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At least 55 records · Page 3

Scalable quantum simulations of scattering in scalar field theory on 120 qubits

Simulations of collisions of fundamental particles on a quantum computer are expected to have an exponential advantage over classical methods and promise to enhance searches for new physics. Furthermore, scattering in scalar field theory has been shown to be bounded-error quantum polynomial time (BQP) complete, making it a representative problem for which quantum computation is efficient. As a step toward large-scale quantum simulations of collision processes, scattering of wave packets in one-dimensional scalar field theory is simulated using 120 qubits of IBM’s Heron superconducting quantum computer ibm_fez. Variational circuits compressing vacuum preparation, wave packet initialization, and time evolution are determined using classical resources. By leveraging physical properties of states in the theory, such as symmetries and locality, the variational quantum algorithm constructs scalable circuits that can be used to simulate arbitrarily large system sizes. A new strategy is introduced to mitigate errors in quantum simulations, which enables the extraction of meaningful results from circuits with up to 4924 two-qubit gates and two-qubit gate depths of 103. The effect of interactions is clearly seen, and is found to be in agreement with classical matrix product state simulations. Finally, the developments that will be necessary to simulate high-energy inelastic collisions on a quantum computer are discussed.

quantum circuits↗

Kernel fusion in atomistic spin dynamics simulations on Nvidia GPUs using tensor core

In atomistic spin dynamics simulations, the time cost of constructing the space- and time-displaced pair correlation function in real space increases quadratically as the number of spins N, leading to significant computational effort. The GEMM subroutine can be adopted to accelerate the calculation of the dynamical spin-spin correlation function, but the computational cost of simulating large spin systems (>40000 spins) on CPUs remains expensive. In this work, we perform the simulation on the graphics processing unit (GPU), a hardware solution widely used as an accelerator for scientific computing and deep learning. Here we show that GPUs can accelerate the simulation up to 25-fold compared to multi-core CPUs when using the GEMM subroutine on both. To hide memory latency, we fuse the element-wise operation into the GEMM kernel using CUTLASS that can improve the performance by 26% ~ 33% compared to implementation based on cuBLAS. Furthermore, we perform the on-the-fly calculation in the epilogue of the GEMM subroutine to avoid saving intermediate results on global memory, which makes the large-scale atomistic spin dynamics simulation feasible and affordable.

97 MATHEMATICS AND COMPUTING↗

Small-world complex network generation on a digital quantum processor

Abstract Quantum cellular automata (QCA) evolve qubits in a quantum circuit depending only on the states of their neighborhoods and model how rich physical complexity can emerge from a simple set of underlying dynamical rules. The inability of classical computers to simulate large quantum systems hinders the elucidation of quantum cellular automata, but quantum computers offer an ideal simulation platform. Here, we experimentally realize QCA on a digital quantum processor, simulating a one-dimensional Goldilocks rule on chains of up to 23 superconducting qubits. We calculate calibrated and error-mitigated population dynamics and complex network measures, which indicate the formation of small-world mutual information networks. These networks decohere at fixed circuit depth independent of system size, the largest of which corresponding to 1,056 two-qubit gates. Such computations may enable the employment of QCA in applications like the simulation of strongly-correlated matter or beyond-classical computational demonstrations.

97 MATHEMATICS AND COMPUTING↗

Intelligently Partitioned Phasor-EMT Hybrid Simulations of Large-Scale, High-IBR Power Systems

As the penetration level of power electronics-interfaced renewables such as photovoltaics (PV) and wind has surged in modern electric grids, new operational risks caused by the dynamics of those inverter-based resources (IBRs) are emerging in parallel. Lessons learned from various grid events include that the impact of IBRs on system-level grid stability will become prominent along with the increase of renewables and that the short-timescale dynamic impacts of IBRs on grid stability are not fully captured by current commercial dynamic simulation tools [1] [2]. For example, IBRs can be controlled to mitigate those destabilizing interactions, but conventional phasor-domain tools (e.g. PSS/E, PSLF) often cannot capture that; likewise, the existing electromagnetic transient (EMT) simulation tools (e.g. PSCAD, EMTP) can simulate detailed IBR controls, but for large power systems with many IBRs, slow simulation speeds severely impede the ability to study dynamic events [3] [4]. Massively paralleling simulations using high-performance computing (HPC) can help address this, especially now that cloud-based HPC capability is widely available, but today s EMT tools are not HPC-compatible, and parallelization of dynamic simulation solvers is not trivial because each region can dynamically affect the others. Thus, dynamic simulation of grids with very large numbers of IBRs potentially poses a barrier to the ongoing energy transition.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Low-Dissipation Advection Schemes Designed for Large Eddy Simulations of Hypersonic Propulsion Systems

