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At least 91 records · Page 5

An analysis of carrier dynamics in methylammonium lead triiodide perovskite solar cells using cross correlation noise spectroscopy

Using cross correlation current noise spectroscopy, we have investigated carrier dynamics in methylammonium lead triiodide solar cells. This method provides space selectivity for devices with a planar multi-layered structure, effectively amplifying current noise contributions coming from the most resistive element of the stack. In the studied solar cells, we observe near full-scale shot noise, indicating the dominance of noise generation by a single source, likely the interface between the perovskite and the spiro-organic 2,2',7,7'-tetrakis(N,N-di-p-methoxyphenyl-amine)9,9'-spirobifluorene hole-transport layer. In this paper, we argue that the strong 1/f noise term has contributions from both the perovskite layer and interfaces. It displays a non-ideal dependence on photocurrent, S $\propto$ I 1.4 (instead of usual S $\propto$ I 2 ), which is likely due to current-induced halide migration. Finally, we observe generation–recombination noise. We argue that this contribution is due to bimolecular recombination in the perovskite bulk absorption layer. Extrapolating our results, we estimate that at standard 1 sun illumination, the electron–hole recombination time is 5 microseconds.

14 SOLAR ENERGY↗

Excess noise in high-current diamond diodes

We report the results of an investigation of low-frequency excess noise in high-current diamond diodes. It was found that the electronic excess noise of the diamond diodes is dominated by the 1/f and generation-recombination noise, which reveals itself as Lorentzian spectral features (f is the frequency). The generation-recombination bulges are characteristic of diamond diodes with lower turn-on voltages. The noise spectral density dependence on forward current, I, reveals three distinctive regions in all examined devices—it scales as I 2 at the low (I < 10 μA) and high (I > 10 mA) currents and, rather unusually, remains nearly constant at the intermediate current range. The characteristic trap time constants, extracted from the noise data, show a uniquely strong dependence on current. Interestingly, the performance of the diamond diodes improves with the increasing temperature. The obtained results are important for the development of noise spectroscopy-based approaches for device reliability assessment for high-power diamond electronics.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Anomalous magnetic noise in an imperfectly flat landscape in the topological magnet Dy 2 Ti 2 O 7

Noise generated by motion of charge and spin provides a unique window into materials at the atomic scale. From temperature of resistors to electrons breaking into fractional quasiparticles, “listening” to the noise spectrum is a powerful way to decode underlying dynamics. Here, we use ultrasensitive superconducting quantum interference device (SQUIDs) to probe the puzzling noise in a frustrated magnet, the spin-ice compound Dy 2 Ti 2 O 7 (DTO), revealing cooperative and memory effects. DTO is a topological magnet in three dimensions—characterized by emergent magnetostatics and telltale fractionalized magnetic monopole quasiparticles—whose real-time dynamical properties have been an enigma from the very beginning. We show that DTO exhibits highly anomalous noise spectra, differing significantly from the expected Brownian noise of monopole random walks, in three qualitatively different regimes: equilibrium spin ice, a “frozen” regime extending to ultralow temperatures, and a high-temperature “anomalous” paramagnet. We present several distinct mechanisms that give rise to varied colored noise spectra. In addition, we identify the structure of the local spin-flip dynamics as a crucial ingredient for any modeling. Thus, the dynamics of spin ice reflects the interplay of local dynamics with emergent topological degrees of freedom and a frustration-generated imperfectly flat energy landscape, and as such, it points to intriguing cooperative and memory effects for a broad class of magnetic materials.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Noise and thermal depinning of Wigner crystals

We examine changes in the depinning threshold and conduction noise fluctuations for driven Wigner crystals in the presence of quenched disorder. At low temperatures there is a well defined depinning threshold and a strong peak in the noise power with 1/f noise characteristics. At higher temperatures, the depinning threshold shifts to lower drives and the noise, which is also reduced in power, becomes more white in character. At lower temperatures, a washboard frequency appears when the system depins elastically or forms a moving smectic state; however, this washboard signal is strongly reduced for higher temperatures and completely disappears above the melting temperature of a system without quenched disorder. Our results are in good agreement with recent transport and noise studies for systems where electron crystal depinning is believed to arise, and also show how noise can be used to distinguish between crystal, glass, and liquid phases.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Stabilizing and Improving Qubit Coherence by Engineering the Noise Spectrum of Two-Level Systems

