Noise-equivalent sensitivity of photoacoustics

The fundamental limitations of photoacoustic microscopy for detecting optically absorbing molecules are investigated both theoretically and experimentally. We experimentally demonstrate noise-equivalent detection sensitivities of 160,000 methylene blue molecules (270 zeptomol or 2.7×10-19  mol) and 86,000 oxygenated hemoglobin molecules (140 zeptomol) using narrowband continuous-wave photoacoustics. The ultimate sensitivity of photoacoustics is fundamentally limited by thermal noise, which can present in the acoustic detection system as well as in the medium itself. Under the optimized conditions described herein and using commercially available detectors, photoacoustic microscopy can detect as few as 100s of oxygenated hemoglobin molecules. Realizable improvements to the detector may enable single molecule detection of select molecules.

Improving impedance of implantable microwire multi-electrode arrays by ultrasonic electroplating of durable platinum black

Implantable microelectrode arrays (MEAs) have been a boon for neural stimulation and recording experiments. Commercially available MEAs have high impedances, due to their low surface area and small tip diameters, which are suitable for recording single unit activity. Lowering the electrode impedance, but preserving the small diameter, would provide a number of advantages, including reduced stimulation voltages, reduced stimulation artifacts and improved signal-to-noise ratio. Impedance reductions can be achieved by electroplating the MEAs with platinum (Pt) black, which increases the surface area but has little effect on the physical extent of the electrodes. However, because of the low durability of Pt black plating, this method has not been popular for chronic use. Sonicoplating (i.e. electroplating under ultrasonic agitation) has been shown to improve the durability of Pt black on the base metals of macro-electrodes used for cyclic voltammetry. This method has not previously been characterized for MEAs used in chronic neural implants. We show here that sonicoplating can lower the impedances of microwire multi-electrode arrays (MMEA) by an order of magnitude or more (depending on the time and voltage of electroplating), with better durability compared to pulsed plating or traditional DC methods. We also show the improved stimulation and recording performance that can be achieved in an in vivo implantation study with the sonicoplated low-impedance MMEAs, compared to high-impedance unplated electrodes.

Cantilever Micro-rheometer for the Characterization of Sugar Solutions

The volume required for the rheological characterization of fluids can be minimized by using micromechanical cantilevers as viscosity sensors. Here, a simple measurement tool for the characterization of sugar solutions is proposed. The sensor consists of a micromechanical cantilever as used in an atomic force microscopy which is integrated into a closed fluid handling system. Fluid properties are derived from an analysis of the power spectral density of the fluctuations of the cantilever deflection signal. The data acquisition system is operated with standard consumer computer components, which limits the costs for the hardware. Measurements with different sugar solutions indicate that the sensor system provides reliable viscosity values for sugar concentrations as they occur in biological systems. The viscosities of the sugar solutions could be evaluated with an error smaller than 5 %.