The 2nd-order upwind inviscid flux scheme implemented in the multi-block, structured grid, cell centered, finite volume, high-speed reacting flow code VULCAN has been modified to reduce numerical dissipation. This modification was motivated by the desire to improve the codes ability to perform large eddy simulations. The reduction in dissipation was accomplished through a hybridization of non-dissipative and dissipative discontinuity-capturing advection schemes that reduces numerical dissipation while maintaining the ability to capture shocks. A methodology for constructing hybrid-advection schemes that blends nondissipative fluxes consisting of linear combinations of divergence and product rule forms discretized using 4th-order symmetric operators, with dissipative, 3rd or 4th-order reconstruction based upwind flux schemes was developed and implemented. A series of benchmark problems with increasing spatial and fluid dynamical complexity were utilized to examine the ability of the candidate schemes to resolve and propagate structures typical of turbulent flow, their discontinuity capturing capability and their robustness. A realistic geometry typical of a high-speed propulsion system flowpath was computed using the most promising of the examined schemes and was compared with available experimental data to demonstrate simulation fidelity.

White, Jeffrey A.↗

Liquid Oxygen/Liquid Methane Test Summary of the RS-18 Lunar Ascent Engine at Simulated Altitude Conditions at NASA White Sands Test Facility

Tests were conducted with the RS18 rocket engine using liquid oxygen (LO2) and liquid methane (LCH4) propellants under simulated altitude conditions at NASA Johnson Space Center White Sands Test Facility (WSTF). This project is part of NASA s Propulsion and Cryogenics Advanced Development (PCAD) project. "Green" propellants, such as LO2/LCH4, offer savings in both performance and safety over equivalently sized hypergolic propellant systems in spacecraft applications such as ascent engines or service module engines. Altitude simulation was achieved using the WSTF Large Altitude Simulation System, which provided altitude conditions equivalent up to approx.120,000 ft (approx.37 km). For specific impulse calculations, engine thrust and propellant mass flow rates were measured. Propellant flow rate was measured using a coriolis-style mass-flow meter and compared with a serial turbine-style flow meter. Results showed a significant performance measurement difference during ignition startup. LO2 flow ranged from 5.9-9.5 lbm/sec (2.7-4.3 kg/sec), and LCH4 flow varied from 3.0-4.4 lbm/sec (1.4-2.0 kg/sec) during the RS-18 hot-fire test series. Thrust was measured using three load cells in parallel. Ignition was demonstrated using a gaseous oxygen/methane spark torch igniter. Data was obtained at multiple chamber pressures, and calculations were performed for specific impulse, C* combustion efficiency, and thrust vector alignment. Test objectives for the RS-18 project are 1) conduct a shakedown of the test stand for LO2/methane lunar ascent engines, 2) obtain vacuum ignition data for the torch and pyrotechnic igniters, and 3) obtain nozzle kinetics data to anchor two-dimensional kinetics codes.

Melcher, John C., IV↗

Liquid Oxygen/Liquid Methane Test Results of the RS-18 Lunar Ascent Engine at Simulated Altitude Conditions at NASA White Sands Test Facility