Superconducting circuits are a leading platform for quantum computing. However, their coherence times are still limited and exhibit temporal fluctuations. Those phenomena are often attributed to the coupling between qubits and material defects that can be well described as an ensemble of two-level systems (TLSs). Among them, charge fluctuators inside amorphous oxide layers contribute to both low-frequency 1 / f charge noise and high-frequency dielectric loss, causing fast qubit dephasing and relaxation. Moreover, spectral diffusion from mutual TLS interactions varies the noise amplitude over time, fluctuating the qubit lifetime. Here, we propose to mitigate those harmful effects by engineering the relevant TLS noise spectral densities. Specifically, our protocols smooth the high-frequency noise spectrum and suppress the low-frequency noise amplitude via depolarizing and dephasing the TLSs, respectively. As a result, we predict a drastic stabilization in qubit lifetime and an increase in qubit pure dephasing time. Our detailed analysis of feasible experimental implementations shows that the improvement is not compromised by spurious coupling from the applied noise to the qubit.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Readout Noise of Digital Frequency Multiplexed TES Detectors for CUPID

The superconducting transition-edge sensor (TES) detectors have been the standard in cosmic microwave background (CMB) experiments for almost two decades and are now being adapted for use in nuclear physics, such as neutrinoless double beta decay searches. In this article, we focus on a new high-bandwidth frequency multiplexed TES readout system developed for CUPID, a neutrinoless double beta decay experiment that will replace CUORE. In order to achieve the high energy resolution requirements for CUPID, the readout noise of the system must be kept to a minimum. Low TES operating resistance and long wiring between the readout SQUID and the warm electronics are needed for CUPID, prompting a careful consideration of the design parameters of this application of frequency multiplexing. In this work, we characterize the readout noise of the newly designed frequency multiplexed TES readout system for CUPID and construct a noise model to understand it. Here, we find that current sharing between the SQUID coil impedance and other branches of the circuit, as well as the long output wiring, worsen the readout noise of the system. To meet noise requirements, a SQUID with a low input inductance, high transimpedance, and/or low dynamic impedance is needed, and the wiring capacitance should be kept as small as possible. Alternatively, the option of adding a cryogenic low-noise amplifier at the output of the SQUID should be explored.

CUPID↗

Noise-aware optimization in nominally identical manufacturing and measuring systems for high-throughput parallel workflows

Device-to-device variability in experimental noise critically impacts reproducibility, especially in automated, high-throughput systems like additive manufacturing farms. While manageable in small labs, such variability can escalate into serious risks at larger scales, such as architectural 3D printing, where noise may cause structural or economic failures. This contribution presents a noise-aware decision-making algorithm that quantifies and models device-specific noise profiles to manage variability adaptively. It uses distributional analysis and pairwise divergence metrics with clustering to choose between single-device and robust multi-device Bayesian optimization strategies. Unlike conventional methods that assume homogeneous devices or enforce generic robustness, the proposed framework explicitly determines whether shared optimization across devices is appropriate based on the degree of inter-device noise heterogeneity. This enables improved performance, reproducibility, and efficiency. An experimental case study involving three nominally identical 3D printers (same brand, model, and close serial numbers) demonstrates reduced redundancy, lower resource usage, and improved reliability, along with improved convergence stability and solution quality through the selection of the appropriate optimization strategy based on the degree of inter-device noise heterogeneity. Overall, this framework establishes a general approach for precision- and resource-aware optimization in scalable, automated experimental platforms, demonstrated here on a representative multi-device 3D printing case study.

