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At least 379 records · Page 21

Data-driven quantum approximate optimization algorithm for power systems

Abstract Quantum technology provides a ground-breaking methodology to tackle challenging computational issues in power systems. It is especially promising for Distributed Energy Resources (DERs) dominant systems that have been widely developed to promote energy sustainability. In those systems, knowing the maximum sections of power and data delivery is essential for monitoring, operation, and control. However, high computational effort is required. By leveraging quantum resources, Quantum Approximate Optimization Algorithm (QAOA) provides a means to search for these sections efficiently. However, QAOA performance relies heavily on critical parameters, especially for weighted graphs. Here we present a data-driven QAOA, which transfers quasi-optimal parameters between weighted graphs based on the normalized graph density. We verify the strategy with 39,774 expectation value calculations. Without parameter optimization, our data-driven QAOA is comparable with the Goemans-Williamson algorithm. This work advances QAOA and pilots its practical application to power systems in noisy intermediate-scale quantum devices.

Jing, Hang (ORCID:0000000256343489)↗

Parallelized Kalman-Filter-Based Reconstruction of Particle Tracks on Many-Core Processors and GPUs

For over a decade now, physical and energy constraints have limited clock speed improvements in commodity microprocessors. Instead, chipmakers have been pushed into producing lower-power, multi-core processors such as Graphical Processing Units (GPU), ARM CPUs, and Intel MICs. Broad-based efforts from manufacturers and developers have been devoted to making these processors user-friendly enough to perform general computations. However, extracting performance from a larger number of cores, as well as specialized vector or SIMD units, requires special care in algorithm design and code optimization. One of the most computationally challenging problems in high-energy particle experiments is finding and fitting the charged-particle tracks during event reconstruction. This is expected to become by far the dominant problem at the High-Luminosity Large Hadron Collider (HL-LHC), for example. Today the most common track finding methods are those based on the Kalman filter. Experience with Kalman techniques on real tracking detector systems has shown that they are robust and provide high physics performance. This is why they are currently in use at the LHC, both in the trigger and offine. Previously we reported on the significant parallel speedups that resulted from our investigations to adapt Kalman filters to track fitting and track building on Intel Xeon and Xeon Phi. Here, we discuss our progresses toward the understanding of these processors and the new developments to port the Kalman filter to NVIDIA GPUs.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

PHYSLITE - A new reduced common data format for ATLAS

The High Luminosity LHC (HL-LHC) era brings unprecedented computing challenges that call for novel approaches to reduce the amount of real and Monte Carlo-simulated data that is stored, while continuing to support the rich physics program of the ATLAS experiment. With the beginning of LHC Run 3, ATLAS introduced a new common data format, PHYS, that replaces most of the analysis-specific formats that were used in Run 2, and therefore reduces the disk storage significantly. ATLAS also launched the prototype of another common format, PHYSLITE, that is about a third of the size of PHYS. PHYSLITE will be the main format for ATLAS at the HL-LHC and aims to serve 80% of all physics analyses. To simplify analysis workloads and further reduce disk usage it is designed to largely replace user-defined analysis n-tuples and consequently contains pre-calibrated objects. Various forms of validations are in place to ensure correct functionality for users. Developments continue towards HL-LHC to improve the PHYSLITE format further.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

On-the-fly data set combinations with RNTuple

With the expected data volume increase for HL-LHC and the even more complex computing challenges set by future colliders, the need for efficient data storage and processing becomes more pressing. ROOT’s next-generation data format and I/O subsystem, RNTTuple, is designed to address these challenges. RNTTuple already demonstrates a clear improvement in storage and I/O efficiency, as well as overall stability and robustness with respect to its predecessor, TTTree. These improvements provide a solid baseline to introduce novel extensions to common high-energy and nuclear physics (HENP) workflows. Notably, many workflows could benefit from the ability to arbitrarily join and chain data set samples at runtime, which could reduce overall storage requirements and improve application runtime and ergonomics. In this paper, we present the RNTupleProcessor, which enables HENP data set combinations with RNTuple. We will discuss the main design considerations, present the interfaces to support data set combinations and show how they integrate in typical workflows.

