Perfect Simulation Research Articles

Al0.7Sc0.3N butterfly-shaped laterally vibrating resonator with a figure-of-merit (kt2·Qm) over 146

This work presents the laterally vibrating Lamb wave resonators (LVRs) based on a 30% aluminum scandium nitride (Al0.7Sc0.3N) thin film with three interdigited transducer pairs operating in the S0 mode. In order to reduce the anchor loss, perfect matched layer-based finite element analysis simulations are utilized to design and optimize the device. Thanks to the high quality AlScN using magnetron sputtering with a single alloy target, vertical etching profile, and designed device structure, 1-μm-thick Al0.7Sc0.3N-based LVRs with high performance are fabricated. The resonator equivalent electric parameters are extracted utilizing the modified Butterworth–Van Dyke model. The best Al0.7Sc0.3N LVR achieves an electromechanical coupling coefficient (kt2) of 9.7% and a loaded quality factor (Qr) of 1141.5 operating at approximately 305 MHz. The same resonator shows a motional quality factor (Qm) of 1507.2, resulting in a high figure-of-merit (FoM = kt2 · Qm) of 146.2. A 1.8 MHz tuning range is measured for an Al0.7Sc0.3N LVR by applying DC voltage in the range of −40 to 40 V due to the ferroelectric property of high Sc doping in Al0.7Sc0.3N. With the high FoM, Qr, Qm, and low motional resistance (Rm), the Al0.7Sc0.3N-based LVRs show strong potential in applications of radio frequency communications and piezoelectric transducers.

Graphical construction of spatial Gibbs random graphs

We consider a random graph model on Zd that incorporates the interplay between the statistics of the graph and the underlying space where the vertices are located. Based on a graphical construction of the model as the invariant measure of a birth and death process, we prove the existence and uniqueness of a measure defined on graphs with vertices in Zd, which coincides with the limit along the measures over graphs with the finite vertex set. As a consequence, theoretical properties, such as exponential mixing of the infinite volume measure and central limit theorem for averages of a real-valued function of the graph, are obtained. Moreover, a perfect simulation algorithm based on the clan of ancestors is described in order to sample a finite window of the equilibrium measure defined on Zd.

From the Bernoulli factory to a dice enterprise via perfect sampling of Markov chains

Given a p-coin that lands heads with unknown probability p, we wish to produce an f(p)-coin for a given function f:(0,1)→(0,1). This problem is commonly known as the Bernoulli factory and results on its solvability and complexity have been obtained in (ACM Trans. Model. Comput. Simul. 4 (1994) 213–219; Ann. Appl. Probab. 15 (2005) 93–115). Nevertheless, generic ways to design a practical Bernoulli factory for a given function f exist only in a few special cases. We present a constructive way to build an efficient Bernoulli factory when f(p) is a rational function with coefficients in R. Moreover, we extend the Bernoulli factory problem to a more general setting where we have access to an m-sided die and we wish to roll a v-sided one; that is, we consider rational functions between open probability simplices. Our construction consists of rephrasing the original problem as simulating from the stationary distribution of a certain class of Markov chains—a task that we show can be achieved using perfect simulation techniques with the original m-sided die as the only source of randomness. In the Bernoulli factory case, the number of tosses needed by the algorithm has exponential tails and its expected value can be bounded uniformly in p. En route to optimizing the algorithm we show a fact of independent interest: every finite, integer valued, random variable will eventually become log-concave after convolving with enough Bernoulli trials.

MCMC Computations for Bayesian Mixture Models Using Repulsive Point Processes

Repulsive mixture models have recently gained popularity for Bayesian cluster detection. Compared to more traditional mixture models, repulsive mixture models produce a smaller number of well-separated clusters. The most commonly used methods for posterior inference either require to fix a priori the number of components or are based on reversible jump MCMC computation. We present a general framework for mixture models, when the prior of the “cluster centers” is a finite repulsive point process depending on a hyperparameter, specified by a density which may depend on an intractable normalizing constant. By investigating the posterior characterization of this class of mixture models, we derive a MCMC algorithm which avoids the well-known difficulties associated to reversible jump MCMC computation. In particular, we use an ancillary variable method, which eliminates the problem of having intractable normalizing constants in the Hastings ratio. The ancillary variable method relies on a perfect simulation algorithm, and we demonstrate this is fast because the number of components is typically small. In several simulation studies and an application on sociological data, we illustrate the advantage of our new methodology over existing methods, and we compare the use of a determinantal or a repulsive Gibbs point process prior model. Supplementary files for this article are available online.