Schenk, Christina↗

Dynamics of coupled thermoacoustic modes: Noise and frequency spacing effects

Practical combustion systems consist of multiple thermoacoustic modes that are linearly stable or unstable at a wide range of frequencies. When coupled, the modal interactions are a strong function of the frequency spacing between them – having very significant implications on interpretation of linear stability or instability of modes from experimental data. Frequency spacing between the modes particularly influences the stability and existence of potential limit cycle solutions. In this paper, we extend earlier deterministic studies to include the effects of noise, studying how deterministic dynamics change with the addition of noise and the simultaneous impact of frequency spacing (i.e., closely, or widely spaced). Specifically, this paper characterizes three key effects of noise, which are (1) distribution of limit cycle amplitudes (“diffusion”), (2) shift in the average limit cycle amplitudes (“noise induced drift”), and (3) introduction of new bifurcations that are not present in the deterministic system. Key conclusions from this work are that in highly noisy practical environments, a deterministic/ low noise analysis will not be sufficient to explain even critical qualitative features of the system – such as existence of stable limit cycles or their amplitudes. Furthermore, the nature of noise-induced effects on nonlinear modal interactions can be fundamentally different for degenerate, closely spaced, and widely spaced modes.

42 ENGINEERING↗

Noise-induced barren plateaus in variational quantum algorithms

Abstract Variational Quantum Algorithms (VQAs) may be a path to quantum advantage on Noisy Intermediate-Scale Quantum (NISQ) computers. A natural question is whether noise on NISQ devices places fundamental limitations on VQA performance. We rigorously prove a serious limitation for noisy VQAs, in that the noise causes the training landscape to have a barren plateau (i.e., vanishing gradient). Specifically, for the local Pauli noise considered, we prove that the gradient vanishes exponentially in the number of qubits n if the depth of the ansatz grows linearly with n . These noise-induced barren plateaus (NIBPs) are conceptually different from noise-free barren plateaus, which are linked to random parameter initialization. Our result is formulated for a generic ansatz that includes as special cases the Quantum Alternating Operator Ansatz and the Unitary Coupled Cluster Ansatz, among others. For the former, our numerical heuristics demonstrate the NIBP phenomenon for a realistic hardware noise model.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

The learnability of Pauli noise

Recently, several quantum benchmarking algorithms have been developed to characterize noisy quantum gates on today’s quantum devices. A fundamental issue in benchmarking is that not everything about quantum noise is learnable due to the existence of gauge freedom, leaving open the question what information is learnable and what is not, which is unclear even for a single CNOT gate. Here we give a precise characterization of the learnability of Pauli noise channels attached to Clifford gates using graph theoretical tools. Our results reveal the optimality of cycle benchmarking in the sense that it can extract all learnable information about Pauli noise. We experimentally demonstrate noise characterization of IBM’s CNOT gate up to 2 unlearnable degrees of freedom, for which we obtain bounds using physical constraints. In addition, we show that an attempt to extract unlearnable information by ignoring state preparation noise yields unphysical estimates, which is used to lower bound the state preparation noise.

97 MATHEMATICS AND COMPUTING↗

Noise reduction in X-ray photon correlation spectroscopy with convolutional neural networks encoder–decoder models

Abstract Like other experimental techniques, X-ray photon correlation spectroscopy is subject to various kinds of noise. Random and correlated fluctuations and heterogeneities can be present in a two-time correlation function and obscure the information about the intrinsic dynamics of a sample. Simultaneously addressing the disparate origins of noise in the experimental data is challenging. We propose a computational approach for improving the signal-to-noise ratio in two-time correlation functions that is based on convolutional neural network encoder–decoder (CNN-ED) models. Such models extract features from an image via convolutional layers, project them to a low dimensional space and then reconstruct a clean image from this reduced representation via transposed convolutional layers. Not only are ED models a general tool for random noise removal, but their application to low signal-to-noise data can enhance the data’s quantitative usage since they are able to learn the functional form of the signal. We demonstrate that the CNN-ED models trained on real-world experimental data help to effectively extract equilibrium dynamics’ parameters from two-time correlation functions, containing statistical noise and dynamic heterogeneities. Strategies for optimizing the models’ performance and their applicability limits are discussed.