de Geus, Florine Willemijn [CERN; Twente U., Ensch↗

Ab initio calculations of light-ion fusion reactions

The exact treatment of nuclei starting from the constituent nucleons and the fundamental interactions among them has been a long-standing goal in nuclear physics. Above all nuclear scattering and reactions, which require the solution of the many-body quantum-mechanical problem in the continuum, represent an extraordinary theoretical as well as computational challenge for ab initio approaches. The ab initio No-Core Shell Model/Resonating-Group Method (NCSM/RGM) complements a microscopic cluster technique with the use of realistic interactions, and a microscopic and consistent description of the nucleon clusters. This approach is capable of describing simultaneously both bound and scattering states in light nuclei. Recent applications to light nuclei scattering and fusion reactions relevant to energy production in stars and Earth based fusion facilities, such as the deuterium-{sup 3}He fusion, are presented. Progress toward the inclusion of the three nucleon force into the formalism is outlined.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Structure and dynamics of H{sub 2}O vis-á-vis phenylalanine recognition at a DPPC lipid membrane via interfacial H-bond types: Insights from polarized FT-IRRAS and ADMP simulations

Preferential and enantioselective interactions of L-/D-Phenylalanine (L-Phe and D-Phe) and butoxycarbonyl-protected L-/D-Phenylalanine (LPA and DPA) as guest with 1,2-dipalmitoyl-sn-glycero-3-phosphocholine (L-DPPC) as host were tapped by using real time Fourier transform infrared reflection absorption spectroscopy (FT-IRRAS). Polarization-modulated FT-IRRAS of DPPC monolayers above the phenylalanine modified subphases depicted fine structure/conformation differences under considerations of controlled 2D surface pressure. Selective molecular recognition of D-enantiomer over L-enantiomer driven by the DPPC head group via H-bonding and electrostatic interactions was evident spectroscopically. Accordingly, binding constants (K) of 145, 346, 28, and 56 M{sup −1} for LPA, DPA, L-Phe, and D-Phe, respectively, were estimated. The real time FT-IRRAS water bands were strictly conformation sensitive. The effect of micro-solvation on the structure and stability of the 1:1 diastereomeric L-lipid⋯, LPA/DPA and L-lipid⋯, (L/D)-Phe adducts was investigated with the aid of Atom-centered Density Matrix Propagation (ADMP), a first principle quantum mechanical molecular dynamics approach. The phosphodiester fragment was the primary site of hydration where specific solvent interactions were simulated through single- and triple- “water-phosphate” interactions, as water cluster’s “tetrahedral dice” to a “trimeric motif” transformation as a partial de-clusterization was evident. Under all the hydration patterns considered in both static and dynamic descriptions of density functional theory, L-lipid/D-amino acid enantiomer adducts continued to be stable structures while in dynamic systems, water rearranged without getting “squeezed-out” in the process of recognition. In spite of the challenging computational realm of this multiscale problem, the ADMP simulated molecular interactions complying with polarized vibrational spectroscopy unraveled a novel route to chiral recognition and interfacial water structure.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Surface thermodynamics of planar, cylindrical, and spherical vapour-liquid interfaces of water

The test-area (TA) perturbation approach has been gaining popularity as a methodology for the direct computation of the interfacial tension in molecular simulation. Though originally implemented for planar interfaces, the TA approach has also been used to analyze the interfacial properties of curved liquid interfaces. Here, we provide an interpretation of the TA method taking the view that it corresponds to the change in free energy under a transformation of the spatial metric for an affine distortion. By expressing the change in configurational energy of a molecular configuration as a Taylor expansion in the distortion parameter, compact relations are derived for the interfacial tension and its energetic and entropic components for three different geometries: planar, cylindrical, and spherical fluid interfaces. While the tensions of the planar and cylindrical geometries are characterized by first-order changes in the energy, that of the spherical interface depends on second-order contributions. We show that a greater statistical uncertainty is to be expected when calculating the thermodynamic properties of a spherical interface than for the planar and cylindrical cases, and the evaluation of the separate entropic and energetic contributions poses a greater computational challenge than the tension itself. The methodology is employed to determine the vapour-liquid interfacial tension of TIP4P/2005 water at 293 K by molecular dynamics simulation for planar, cylindrical, and spherical geometries. A weak peak in the curvature dependence of the tension is observed in the case of cylindrical threads of condensed liquid at a radius of about 8 Å, below which the tension is found to decrease again. In the case of spherical drops, a marked decrease in the tension from the planar limit is found for radii below ∼ 15 Å; there is no indication of a maximum in the tension with increasing curvature. The vapour-liquid interfacial tension tends towards the planar limit for large system sizes for both the cylindrical and spherical cases. Estimates of the entropic and energetic contributions are also evaluated for the planar and cylindrical geometries and their magnitudes are in line with the expectations of our simple analysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Site-specific dissociation dynamics of H{sub 2}/D{sub 2} on Ag(111) and Co(0001) and the validity of the site-averaging model

