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This paper addresses the problem of anomaly detection for high-dimensional sensing data. The one-class support vector machine (OCSVM) is one of the most popular unsupervised methods for anomaly detection. When data are high dimensional and large scale, however, the efficiency of OCSVM-based methods in anomaly detection suffers. Although dimensionality-reduction tools, such as deep belief networks, can be applied to compress the high-dimensional data to alleviate the problem, the accuracy and timely detection are still hard to improve due to the inherent features of OCSVM. In this paper, we propose a new form of OCSVM model based on the structure of the compressed data and the characteristics of OCSVM. Based on the new model, we design both optimal and approximate methods for model training and testing. We evaluate the performance of our methods with extensive experiments on four real-world datasets. The experimental results demonstrate that our new methods, both optimal and approximate ones, not only significantly outperform the state-of-the-art in accuracy and efficiency, but also achieve the good performance without the need of manual parameter tuning. In addition, our approximate training and testing mechanism can reduce the computing time by three orders of magnitude with a negligible loss in accuracy.

In this work we study the distance distribution computation problem. It has been widely used in many real-world applications, e.g., human genome clustering, cosmological model analysis, and parameter tuning. The straightforward solution for the exact distance distribution computation problem is unacceptably slow due to (i) massive data size, and (ii) expensive distance computation. In this paper, we propose a novel method to compute approximate distance distributions with error bound guarantees. Furthermore, our method is generic to different distance measures. We conduct extensive experimental studies on three widely used distance measures with real-world datasets. The experimental results demonstrate that our proposed method outperforms sampling-based solution (without error guarantees) by up to three orders of magnitude.

Motivation In silico saturation mutagenesis (ISM) is a popular approach in computational genomics for calculating feature attributions on biological sequences that proceeds by systematically perturbing each position in a sequence and recording the difference in model output. However, this method can be slow because systematically perturbing each position requires performing a number of forward passes proportional to the length of the sequence being examined. Results In this work, we propose a modification of ISM that leverages the principles of compressed sensing to require only a constant number of forward passes, regardless of sequence length, when applied to models that contain operations with a limited receptive field, such as convolutions. Our method, named Yuzu, can reduce the time that ISM spends in convolution operations by several orders of magnitude and, consequently, Yuzu can speed up ISM on several commonly used architectures in genomics by over an order of magnitude. Notably, we found that Yuzu provides speedups that increase with the complexity of the convolution operation and the length of the sequence being analyzed, suggesting that Yuzu provides large benefits in realistic settings. Availability and implementation We have made this tool available at https://github.com/kundajelab/yuzu.

In the centre of mass frame, we have studied theoretically the Z -boson resonant production in the presence of an intense laser field via the weak process e + e − → μ + μ − . Dressing the incident particles by a Circularly Polarized laser field (CP-laser field), at the first step, shows that for a given laser field’s parameters, the Z - boson cross section decreases by several orders of magnitude. We have compared the Total Cross Section (TCS) obtained by using the scattering matrix method with that given by the Breit-Wigner approach in the presence of a CP-laser field and the results are found to be very consistent. This result indicates that Breit-Wigner formula is valid not only for the laser-free process but also in the presence of a CP-laser field. The dependence of the laser-assisted differential cross section on the Centre of Mass Energy (CME) for different scattering angles proves that it reaches its maximum for small and high scattering angles. At the next step and by dressing both incident and scattered particles, we have shown that the CP-laser field largely affects the TCS, especially when its strength reaches 1 0 9 V . c m − 1 . This result is interpreted by the fact that heavy interacting particles require high laser field intensities to affect the collision’s cross section.

Numerical simulations of combustion processes in rocket engines requires a long run time of supercomputer systems even for a very short physical time. Therefore, creating digital twins of rocket engines needs enormous processor time, and is not very effective. This computational time surpasses the actual physical time of the process in many orders of magnitude. To speed up numerical simulations the paper presents a solution of the chemical kinetics problem using artificial neural network approach. Using the architecture of a multilayer neural network with bypass connections, namely residual network, it is possible to obtain a fast and reliable solution to the problem. The neural network is trained to predict the state of the system only one time step ahead. Using it in a recursive mode, it is possible to forecast for thousands of steps without loss of accuracy.

Popular computational catalyst design strategies rely on the identification of reactivity descriptors, which can be used along with Bronsted−Evans−Polanyi (BEP) and scaling relations as input to a microkinetic model (MKM) to make predictions for activity or selectivity trends. The main benefit of this approach is related to the inherent dimensionality reduction of the large material space to just a few catalyst descriptors. Conversely, it is well documented that a small set of descriptors is insufficient to capture the intricacies and complexities of a real catalytic system. The inclusion of coverage effects through lateral adsorbate-adsorbate interactions can narrow the gap between simplified descriptor predictions and real systems, but mean-field MKMs cannot properly account for local coverage effects. This shortcoming of the mean-field approximation can be rectified by switching to a lattice-based kinetic Monte Carlo (kMC) method using cluster expansion representation of adsorbate−adsorbate lateral interactions. Using the prototypical CO oxidation reaction as an example, we critically evaluate the benefits of kMC over MKM in terms of trend predictions and computational cost when using only a small set of input parameters. After confirming that in the absence of lateral interactions the kMC and MKM approaches yield identical trends and mechanistic information, we observed substantial differences between the two kinetic models when lateral interactions were introduced. The mean-field implementation applies coverage corrections directly to the descriptors, causing an artificial overprediction of the activity of strongly binding metals. In contrast, the cluster expansion in kMC implementation can differentiate among the highly active metals but it is very sensitive to the set of included interaction parameters. Considering that computational screening relies on a minimal set of descriptors, for which MKM makes reasonable trend predictions at a ca. three orders of magnitude lower computational cost than kMC, the MKM approach does provide a better entry point for computational catalyst design.

Streaming data applications are becoming more common due to the ability of different information sources to continuously capture or produce data, such as sensors and social media. Although there are recent advances, most visualization approaches, particularly Dimensionality Reduction (DR) techniques, cannot be directly applied in such scenarios due to the transient nature of streaming data. A few DR methods currently address this limitation using online or incremental strategies, continuously updating the visualization as data is received. Despite their relative success, most impose the need to store and access the data multiple times to produce a complete projection, not being appropriate for streaming where data continuously grow. Others do not impose such requirements but cannot update the position of the data already projected, potentially resulting in visual artifacts. This paper presents Xtreaming, a novel incremental DR technique that continuously updates the visual representation to reflect new emerging structures or patterns without visiting the high-dimensional data more than once. Our tests show that in streaming scenarios where data is not fully stored in-memory, Xtreaming is competitive in terms of quality compared to other streaming and incremental techniques while being orders of magnitude faster.