Modeling the detectability of vesicoureteral reflux using microwave radiometry

We present the modeling efforts on antenna design, frequency selection and receiver sensitivity estimation to detect vesicoureteral reflux (VUR) using microwave (MW) radiometry as warm urine from the bladder maintained at fever range temperature using a MW hyperthermia device reflows into the kidneys. The radiometer center frequency (f(c)), frequency band (Deltaf) and aperture radius (r(a)) of the physical antenna for kidney temperature monitoring are determined using a simplified universal antenna model with a circular aperture. Anatomical information extracted from the computed tomography (CT) images of children aged 4-6 years is used to construct a layered 3D tissue model. Radiometric antenna efficiency is evaluated in terms of the ratio of the power collected from the target at depth to the total power received by the antenna (eta). The power ratio of the theoretical antenna is used to design a microstrip log spiral antenna with directional radiation pattern over f(c) +/- Deltaf/2. Power received by the log spiral from the deep target is enhanced using a thin low-loss dielectric matching layer. A cylindrical metal cup is proposed to shield the antenna from electromagnetic interference (EMI). Transient thermal simulations are carried out to determine the minimum detectable change in the antenna brightness temperature (deltaT(B)) for 15-25 mL urine refluxes at 40-42 degrees C located 35 mm from the skin surface. Theoretical antenna simulations indicate maximum eta over 1.1-1.6 GHz for r(a) = 30-40 mm. Simulations of the 35 mm radius tapered log spiral yielded a higher power ratio over f(c) +/- Deltaf/2 for the 35-40 mm deep targets in the presence of an optimal matching layer. Radiometric temperature calculations indicate deltaT(B) 0.1 K for the 15 mL urine at 40 degrees C and 35 mm depth. Higher eta and deltaT(B) were observed for the antenna and matching layer inside the metal cup. Reflection measurements of the log spiral in a saline phantom are in agreement with the simulation data. The numerical study suggests that a radiometer with f(c) = 1.35 GHz, Deltaf = 500 MHz and detector sensitivity better than 0.1 K would be the appropriate tool to noninvasively detect VUR using the log spiral antenna.

Practical Considerations for Accuracy Evaluation in Sensor-Based Machine Learning and Deep Learning

Accuracy evaluation in machine learning is based on the split of data into a training set and a test set. This critical step is applied to develop machine learning models including models based on sensor data. For sensor-based problems, comparing the accuracy of machine learning models using the train/test split provides only a baseline comparison in ideal situations. Such comparisons won't consider practical production problems that can impact the inference accuracy such as the sensors' thermal noise, performance with lower inference quantization, and tolerance to sensor failure. Therefore, this paper proposes a set of practical tests that can be applied when comparing the accuracy of machine learning models for sensor-based problems. First, the impact of the sensors' thermal noise on the models' inference accuracy was simulated. Machine learning algorithms have different levels of error resilience to thermal noise, as will be presented. Second, the models' accuracy using lower inference quantization was compared. Lowering inference quantization leads to lowering the analog-to-digital converter (ADC) resolution which is cost-effective in embedded designs. Moreover, in custom designs, analog-to-digital converters' (ADCs) effective number of bits (ENOB) is usually lower than the ideal number of bits due to various design factors. Therefore, it is practical to compare models' accuracy using lower inference quantization. Third, the models' accuracy tolerance to sensor failure was evaluated and compared. For this study, University of California Irvine (UCI) 'Daily and Sports Activities' dataset was used to present these practical tests and their impact on model selection.

Mechanical-thermal noise in drive-mode of a silicon micro-gyroscope

A new closed-loop drive scheme which decouples the phase and the gain of the closed-loop driving system was designed in a Silicon Micro-Gyroscope (SMG). We deduce the system model of closed-loop driving and use stochastic averaging to obtain an approximate “slow” system that clarifies the effect of thermal noise. The effects of mechanical-thermal noise on the driving performance of the SMG, including the noise spectral density of the driving amplitude and frequency, are derived. By calculating and comparing the noise amplitude due to thermal noise both in the opened-loop driving and in the closed-loop driving, we find that the closed-loop driving does not reduce the RMS noise amplitude. We observe that the RMS noise frequency can be reduced by increasing the quality factor and the drive amplitude in the closed-loop driving system. The experiment and simulation validate the feasibility of closed-loop driving and confirm the validity of the averaged equation and its stablility criterion. The experiment and simulation results indicate the electrical noise of closed-loop driving circuitry is bigger than the mechanical-thermal noise and as the driving mass decreases, the mechanical-thermal noise may get bigger than the electrical noise of the closed-loop driving circuitry.

Single molecule detection, thermal fluctuation and life

Single molecule detection has contributed to our understanding of the unique mechanisms of life. Unlike artificial man-made machines, biological molecular machines integrate thermal noises rather than avoid them. For example, single molecule detection has demonstrated that myosin motors undergo biased Brownian motion for stepwise movement and that single protein molecules spontaneously change their conformation, for switching to interactions with other proteins, in response to thermal fluctuation. Thus, molecular machines have flexibility and efficiency not seen in artificial machines.