36 MATERIALS SCIENCE↗

Experimental and modeling study of 1/ f noise in multilayer MoS2 and MoSe2 field-effect transistors

In field-effect transistors (FETs) with two-dimensional (2D) transition metal dichalcogenide channels, the dependence of field-effect mobility on atomic layer thickness has been studied and interpreted in terms of interface scattering and interlayer coupling resistance (Rint). However, a model for 1/f noise, such as in MoS2 and in MoSe2 FETs, for various contact metals and layer number thicknesses has not been reported. In this work, we have experimentally studied current–voltage and 1/f noise on MoS2 and MoSe2 FETs with source and drain contacts of high and low work function metals to understand both the mobility and the noise behavior. We have developed a noise model incorporating layer number dependent Hooge parameters and Rint. The noise and mobility models utilize screening lengths for charge, mobility, and Hooge parameter to describe the variation of these quantities with a layer number. Using our single model topology with appropriate fitting parameters for each material and each contact metal, the model captures the experimentally observed layer thickness dependence of the Hooge parameter. Our noise analysis is fully comprehensive and, hence, could be applied to any 2D layered systems.

Kwon, Jiseok↗

A model for excess Johnson noise in superconducting transition-edge sensors

Transition-edge sensors (TESs) are two-dimensional superconducting films utilized as highly sensitive detectors of energy or power. These detectors are voltage biased in the superconducting-normal transition where the film resistance is both finite and a strong function of temperature. Unfortunately, the amount of electrical noise observed in TESs exceeds the predictions of existing noise theories. We describe a possible mechanism for the unexplained excess noise, which we term “mixed-down noise.” The source is Johnson noise, which is mixed down to low frequencies by Josephson oscillations in devices with a nonlinear current–voltage relationship. We derive an expression for the power spectral density of this noise and show that its predictions agree with measured data.

Wessels, Abigail (ORCID:0000000173918339)↗

Stability of Kuramoto networks subject to large and small fluctuations from heterogeneous and spatially correlated noise

Oscillatory networks subjected to noise are broadly used to model physical and technological systems. Due to their nonlinear coupling, such networks typically have multiple stable and unstable states that a network might visit due to noise. In this article, we focus on the assessment of fluctuations resulting from heterogeneous and spatially correlated noise inputs on Kuramoto model networks. We evaluate the typical, small fluctuations near synchronized states and connect the network variance to the overlap between stable modes of synchronization and the input noise covariance. Going beyond small to large fluctuations, we introduce the indicator mode approximation that projects the dynamics onto a single amplitude dimension. Such an approximation allows for estimating rates of fluctuations to saddle instabilities, resulting in phase slips between connected oscillators. Statistics for both regimes are quantified in terms of effective noise amplitudes that are compared and contrasted for several noise models. In conclusion, bridging the gap between small and large fluctuations, we show that a larger network variance does not necessarily lead to higher rates of large fluctuations.

42 ENGINEERING↗

Modulation of seismic noise near the San Jacinto fault in southern California: origin and observations of the cyclical time dependence and associated crustal properties

SUMMARY We examine the cyclic amplitude variation of seismic noise recorded by continuous three-component broad-band seismic data with durations spanning 91–713 d (2008–2011) from three different networks: Anza seismic network, IDA network and the transportable seismic array. These stations surround the San Jacinto Fault Zone (SJFZ) in southern California. We find the seismic noise amplitudes exhibit a cyclical variation between 0.3 and 7.2 Hz. The high-frequency (≥0.9 Hz) noise variations can be linked to human activity and are not a concern. Our primary interest is signals in the low frequencies (0.3–0.9 Hz), where the seismic noise is modulated by semi-diurnal tidal mode M2. These long-period (low-frequency) variations of seismic noise can be attributed to a temporal change of the ocean waves breaking at the shoreline, driven by ocean tidal loading. We focus on the M2 variation of seismic noise at f = 0.6 Hz, travelling distances of ∼92 km through the crust from offshore California to the inland Anza, California, region. Relative to the shoreline station, data from the inland stations show a phase lag of ∼ –12°, which we attribute to the cyclic change in M2 that can alter crustal seismic attenuation. We also find that for mode M2 at 0.6 Hz, the amplitude variations of the seismic quality factor (Q) depend on azimuth and varies from 0.22 per cent (southeast to northwest) to 1.28 per cent (northeast to southwest) with Q = 25 for Rayleigh waves. We propose the direction dependence of the Q variation at 0.6 Hz reflects the preferred orientation of subfaults parallel to the main faulting defined by the primarily N45°W strike of the SJFZ.

