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At least 199 records · Page 11

Designing a Framework for Solving Multiobjective Simulation Optimization Problems

Multiobjective simulation optimization (MOSO) problems are optimization problems with multiple conflicting objectives, where evaluation of at least one of the objectives depends on a black-box numerical code or real-world experiment, which we refer to as a simulation. Whereas an extensive body of research is dedicated to developing new algorithms and methods for solving these and related problems, it is challenging and time-consuming to integrate these techniques into real-world production-ready solvers. This is partly because of the diversity and complexity of modern state-of-the-art MOSO algorithms and methods and partly because of the complexity and specificity of many real-world problems and their corresponding computing environments. The complexity of this problem is only compounded when introducing potentially complex and/or domain-specific surrogate-modeling techniques, problem formulations, design spaces, and data acquisition functions. Here, this paper carefully surveys the current state of the art in MOSO algorithms, techniques, and solvers, as well as problem types and computational environments where MOSO is commonly applied. We then present several key challenges in the design of a parallel multiobjective simulation optimization framework (ParMOO) and how they have been addressed. Finally, we provide two case studies demonstrating how customized ParMOO solvers can be quickly built and deployed to solve real-world MOSO problems.

engineering design optimization↗

Improved energies and local energies with weighted variational Monte Carlo

Neural network parametrizations have increasingly been used to represent the ground and excited states in variational Monte Carlo (VMC) with promising results. However, traditional VMC methods only optimize the wave function in regions of peak probability. The wave function is uncontrolled in the tails of the probability distribution, which can limit the accuracy of the trained wave function. To improve the approximation accuracy in the probability tails, this paper interprets VMC as a gradient flow in the space of wave functions, followed by a projection step. From this perspective, arbitrary probability distributions can be used in the projection step, allowing the user to prioritize accuracy in different regions of state space. Motivated by this theoretical perspective, the paper tests a weighted VMC method on the antiferromagnetic Heisenberg model for a periodic spin chain. Compared to traditional VMC, weighted VMC reduces the error in the ground state energy by a factor of 2, and it reduces the errors in the local energies away from the mode by large factors of 10 2 –10 4 .

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Distinguishing homolytic vs heterolytic bond dissociation of phenylsulfonium cations with localized active space methods

Modeling chemical reactions with quantum chemical methods is challenging when the electronic structure varies significantly throughout the reaction and when electronic excited states are involved. Multireference methods, such as complete active space self-consistent field (CASSCF), can handle these multiconfigurational situations. However, even if the size of the needed active space is affordable, in many cases, the active space does not change consistently from reactant to product, causing discontinuities in the potential energy surface. The localized active space SCF (LASSCF) is a cheaper alternative to CASSCF for strongly correlated systems with weakly correlated fragments. The method is used for the first time to study a chemical reaction, namely the bond dissociation of a mono-, di-, and triphenylsulfonium cation. LASSCF calculations generate smooth potential energy scans more easily than the corresponding, more computationally expensive CASSCF calculations while predicting similar bond dissociation energies. Furthermore, our calculations suggest a homolytic bond cleavage for di- and triphenylsulfonium and a heterolytic pathway for monophenylsulfonium.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Spin structures and baby universes

We extend a 2d topological model of the gravitational path integral to include sums over spin structure, corresponding to Neveu-Schwarz (NS) or Ramond (R) boundary conditions for fermions. This path integral corresponds to a correlator of boundary creation operators on a non-trivial baby universe Hilbert space, and vanishes when the number of R boundaries is odd. This vanishing implies a non-factorization of the correlator, which necessitates a dual interpretation of the bulk path integral in terms of a product of partition functions (associated to NS boundaries) and Witten indices (associated to R boundaries), averaged over an ensemble of theories with varying Hilbert space dimension and different numbers of bosonic and fermionic states. We also consider a model with End-of-the-World (EOW) branes, for which the dual ensemble then includes a sum over randomly chosen fermionic and bosonic states. We propose two modifications of the bulk path integral which restore an interpretation in a single dual theory: (i) a geometric prescription where we add extra boundaries with a sum over their spin structures, and (ii) an algebraic prescription involving “spacetime D-branes”. We extend our ideas to Jackiw-Teitelboim gravity, and propose a dual description of a single unitary theory with spin structure in a system with eigenbranes.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