Screening vs. gevolution: In chase of a perfect cosmological simulation code

We compare two competing relativistic approaches to the N-body simulation of the Universe large-scale structure. To this end, employing the corresponding alternative computer codes (“gevolution” and “screening”), we conduct a series of cosmological simulations in boxes of different sizes and calculate the power spectra of the scalar perturbation Φ, the frame-dragging vector potential B and the difference between scalar modes χ=Φ−Ψ. We demonstrate that the corresponding power spectra are in very good agreement between the compared schemes. For example, the relative difference of the power spectra for Φ is 0.04% maximum. Since the perturbed Einstein equations have much simpler form in the screening approach, the simulation with this code consumes less computational time, saving almost 40% of CPU hours.

Molecular understanding of calorimetric protein unfolding experiments

Testing and predicting protein stability gained importance because proteins, including antibodies, became pharmacologically relevant in viral and cancer therapies. Isothermal scanning calorimetry is the principle method to study protein stability. Here, we use the excellent experimental heat capacity Cp(T) data from the literature for a critical inspection of protein unfolding as well as for the test of a new cooperative model. In the relevant literature, experimental temperature profiles of enthalpy, Hcal(T), entropy, Scal(T), and free energy, Gcal(T) are missing. First, we therefore calculate the experimental Hcal(T), Scal(T), and Gcal(T) from published Cp(T) thermograms. Considering only the unfolding transition proper, the heat capacity and all thermodynamic functions are zero in the region of the native protein. In particular, the free energy of the folded proteins is also zero and Gcal(T) displays a trapezoidal temperature profile when cold denaturation is included. Second, we simulate the DSC-measured thermodynamic properties with a new molecular model based on statistical-mechanical thermodynamics. The model quantifies the protein cooperativity and predicts the aggregate thermodynamic variables of the system with molecular parameters only. The new model provides a perfect simulation of all thermodynamic properties, including the observed trapezoidal Gcal(T) temperature profile. Importantly, the new cooperative model can be applied to a broad range of protein sizes, including antibodies. It predicts not only heat and cold denaturation but also provides estimates of the unfolding kinetics and allows a comparison with molecular dynamics calculations and quasielastic neutron scattering experiments.

An Enchantment of Digital Archaeology: Raising the Dead with Agent-Based Models, Archaeogaming and Artificial Intelligence By Shawn Graham (Digital Archaeology 1). New York: Berghahn Books 2020. Pp. 210. $149. ISBN 9781789207866 (cloth).

<i>An Enchantment of Digital Archaeology: Raising the Dead with Agent-Based Models, Archaeogaming and Artificial Intelligence</i> By Shawn Graham (Digital Archaeology 1). New York: Berghahn Books 2020. Pp. 210. $149. ISBN 9781789207866 (cloth).

A hierarchical bilayer architecture for complex tissue regeneration

Engineering a complete, physiologically functional, periodontal complex structure remains a great clinical challenge due to the highly hierarchical architecture of the periodontium and coordinated regulation of multiple growth factors required to induce stem cell multilineage differentiation. Using biomimetic self-assembly and microstamping techniques, we construct a hierarchical bilayer architecture consisting of intrafibrillarly mineralized collagen resembling bone and cementum, and unmineralized parallel-aligned fibrils mimicking periodontal ligament. The prepared biphasic scaffold possesses unique micro/nano structure, differential mechanical properties, and growth factor-rich microenvironment between the two phases, realizing a perfect simulation of natural periodontal hard/soft tissue interface. The interconnected porous hard compartment with a Young's modulus of 1409.00 ± 160.83 MPa could induce cross-arrangement and osteogenic differentiation of stem cells in vitro, whereas the micropatterned soft compartment with a Young's modulus of 42.62 ± 4.58 MPa containing abundant endogenous growth factors, could guide parallel arrangement and fibrogenic differentiation of stem cells in vitro. After implantation in critical-sized complete periodontal tissue defect, the biomimetic bilayer architecture potently reconstructs native periodontium with the insertion of periodontal ligament fibers into newly formed cementum and alveolar bone by recruiting host mesenchymal stem cells and activating the transforming growth factor beta 1/Smad3 signaling pathway. Taken together, integration of self-assembly and microstamping strategies could successfully fabricate a hierarchical bilayer architecture, which exhibits great potential for recruiting and regulating host stem cells to promote synergistic regeneration of hard/soft tissues.