The nature of dark matter remains unknown to date, although several candidate particles are being considered in a dynamically changing research landscape1. Scalar field dark matter is a prominent option that is being explored with precision instruments, such as atomic clocks and optical cavities2–8. Here we describe a direct search for scalar field dark matter using a gravitational-wave detector, which operates beyond the quantum shot-noise limit. We set new upper limits on the coupling constants of scalar field dark matter as a function of its mass, by excluding the presence of signals that would be produced through the direct coupling of this dark matter to the beam splitter of the GEO600 interferometer. These constraints improve on bounds from previous direct searches by more than six orders of magnitude and are, in some cases, more stringent than limits obtained in tests of the equivalence principle by up to four orders of magnitude. Our work demonstrates that scalar field dark matter can be investigated or constrained with direct searches using gravitational-wave detectors and highlights the potential of quantum-enhanced interferometry for dark matter detection., Using a gravitational-wave detector to listen for dark matter signatures, a direct search for scalar field dark matter was conducted and new upper limits are set on the coupling constants.

The National Natural Science Foundation of China is acknowledged, project approval number: 21673071. The One Hundred Talents Foundation of Hunan Province are gratefully acknowledged for the support of S.J. and S.R.K. The effect of a static electric ( field and an unchirped and chirped laser pulse field on the cycl[3.3.3]azine molecule was investigated using next generation quantum theory of atoms in molecules (NG QTAIM). Despite the magnitude of the E field of the laser pulses being an order of magnitude lower than for the static E field, the variation of the energy gap between the lowest lying singlet (S1) and triplet (T1) excited states was orders of magnitude greater for the laser pulse than for the static E field. Insights into the response of the electronic structure were captured by NG QTAIM, where differences in the inverted singlet triplet gap due to the laser pulses were significant larger compared to those induced by the static E field. The response of the S1 and T1 excited states, as determined by NG QTAIM, switched discontinuously between weak and strong chemical character for the static E field. In contrast, the response to the laser pulses, determined by NG QTAIM, is to induce a continuous range of chemical character, indicating the unique ability of the laser pulses to induce polarization effects in the form of ‘mixed’ bond types. Our analysis demonstrates that NG QTAIM is a useful tool for understanding the response to laser irradiation of the lowest lying singlet S1 and triplet T1 excited states of emitters exhibiting thermally activated delayed fluorescence (TADF). The chirped laser pulse led to more frequent instances of the desired outcome of an inverted singlet triplet gap than the unchirped pulse, indicating its usefulness as a tool to design more efficient OLED devices. Postprint Postprint

We report a comprehensive study of the efficacy of least-squares fitting of multidimensional spectra to generalized Kubo line-shape models and introduce a novel least-squares fitting metric, termed the scale invariant gradient norm (SIGN), that enables a highly reliable and versatile algorithm. The precision of dephasing parameters is between 8× and 50× better for nonlinear model fitting compared to that for the centerline-slope (CLS) method, which effectively increases data acquisition efficiency by 1–2 orders of magnitude. Whereas the CLS method requires sequential fitting of both the nonlinear and linear spectra, our model fitting algorithm only requires nonlinear spectra but accurately predicts the linear spectrum. We show an experimental example in which the CLS time constants differ by 60% for independent measurements of the same system, while the Kubo time constants differ by only 10% for model fitting. This suggests that model fitting is a far more robust method of measuring spectral diffusion than the CLS method, which is more susceptible to structured residual signals that are not removable by pure solvent subtraction. Statistical analysis of the CLS method reveals a fundamental oversight in accounting for the propagation of uncertainty by Kubo time constants in the process of fitting to the linear absorption spectrum. A standalone desktop app and source code for the least-squares fitting algorithm are freely available, with example line-shape models and data. We have written the MATLAB source code in a generic framework where users may supply custom line-shape models. Using this application, a standard desktop fits a 12-parameter generalized Kubo model to a 106 data-point spectrum in a few minutes.

Accurate theoretical simulation of electrochemical activation barriers is key to understanding electrocatalysis and guides the design of more efficient catalysts. Providing a detailed picture of proton transfer processes encounters several challenges: the constant potential requirement during charge transfer, the different time scales involved in the processes, and the thermal fluctuation of the solvent. Hence, it is prohibitively expensive computationally to apply density functional theory (DFT) calculations in modeling the potential-dependent activation barrier at the electrode-solvent interface, and the results are dubious. To address these challenges, we have developed an analytical approach based on charge conservation and decoupled potential energy surfaces to compute charge transfer barriers. The method makes it possible to simulate an electrochemical process at different potentials and explicitly include thermal fluctuations of the solvent at the electrode-solvent interface. We use the Pt-catalyzed alkaline hydrogen evolution reaction (HER) as our benchmark reaction, and we model the microkinetics of HER with consideration of the spatial fluctuations between the metal surface and the first solvent layer at room temperature. The distribution of water-metal distances has a large effect on the barriers of the charge transfer processes, and an accurate account of the statistical fluctuation in the reaction network leads to a several orders of magnitude increase in HER current as compared to transfer from a static solvent. The trends of the different reaction mechanisms in HER were successfully simulated with our model, and the theoretical I-V curves obtained are in good qualitative agreement with experimental results.

Two-dimensional transition metal dichalcogenide-based phototransistors have been intensively studied in recent years due to their high detection rate and flexibility. However, the photogating effect, usually appearing in the devices, leads to a poor transient photoresponse, which slows down the imaging rate of the camera based on the devices. Here, we demonstrate a dual-channel two-dimensional field-effect phototransistor composed of a vertical molybdenum disulfide (MoS2) p-n homojunction as the sensitizing channel layer. Owing to the effective separation by the vertical built-in electric field and rapid migration of photoexcited electrons and holes in the separated channels, the fabricated dual-channel FET device simultaneously exhibits prominent responsivity and greatly improved time response in comparison to the pristine MoS2 FET detectors. Excellent device performance has been achieved, with a responsivity of 3.4 × 104 A/W at a source-drain voltage (VDS) of 1 V, corresponding to a detectivity (D*) of 1.9 × 1013 Jones@532 nm and a gain of more than 105 electrons per photon, an external quantum efficiency of 9.6%, and a response time of tens of milliseconds. Especially, the response time of the dual-channel FET device is 3 orders of magnitude faster than that of the pristine device. Our results provide a new way to overcome the inherent photogating drawback of two-dimensional FET optoelectronic devices and to develop a related high frame rate imaging system.