Characterization of the mechanical properties of qPlus sensors

In this paper we present a comparison of three different methods that can be used for estimating the stiffness of qPlus sensors. The first method is based on continuum theory of elasticity. The second (Cleveland's method) uses the change in the eigenfrequency that is induced by the loading of small masses. Finally, the stiffness is obtained by analysis of the thermal noise spectrum. We show that all three methods give very similar results. Surprisingly, neither the gold wire nor the gluing give rise to significant changes of the stiffness in the case of our home-built sensors. Furthermore we describe a fast and cost-effective way to perform Cleveland's method. This method is based on gluing small pieces of a tungsten wire; the mass is obtained from the volume of the wire, which is measured by optical microscopy. To facilitate detection of oscillation eigenfrequencies under ambient conditions, we designed and built a device for testing qPlus sensors.

Real-Time Measurement of Nanotube Resonator Fluctuations in an Electron Microscope

Mechanical resonators based on low-dimensional materials provide a unique platform for exploring a broad range of physical phenomena. The mechanical vibrational states are indeed extremely sensitive to charges, spins, photons, and adsorbed masses. However, the roadblock is often the readout of the resonator, because the detection of the vibrational states becomes increasingly difficult for smaller resonators. Here, we report an unprecedentedly sensitive method to detect nanotube resonators with effective masses in the 10^-20 kg range. We use the beam of an electron microscope to resolve the mechanical fluctuations of a nanotube in real-time for the first time. We obtain full access to the thermally driven Brownian motion of the resonator, both in space and time domains. Our results establish the viability of carbon nanotube resonator technology at room temperature and pave the way toward the observation of novel thermodynamics regimes and quantum effects in nanomechanics.

Development of mirror coatings for gravitational-wave detectors

Gravitational waves are detected by measuring length changes between mirrors in the arms of kilometre-long Michelson interferometers. Brownian thermal noise arising from thermal vibrations of the mirrors can limit the sensitivity to distance changes between the mirrors, and, therefore, the ability to measure gravitational-wave signals. Thermal noise arising from the highly reflective mirror coatings will limit the sensitivity both of current detectors (when they reach design performance) and of planned future detectors. Therefore, the development of coatings with low thermal noise, which at the same time meet strict optical requirements, is of great importance. This article gives an overview of the current status of coatings and of the different approaches for coating improvement.This article is part of a discussion meeting issue 'The promises of gravitational-wave astronomy'.

Understanding the physical relations governing the noise navigator

Purpose

The noise navigator is a passive way to detect physiological motion occurring in a patient through thermal noise modulations measured by standard clinical radiofrequency receive coils. The aim is to gain a deeper understanding of the potential and applications of physiologically induced thermal noise modulations.

Methods

Numerical electromagnetic simulations and MR measurements were performed to investigate the relative contribution of tissue displacement versus modulation of the dielectric lung properties over the respiratory cycle, the impact of coil diameter and position with respect to the body. Furthermore, the spatial motion sensitivity of specific noise covariance matrix elements of a receive array was investigated.

Results

The influence of dielectric lung property variations on the noise variance is negligible compared to tissue displacement. Coil size affected the thermal noise variance modulation, but the location of the coil with respect to the body had a larger impact. The modulation depth of a 15 cm diameter stationary coil approximately 3 cm away from the chest (i.e. radiotherapy setup) was 39.7% compared to 4.2% for a coil of the same size on the chest, moving along with respiratory motion. A combination of particular noise covariance matrix elements creates a specific spatial sensitivity for motion.

Conclusions

The insight gained on the physical relations governing the noise navigator will allow for optimized use and development of new applications. An optimized combination of elements from the noise covariance matrix offer new ways of performing, e.g. motion tracking.