Tests were conducted with the RS-18 rocket engine using liquid oxygen (LO2) and liquid methane (LCH4) propellants under simulated altitude conditions at NASA Johnson Space Center White Sands Test Facility (WSTF). This project is part of NASA's Propulsion and Cryogenics Advanced Development (PCAD) project. "Green" propellants, such as LO2/LCH4, offer savings in both performance and safety over equivalently sized hypergolic propulsion systems in spacecraft applications such as ascent engines or service module engines. Altitude simulation was achieved using the WSTF Large Altitude Simulation System, which provided altitude conditions equivalent up to ~122,000 ft (~37 km). For specific impulse calculations, engine thrust and propellant mass flow rates were measured. LO2 flow ranged from 5.9 - 9.5 lbm/sec (2.7 - 4.3 kg/sec), and LCH4 flow varied from 3.0 - 4.4 lbm/sec (1.4 - 2.0 kg/sec) during the RS-18 hot-fire test series. Propellant flow rate was measured using a coriolis mass-flow meter and compared with a serial turbine-style flow meter. Results showed a significant performance measurement difference during ignition startup due to two-phase flow effects. Subsequent cold-flow testing demonstrated that the propellant manifolds must be adequately flushed in order for the coriolis flow meters to give accurate data. The coriolis flow meters were later shown to provide accurate steady-state data, but the turbine flow meter data should be used in transient phases of operation. Thrust was measured using three load cells in parallel, which also provides the capability to calculate thrust vector alignment. Ignition was demonstrated using a gaseous oxygen/methane spark torch igniter. Test objectives for the RS-18 project are 1) conduct a shakedown of the test stand for LO2/methane lunar ascent engines, 2) obtain vacuum ignition data for the torch and pyrotechnic igniters, and 3) obtain nozzle kinetics data to anchor two-dimensional kinetics codes. All of these objectives were met with the RS-18 data and additional testing data from subsequent LO2/methane test programs in 2009 which included the first simulated-altitude pyrotechnic ignition demonstration of LO2/methane.

Melcher, John C., IV↗

Situational Awareness of Grid Anomalies (SAGA)

The modern power industry becomes more vulnerable to cyber events due to the growing interconnectivity, interdependence, and complexity of the electric power grid. High-fidelity modeling and simulation tools that support the preventative risk analysis on potential cyber-relevant events is essential for ensuring the situational awareness of the system operator as it provides an inexpensive and risk-free environment to test the system responses under various cyber-relevant events and hereby can support research on cyber anomaly detection, optimal protective resource allocation, and mitigation measures. In this webinar, we will share NREL's cybersecurity research capabilities by highlighting the development of a scalable cyber-physical event test bed and demonstration with real hardware in the loop. The developed cyber-physical event test bed is backboned by an integrated transmission, distribution, and communication dynamic co-simulation framework and a plug-and-play cyber event generation module. It is designed to be modular and compatible with parallel computing, and thereby supports large-scale system simulations at an affordable computation cost. The test bed can capture millisecond-to-minutes dynamic frequency and voltage responses under cyber events from the bulk transmission system to the active distribution systems and distributed energy resources at the grid edge.

co-simulation↗

Marshall system for aerospace simulation (MARSYAS)

System is simple flexible language which can be coded by users unfamiliar with computer programming. It is designed for engineers with little experience in simulation, who desire to simulate large physical systems. User has ability to mix differential equations with diagrams in his model. With few exceptions, there is no rigid statement-operator structure within given module.

Tranboth, H. H.↗

Learning Design at White Sands Test Facility

During the Fall of 2010, I spent my time at NASA White Sands Test Facility in Las Cruces, NM as an Undergraduate Student Research Program (USRP) Intern. During that time, I was given three projects to work on: Large Altitude Simulation System (LASS) basket strainer, log books, and the design of a case for touch screen monitors used for simulations. I spent most of my time on the LASS basket strainer. The LASS system has a water feed line with a basket strainer that filters out rust. In 2009, there were three misfires which cost approximately $27,000 and about 8% of the allotted time. The strainer was getting a large change in pressure that would result in a shutdown of the system. I have designed a new basket that will eliminate the large pressure change and it can be used with the old basket strainer housing. The LASS system has three steam generators (modules). Documents pertaining to these modules are stored electronically, and the majority of the documents are not able to be searched with keywords, so they have to be gone through one by one. I have come up with an idea on how to organize these files so that the Propulsion Department may efficiently search through the documents needed. Propulsion also has a LASS simulator that incorporates two touch screen monitors. Currently these monitors are in six foot by two foot metal cabinet on wheels. During simulation these monitors are used in the block house and need to be taken out of the block house when not in use. I have designed different options for hand held cases for storing and transporting the monitors in and out of the block house. The three projects previously mentioned demonstrate my contributions to the Propulsion Department and have taught me real world experience that is essential in becoming a productive engineer.