Dissociation of a ligand isoniazid from a protein catalase was investigated using all-atom molecular dynamics (MD) simulations. Random acceleration MD (τ-RAMD) was used, in which a random artificial force applied to the ligand facilitates its dissociation. We have suggested a novel approach to extrapolate such obtained dissociation times to the zero-force limit assuming never before attempted universal exponential dependence of the bond strength on the applied force, allowing direct comparison with experimentally measured values. We have found that our calculated dissociation time was equal to 36.1 s with statistically significant values distributed in the interval of 0.2-72.0 s, which quantitatively matches the experimental value of 50 ± 8 s despite the extrapolation over 9 orders of magnitude in time.

Charge control of color centers in semiconductors promises opportunities for novel forms of sensing and quantum information processing. Here, we articulate confocal fluorescence microscopy and magnetic resonance protocols to induce and probe charge transport between discrete sets of engineered nitrogen-vacancy (NV) centers in diamond, down to the level of individual defects. In our experiments, a "source" NV undergoes optically-driven cycles of ionization and recombination to produce a stream of photo-generated carriers, one of which we subsequently capture via a "target" NV several micrometers away. We use a spin-to-charge conversion scheme to encode the spin state of the source color center into the charge state of the target, in the process allowing us to set an upper bound to carrier injection from other background defects. We attribute our observations to the action of unscreened Coulomb potentials producing giant carrier capture cross-sections, orders of magnitude greater than those typically attained in ensemble measurements. Besides their fundamental interest, these results open intriguing prospects in the use of free carriers as a quantum bus to mediate effective interactions between paramagnetic defects in a solid-state chip.

Entangled two-photon absorption (ETPA) is known to create photoinduced transitions with extremely low light intensity, reducing the risk of phototoxicity compared to classical two-photon absorption. Previous works have predicted the ETPA cross-section, σe, to vary inversely with the product of entanglement time (Te) and entanglement area (Ae), i.e., σe ∼ 1/AeTe. The decreasing σe with increasing Te has limited ETPA to fs-scale Te, while ETPA applications for ps-scale spectroscopy have been unexplored. However, we show that spectral-spatial coupling, which reduces Ae as the SPDC bandwidth (σf) decreases, plays a significant role in determining σe when Te > ∼100 fs. We experimentally measured σe for zinc tetraphenylporphyrin at several σf values. For type-I ETPA, σe increases as σf decreases down to 0.1 ps-1. For type-II SPDC, σe is constant for a wide range of σf. With a theoretical analysis of the data, the maximum type-I σe would occur at σf = 0.1 ps-1 (Te = 10 ps). At this maximum, σe is 1 order of magnitude larger than fs-scale σe and 3 orders of magnitude larger than previous predictions of ps-scale σe. By utilizing this spectral-spatial coupling, narrowband type-I ETPA provides a new opportunity to increase the efficiency of measuring nonlinear optical signals and to control photochemical reactions requiring ps temporal precision.

Processing and analyzing time series datasets have become a central issue in many domains requiring data management systems to support time series as a native data type. A core access primitive of time series is matching, which requires efficient algorithms on-top of appropriate representations like the symbolic aggregate approximation (SAX) representing the current state of the art. This technique reduces a time series to a low-dimensional space by segmenting it and discretizing each segment into a small symbolic alphabet. Unfortunately, SAX ignores the deterministic behavior of time series such as cyclical repeating patterns or a trend component affecting all segments, which may lead to a sub-optimal representation accuracy. We therefore introduce a novel season- and a trend-aware symbolic approximation and demonstrate an improved representation accuracy without increasing the memory footprint. Most importantly, our techniques also enable a more efficient time series matching by providing a match up to three orders of magnitude faster than SAX.

Chemical ionization mass spectrometry (CIMS) using iodide as a reagent ion has been widely used to classify organic compounds in the atmosphere by their elemental formula. Unfortunately, calibration of these instruments is challenging due to a lack of commercially available standards for many compounds, which has led to the development of methods for estimating CIMS sensitivity. By coupling a thermal desorption aerosol gas chromatograph (TAG) simultaneously to a flame ionization detector (FID) and an iodide CIMS, we use the individual particle-phase analytes, quantified by the FID, to examine the sensitivity of the CIMS and its variability between isomers of the same elemental formula. Iodide CIMS sensitivities of isomers within a formula are found to generally vary by 1 order of magnitude with a maximum deviation of 2 orders of magnitude. Furthermore, we compare directly measured sensitivity to a method of estimating sensitivity based on declustering voltage (i.e., "voltage scanning"). This approach is found to carry high uncertainties for individual analytes (0.5 to 1 order of magnitude) but represents a central tendency that can be used to estimate the sum of analytes with reasonable error (similar to 30% differences between predicted and measured moles). Finally, gas chromatography (GC) retention time, which is associated with vapor pressure and chemical functionality of an analyte, is found to qualitatively correlate with iodide CIMS sensitivity, but the relationship is not close enough to be quantitatively useful and could be explored further in the future as a potential calibration approach. Alfred P. Sloan FoundationAlfred P. Sloan Foundation [P-2018-11129] Published version This research has been supported by the Alfred P. Sloan Foundation (grant no. P-2018-11129).

Recent technical progress in the industry has led to an urgent requirement on new materials with enhanced multi-properties. To meet this multi-property requirement, the materials consisting of three and more elements have attracted increasing attention. However, facing to the nearly unknown huge multi-component materials system, the traditional trial and error method cannot provide sufficient data efficiently. Therefore, an efficient material innovation strategy is significant. The first-principles calculation based on the density functional theory is a powerful tool for both the accurate prediction of material properties and the identification of its underlying thermodynamics and dynamics. At the same time, the advances of computational methods and computer calculation abilities that are orders of magnitude faster than before make the high throughput first-principles calculations popular. At present, the simulation-assisted material design has become a main branch in the material research field and a great many successes have been made. In this article, the advances of the high throughput first-principles calculations are reviewed to show the achievements of the first-principles calculations and guide the future directions of its applications in ceramics.