On-Line Multi-Frequency Electrical Resistance Tomography (mfERT) Device for Crystalline Phase Imaging in High-Temperature Molten Oxide

An on-line multi-frequency electrical resistance tomography (mfERT) device with a melt-resistive sensor and noise reduction hardware has been proposed for crystalline phase imaging in high-temperature molten oxide. The melt-resistive sensor consists of eight electrodes made of platinum-rhodium (Pt-20mass%Rh) alloy covered by non-conductive aluminum oxide (Al₂O₃) to prevent an electrical short. The noise reduction hardware has been designed by two approaches: (1) total harmonic distortion (THD) for the robust multiplexer, and (2) a current injection frequency pair: low fL and high fH, for thermal noise compensation. THD is determined by a percentage evaluation of k-th harmonic distortions of ZnO at f=0.1~10,000 Hz. The fL and fH are determined by the thermal noise behavior estimation at different temperatures. At &nbsp;f&nbsp;<100 Hz, the THD percentage is relatively high and fluctuates; otherwise, THD dramatically declines, nearly reaching zero. At the determined fL≥ 10,000 Hz and fH≈ 1,000,000 Hz, thermal noise is significantly compensated. The on-line mfERT was tested in the experiments of a non-conductive Al₂O₃ rod dipped into conductive molten zinc-borate (60ZnO-40B₂O₃) at 1000~1200 °C. As a result, the on-line mfERT is able to reconstruct the Al₂O₃ rod inclusion images in the high-temperature fields with low error, ςfL,&nbsp;T = 5.99%, at 1000 °C, and an average error&nbsp;⟨ςfL⟩ = 9.2%.

Adaptive-Cognitive Kalman Filter and Neural Network for an Upgraded Nondispersive Thermopile Device to Detect and Analyze Fusarium Spores

Noises such as thermal noise, background noise or burst noise can reduce the reliability and confidence of measurement devices. In this work, a recursive and adaptive Kalman filter is proposed to detect and process burst noise or outliers and thermal noise, which are popular in electrical and electronic devices. The Kalman filter and neural network are used to preprocess data of three detectors of a nondispersive thermopile device, which is used to detect and quantify Fusarium spores. The detectors are broadband (1 µm to 20 µm), λ 1 (6.09 ± 0.06 µm) and λ 2 (9.49 ± 0.44 µm) thermopiles. Additionally, an artificial neural network (NN) is applied to process background noise effects. The adaptive and cognitive Kalman Filter helps to improve the training time of the neural network and the absolute error of the thermopile data. Without applying the Kalman filter for λ 1 thermopile, it took 12 min 09 s to train the NN and reach the absolute error of 2.7453 × 104 (n. u.). With the Kalman filter, it took 46 s to train the NN to reach the absolute error of 1.4374 × 104 (n. u.) for λ 1 thermopile. Similarly, to the λ 2 (9.49 ± 0.44 µm) thermopile, the training improved from 9 min 13 s to 1 min and the absolute error of 2.3999 × 105 (n. u.) to the absolute error of 1.76485 × 105 (n. u.) respectively. The three-thermopile system has proven that it can improve the reliability in detection of Fusarium spores by adding the broadband thermopile. The method developed in this work can be employed for devices that encounter similar noise problems.

An Inbuilt Electronic Pawl Gates Orbital Information Processing and Controls the Rotation of a Double Ratchet Rotary Motor