Rejection- and importance-sampling-based perfect simulation for Gibbs hard-sphere models

AbstractCoupling-from-the-past (CFTP) methods have been used to generate perfect samples from finite Gibbs hard-sphere models, an important class of spatial point processes consisting of a set of spheres with the centers on a bounded region that are distributed as a homogeneous Poisson point process (PPP) conditioned so that spheres do not overlap with each other. We propose an alternative importance-sampling-based rejection methodology for the perfect sampling of these models. We analyze the asymptotic expected running time complexity of the proposed method when the intensity of the reference PPP increases to infinity while the (expected) sphere radius decreases to zero at varying rates. We further compare the performance of the proposed method analytically and numerically with that of a naive rejection algorithm and of popular dominated CFTP algorithms. Our analysis relies upon identifying large deviations decay rates of the non-overlapping probability of spheres whose centers are distributed as a homogeneous PPP.

Expressivism, Inferentialism and the Simulation Game

Expressivism, Inferentialism and the Simulation Game

CABE-RY: A PAM-flexible dual-mutation base editor for reliable modeling of multi-nucleotide variants

Multi-nucleotide variants (MNVs) represent an important type of genetic variation and have biological and clinical significance. To simulate MNVs, we designed four dual-mutation base editors combining hA3A(Y130F), TadA8e(V106W), and protospacer adjacent motif (PAM)-flexible SpRY and selected cytosine and adenine base editor-SpRY (CABE-RY), which had the best editing performance, for further study. Characterization and comparison showed that CABE-RY had a smaller DNA editing window and lower RNA off-target edits than the corresponding single base editors. Thus, we have established a versatile tool to efficiently simulate MNVs over the genome, which could be very useful for functional studies on MNVs in humans.

Hypersonic Boundary-Layer Receptivity over a Blunt Cone to Freestream Pulse Disturbances

Although receptivity plays a key role in the transition of hypersonic flows, most prior computational receptivity studies have neglected to study broadband frequency disturbance spectra. This work uses perfect gas linear stability theory (LST) and direct numerical simulation (DNS) to study the receptivity of flow over a 9.525 mm nose radius, 7 deg half-angle straight cone at Mach 10 using finite spherical and planar pulses to approximate disturbances with broadband frequency spectra. Freestream fast acoustic, slow acoustic, temperature, and vorticity pulses of both geometries were studied to investigate a wide range of forcing conditions. Unsteady DNS predicts second mode growth and agrees well with LST. DNS and LST data are used to extract second mode receptivity coefficients and phase spectra. For the finite pulses the strongest to weakest responses are for the fast acoustic, temperature, slow acoustic, and vorticity pulses, respectively. The planar disturbances show the strongest response for the slow acoustic, temperature, vorticity, and fast acoustic pulses in that order. Fast Fourier transform results show significant variation in the spectral disturbance response between disturbance types and geometries, and the planar fast acoustic pulse in particular is shown to much more readily excite modal disturbances other than the primary second mode.

Methodologies of heat calculation and selection of rational parameters of regenerative burners operation

Decrease of energy intensity of products is an actual task for all the industries, including steel industry. One of the best solutions to increase energy efficiency of heating facilities is application of recuperative and regenerative burners, which ensure high temperature of air heating. Such high temperatures cannot be achieved at application of heating systems based on central recuperator. It was shown that many countries accomplish studies to perfect recuperative burners and simulation of their thermal operation. However at present there are no universally recognized methodologies of calculation and designing of such equipment. Results of studies presented, which were implemented in three methodologies intended for heat calculation and selection of rational parameters of regenerative burners operation. The methodologies enable also to determine a fuel utilization coefficient for a furnace system based on regenerative burners, to estimate competitiveness of solutions at creation new and modernization existing furnaces comparing with utilization of modern central recuperators. Comparative simplicity of the mathematical apparatus used in the methodologies highlighted, as well as correspondence of the used calculated expressions to the physical nature of the processes taking place. Besides, the methodologies enable during calculation to set the values of important characteristics, which can be reached based on determination of values of basic structure parameters of lining. A scheme of joint application of the elaborated methodologies proposed.