Shoaling internal solitary waves near the Dongsha Atoll in the South China Sea dissipate their energy and enhance diapycnal mixing, which have an important impact on the oceanic environment and primary productivity. The enhanced diapycnal mixing is patchy and instantaneous. Evaluating its spatiotemporal distribution requires comprehensive observation data. Fortunately, seismic oceanography meets the requirements, thanks to its high spatial resolution and large spatial coverage. In this paper, we studied three internal solitary waves in reversing polarity near the Dongsha Atoll and calculated their spatial distribution of diapycnal diffusivity. Our results show that the average diffusivities along three survey lines are 2 orders of magnitude larger than the open-ocean value. The average diffusivity in internal solitary waves with reversing polarity is 3 times that of the non-polarity reversal region. The diapycnal diffusivity is higher at the front of one internal solitary wave and gradually decreases from shallow to deep water in the vertical direction. Our results also indicate that (1) the enhanced diapycnal diffusivity is related to reflection seismic events, (2) convective instability and shear instability may both contribute to the enhanced diapycnal mixing in the polarity-reversing process, and (3) the difference between our results and Richardson-number-dependent turbulence parameterizations is about 2–3 orders of magnitude, but its vertical distribution is almost the same.

The main scientific goal of LHAASO-WCDA is to survey gamma-ray sources with energy from 100 GeV to 30 TeV. To observe high-energy shower events, especially to measure the energy spectrum of cosmic rays from 100 TeV to 10 PeV, a dynamic range extension system (WCDA++) is designed to use a 1.5-inch PMT with a dynamic range of four orders of magnitude for each cell in WCDA-1. The dynamic range is extended by using these PMTs to measure the effective charge density in the core region of air shower events, which is an important parameter for identifying the composition of primary particles. The system has been running for more than one year. In this paper, the details of the design and performance of WCDA++ are presented.

Nowadays, realizing miniaturized nonlinear optical (NLO) device is crucial to meet the growing needs in on-chip nanophotonics as well as compact integrated devices. The strong optical nonlinearities, ultrafast photoexcitation dynamics, available exciton effects as well as without lattice matching make two-dimensional (2D) layered materials potential candidates for integrated and nano-scale NLO devices. Herein, a novel and inversion symmetry broken 2D layered SnP2S6 with strong second-harmonic and third-harmonic response has been reported for the first time. The second-order susceptibility (χ(2)) of SnP2S6 flakes can reach up to 4.06 × 10−9 m·V−1 under 810 nm excitation wavelength, which is around 1–2 orders of magnitude higher than that of most reported 2D materials. In addition, the NLO response of 2D SnP2S6 can break through the limitation of odd/even layers and exhibit broadband spectral response. Moreover, since the second-harmonic signal is closely related to structure variation, the second-harmonic response in 2D SnP2S6 is extremely sensitive to polarization angle and temperature, which is beneficial to some specific applications. The excellent NLO response in 2D SnP2S6 provides a new arena for realizing miniaturized NLO devices in the future.

Detailed characterization of the spatially and temporally varying inherent optical properties (IOPs) of sea ice is necessary to better predict energy and mass balances, as well as ice-associated primary production. Here we present the development of an active optical probe to measure IOPs of a small volume of sea ice (dm3) in situ and non-destructively. The probe is derived from the diffuse reflectance method used to measure the IOPs of human tissues. The instrument emits light into the ice by the use of an optical fibre. Backscattered light is measured at multiple distances away from the source using several receiving fibres. Comparison to a Monte Carlo simulated lookup table allows, in theory, retrieval of the absorption coefficient, the reduced scattering coefficient and a phase function similarity parameter γ, introduced by Bevilacqua and Depeursinge (1999). γ depends on the two first moments of the Legendre polynomials, allowing the analysis of the backscattered light not satisfying the diffusion regime. The depth reached into the medium by detected photons was estimated using Monte Carlo simulations: the maximum depth reached by 95 % of the detected photons was between 40±2 and 270±20 mm depending on the source–detector distance and on the ice scattering properties. The magnitude of the instrument validation error on the reduced scattering coefficient ranged from 0.07 % for the most scattering medium to 35 % for the less scattering medium over the 2 orders of magnitude we validated. Fixing the absorption coefficient and γ, which proved difficult to measure, vertical profiles of the reduced scattering coefficient were obtained with decimetre resolution on first-year Arctic interior sea ice on Baffin Island in early spring 2019. We measured values of up to 7.1 m−1 for the uppermost layer of interior ice and down to 0.15±0.05 m−1 for the bottommost layer. These values are in the range of polar interior sea ice measurements published by other authors. The inversion of the reduced scattering coefficient at this scale was strongly dependent on the value of γ, highlighting the need to define the higher moments of the phase function. This newly developed probe provides a fast and reliable means for measurement of scattering in sea ice.

This work aims to establish a theoretical framework for the modeling of bubble nucleation in histotripsy. A phenomenological version of the classical nucleation theory was parametrized with histotripsy experimental data, fitting a temperature-dependent activity factor that harmonizes theoretical predictions and experimental data for bubble nucleation at both high and low temperatures. Simulations of histotripsy pressure and temperature fields are then used in order to understand spatial and temporal properties of bubble nucleation at varying sonication conditions. This modeling framework offers a thermodynamic understanding on the role of the ultrasound frequency, waveforms, peak focal pressures, and duty cycle on patterns of ultrasound-induced bubble nucleation. It was found that at temperatures lower than 50 °C, nucleation rates are more appreciable at very large negative pressures such as -30 MPa. For focal peak-negative pressures of -15 MPa, characteristic of boiling histotripsy, nucleation rates grow by 20 orders of magnitude in the temperature interval 60 °C-100 °C.

We demonstrate the applicability of covariance analysis to three-dimensional velocity-map imaging experiments using a fast time stamping detector. Studying the photofragmentation of strong-field doubly ionized D2O molecules, we show that combining high count rate measurements with covariance analysis yields the same level of information typically limited to the “gold standard” of true, low count rate coincidence experiments, when averaging over a large ensemble of photofragmentation events. This increases the effective data acquisition rate by approximately 2 orders of magnitude, enabling a new class of experimental studies. This is illustrated through an investigation into the dependence of three-body D2O2+ dissociation on the intensity of the ionizing laser, revealing mechanistic insights into the nuclear dynamics driven during the laser pulse. The experimental methodology laid out, with its drastic reduction in acquisition time, is expected to be of great benefit to future photofragment imaging studies.

