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Continuum Dexterous Manipulators (CDMs) are well-suited tools for minimally invasive surgery due to their inherent dexterity and reachability. Nonetheless, their flexible structure and non-linear curvature pose significant challenges for shape-based feedback control. The use of Fiber Bragg Grating (FBG) sensors for shape sensing has shown great potential in estimating the CDM's tip position and subsequently reconstructing the shape using optimization algorithms. This optimization, however, is under-constrained and may be ill-posed for complex shapes, falling into local minima. In this work, we introduce a novel method capable of directly estimating a CDM's shape from FBG sensor wavelengths using a deep neural network. In addition, we propose the integration of uncertainty estimation to address the critical issue of uncertainty in neural network predictions. Neural network predictions are unreliable when the input sample is outside the training distribution or corrupted by noise. Recognizing such deviations is crucial when integrating neural networks within surgical robotics, as inaccurate estimations can pose serious risks to the patient. We present a robust method that not only improves the precision upon existing techniques for FBG-based shape estimation but also incorporates a mechanism to quantify the models' confidence through uncertainty estimation. We validate the uncertainty estimation through extensive experiments, demonstrating its effectiveness and reliability on out-of-distribution (OOD) data, adding an additional layer of safety and precision to minimally invasive surgical robotics.

Surgery digitalization is the process of creating a virtual replica of real-world surgery, also referred to as a surgical digital twin (SDT). It has significant applications in various fields such as education and training, surgical planning, and automation of surgical tasks. In addition, SDTs are an ideal foundation for machine learning methods, enabling the automatic generation of training data. In this paper, we present a proof of concept (PoC) for surgery digitalization that is applied to an ex-vivo spinal surgery. The proposed digitalization focuses on the acquisition and modelling of the geometry and appearance of the entire surgical scene. We employ five RGB-D cameras for dynamic 3D reconstruction of the surgeon, a high-end camera for 3D reconstruction of the anatomy, an infrared stereo camera for surgical instrument tracking, and a laser scanner for 3D reconstruction of the operating room and data fusion. We justify the proposed methodology, discuss the challenges faced and further extensions of our prototype. While our PoC partially relies on manual data curation, its high quality and great potential motivate the development of automated methods for the creation of SDTs., Comment: Accepted for the DCA in MI Workshop @ CVPR 2024. Project page: https://jonashein.github.io/surgerydigitization/

The impact of magnetic domains in magnetic flux concentrators is studied using the simulation software MuMax3. First, the simulation parameters are validated using experimental results from magnetic force microscopy; second the simulation output is benchmarked with the one obtained using Comsol Multiphysics. Finally, the impact of magnetic domain is assessed, showing how micromagnetic effects can become relevant, if not dominant, when scaling the gap between the MFC and the sensor., Comment: this is the accepted manuscript

We present a novel locking scheme for active length-stabilization and frequency detuning of a cavity optomechanical device based on the optical spring effect. The scheme can be used as an alternative to the Pound-Drever-Hall locking technique but in contrast doesn't require signal processing on time-scales of the cavity decay rate. It is therefore particularly suited for stabilizing micro cavities, where this time-scale can be extremely fast. The error signal is generated through the optical spring effect, i.e. the detuning-dependent frequency-shift of a nanomechanical oscillator that is dispersively coupled to the intra-cavity light field. We explain the functional principle of the lock and characterize its performance in terms of bandwidth and gain profile. The optical spring locking scheme can be implemented without larger efforts in a wide variety of optomechanical systems in the unresolved sideband regime., Comment: 5 pages, 2 figures