NuQKD: A Modular Quantum Key Distribution Simulation Framework for Engineering Applications

Abstract An experimental Quantum Key Distribution (QKD) implementation requires advanced costly hardware, unavailable in most research environments, making protocol testing and performance evaluation complicated. This has been a major motivation for the development of QKD simulation frameworks, to allow researchers to obtain insight before proceeding into practical implementations. Several simulators have been introduced over the recent years. However, only four are publicly available, only one of which models equipment imperfections. Currently, no open‐source simulator includes all following capabilities: channel attenuation modelling, equipment imperfections and effects on key rates, estimation of elapsed time during classical and quantum‐ channel processes, use of truly random binary sequences for qubits and measurement bases, shared ‐bit fraction customization. In this paper, we present NuQKD, an open‐ source modular, intuitive simulator, featuring all the above capabilities. NuQKD establishes communication between two computer terminals, accepts custom user inputs (iterations, raw key size, attacker interception rate etc.) and evaluates the sifted key, Quantum Bit Error Rate (QBER), elapsed communication time, and more. NuQKD capabilities include optical fiber and free ‐space simulation, modeling of equipment/channel imperfections, bitstrings from True Random Number Generators, decoy‐state protocol support, and automated evaluation of performance metrics. We expect NuQKD to enable convenient and accurate representation of actual experimental conditions.

Gkouliaras, Konstantinos↗

The wavefunction of a quantum S 1 × S 2 universe

We study quantum gravity corrections to the no-boundary wavefunction describing a universe with spatial topology S 1 × S 2 . It has been suggested that quantum effects become increasingly important when the size of the circle is large relative to the sphere. In this paper, we confirm this claim by an explicit four-dimensional one-loop calculation of the gravitational path integral preparing such a state. In the process, we clarify some aspects of the gravitational path integral on complex spacetimes. These quantum corrections play a crucial role in ensuring that the norm of the wavefunction is naturally expressed in terms of a path integral over S 2 × S 2 at the classical level. We extend some of the analysis to more general spatial topologies, as well as to the inclusion of fermions.

cosmological models↗

Full-Scale Ab Initio Simulation of Magic-Angle-Spinning Dynamic Nuclear Polarization

Theoretical models aimed at describing magic-angle-spinning (MAS) dynamic nuclear polarization (DNP) NMR have great potential in facilitating the in silico design of DNP polarizing agents and formulations. These models must typically face a trade-off between the accuracy of a strict quantum mechanical description and the need for using realistically large spin systems, for instance, using phenomenological models. In this paper, we show that the use of aggressive state-space restrictions and an optimization strategy allows full-scale ab initio MAS-DNP simulations of spin systems containing thousands of nuclei. Our simulations are shown to reproduce experimental DNP enhancements quantitatively, including their MAS rate dependence, for both frozen solutions and solid materials. They also reveal the importance of a previously unrecognized structural feature found in some polarizing agents that helps minimize the sensitivity losses imposed by the spin diffusion barrier.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Interplay of coulomb and exciton–phonon coupling controls singlet fission dynamics in two pentacene polymorphs

Pentacene is an important model organic semiconductor in both the singlet exciton fission (SF) and organic electronics communities. We have investigated the effect of changing crystal structure on the SF process, generating multiple triplet excitons from an initial singlet exciton, and subsequent triplet recombination. Unlike for similar organic semiconductors that have strong SF sensitive to polymorphism, we find almost no quantitative difference between the kinetics of triplet pair (TT) formation in the two dominant polymorphs of pentacene. Both pairwise dimer coupling and momentum-space crystal models predict much faster TT formation from the bright singlet excited state of the Bulk vs ThinFilm polymorph, contrasting with the experiment. GW and Bethe–Salpeter equation calculations, including exciton–phonon coupling, reveal that ultrafast phonon-driven transitions in the ThinFilm polymorph compensate the intrinsically slower purely Coulomb-mediated TT formation channel, rationalizing the similarity in observed rates. Taking into account the influence of subtle structural distinctions on both the direct and phonon-mediated SF pathways reveals a predictive capability to these methods, expected to be applicable to a wide variety of molecular crystals.