A scalable stochastic algorithm is presented that can evaluate explicitly correlated (F12) second-order many-body perturbation (MP2) energies of weak, noncovalent, intermolecular interactions. It first transforms the formulas of the MP2 and F12 energy differences into a short sum of high-dimensional integrals of Green's functions in real space and imaginary time. These integrals are then evaluated by the Monte Carlo method augmented by parallel execution, redundant-walker convergence acceleration, direct-sampling autocorrelation elimination, and control-variate error reduction. By sharing electron-pair walkers across the supermolecule and its subsystems spanned by the joint basis set, the statistical uncertainty is reduced by one to 2 orders of magnitude in the MP2 binding energy corrected for the basis-set incompleteness and superposition errors. The method predicts the MP2-F12/aug-cc-pVDZ binding energy of 19.1 ± 4.0 kcal mol-1 for the C60 dimer at the center distance of 9.748 A.

Computationally fast and accurate mathematical models are essential for effective design, optimization, and control of wave energy converters. However, the energy-maximising control strategy, essential for reaching economic viability, inevitably leads to the violation of linearising assumptions, so the common linear models become unreliable and potentially unrealistic. Partially nonlinear models based on the computation of Froude–Krylov forces with respect to the instantaneous wetted surface are promising and popular alternatives, but they are still too slow when floaters of arbitrary complexity are considered; in fact, mesh-based spatial discretisation, required by such geometries, becomes the computational bottle-neck, leading to simulations 2 orders of magnitude slower than real-time, unaffordable for extensive iterative optimizations. This paper proposes an alternative analytical approach for the subset of prismatic floating platforms, common in the wave energy field, ensuring computations 2 orders of magnitude faster than real-time, hence 4 orders of magnitude faster than state-of-the-art mesh-based approaches. The nonlinear Froude–Krylov model is used to investigate the nonlinear hydrodynamics of the floater of a pitching wave energy converter, extracting energy either from pitch or from an inertially coupled internal degree of freedom, especially highlighting the impact of state constraints, controlled/uncontrolled conditions, and impact on control parameters’ optimization, sensitivity and effectiveness.

Because of the complex composition of the apparent activation energy, the rate-determining step in a photocatalytic reaction like hydrogen evolution is still being explored even after sluggish oxygen evolution is replaced with efficient hole extraction. This issue severely limits the implementation of certain strategies like the synergistic thermal effect. Here, by developing a combined monitor method based on open-circuit potential decay, we demonstrate that semiconductor-cocatalyst interfacial electron transfer occurring on a decisecond to second time scale dominates photocatalytic hydrogen evolution. This time scale is approximately 6-12 orders of magnitude larger than the widely reported values of picoseconds to microseconds and is comparable to that predicted by Durrant et al. To improve photocatalytic hydrogen evolution, we manage to create more intermediate sites by electronically doping the semiconductor surface. This measure promotes semiconductor-cocatalyst interfacial electron transfer by charge recombination and makes the synergistic thermal effect very evident.

Passive radar (PR) systems need to detect the presence of a target response, which is many orders of magnitude weaker than the clutter (direct signal and multipath). Indeed, the clutter cancellation is a key stage within a PR processing scheme. One of the most effective techniques in this field is using the CLEAN approach. In this paper, the batch-based CLEAN technique based on GMP and FFT has been proposed, which can speed up the computational processing and have better cancellation gain. Furthermore, segmenting operation can be applied to the signal obtained over long time. It is helpful to enhance temporal or spatial efficiency and overcome effect of time-varying clutter. Experiment results with simulated and real passive radar data verify the effectiveness of the proposed algorithm.

Although previous studies reported that currents over topographic features, such as seamounts and ridges, cause strong turbulence in close proximity, it has been elusive how far intense turbulence spreads toward the downstream. Here, we conducted a series of intensive in-situ turbulence observations using a state-of-the-art tow-yo microstructure profiler in the Kuroshio flowing over the seamounts of the Tokara Strait, south of Kyusyu Japan, in November 2017, June 2018, and November 2019, and employed a high-resolution numerical model to elucidate the turbulence generation mechanisms. We find that the Kuroshio flowing over seamounts generates streaks of negative potential vorticity and near-inertial waves. With these long-persisting mechanisms in addition to other near-field mixing processes, intense mixing hotspots are formed over a 100-km scale with the elevated energy dissipation by 100- to 1000-fold. The observed turbulence could supply nutrients to sunlit layers, promoting phytoplankton primary production and CO2 uptake. Persistent and intense mixing hotspots are generated where the Kuroshio flows over steep seamounts, with an increase in energy dissipation by two to three orders of magnitude, according to tow-yo microstructure measurements combined with numerical simulations.

We demonstrate a high-precision, high robustness frequency offset locking method,which made the frequency offset between mode-locked laser and continuous-wave laser below less than 3 Hz.The coarse frequency lock control is realized by the feedback control of PZT with electrical delay line as the reference. The fine frequency compensation is realized by feed-forward control of an acousto-optic modulator. The fractional frequency instability was ${7.4}\times {10}^{-10}$ for an averaging time of 1 s, $3.3\times {10}^{-8}$ for an averaging time of 10 000 s when the narrow linewidth laser is free-running. In this experiment, the fractional frequency instability can be achieved at $1.1\times {10}^{-15}$ for an averaging time of 1 s, at $3.6\times {10}^{-18}$ for an averaging time of 10 000 s when the system is fine frequency locked. Compared with the unlocked laser, the fractional frequency instability can be improved about 5–6 orders of magnitude. This work lays the foundation for simple structure, high robustness and high precision laser frequency control situation, such as quantum precision measurement and optical lattice clocks.

The superposition principle is widely used to accelerate the computation of hourly fluid temperatures in ground heat exchangers. This work presents a first attempt at adapting this technique to non-stationary situations of ground-source heat pump operations that involve time-variant parameters, such as flow rates. An advanced response model is first employed to evaluate the outlet temperature signals corresponding to different sets of constant operating conditions. The transitions are then considered by combining the functions linearly and by using a scaled correction function. Eight synthetic validation studies were conducted, representing the dynamic operation of a closed-loop and a standing column well with time-variant circulation, pumping, and discharge rates, and groundwater velocities. It is shown that the developed method reproduces reference numerical results with mean absolute and relative errors that are lower than 0.04 ° C and 0.68%, respectively, and achieves a 30-day simulation with a 5-min time step in a few hundredths of a second. This represents a reduction of five to seven orders of magnitude in computing times and demonstrates the potential of the proposed method to accelerate the simulation of ground heat exchangers that operate with time-variant flow rates.