A direct external input energy source (e.g., light, chemical reaction, redox potential, etc.) is compulsory to supply energy to rotary motors for accomplishing rotation around the axis. The stator leads the direction of rotation, and a sustainable rotation requires two mutual input energy supplies (e.g., light and heat, light and pH or metal ion, etc.); however, there are some exceptions (e.g., covalent single bond rotors and/or motors). On the contrary, our experiment suggested that double ratchet rotary motors (DRMs) can harvest power from available thermal noise, kT, for sustainable rotation around the axis. Under a scanning tunneling microscope, we have imaged live thermal noise movement as a dynamic orbital density and resolved the density diagram up to the second derivative. A second input energy can synchronize multiple rotors to afford a measurable output. Therefore, we hypothesized that rotation control in a DRM must be evolved from an orbital-level information transport channel between the two coupled rotors but was not limited to the second input energy. A DRM comprises a Brownian rotor and a power stroke rotor coupled to a -C≡C- stator, where the transport of information through coupled orbitals between the two rotors is termed the vibrational information flow chain (VIFC). We test this hypothesis by studying the DRM's density functional theory calculation and variable-temperature ¹H nuclear magnetic resonance. Additionally, we introduced inbuilt pawl-like functional moieties into a DRM to create different electronic environments by changing proton intercalation interactions, which gated information processing through the VIFC. The results show the VIFC can critically impact the motor's noise harvesting, resulting in variable rotational motions in DRMs.

Evaluation of Uncertainties of the Null-Balanced Total-Power Radiometer System NCS1

Standard uncertainties are evaluated for the null-balanced, total-power, heterodyned radiometer system with a switched input that was recently developed at NIST to calibrate thermal noise sources. Eight significant sources of uncertainty due to systematic effects are identified, two attributable to the two noise standards, and one each to connectors, the input mismatch, the input switch asymmetry, the isolator, the broadband mismatch and the attenuator. The combined standard uncertainty of a typical coaxial noise source calibration at a representative frequency of 2 GHz is about 1%, A strategy for reducing uncertainties is discussed.

Noise Reduction Techniques and Scaling Effects towards Photon Counting CMOS Image Sensors

This paper presents an overview of the read noise in CMOS image sensors (CISs) based on four-transistors (4T) pixels, column-level amplification and correlated multiple sampling. Starting from the input-referred noise analytical formula, process level optimizations, device choices and circuit techniques at the pixel and column level of the readout chain are derived and discussed. The noise reduction techniques that can be implemented at the column and pixel level are verified by transient noise simulations, measurement and results from recently-published low noise CIS. We show how recently-reported process refinement, leading to the reduction of the sense node capacitance, can be combined with an optimal in-pixel source follower design to reach a sub-0.3erms- read noise at room temperature. This paper also discusses the impact of technology scaling on the CIS read noise. It shows how designers can take advantage of scaling and how the Metal-Oxide-Semiconductor (MOS) transistor gate leakage tunneling current appears as a challenging limitation. For this purpose, both simulation results of the gate leakage current and 1/f noise data reported from different foundries and technology nodes are used.

Advanced technologies for future ground-based, laser-interferometric gravitational wave detectors

We present a review of modern optical techniques being used and developed for the field of gravitational wave detection. We describe the current state-of-the-art of gravitational waves detector technologies with regard to optical layouts, suspensions and test masses. We discuss the dominant sources and noise in each of these subsystems and the developments that will help mitigate them for future generations of detectors. We very briefly summarise some of the novel astrophysics that will be possible with these upgraded detectors.

NOise Reduction with DIstribution Corrected (NORDIC) principal component analysis improves brain activity detection across rodent and human functional MRI contexts