Dissociative chemisorption of polyatomic molecules on metal surfaces involves high-dimensional dynamics, of which quantum mechanical treatments are computationally challenging. A promising reduced-dimensional approach approximates the full-dimensional dynamics by a weighted average of fixed-site results. To examine the performance of this site-averaging model, we investigate two distinct reactions, namely, hydrogen dissociation on Co(0001) and Ag(111), using accurate first principles potential energy surfaces (PESs). The former has a very low barrier of ∼0.05 eV while the latter is highly activated with a barrier of ∼1.15 eV. These two systems allow the investigation of not only site-specific dynamical behaviors but also the validity of the site-averaging model. It is found that the reactivity is not only controlled by the barrier height but also by the topography of the PES. Moreover, the agreement between the site-averaged and full-dimensional results is much better on Ag(111), though quantitative in neither system. Further quasi-classical trajectory calculations showed that the deviations can be attributed to dynamical steering effects, which are present in both reactions at all energies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Three dimensional full-wave nonlinear acoustic simulations: Applications to ultrasound imaging

Characterization of acoustic waves that propagate nonlinearly in an inhomogeneous medium has significant applications to diagnostic and therapeutic ultrasound. The generation of an ultrasound image of human tissue is based on the complex physics of acoustic wave propagation: diffraction, reflection, scattering, frequency dependent attenuation, and nonlinearity. The nonlinearity of wave propagation is used to the advantage of diagnostic scanners that use the harmonic components of the ultrasonic signal to improve the resolution and penetration of clinical scanners. One approach to simulating ultrasound images is to make approximations that can reduce the physics to systems that have a low computational cost. Here a maximalist approach is taken and the full three dimensional wave physics is simulated with finite differences. This paper demonstrates how finite difference simulations for the nonlinear acoustic wave equation can be used to generate physically realistic two and three dimensional ultrasound images anywhere in the body. A specific intercostal liver imaging scenario for two cases: with the ribs in place, and with the ribs removed. This configuration provides an imaging scenario that cannot be performed in vivo but that can test the influence of the ribs on image quality. Several imaging properties are studied, in particular the beamplots, the spatial coherence at the transducer surface, the distributed phase aberration, and the lesion detectability for imaging at the fundamental and harmonic frequencies. The results indicate, counterintuitively, that at the fundamental frequency the beamplot improves due to the apodization effect of the ribs but at the same time there is more degradation from reverberation clutter. At the harmonic frequency there is significantly less improvement in the beamplot and also significantly less degradation from reverberation. It is shown that even though simulating the full propagation physics is computationally challenging it is necessary to quantify ultrasound image quality and its sources of degradation.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Efficient measurement of point-to-set correlations and overlap fluctuations in glass-forming liquids

Cavity point-to-set correlations are real-space tools to detect the roughening of the free-energy landscape that accompanies the dynamical slowdown of glass-forming liquids. Measuring these correlations in model glass formers remains, however, a major computational challenge. Here, we develop a general parallel-tempering method that provides orders-of-magnitude improvement for sampling and equilibrating configurations within cavities. We apply this improved scheme to the canonical Kob-Andersen binary Lennard-Jones model for temperatures down to the mode-coupling theory crossover. Most significant improvements are noted for small cavities, which have thus far been the most difficult to study. This methodological advance also enables us to study a broader range of physical observables associated with thermodynamic fluctuations. We measure the probability distribution of overlap fluctuations in cavities, which displays a non-trivial temperature evolution. The corresponding overlap susceptibility is found to provide a robust quantitative estimate of the point-to-set length scale requiring no fitting. By resolving spatial fluctuations of the overlap in the cavity, we also obtain quantitative information about the geometry of overlap fluctuations. We can thus examine in detail how the penetration length as well as its fluctuations evolve with temperature and cavity size.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Inversion of coherent surface scattering images via deep learning network

Coherent surface scattering imaging is a powerful tool for imaging a surface/interface of a thin nanostructure deposited on an opaque substrate. A mathematical conversion of an object image from a scattering pattern is essential for coherent surface scattering imaging to visualize structures of specimens. It has been achieved by using phase retrieval algorithms requiring oversampling in scattering patterns and employing alternating projection approaches. It is a computationally challenging and time-consuming process. In this paper, we demonstrate CSSI-NN, which is a deep learning neural network model to predict images of objects from scattering intensities in coherent surface scattering imaging. This model allowing for the instant outcome from scattering patterns would be tremendously beneficial not only for effective experiments but also for data analysis of phase retrieval.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

