods, delivering an approximately 93 times improvement in efficiency (as quantified by the reduction of measurements and resets required to achieve a target residual uncertainty and multiplied by the increase in accuracy). In simulated and experimental demonstrations, we see that successively longer pulses are selected as the posterior uncertainty iteratively decreases, leading to an exponential improvement in the accuracy of model parameters with the number of experimental queries, and a commensurate increase in the per-query time.

Atom-interferometric quantum sensors could revolutionize navigation, civil engineering, and Earth observation. However, operation in real-world environments is challenging due to external interference, platform noise, and constraints on size, weight, and power. Here we experimentally demonstrate that tailored light pulses designed using robust control techniques mitigate significant error sources in an atom-interferometric accelerometer. To mimic the effect of unpredictable lateral platform motion, we apply laser-intensity noise that varies up to 20% from pulse-to-pulse. Our robust control solution maintains performant sensing, while the utility of conventional pulses collapses. By measuring local gravity, we show that our robust pulses preserve interferometer scale factor and improve measurement precision by 10× in the presence of this noise. We further validate these enhancements by measuring applied accelerations over a 200 μ g range up to 21× more precisely at the highest applied noise level. Our demonstration provides a pathway to improved atom-interferometric inertial sensing in real-world settings.

Imaging individual conformational instances of generic, inhomogeneous, transient or intrinsically disordered protein systems at the single molecule level in situ is one of the notable challenges in structural biology. Present techniques access averaged structural information by measuring over large ensembles of proteins in nearly uniform conformational states in synthetic environments. This poses significant implications for diagnostics and drug design which require a detailed understanding of subtle conformational changes, small molecule interactions and ligand dynamics. Here we tackle the problem by designing a single molecule imaging platform technology embracing the advantages silicon-based spin qubits offer in terms of quantum coherence and established fabrication pathways. We demonstrate through detailed simulation, that this platform enables scalable atomic-level structure-determination of individual molecular systems in native environments. The approach is particularly well suited to the high-value lipid-membrane context, and as such its experimental implementation could have far-reaching consequences for the understanding of membrane biology and drug development.

A precessing spin observed in a rotating frame of reference appears frequency-shifted, an effect analogous to the precession of a Foucault pendulum observed on the rotating Earth. This frequency shift can be understood as arising from a magnetic pseudo-field in the rotating frame that nevertheless has physically significant consequences, such as the Barnett effect. Detecting these pseudo-fields is experimentally challenging, as a rotating-frame sensor is required. Previous work has realised classical rotating-frame detectors. Here we use quantum sensors, nitrogen-vacancy (NV) centres, in a rapidly rotating diamond to detect pseudo-fields in the rotating frame. While conventional magnetic fields induce precession at a rate proportional to the gyromagnetic ratio, rotation shifts the precession of all spins equally, and thus primarily affect nearby $^{13}$C nuclear spins. We are thus able to explore these effects via quantum sensing in a rapidly rotating frame, and define a new approach to quantum control using rotationally-induced nuclear spin-selective magnetic fields. This work provides an integral step towards realising precision rotation sensing and quantum spin gyroscopes.

Imaging the atomic structure of a single biomolecule is an important challenge in the physical biosciences. Whilst existing techniques all rely on averaging over large ensembles of molecules, the single-molecule realm remains unsolved. Here we present a protocol for 3D magnetic resonance imaging of a single molecule using a quantum spin probe acting simultaneously as the magnetic resonance sensor and source of magnetic field gradient. Signals corresponding to specific regions of the molecule's nuclear spin density are encoded on the quantum state of the probe, which is used to produce a 3D image of the molecular structure. Quantum simulations of the protocol applied to the rapamycin molecule (C51H79NO13) show that the hydrogen and carbon substructure can be imaged at the angstrom level using current spin-probe technology. With prospects for scaling to large molecules and/or fast dynamic conformation mapping using spin labels, this method provides a realistic pathway for single-molecule microscopy.

Nanomagnetometry using the nitrogen-vacancy (NV) center in diamond has attracted a great deal of interest due to its unique combination of room temperature operation, nanoscale resolution, and high sensitivity. One of the important goals for nanomagnetometry is to be able to detect nanoscale nuclear magnetic resonance (NMR) in individual molecules. Our theoretical analysis details a method by which a single molecule on the surface of diamond, with characteristic NMR frequencies, can be detected using a proximate NV center on a time scale of an order of seconds with nanometer precision. We perform spatiotemporal resolution optimization and subsequently outline paths to greater sensitivity. Our method is suitable for application in low and relatively inhomogeneous background magnetic fields in contrast to both conventional liquid and solid state NMR spectroscopy.

Magnetic field fluctuations arising from fundamental spins are ubiquitous in nanoscale biology, and are a rich source of information about the processes that generate them. However, the ability to detect the few spins involved without averaging over large ensembles has remained elusive. Here, we demonstrate the detection of gadolinium spin labels in an artificial cell membrane under ambient conditions using a single-spin nanodiamond sensor. Changes in the spin relaxation time of the sensor located in the lipid bilayer were optically detected and found to be sensitive to near-individual (4 ± 2) proximal gadolinium atomic labels. The detection of such small numbers of spins in a model biological setting, with projected detection times of 1 s [corresponding to a sensitivity of ∼5 Gd spins per Hz(1/2)], opens a pathway for in situ nanoscale detection of dynamical processes in biology.