Grotewiel, Shane↗

Machine-Learned Committor Functions for Reactive Molecular Dynamics

Reactive molecular dynamics (MD) is a powerful tool for atomistic-scale modeling of a diverse range of chemical processes. However, scaling these simulations to large systems and long times scales remains a challenge because of the complexity of the potential energy function required. The authors previously developed a heuristic approach, called REACTER, that incorporates reactivity in MD simulations in a less general but much more computationally efficient manner. REACTER uses standard, fixed valence force fields as the underlying potentialenergy surface for describing all interatomic interactions but adds a procedure for enforcing user-defined reactions that occur when certain geometric constraints on relative atomic positions are satisfied. Further, these bonding changes can be accepted or rejected with a probability related tothe local thermal energy. This work seeks to generalize this approach by replacing the set of user defined geometric constraints and energetic criteria with a committor function that specifies the probability of a reaction occurring on the basis of the local atomic configuration. The committor function is a useful mathematical tool for modeling rare events but, unfortunately, is very difficult to compute for realistic systems in a general way. This work describes a method for approximating the committor function using a machine learning approach, specifically a deep neural network trained with data from reactive MD and DFT-based dynamics simulations. This network is coupled to the existing REACTER protocol, as implemented in the LAMMPS MD package, and used to make on-the-fly predictions of reaction probabilities without the more extensive user input previously required. The new method is demonstrated using the polymerization of polystyrene as a case study. Although very dependent on the quality and quantity of training data, machine-learned committor functions show promise as a method for incorporating reaction probability from higher level calculations into highly scalable MD simulations.

polymer simulations↗

V-SUIT Model Validation Using PLSS 1.0 Test Results

The dynamic portable life support system (PLSS) simulation software Virtual Space Suit (V-SUIT) has been under development at the Technische Universitat Munchen since 2011 as a spin-off from the Virtual Habitat (V-HAB) project. The MATLAB(trademark)-based V-SUIT simulates space suit portable life support systems and their interaction with a detailed and also dynamic human model, as well as the dynamic external environment of a space suit moving on a planetary surface. To demonstrate the feasibility of a large, system level simulation like V-SUIT, a model of NASA's PLSS 1.0 prototype was created. This prototype was run through an extensive series of tests in 2011. Since the test setup was heavily instrumented, it produced a wealth of data making it ideal for model validation. The implemented model includes all components of the PLSS in both the ventilation and thermal loops. The major components are modeled in greater detail, while smaller and ancillary components are low fidelity black box models. The major components include the Rapid Cycle Amine (RCA) CO2 removal system, the Primary and Secondary Oxygen Assembly (POS/SOA), the Pressure Garment System Volume Simulator (PGSVS), the Human Metabolic Simulator (HMS), the heat exchanger between the ventilation and thermal loops, the Space Suit Water Membrane Evaporator (SWME) and finally the Liquid Cooling Garment Simulator (LCGS). Using the created model, dynamic simulations were performed using same test points also used during PLSS 1.0 testing. The results of the simulation were then compared to the test data with special focus on absolute values during the steady state phases and dynamic behavior during the transition between test points. Quantified simulation results are presented that demonstrate which areas of the V-SUIT model are in need of further refinement and those that are sufficiently close to the test results. Finally, lessons learned from the modelling and validation process are given in combination with implications for the future development of other PLSS models in V-SUIT.

Olthoff, Claas↗

Kinetic simulations underestimate the effects of waves during magnetic reconnection

Collisionless plasma systems are often studied using fully kinetic simulations, where protons and electrons are treated as particles. Due to their computational expense, it is necessary to reduce the ion-to-electron mass ratio $m_i/m_e$ or the ratio between plasma and cyclotron frequencies in simulations of large systems. In this Letter we show that when electron-scale waves are present in larger-scale systems, numerical parameters affect their amplitudes and effects on the larger system. Using lower-hybrid drift waves during magnetic reconnection as an example, we find that the ratio between the wave electric field and the reconnection electric field scales as $\sqrt{m_i/m_e}$, while the phase relationship is also affected. The combination of these effects means that the anomalous drag that contributes to momentum balance in the reconnection region can be underestimated by an order of magnitude. The results are relevant to the coupling of electron-scale waves to ion-scale reconnection regions, and other systems such as collisionless shocks.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Recent Developments in DFTB+, a Software Package for Efficient Atomistic Quantum Mechanical Simulations

DFTB+ is a flexible, open-source software package developed by its community, designed for fast and efficient atomistic quantum mechanical simulations. It employs various methods that approximate density functional theory (DFT), such as density functional-based tight binding (DFTB) and the extended tight binding (xTB) approach allowing simulations of large systems over extended time scales with reasonable accuracy, while being significantly faster than traditional ab initio methods. In recent years, several new extensions of the DFTB method have been developed and implemented in the DFTB+ program package in order to improve the accuracy and generality of the available simulation results. In this paper, we review those enhancements, show several use case examples and discuss the strengths and limitations of its features.