A new merged dataset for analyzing clouds, precipitation and atmospheric parameters based on ERA5 reanalysis data and the measurements of the Tropical Rainfall Measuring Mission (TRMM) precipitation radar and visible and infrared scanner

Abstract. Clouds and precipitation have vital roles in the global hydrological cycle and the radiation budget of the atmosphere–Earth system and are closely related to both the regional and the global climate. Changes in the status of the atmosphere inside clouds and precipitation systems are also important, but the use of multi-source datasets is hampered by their different spatial and temporal resolutions. We merged the precipitation parameters measured by the Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) with the multi-channel cloud-top radiance measured by the visible and infrared scanner (VIRS) and atmospheric parameters in the ERA5 reanalysis dataset. The merging of pixels between the precipitation parameters and multi-channel cloud-top radiance was shown to be reasonable. The 1B01-2A25 dataset of pixel-merged data (1B01-2A25-PMD) contains cloud parameters for each PR pixel. The 1B01-2A25 gridded dataset (1B01-2A25-GD) was merged spatially with the ERA5 reanalysis data. The statistical results indicate that gridding has no unacceptable influence on the parameters in 1B01-2A25-PMD. In one orbit, the difference in the mean value of the near-surface rain rate and the signals measured by the VIRS was no more than 0.87 and the standard deviation was no more than 2.38. The 1B01-2A25-GD and ERA5 datasets were spatiotemporally collocated to establish the merged 1B01-2A25 gridded dataset (M-1B01-2A25-GD). Three case studies of typical cloud and precipitation events were analyzed to illustrate the practical use of M-1B01-2A25-GD. This new merged gridded dataset can be used to study clouds and precipitation systems and provides a perfect opportunity for multi-source data analysis and model simulations. The data which were used in this paper are freely available at https://doi.org/10.5281/zenodo.4458868 (Sun and Fu, 2021).

Metamaterial perfect absorber simulations for intensifying the thermal gradient across a thermoelectric device.

The thermal gradient across a thermoelectric device is the key to convert heat energy into electricity. Here, we propose a metamaterial perfect absorber (MPA) that increases the thermal gradient across a thermoelectric device by local heat generation through absorbing thermal radiation emitted from an infinite-size blackbody radiator. The MPA, when attached on top of a bismuth telluride thermoelectric device, generates local heat that propagates to the device, resulting in an additional thermal gradient. The amount of local heat generated at the MPA and the output power of the thermoelectric device loaded with the MPA are examined through numerical calculations.

Multi-Mode Surface Generalization Supports a Detailed Urban Flooding Simulation Model

With the aim of achieving high precision and high efficiency, recent research on hydraulic flood models has tended to focus on the algorithms for solving the shallow water equations of Saint-Venant. While development of the algorithms will help to improve the simulation precision and the solving of specific problems, the other influential factor in flood risk modeling is the precision and reasonable generalization of the data. This is even more important for increasing the model’s computational accuracy and efficiency but is frequently undervalued. Frequent rainstorm waterlogging is having a serious impact on China’s large cities. Early warning of waterlogging risk following a rainstorm forecast is an effective method for preventing or reducing potential losses. Concrete waterlogging information including locations, depth, and process is essential for early warnings. This paper focuses on the influence of data precision and reasonable generalization on an urban flooding model. A detailed hydraulic urban flooding model characterized by detailed data processing and component coupling can help to provide advance information. In Beijing city, road networks, overpasses, and buildings are so highly concentrated that rainstorms easily result in waterlogging in low-lying locations. Therefore, partial microrelief is the determinate factor in waterlogging simulation. This paper shows that multi-mode surface data generalization and detailed model coupling support a perfect simulation of a Beijing urban flooding model. The influence of buildings, roads, and overpasses on surface water flow was carefully considered based on the innovative aspect of a fine generalization of partial microrelief. One novelty is the simulation of the whole overland flow from the beginning of rainfall to mesh, not only from manhole overflow, because the waterlogging is caused mainly by initial surface water runoff rather than by manhole overflow. A second novelty is the use of a new kind of coupling mode based on physical mechanisms between surface and pipe models. Here, rain perforated strainers instead of manholes play a role as flow exchange points between pipe and surface. This coupling mode is much closer to the real world. Based on a detailed Beijing urban flooding model, a scenarios library of typical rainfall events and corresponding waterlogging results was constructed. Several years of practice have demonstrated that a rich library of scenarios can be used effectively for the quick identification and early warning of waterlogging risk for a forecast rainfall. Test results show that multi-mode surface generalization is effective in improving outcomes and useful for scientific decision making in controlling urban waterlogging.