We investigate theoretically and numerically the use of the Least-Squares Finite-element method (LSFEM) to approach data-assimilation problems for the steady-state, incompressible Navier-Stokes equations. Our LSFEM discretization is based on a stress-velocity-pressure (S-V-P) first-order formulation, using discrete counterparts of the Sobolev spaces $H({\rm div}) \times H^1 \times L^2$ respectively. Resolution of the system is via minimization of a least-squares functional representing the magnitude of the residual of the equations. A simple and immediate approach to extend this solver to data-assimilation is to add a data-discrepancy term to the functional. Whereas most data-assimilation techniques require a large number of evaluations of the forward-simulations and are therefore very expensive, the approach proposed in this work uniquely has the same cost as a single forward run. However, the question arises: what is the statistical model implied by this choice? We answer this within the Bayesian framework, establishing the latent background covariance model and the likelihood. Further we demonstrate that - in the linear case - the method is equivalent to application of the Kalman filter, and derive the posterior covariance. We practically demonstrate the capabilities of our method on a backward-facing step case. Our LSFEM formulation (without data) is shown to have good approximation quality, even on relatively coarse meshes - in particular with respect to mass-conservation and reattachment location. Adding limited velocity measurements from experiment, we show that the method is able to correct for discretization error on very coarse meshes, as well as correct for the influence of unknown and uncertain boundary-conditions.

A promising route to novel quantum technologies are hybrid quantum systems, which combine the advantages of several individual quantum systems. We have realized a hybrid atomic-mechanical experiment consisting of a SiN membrane oscillator cryogenically precooled to 500 mK and optically coupled to a cloud of laser cooled Rb atoms. Here, we demonstrate active feedback cooling of the oscillator to a minimum mode occupation of n = 16 corresponding to a mode temperature of T = 200 {\mu}K. Furthermore, we characterize in detail the coupling of the membrane to the atoms by means of sympathetic cooling. By simultaneously applying both cooling methods we demonstrate the possibility of preparing the oscillator near the motional ground state while it is coupled to the atoms. Realistic modifications of our setup will enable the creation of a ground state hybrid quantum system, which opens the door for coherent quantum state transfer, teleportation and entanglement as well as quantum enhanced sensing applications.

We demonstrate that the magnetic nanoskyrmion lattice on the Fe monolayer on Ir(111) and the positions of the Fe atoms can be resolved simultaneously using magnetic exchange force microscopy. Thus, the relation between magnetic and atomic structure can be determined straightforwardly by evaluating the Fourier transformation of the real space image data. We further show that the magnetic contrast can be mapped on a Heisenberg-like magnetic interaction between tip and sample spins. Since our imaging technique is based on measuring forces, our observation paves the way to study skyrmions or other complex spin textures on insulating sample systems with atomic resolution.

We describe the construction of an apparatus designed to realize a hybrid quantum system comprised of a cryogenically cooled mechanical oscillator and ultra-cold $^{87}$Rb atoms coupled via light. The outstanding feature of our instrument is an in-situ adjustable asymmetric all-fiber membrane-in-the-middle cavity located inside an ultra-high vacuum dilution refrigerator based cryostat. We show that Bose-Einstein condensates of $N=2\times10^6$ atoms can be produced in less than 20 s and demonstrate a single photon optomechanical coupling strength of $g_0=2\pi\times9$ kHz employing a high-stress Si$_3$N$_4$ membrane with a mechanical quality factor $Q_{\rm m}>10^7$ at a cavity set-up temperature of $T_{\rm MiM}=480$ mK., Comment: 12 pages, 12 figures; added references; modified figures

The design of an atomic force microscope with an all-fiber interferometric detection scheme capable of atomic resolution at about 500 mK is presented. The microscope body is connected to a small pumped 3He reservoir with a base temperature of about 300 mK. The bakeable insert with the cooling stage can be moved from its measurement position inside the bore of a superconducting 10 T magnet into an ultra-high vacuum chamber, where tip and sample can be exchanged in-situ. Moreover, single atoms or molecules can be evaporated onto a cold substrate located inside the microscope. Two side chambers are equipped with standard surface preparation and surface analysis tools. The performance of the microscope at low temperatures is demonstrated by resolving single Co atoms on Mn/W(110) and by showing atomic resolution on NaCl(001).