36 MATERIALS SCIENCE↗

Accurate Hellmann–Feynman forces from density functional calculations with augmented Gaussian basis sets

The Hellmann–Feynman (HF) theorem provides a way to compute forces directly from the electron density, enabling efficient force calculations for large systems through machine learning (ML) models for the electron density. The main issue holding back the general acceptance of the HF approach for atom-centered basis sets is the well-known Pulay force which, if naively discarded, typically constitutes an error upward of 10 eV/Å in forces. In this work, we demonstrate that if a suitably augmented Gaussian basis set is used for density functional calculations, the Pulay force can be suppressed, and HF forces can be computed as accurately as analytical forces with state-of-the-art basis sets, allowing geometry optimization and molecular dynamics to be reliably performed with HF forces. Our results pave a clear path forward for the accurate and efficient simulation of large systems using ML densities and the HF theorem.

Pathak, Shivesh (ORCID:0000000172798195)↗

Minimal implicit-solvent coarse-grained simulation of Pluronic block copolymers with ionic liquids

Pluronic block copolymers, composed of poly(ethylene oxide) (PEO) and poly(propylene oxide) (PPO) in a triblock structure (PEO–PPO–PEO), are well known for their amphiphilic character and ability to self‐assemble into micelles in aqueous solution. The addition of ionic liquids (ILs) can further modulate the core–shell structures of these copolymers, influencing their stability, critical micellization temperature, and size. However, fully atomistic simulations often become prohibitively expensive due to the size and complexity of these systems. In this work, coarse‐grained simulations using a minimal implicit‐solvent model were performed to examine how two classes of ILs, namely, 1‐alkyl‐3‐methylimidazolium ([C n C 1 im]) and 1‐alkyl‐3‐methylpyrrolidinium ([C n C 1 pyrr]), change the micellization of Pluronic block copolymers in aqueous solution. The effects of IL concentration and alkyl group length were investigated, and the model greatly improved the efficiency of simulating large‐scale micelle systems. Furthermore, the numerical simulations are qualitatively compared with experimental investigations. Our results show that adding ILs expands the micelle core by embedding IL tails among the PPO blocks, thereby increasing overall micelle size. Less polar ILs generally induce more pronounced micellar growth. However, the effect of IL tail length on conformation and micellar packing is non‐monotonic. Up to moderate chain lengths (around C8–C10), the IL tails can extend sufficiently to increase local separation within the micelle; at longer tail lengths, enhanced hydrophobic clustering and steric hindrance cause the tails to bend or fold, capping further expansion. In addition, although block copolymer chains tend to pack more closely in the presence of longer‐tailed ILs, the random coil size of an individual polymer chain does not necessarily shrink. Meanwhile, these insights provide a deeper understanding of how Pluronic/IL systems interact, informing applications in drug delivery, cosmetics, food, and environmental engineering. Finally, our minimal implicit‐solvent model can be applied to larger systems and longer timescales, substantially reducing computational cost while reproducing key structural trends observed experimentally.

Atomistic simulations↗

Triviality of quantum trajectories close to a directed percolation transition

Here we study quantum circuits consisting of unitary gates, projective measurements, and control operations that steer the system toward a pure absorbing state. Two types of phase transition occur as the rate of these control operations is increased: a measurement-induced entanglement transition, and a directed percolation transition into the absorbing state (taken here to be a product state). In this work, we show analytically that these transitions are generically distinct, with the quantum trajectories becoming disentangled before the absorbing state transition is reached, and we analyze their critical properties. We introduce a simple class of models where the measurements in each quantum trajectory define an effective tensor network (ETN)—a subgraph of the initial spacetime graph where nontrivial time evolution takes place. By analyzing the entanglement properties of the ETN, we show that the entanglement and absorbing-state transitions coincide only in the limit of the infinite local Hilbert-space dimension. Focusing on a Clifford model which allows numerical simulations for large system sizes, we verify our predictions and study the finite-size crossover between the two transitions at large local Hilbert space dimension. We give evidence that the entanglement transition is governed by the same fixed point as in hybrid circuits without feedback.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