The Impact of the Variation in Weather and Season on WRF Dynamical Downscaling in the Pearl River Delta Region

In this study, National Centers for Environmental Prediction (NCEP) Final (FNL) operational global analysis data and meteorological observation data from 2013 to 2017 were used to evaluate the impact of seasonal changes and different circulation classifications on the dynamical downscaling simulation results of Weather Research and Forecasting (WRF) in the Pearl River Delta (PRD) region. The results show that the dynamical downscaling method can accurately simulate the time variation characteristics of the near-surface meteorological field and the hit rates of a 2-m temperature, 2-m relative humidity, 10-m wind speed, and 10-m wind direction are 92.66%, 93.98%, 26.78%, and 76.78%, respectively. The WRF model slightly underestimates the temperature and relative humidity, and overestimates the wind speed and precipitation. For precipitation, the WRF model can better simulate the variation characteristics of light rain and heavy rain, with the probability of detection are 0.59 and 0.69, respectively. For seasonal factors, the WRF model can conduct a perfect simulation in autumn and winter, followed by spring, while summer is vulnerable to extreme weather, so the result of the simulation is relatively poor. The circulation type is an important parameter of downscaling assessment. When the PRD is controlled by high pressure, the simulated results of WRF are good, and when the PRD is affected by low pressure or extreme weather, the simulation results are relatively poor.

Estimating parameters in a sea ice model using an ensemble Kalman filter

Abstract. Uncertain or inaccurate parameters in sea ice models influence seasonal predictions and climate change projections in terms of both mean and trend. We explore the feasibility and benefits of applying an ensemble Kalman filter (EnKF) to estimate parameters in the Los Alamos sea ice model (CICE). Parameter estimation (PE) is applied to the highly influential dry snow grain radius and combined with state estimation in a series of perfect model observing system simulation experiments (OSSEs). Allowing the parameter to vary in space improves performance along the sea ice edge but degrades in the central Arctic compared to requiring the parameter to be uniform everywhere, suggesting that spatially varying parameters will likely improve PE performance at local scales and should be considered with caution. We compare experiments with both PE and state estimation to experiments with only the latter and have found that the benefits of PE mostly occur after the data assimilation period, when no observations are available to assimilate (i.e., the forecast period), which suggests PE's relevance for improving seasonal predictions of Arctic sea ice.

Perfect simulation of the hard disks model by partial rejection sampling

We present a perfect simulation of the hard disks model via the partial rejection sampling method. Provided the density of disks is not too high, the method produces exact samples in O (log n ) rounds, and total time O(n) , where n is the expected number of disks. The method extends easily to the hard spheres model in d &gt; 2 dimensions. In order to apply the partial rejection method to this continuous setting, we provide an alternative perspective of its correctness and run-time analysis that is valid for general state spaces.

Benchmarking Quantum Coprocessors in an Application-Centric, Hardware-Agnostic, and Scalable Way

Existing protocols for benchmarking current quantum co-processors fail to meet the usual standards for assessing the performance of High-Performance-Computing platforms. After a synthetic review of these protocols -- whether at the gate, circuit or application level -- we introduce a new benchmark, dubbed Atos Q-score (TM), that is application-centric, hardware-agnostic and scalable to quantum advantage processor sizes and beyond. The Q-score measures the maximum number of qubits that can be used effectively to solve the MaxCut combinatorial optimization problem with the Quantum Approximate Optimization Algorithm. We give a robust definition of the notion of effective performance by introducing an improved approximation ratio based on the scaling of random and optimal algorithms. We illustrate the behavior of Q-score using perfect and noisy simulations of quantum processors. Finally, we provide an open-source implementation of Q-score that makes it easy to compute the Q-score of any quantum hardware.