A generative artificial intelligence framework for long-time plasma turbulence simulations

Generative deep learning techniques are employed in a novel framework for the construction of surrogate models capturing the spatiotemporal dynamics of 2D plasma turbulence. The proposed Generative Artificial Intelligence Turbulence (GAIT) framework enables the acceleration of turbulence simulations for long-time transport studies. GAIT leverages a convolutional variational auto-encoder and a recurrent neural network to generate new turbulence data from existing simulations, extending the time horizon of transport studies with minimal computational cost. The application of the GAIT framework to plasma turbulence using the Hasegawa–Wakatani (HW) model is presented, evaluating its performance via various analyses. Very good agreement is found between the GAIT and the HW models in the spatiotemporal Fourier and Proper Orthogonal Decomposition spectra, the flow topology characterized by the Okubo–Weiss parameter, and the time autocorrelation function of turbulent fluctuations. Excellent agreement has also been obtained in the probability distribution function of particle displacements and the effective turbulent diffusivity. In-depth analyses of the latent space of turbulent states, choice of hyperparameters and alternative deep learning models for the time prediction are presented. Our results highlight the potential of Artificial Intelligence-based surrogate models to overcome the computational challenges in turbulence simulation, which can be extended to other situations such as geophysical fluid dynamics.

Artificial intelligence↗

Probing the self-ionization of liquid water with ab initio deep potential molecular dynamics

The chemical equilibrium between self-ionized and molecular water dictates the acid–base chemistry in aqueous solutions, yet understanding the microscopic mechanisms of water self-ionization remains experimentally and computationally challenging. Herein, Density Functional Theory (DFT)–based deep neural network (DNN) potentials are combined with enhanced sampling techniques and a global acid–base collective variable to perform extensive atomistic simulations of water self-ionization for model systems of increasing size. The explicit inclusion of long-range electrostatic interactions in the DNN potential is found to be crucial to accurately reproduce the DFT free energy profile of solvated water ion pairs in small (64 and 128 H 2 O) cells. The reversible work to separate the hydroxide and hydronium to a distance S is found to converge for simulation cells containing more than 500 H 2 O, and a distance of ∼ 8 Å is the threshold beyond which the work to further separate the two ions becomes approximately zero. The slow convergence of the potential of mean force with system size is related to a restructuring of water and an increase of the local order around the water ions. Calculation of the dissociation equilibrium constant illustrates the key role of long-range electrostatics and entropic effects in the water autoionization process.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

RELATIVISTIC CALCULATION OF TRANSITION PROBABILITIES FOR 557.7 nm AND 297.2 nm EMISSION LINES IN OXYGEN

The 557.7 nm green line and the 297.2 nm ultraviolet line in oxygen have been studied extensively due to their importance in astrophysics and atmospheric science. Despite the enormous effort devoted to these two prominent transition lines over 30 years, and in fact going back to 1934, the ratio of their transition probabilities remains a subject of major discrepancies amongst various theoretical calculations for many decades. Moreover, theoretical results are inconsistent with available laboratory results, as well as recent spacecraft measurements of Earth's airglow. This work presents new relativistic theoretical calculations of the transition probabilities of these two photoemission lines from neutral oxygen using the multi-configuration Dirac-Hartree-Fock method. Our calculations were performed in both length and velocity gauges in order to check for accuracy and consistency, with agreement to 8%. Whilst remaining a challenging computation, these results directly bear upon interpretations of plasma processes and ionization regimes in the universe.

79 ASTRONOMY AND ASTROPHYSICS↗

Simulations of the fault current limiting operation of a long-length REBCO CORC ® superconducting cable cooled by helium gas