The calculation of electric field in space excited by thunderclouds is an important basis for lightning warning and protection. In numerical calculation of the electromagnetic field, it is often necessary to perform multiple loop nesting calculations on several triple integrals, which consume a lot of computing resources. In order to shorten the calculation time and improve the calculation efficiency, the electric field excited by the charged thunderclouds in space is theoretically derived with the analytical method by the thundercloud cylindrical charge pile model and based on the electrostatic field theory. The complex integrand function is approximated, so that the analytic expression of electric field in space is obtained in this paper. Through simulation and comparison, it is found that the approximate solution and the exact solution are similar in size, the change trend is the same, and the approximate analytical expression can be used for the approximate calculation of the electric field in a short range. Under certain conditions, the approximate solution can be converted into an accurate solution, which can be used for the accurate calculation of the electric field. Approximate calculation not only simplifies theoretical derivation but also improves calculation efficiency. The calculation time has been shortened from tens of hours to less than one second by using different calculation methods, which is a difference of 7 orders of magnitude. With approximate analytical expression, the electric field excited by charge pile with typical structures in thunderclouds in space is calculated and the characteristics of that are analyzed in this paper. For lightning protection of mobile targets, approximate calculation is of great significance in shortening the lightning warning time and enhancing the protection effect.

Cross-linking mass spectrometry methods have not been successfully applied to protein-protein interaction discovery at a proteome-wide level mainly due to the computation complexity (O (n2)) issue. In a previous report, we proposed a decision tree searching strategy (DTSS), which can reduce complexity by orders of magnitude. In this study, we further found that the monolinked peptides carry out the information on the retention time of the corresponding cross-linked pairs; therefore, the retention time of cross-linked peptide pairs can be predicted accurately. By utilizing the retention time as an extra filter, the false positive rate can be reduced by around 86% with a sensitivity loss of 10%. The method combined with DTSS (T-DTSS) not only benefits improving identification confidence but also leads to lower cutoff scores and facilitates substantially increasing inter-cross-link identification. T-DTSS was successfully applied to the identification of inter-cross-links obtained from Escherichia coli cell lysate cross-linked by a newly synthesized enrichable cross-linker, pDSBE. The approach can be applicable to both cleavable and noncleavable methods.

X-ray free-electron lasers can generate intense and coherent radiation at wavelengths down to the sub-angstrom region1-5, and have become indispensable tools for applications in structural biology and chemistry, among other disciplines6. Several X-ray free-electron laser facilities are in operation2-5; however, their requirement for large, high-cost, state-of-the-art radio-frequency accelerators has led to great interest in the development of compact and economical accelerators. Laser wakefield accelerators can sustain accelerating gradients more than three orders of magnitude higher than those of radio-frequency accelerators7-10, and are regarded as an attractive option for driving compact X-ray free-electron lasers11. However, the realization of such devices remains a challenge owing to the relatively poor quality of electron beams that are based on a laser wakefield accelerator. Here we present an experimental demonstration of undulator radiation amplification in the exponential-gain regime by using electron beams based on a laser wakefield accelerator. The amplified undulator radiation, which is typically centred at 27 nanometres and has a maximum photon number of around 1010 per shot, yields a maximum radiation energy of about 150 nanojoules. In the third of three undulators in the device, the maximum gain of the radiation power is approximately 100-fold, confirming a successful operation in the exponential-gain regime. Our results constitute a proof-of-principle demonstration of free-electron lasing using a laser wakefield accelerator, and pave the way towards the development of compact X-ray free-electron lasers based on this technology with broad applications.

The use of continuum emission radio galaxies as cosmological tracers of the large-scale structure will soon move into a new phase. Upcoming surveys from the Australian Square Kilometre Array Pathfinder (ASKAP), MeerKAT, and the Square Kilometre Array project (SKA) will survey the entire available sky down to an ~100uJy flux limit, increasing the number of detected extra-galactic radio sources by several orders of magnitude. External data and machine learning algorithms will also enable some low resolution radial selection (photometric redshift binning) of the sample, increasing the cosmological utility of the sample observed. In this paper, we discuss the flux limit required to detect enough galaxies to decrease the shot noise term in the error to be 10% of the total. We show how future surveys of this type will be limited by available technology. The confusion generated by the intrinsic sizes of galaxies may have the consequence that surveys of this type eventually reach a hard flux limit of ~100nJy, as is predicted by the current modelling of AGN sizes by simulations such as the Tiered Radio Extragalactic Continuum Simulation (T-RECS). Finally, when considering the multi-tracer approach, where galaxies are split by type to measure some bias ratio, we find that there are not enough AGN present to achieve a reasonable level of shot noise for this kind of measurement., 10 pages, 8 figures, submitted to the journal

In this two-part paper, a stable and efficient nodally-integrated reproducing kernel particle method (RKPM) is introduced for solving the governing equations of generalized thermomechanical theories. Part I investigates quadrature in the weak form using coupled and uncoupled classical thermoelasticity as model problems. It is first shown that nodal integration of these equations results in spurious oscillations in the solution many orders of magnitude greater than pure elasticity. A naturally stabilized nodal integration is then proposed for the coupled equations. The variational consistency conditions for nth order exactness and convergence in the two-field problem are then derived, and a uniform correction on the test function approximations is proposed to achieve these conditions. Several benchmark problems are solved to demonstrate the effectiveness of the proposed method. In the sequel, these methods are developed for generalized thermoelasticity and generalized finite-strain thermoplasticity theories of the hyperbolic type that are amenable to efficient explicit time integration.

Two-dimensional (2D) layered materials such as GaSe recently have emerged as novel nonlinear optical materials with exceptional properties. Although exhibiting large nonlinear susceptibilities, the nonlinear responses of 2D materials are generally limited by the short interaction lengths with light, thus further enhancement via resonant photonic nanostructures is highly desired for building high-efficiency nonlinear devices. Here, we demonstrate a giant second-harmonic generation (SHG) enhancement by coupling 2D GaSe flakes to silicon metasurfaces supporting quasi-bound states in the continuum (quasi-BICs) under continuous-wave (CW) operation. Taking advantage of both high-quality factors and large mode areas of quasi-BICs, SHG from a GaSe flake is uniformly enhanced by nearly 4 orders of magnitude, which is promising for high-power coherent light sources. Our work provides an effective approach for enhancing nonlinear optical processes in 2D materials within the framework of silicon photonics, which also brings second-order nonlinearity associated with 2D materials to silicon photonic devices.