Geochemistry & Geophysics↗

Evaluation of a generalized least squares algorithm for infrasound beamforming with coherent background noise

Infrasonic signals of interest can occur during periods with persistent, coherent, background noise, which may be natural or anthropogenic. For high signal-to-noise (SNR) ratio transient signals, an ‘overprinting’ of the coherent background may occur, and the signal may still be detected. However, this approach fails for low SNR signals of interest, which may be obscured by coherent noise. An infrasound beamforming method based on generalized least squares (GLS) is investigated for detecting transient signals of interest in the presence of coherent and incoherent background noise. This approach relies on an estimate of the noise covariance, captured in a covariance matrix, to effectively null contributions to the array response from noisy directions of arrival. Synthetic array data is used to investigate the performance of the GLS beamformer compared to the Bartlett beamformer when coherent and incoherent backgrounds are present. Additionally, the effects of array element number and relative strength of the interfering signal on the GLS estimates is investigated. GLS empirical area under the curve estimates suggest that the beamformer can recover coherent power for a signal of interest lower in amplitude than the coherent background, but this effectiveness degrades more quickly with SNR for a four element array compared to a six or eight element infrasound array. Finally, infrasound from the Forensic Surface Experiment, a bolide signal observed at IMS array I37NO, and a volcanic signal recorded at the Alaska Volcano Observatory array ADKI are used to evaluate GLS performance on recorded data. A ten minute window was used to capture the background noise, and the coherent background signal was nulled in all three examples.

58 GEOSCIENCES↗

Noise from undetected sources in Dark Energy Survey images

ABSTRACT For ground-based optical imaging with current CCD technology, the Poisson fluctuations in source and sky background photon arrivals dominate the noise budget and are readily estimated. Another component of noise, however, is the signal from the undetected population of stars and galaxies. Using injection of artifical galaxies into images, we demonstrate that the measured variance of galaxy moments (used for weak gravitational lensing measurements) in Dark Energy Survey (DES) images is significantly in excess of the Poisson predictions, by up to 30 per cent, and that the background sky levels are overestimated by current software. By cross-correlating distinct images of ‘empty’ sky regions, we establish that there is a significant image noise contribution from undetected static sources (US), which, on average, are mildly resolved at DES resolution. Treating these US as a stationary noise source, we compute a correction to the moment covariance matrix expected from Poisson noise. The corrected covariance matrix matches the moment variances measured on the injected DES images to within 5 per cent. Thus, we have an empirical method to statistically account for US in weak lensing measurements, rather than requiring extremely deep sky simulations. We also find that local sky determinations can remove most of the bias in flux measurements, at a small penalty in additional, but quantifiable, noise.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

An iterative CMB lensing estimator minimizing instrumental noise bias

Noise maps from cosmic microwave background (CMB) experiments are generally statistically anisotropic, due to scanning strategies, atmospheric conditions, or instrumental effects. Any mismodeling of this complex noise can bias the reconstruction of the lensing potential and the measurement of the lensing power spectrum from the observed CMB maps. We introduce a new CMB lensing estimator based on the maximum (MAP) reconstruction that is minimally sensitive to these instrumental noise biases. By modifying the likelihood to rely exclusively on correlations between CMB map splits with independent noise realizations, we minimize autocorrelations that contribute to biases. In the regime of many independent splits, this maximum closely approximates the optimal MAP reconstruction of the lensing potential. In simulations, we demonstrate that this method is able to determine lensing observables that are immune to any noise mismodeling with a negligible cost in signal-to-noise ratio. Our estimator enables unbiased and nearly optimal lensing reconstruction for next-generation CMB surveys.

Legrand, Louis [University of Cambridge (United Ki↗