Conductor-on-round-core (CORC®) cables composed of rare-earth-barium-copper-oxide high-temperature superconducting (HTS) tapes are of great interest for power transmission applications due to their many advantages such as high power density, light weight, and low loss. Closed circulation loops of cryogenic helium gas can be used to cool HTS cables down to low temperatures to significantly improve their current-carrying capacity. Coupled circuit-electromagnetic-thermal finite element simulations implemented in the COMSOL Multiphysics package were developed, validated, and then used for simulating the fault current limiting (FCL) performance and the cooling processes of an 8-layer CORC® cable cooled with a flow of cryogenic helium gas. In the simulations, the temperature dependence of the electrical and thermal properties of all component materials is implemented for improved accuracy. To overcome computational challenges caused by the considerable difference in geometrical scales (i.e. few-µm-thick HTS layers versus 10 m-long HTS cable), the model is divided into two separate simulations. The first simulation is performed on the transverse cross-section of the cable to calculate the electric field, heating power and temperature rise in each component of a CORC® cable during FCL operation. The heating power calculated in the first simulation is transferred to the second model to simulate the cooling of a 10 m-long cable after the fault is cleared. The effect of the helium gas flow rate on the cooling process is also investigated to develop strategic approaches for optimizing cooling systems for HTS cables with FCL capability. The simulations indicated that a 40 ms fault with a voltage drop of 20 V m −1 along the cable can result in a temperature increase from 60 K to about 165 K inside the cable, and it takes about 500 s to cool the cable back to nearly 60 K with a flow of cold helium gas at a rate of 5 g s −1 .

24 POWER TRANSMISSION AND DISTRIBUTION↗

Window convolution of the galaxy clustering bispectrum

In galaxy survey analysis, the observed clustering statistics do not directly match theoretical predictions but rather have been processed by a window function that arises from the survey geometry including the sky footprint, redshift-dependent background number density and systematic weights. While window convolution of the power spectrum is well studied, for the bispectrum with a larger number of degrees of freedom, it poses a significant numerical and computational challenge. In this work, we consider the effect of the survey window in the tripolar spherical harmonic decomposition of the bispectrum and lay down a formal procedure for their convolution via a series expansion of configuration-space three-point correlation functions, which was first proposed by Sugiyama et al. (2019). We then provide a linear algebra formulation of the full window convolution, where an unwindowed bispectrum model vector can be directly premultiplied by a window matrix specific to each survey geometry. To validate the pipeline, we focus on the Dark Energy Spectroscopic Instrument (DESI) Data Release 1 (DR1) luminous red galaxy (LRG) sample in the South Galactic Cap (SGC) in the redshift bin 0.4 ≤ z ≤ 0.6. We first perform convergence checks on the measurement of the window function from discrete random catalogues, and then investigate the convergence of the window convolution series expansion truncated at a finite of number of terms as well as the performance of the window matrix. This work highlights the differences in window convolution between the power spectrum and bispectrum, and provides a streamlined pipeline for the latter for current surveys such as DESI and the Euclid mission.

79 ASTRONOMY AND ASTROPHYSICS↗

Application of Portable Parallelization Strategies for GPUs on track reconstruction kernels

Utilizing the computational power of GPUs is one of the key ingredients to meet the computing challenges presented to the next generation of High-Energy Physics (HEP) experiments. Unlike CPUs, developing software for GPUs often involves using architecturespecific programming languages promoted by the GPU vendors and hence limits the platform that the code can run on. Various portability solutions have been developed to achieve portable, performant software across different GPU vendors. Given the rapid evolution of these portability solutions, an early adoption of them in simple HEP testbed applications will help us understand the strengths and weaknesses of respective approaches.We apply several portability solutions, including Alpaka, Kokkos, SYCL and std::execution::par, on kernels for track propagation extracted from the mkFit project. We report on the development experience of the same application with different portability solutions, as well as their performance on GPUs, measured as the throughput of the kernels, from different manufacturers such as NVIDIA, AMD and Intel.

Kwok, Martin [Fermilab] (ORCID:0000000286936146)↗

XAFS and XEOL of tetramesityldigermene - An electronic structure study of a heavy group 14 ethylene analogue

Digermene, the germanium analogue of ethylene, has a multiple bonding motif that differs greatly from that of alkenes and exhibits no pure σ or π type bonds. The electronic structure of digermenes is difficult to study experimentally due to their reactivity, and is computationally challenging because of their shallow potential energy surfaces. Using X-ray absorption near edge structures at both the germanium K and L edges we have been able to directly probe the unoccupied electronic states, or the lowest unoccupied molecular orbital (LUMO), and LUMO+ etc. in the Ge=Ge bond of tetramesityldigermene. We have demonstrated that the LUMO, LUMO+, etc. are composed of hybrid Ge 4s and 4p orbitals. Additionally, our data suggest that the LUMO exhibits relatively more Ge 4s character, whereas the LUMO+ and LUMO+2 exhibit relatively more Ge 4p character. An X-ray excited optical luminescence study of Ge 2 Mes 4 revealed one broad optical emission band at 620 nm, which is significantly red shifted compared to the known energy gap of this molecular germanium compound.

Ward, Matthew J.↗