—Perhaps for the first time, we obtained the distributed volume electric currents determined by the observed geomagnetic dipole. To do that, using the Maxwell’s equations and well-established geodynamo estimates, we have shown that the mean current density in the Earth’s liquid core is several orders of magnitude higher than in the solid core. Correspondingly, current density in our model vanishes in the solid core whereas in the liquid core, from maximally realistic simplifications, it is proportional to the distance to the dipole axis and directed around this axis. Using standard expansions, integrations, and the generally accepted IGRF model, we obtained total currents, the associated power of ohmic dissipation, volume current densities, and the directions of the current axis oriented as a dipole pole from 1900 to 2020.

We study the role of small-scale perturbations in the onset of avalanches in a rotating drum in the stick-slip regime. By vibrating the system along the axis of rotation with an amplitude orders of magnitude smaller than the particles’ diameter, we found that the order parameter that properly describes the system is the kinetic energy. We also show that, for high enough frequencies, the onset of the avalanche is determined by the amplitude of the oscillation, contrary to previous studies that showed that either acceleration or velocity was the governing parameter. Finally, we present a theoretical model that explains the transition between the continuous and discrete avalanche regimes as a supercritical Hopf bifurcation.

We present a method to constrain the temperature of astrophysical black holes through detecting the inspiral phase of binary black hole coalescences. At sufficient separation, inspiraling black holes can be regarded as isolated objects, hence their temperature can still be defined. Due to their intrinsic radiation, inspiraling black holes lose part of their masses during the inspiral phase. As a result, coalescence speeds up, introducing a correction to the orbital phase. We show that this dephasing may allow us to constrain the temperature of inspiraling black holes through gravitational-wave detection. Using the binary black-hole coalescences of the first two observing runs of the Advanced LIGO and Virgo detectors, we constrain the temperature of parental black holes to be less than about $ 10^9 $ K. Such a constraint corresponds to luminosity of about $ 10^{-16} M_{\odot} \rm s^{-1} $ for a black hole of $ 20 M_{\odot} $, which is about 20 orders of magnitude below the peak luminosity of the corresponding gravitational-wave event, indicating no evidence for strong quantum-gravity effects through the detection of the inspiral phase., Comment: Match the published version

The article proposes several versions of a half division two-dimensional method, which is the basis of a fundamentally new approach for constructing measuring instruments for sinusoidal or periodic electrical quantities. These measuring instruments are used in the diagnostics of electric power facilities. The most general version, called the midpoint method, is considered. The proposed midpoint method allows measuring much smaller (of the order of hundreds of microamperes) alternating currents or voltages comparing to the widespread methods, especially when the amplitude of the measured signal changes in a very wide range (by 1–2 orders of magnitude). It is shown that using the midpoint method it is possible to suppress sinusoidal or periodic interference in the measuring path, in particular, to measure a small alternating current when the sinusoidal or periodic interference is 1–2 orders of magnitude higher than the useful signal. Based on the results of comparative tests, it was found that a current measuring device implementing the midpoint method is an order of magnitude more sensitive than the currently used high-precision measuring instruments.

Electronic configurations of lanthanides and charge states of ions are analyzed. The main models of energy exchange between neighboring of rare-earth (RE) ions are presented, as well as the emergence of cross-relaxation and ap-conversion processes is outlined. The influence of the local crystal field on the splitting of levels of the shielded 4f-shell in RE ions has been established. The splitting of levels the shielded 4f-shell of RE ions in crystal matrices is determined by the combined influence of the Coulomb interaction forces, the spin-orbit interaction, and the weak action of the static crystal field. It is shown that the probability of non-radiative processes can vary by several orders of magnitude within one luminescent center due to the dependence of this process on the size of energy gap of the semiconductor matrix. Based on the construction of mechanisms of radiative and non-radiative relaxation of RE ions, the possibilities of creating effective light-emitting media for optoelectronic technology are considered.

The ability to accurately and consistently discover anomalies in time series is important in many applications. Fields such as finance (fraud detection), information security (intrusion detection), healthcare, and others all benefit from anomaly detection. Intuitively, anomalies in time series are time points or sequences of time points that deviate from normal behavior characterized by periodic oscillations and long-term trends. For example, the typical activity on e-commerce websites exhibits weekly periodicity and grows steadily before holidays. Similarly, domestic usage of electricity exhibits daily and weekly oscillations combined with long-term season-dependent trends. How can we accurately detect anomalies in such domains while simultaneously learning a model for normal behavior? We propose a robust offline unsupervised framework for anomaly detection in seasonal multivariate time series, called AURORA. A key innovation in our framework is a general background behavior model that unifies periodicity and long-term trends. To this end, we leverage a Ramanujan periodic dictionary and a spline-based dictionary to capture both seasonal and trend patterns. We conduct experiments on both synthetic and real-world datasets and demonstrate the effectiveness of our method. AURORA has significant advantages over existing models for anomaly detection, including high accuracy (AUC of up to 0.98), interpretability of recovered normal behavior (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$100\%$$\end{document}100% accuracy in period detection), and the ability to detect both point and contextual anomalies. In addition, AURORA is orders of magnitude faster than baselines.

According to observations, there is not enough visible mass to explain the rotation speed of stars in the galactic self-gravitating field. It has been noted that this involves gravity field orders of magnitude smaller than the one observed in our solar system and responsible for its dynamics. Therefore, it is natural to look for the strength of the gravitational interaction at distances much bigger than the size of our solar system. In 1934, Dirac and Heisenberg computed a (small) correction to the electrostatic potential of a proton due to the Dirac sea of electrons. This screening makes one contribution to the Lambshift measured in 1947. A similar “screening” exists when massive fermions are scattered by a gravity field. Amazingly, this introduces a very big “screening length” of astrophysical order of magnitude because of the smallness of Newton’s constant. The net result is a change of Newton’s gravitational forces at large distances. This does not introduce any new parameter like the mass of unseen particles interacting by gravitation only. Neither it implies a change of the laws of motion of Newton and Galileo.

The degree of spatial similarity between the gaze of participants viewing dynamic stimuli such as videos has been previously measured using metrics which are based on the NSS (Normalized Scanpath Saliency). Methods currently used to calculate this metric rely upon a numerical grid, which can be computationally prohibitive for a variety of otherwise useful applications such as Monte Carlo analyses. In the present work we derive a new analytical calculation method for the same metric that yields equal or more accurate results, but with speeds than can be orders of magnitude faster (depending on parameters). Our analytical method scales well with dimensionality, and could also be of use for other applications. The drawback is that it can become very slow if the number of participants in the study is very large or if the gaze sampling rate is high. We provide performance benchmarks for a Fortran implementation of our method, and make available the source code developed.