14 SOLAR ENERGY↗

The convergence of quadrupole rotational invariants from the nuclear shell model

Nuclei exhibit both single-particle and collective degrees of freedom, with the latter often subdivided into vibrational and rotational motions. Experimentally identifying the relative roles of these collective modes is extremely challenging, particularly in the face of possible shape coexistence. Model-independent, invariant quantities describing the deformation of a nucleus in the intrinsic frame have long been known but their determination potentially requires a large quantity of experimental data to achieve convergence. Through comparison with the nuclear shell model, the question of convergence is addressed. Shell-model calculations performed in the sd- and pf-shell model spaces are used to determine electric-quadrupole matrix elements for a multitude of low-lying states using the first 40 states of the relevant spins. Relative contributions to the rotationally invariant quantities from multiple states can therefore be determined. It is found that, on average, the inclusion of four intermediate states results in the leading-order invariant, $\langle\hat{Q^2}\rangle$, converging to within 10% of its true value and the triaxiality term, cos (3δ), converging to its true value, though some variance remains. Higher-order quantities relating to the softness of the nuclear shape are found to converge more slowly. The convergence of quadrupole rotationally invariant sum rules was quantified in the sd- and pf-shell model spaces and indicates the challenge inherent in a full determination of nuclear shape. The present study is limited to relatively small valence spaces. Finally, larger spaces, such as the rare-earth region, potentially offer faster convergence.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Benchmarking the exponential ansatz for the Holstein model

Polarons are quasiparticles formed as a result of lattice distortions induced by charge carriers. The single-electron Holstein model captures the fundamentals of single polaron physics. We examine the power of the exponential ansatz for the polaron ground-state wavefunction in its coupled cluster, canonical transformation, and (canonically transformed) perturbative variants across the parameter space of the Holstein model. Our benchmark serves to guide future developments of polaron wavefunctions beyond the single-electron Holstein model.

Chemistry↗

Observation of Unprecedented Fractional Magnetization Plateaus in a New Shastry-Sutherland Ising Compound

Geometrically frustrated magnetic systems, such as those based on the Shastry-Sutherland lattice (SSL), offer a rich playground for exploring unconventional magnetic states. The delicate balance between competing interactions in these systems leads to the emergence of novel phases. We present the characterization of Er 2 ⁢Be 2⁢ GeO 7 , an SSL compound with Er 3+ ions forming orthogonal dimers separated by nonmagnetic layers whose structure is invariant under the 𝑃⁢$\bar{4}21$⁢𝑚 space group. Neutron scattering reveals an antiferromagnetic dimer structure at zero field, typical of Ising spins on that lattice and consistent with the anisotropic magnetization observed. However, magnetization measurements exhibit fractional plateaus at 1/4 and 1/2 of saturation, in contrast to the expected 1/3 plateau of the SSL Ising model. By comparing the energy of candidate states with ground-state lower bounds we show that this behavior requires spatially anisotropic interactions, leading to an anisotropic Shastry-Sutherland Ising model symmetric under the 𝐶⁢𝑚⁢𝑚⁢2 space group. This anisotropy is consistent with the small orthorhombic distortion observed with single-crystal neutron diffraction. The other properties, including thermodynamics, which have been investigated theoretically using tensor networks, point to small residual interactions, potentially due to further couplings and quantum fluctuations. This study highlights Er 2 ⁢Be 2 ⁢GeO 7 as a promising platform for investigating exotic magnetic phenomena.