NOise Reduction with DIstribution Corrected (NORDIC) principal component analysis (PCA) has been shown to selectively suppress thermal noise and improve the temporal signal-to-noise ratio (tSNR) in human functional magnetic resonance imaging (fMRI). However, the feasibility to improve data quality for rodent fMRI using NORDIC PCA remains uncertain. NORDIC PCA may also be particularly beneficial for improving topological brain mapping, as conventional mapping requires precise spatiotemporal signals from large datasets (ideally ~1 hour acquisition) for individual representations. In this study, we evaluated the effects of NORDIC PCA compared with "Standard" processing in various rodent fMRI contexts that range from task-evoked optogenetic fMRI to resting-state fMRI. We also evaluated the effects of NORDIC PCA on human resting-state and retinotopic mapping fMRI via population receptive field (pRF) modeling. In rodent optogenetic fMRI, apart from doubling the tSNR, NORDIC PCA resulted in a larger number of activated voxels and a significant decrease in the variance of evoked brain responses without altering brain morphology. In rodent resting-state fMRI, we found that NORDIC PCA induced a nearly threefold increase in tSNR and preserved task-free relative cerebrovascular reactivity (rCVR) across cortical depth. NORDIC PCA further improved the detection of TGN020-induced aquaporin-4 inhibition on rCVR compared with Standard processing without NORDIC PCA. NORDIC PCA also increased the tSNR for both human resting-state and pRF fMRI, and for the latter also increased activation cluster sizes while retaining retinotopic organization. This suggests that NORDIC PCA preserves the spatiotemporal precision of fMRI signals needed for pRF analysis, and effectively captures small activity changes with high sensitivity. Taken together, these results broadly demonstrate the value of NORDIC PCA for the enhanced detection of neural dynamics across various rodent and human fMRI contexts. This can in turn play an important role in improving fMRI image quality and sensitivity for translational and preclinical neuroimaging research.

In situthermal noise measurements under nanoindentation of suspended graphene

We demonstrated thermal noise measurement under the nanoindentation of monolayer and bilayer graphene nanodrums. The resonant oscillation of the cantilever excited only by a thermal energy is detectable even in the case of contact with a suspended graphene. The contact resonance fRequency can be obtained in 1 millisecond intervals during the force curve measurement by optimizing the parameters of a real-time spectrum analyzer. The pretension value of the graphene nanodrum is evaluated by the minimum frequency just when the applied force of the cantilever becomes zero. The simultaneous measurement of the force and the resonant frequency with respect to the deformation of the graphene nanodrum enables us to determine the value of InvOLS (inverse optical lever sensitivity) more accurately in each measurement. From the analysis scheme, force curve measurements of the graphene nanodrums with the same diameters show good reproducibility. We also revealed that the effective spring constant of the graphene nanodrums consists of a weak sample-dependent pretension factor and a deformation-dependent factor proportional to the number of graphene layers.

Quantum and thermal noise in coupled non-Hermitian waveguide systems with different models of gain and loss

Non-Hermitian (NH) photonic systems leverage gain and loss to open new directions for nanophotonic technologies. However, the quantum and thermal noise intrinsically associated with gain/loss affects the eigenvalue/eigenvector structure of NH systems, and thus the existence of exceptional points, as well as the practical noise performance of these systems. Here, we present a comparative analysis of the impact of different gain and loss mechanisms on the noise generated in gain-loss compensated NH waveguide systems. Our results highlight important differences in the eigenvalue/eigenvector structure, noise power, photon statistics and squeezing. At the same time, we identify some universal properties such as the occurrence of phase-transition points in parameter space and intriguing phenomena related to them, including coalescence of pairs of eigenvectors, gain-loss compensation, and linear scaling of the noise with the length of the waveguide. We believe that these results contribute to a better understanding of the impact of the gain/loss mechanism on the noise generated in NH systems.

Delta-T Flicker Noise Demonstrated with Molecular Junctions

Electronic flicker noise is recognized as the most abundant noise in electronic conductors, either as an unwanted contribution or as a source of information on electron transport mechanisms and material properties. This noise is typically observed when a voltage difference is applied across a conductor or current is flowing through it. Here, we identify an unknown type of electronic flicker noise that is found when a temperature difference is applied across a nanoscale conductor in the absence of a net charge current or voltage bias. The revealed delta-T flicker noise is demonstrated in molecular junctions and characterized using quantum transport theory. This noise is expected to arise in nanoscale electronic conductors subjected to unintentional temperature gradients, where it can be a performance-limiting factor. On the positive side, delta-T flicker noise can detect temperature differences across a large variety of nanoscale conductors, down to atomic-scale junctions with no special setup requirements.