In this letter, the high-order harmonic generation (HHG) of wurtzitic and hexagonal boron nitride (h-BN) under ultrafast intense laser field was studied by solving an extended multiband semiconductor Bloch equations (SBEs). The results showed that for both the wurtzitic and hexagonal structures, the cutoff energy of the HHG was extended linearly by increasing the field strength, and the efficiency was suppressed as the wavelength of laser increased. It was worth noting that for hexagonal structure, the efficiency of HHG was 1–2 orders of magnitude higher than that of the wurtzitic structure. At the same time, the hexagonal structure significantly improved the cutoff energy of HHG from BN.

In this work, 0.75-10 THz band is explored for non-terrestrial communications, by leveraging the improved atmospheric conditions at various altitudes. A channel model for aerial communications at THz band is proposed to calculate the common flat bands for frequency-selective path gain and the colored noise spectrums, both of which are highly affected by the atmospheric conditions. With capacity computation based on common flat bands, we consider aerial vehicles at different altitudes and distances, under realistic weather and channel fading conditions, due to beam misalignment and also multi path fading. An extensive capacity analysis is presented, considering equal and water-filling power allocation. It is shown that, when there is no fading, capacity for aerial links is several orders of magnitude larger than the sea-level capacity. When ergodic capacity is computed for the fading scenarios, it is shown that the impact of fading vanishes with altitude. Sea-level ergodic capacity is increased by an order of magnitude for drone-to-drone communications, providing several Tbps at 10 m range, while 10s of Tbps is achievable among jet planes and UAVs, and several 100s of Tbps is possible for satellites/cubesats at 1 km under fading, suggesting that THz band is a promising alternative for aerial communications.

Fast radio bursts (FRBs) are bright, coherent, short-duration radio transients of as-yet unknown extragalactic origin. FRBs exhibit a variety of spectral, temporal and polarimetric properties that can unveil clues into their emission physics and propagation effects in the local medium. Here, we present the high-time-resolution (down to 1 μs) polarimetric properties of four 1.7 GHz bursts from the repeating FRB 20180916B, which were detected in voltage data during observations with the European Very Long Baseline Interferometry Network. We observe a range of emission timescales that spans three orders of magnitude, with the shortest component width reaching 3–4 μs (below which we are limited by scattering). We demonstrate that all four bursts are highly linearly polarized (≳80%), show no evidence of significant circular polarization (≲15%), and exhibit a constant polarization position angle (PPA) during and between bursts. On short timescales (≲100 μs), however, there appear to be subtle PPA variations (of a few degrees) across the burst profiles. These observational results are most naturally explained in an FRB model in which the emission is magnetospheric in origin, in contrast to models in which the emission originates at larger distances in a relativistic shock. High-time-resolution observations of the repeating fast radio burst source FRB 20180916B reveal changes to the polarization properties of the emission on timescales of a few microseconds, indicating an origin in the source magnetosphere.

The existence of a “dense” lunar ionosphere has been controversial for decades. Positive ions produced from the lunar surface and exosphere are inferred to have densities that are ≲ 10 6 – 10 7 m−3 near the surface and smaller at higher altitudes, yet electron densities derived from radio occultation measurements occasionally exceed these values by orders of magnitude. For example, about 4% of the single-spacecraft radio occultation measurements from Kaguya/SELENE were consistent with peak electron densities of ~ 3 × 10 8 m−3. Space plasmas should be neutral on macroscopic scales, so this represents a substantial discrepancy. Aditional observations of electron densities in the lunar ionosphere are critical to resolving this longstanding paradox. Here we theoretically assess whether radio occultation observations using two-way coherent S-band radio signals from the Lunar Reconnaissance Orbiter (LRO) spacecraft could provide useful measurements of electron densities in the lunar ionosphere. We predict the uncertainty in a single LRO radio occultation measurement of electron density to be ~ 3 × 10 8 m−3, comparable to occasional observations by Kaguya/SELENE of a dense lunar ionosphere. Thus an individual profile from LRO is unlikely to reliably detect the lunar ionosphere; however, averages of multiple ( ~ 10) LRO profiles acquired under similar geophysical and viewing conditions should be able to make reliable detections. An observing rate of six ingress occultations per day ( ~ 2000 per year) could be achieved with minimal impact on current LRO operations. This rate compares favorably with the 378 observations reported from the single-spacecraft experiment on Kaguya/SELENE between November 2007 and June 2009. The large number of observations possible for LRO would be sufficient to permit wide-ranging investigations of spatial and temporal variations in the poorly understood lunar ionosphere. These findings strengthen efforts to conduct such observations with LRO.

Sea ice is composed of discrete units called floes. Observations show that these floes can adopt a range of sizes spanning orders of magnitude, from metres to tens of kilometres. Floe size impacts the nature and magnitude of interactions between the sea ice, ocean, and atmosphere including lateral melt rate and momentum and heat exchange. However, large-scale geophysical sea ice models employ a continuum approach and traditionally either assume floes adopt a constant size or do not include an explicit treatment of floe size. In this study we apply novel observations to analyse two alternative approaches to modelling a floe size distribution (FSD) within the state-of-the-art CICE sea ice model. The first model considered is a prognostic floe size–thickness distribution where the shape of the distribution is an emergent feature of the model and is not assumed a priori. The second model considered, the WIPoFSD (Waves-in-Ice module and Power law Floe Size Distribution) model, assumes floe size follows a power law with a constant exponent. We introduce a parameterisation motivated by idealised models of in-plane brittle fracture to the prognostic model and demonstrate that the inclusion of this scheme enables the prognostic model to achieve a reasonable match against the novel observations for mid-sized floes (100 m–2 km). While neither FSD model results in a significant improvement in the ability of CICE to simulate pan-Arctic metrics in a stand-alone sea ice configuration, larger impacts can be seen over regional scales in sea ice concentration and thickness. We find that the prognostic model particularly enhances sea ice melt in the early melt season, whereas for the WIPoFSD model this melt increase occurs primarily during the late melt season. We then show that these differences between the two FSD models can be explained by considering the effective floe size, a metric used to characterise a given FSD. Finally, we discuss the advantages and disadvantages to these different approaches to modelling the FSD. We note that although the WIPoFSD model is unable to represent potentially important features of annual FSD evolution seen with the prognostic model, it is less computationally expensive and produces a better fit to novel FSD observations derived from 2 m resolution MEDEA imagery, possibly making this a stronger candidate for inclusion in climate models.