Stiffness calibration of qPlus sensors at low temperature through thermal noise measurements

Non-contact atomic force microscopy (nc-AFM) offers a unique experimental framework for topographical imaging of surfaces with atomic and/or sub-molecular resolution. The technique also permits to perform frequency shift spectroscopy to quantitatively evaluate the tip-sample interaction forces and potentials above individual atoms or molecules. The stiffness of the probe, k, is then required to perform the frequency shift-to-force conversion. However, this quantity is generally known with little precision. An accurate stiffness calibration is therefore mandatory if accurate force measurements are targeted. In nc-AFM, the probe may either be a silicon cantilever, a quartz tuning fork (QTF), or a length extensional resonator (LER). When used in ultrahigh vacuum (UHV) and at low temperature, the technique mostly employs QTFs, based on the so-called qPlus design, which actually covers different types of sensors in terms of size and design of the electrodes. They all have in common a QTF featuring a metallic tip glued at the free end of one of its prongs. In this study, we report the stiffness calibration of a particular type of qPlus sensor in UHV and at 9.8 K by means of thermal noise measurements. The stiffness calibration of such high-k sensors, featuring high quality factors (Q) as well, requires to master both the acquisition parameters and the data post-processing. Our approach relies both on numerical simulations and experimental results. A thorough analysis of the thermal noise power spectral density of the qPlus fluctuations leads to an estimated stiffness of the first flexural eigenmode of ≃2000 N/m, with a maximum uncertainty of 10%, whereas the static stiffness of the sensor without tip is expected to be ≃3300 N/m. The former value must not be considered as being representative of a generic value for any qPlus, as our study stresses the influence of the tip on the estimated stiffness and points towards the need for the individual calibration of these probes. Although the framework focuses on a particular kind of sensor, it may be adapted to any high-k, high-Q nc-AFM probe used under similar conditions, such as silicon cantilevers and LERs.

Noise in NC-AFM measurements with significant tip-sample interaction

The frequency shift noise in non-contact atomic force microscopy (NC-AFM) imaging and spectroscopy consists of thermal noise and detection system noise with an additional contribution from amplitude noise if there are significant tip-sample interactions. The total noise power spectral density DΔf (fm) is, however, not just the sum of these noise contributions. Instead its magnitude and spectral characteristics are determined by the strongly non-linear tip-sample interaction, by the coupling between the amplitude and tip-sample distance control loops of the NC-AFM system as well as by the characteristics of the phase locked loop (PLL) detector used for frequency demodulation. Here, we measure DΔf (fm) for various NC-AFM parameter settings representing realistic measurement conditions and compare experimental data to simulations based on a model of the NC-AFM system that includes the tip-sample interaction. The good agreement between predicted and measured noise spectra confirms that the model covers the relevant noise contributions and interactions. Results yield a general understanding of noise generation and propagation in the NC-AFM and provide a quantitative prediction of noise for given experimental parameters. We derive strategies for noise-optimised imaging and spectroscopy and outline a full optimisation procedure for the instrumentation and control loops.

Adiabatic computing for optimal thermodynamic efficiency of information processing

Landauer's principle makes a strong connection between information theory and thermodynamics by stating that erasing a one-bit memory at temperature [Formula: see text] requires an average energy larger than [Formula: see text], with [Formula: see text] Boltzmann's constant. This tiny limit has been saturated in model experiments using quasistatic processes. For faster operations, an overhead proportional to the processing speed and to the memory damping appears. In this article, we show that underdamped systems are a winning strategy to reduce this extra energetic cost. We prove both experimentally and theoretically that, in the limit of vanishing dissipation mechanisms in the memory, the physical system is thermally insulated from its environment during fast erasures, i.e., fast protocols are adiabatic as no heat is exchanged with the bath. Using a fast optimal erasure protocol, we also show that these adiabatic processes produce a maximum adiabatic temperature [Formula: see text], and that Landauer's bound for fast erasures in underdamped systems becomes the adiabatic bound: [Formula: see text].