Yadav, Lalit [Duke University, Durham, NC (United ↗

Scale-dependent spatial variabilities of hydrological exchange flows and transit time in a large regulated river

Hydrological exchange flows (HEF) across the river-aquifer interface and the associated residence time of river water in the aquifer have important implications for contaminant plume migration and biogeochemical processes in the river corridor. HEFs and residence time are influenced by both subsurface physical features and hydrologic forcing related to the transport process, which can exhibit complex spatial and temporal variations. In this study, we used a massively parallel subsurface flow model and a particle-tracking model to study the influences of different control factors on spatial variability of HEFs and residence time distributions (RTD) in the Hanford Reach of the Columbia River in Washington State. A total number of 100M particles were randomly injected in time and space and then tracked in a model domain that covers a 51-km 2 area (15.1M model cells). We used hourly river stages and groundwater levels to drive the model to provide dynamic velocity fields for the particle tracking in the simulation period that was longer than 2 years. The groundwater flow simulation and particle-tracking results provide the first comprehensive assessment of the spatial distribution of HEFs and residence time in large complex river corridors. Overall, our results show that the aquifer hydrogeological structure has the strongest correlation with the extent and magnitude of exchange flux. The residence time exhibits complex patterns that are impacted by all the river geomorphologic, hydrodynamic, and hydrogeologic factors and are strongly correlated with the downwelling ratio of exchange flux. The new insights gained through this study can be used to support the development of reduced-order models of HEFs and RTDs for large complex river systems.

54 ENVIRONMENTAL SCIENCES↗

Using Co-Optimized Machine Learned Manifolds for Modeling Chemically Reacting Flows

Chemically reacting flows play a key role in a wide range of engineered systems, from chemical and polymer processing to combustion-based energy conversion technologies. Simulations of these flows involve solving a coupled set of partial differential equations for mass, momentum, energy, and all relevant chemical species in the system. Chemical reaction pathways may be extremely complex and involve hundreds or more intermediate species, with reactions that occur over timescales varying by several orders of magnitude - presenting a significant numerical stiffness challenge. The combination of these factors makes simulation of chemically reacting flows vastly more expensive than nonreactive simulations, and often makes direct solution of the governing equations intractable. It is necessary to apply lower-fidelity models in place of the detailed governing equations in order to reduce computational cost to enable reacting flow simulation tools to be used in the engineering design process. Many of the models employed for this purpose are based on reducing the dimension of the thermochemical state, motivated by the observation that the observed thermochemical states in a system lie on a low-dimensional manifold in thermochemical state space. This behavior occurs due to the fast equilibration of certain reactive and transport processes, and physics-based manifold models rely on idealized assumptions about the balance of timescales and the way in which chemistry and transport are coupled. In this work, we apply a novel method for data-driven manifold-based modeling that can leverage data from high-fidelity reacting flow simulations to improve model accuracy in cases where the physics-based modeling assumptions break down. The approach is designed to be broadly applicable across chemically reacting flow systems but is applied here to turbulent combustion modeling.

machine learning↗

$Ξ$ 𝑏 → $Ξ$ form factors from lattice QCD and standard-model predictions for $Ξ$ 𝑏 → $Ξ$⁢𝜇 + ⁢𝜇 − and $Ξ$ 𝑏 → $Ξ$⁢𝛾 decays

We present the first lattice QCD determination of the $Ξ$ 𝑏 → $Ξ$ vector, axial-vector, and tensor form factors, which are relevant for the theory of rare decays including $Ξ$ 𝑏 → $Ξ$⁢ℓ + ⁢ℓ − and $Ξ$ 𝑏 → $Ξ$⁢𝛾. The calculation is performed with 2+1 flavors of domain-wall fermions at three different lattice spacings and pion masses in the range from approximately 430 to 230 MeV. The bottom quark is implemented using an anisotropic clover action. Three-point functions with a wide range of source-sink separations and model averaging are used to extract the ground-state contributions. We fit the dependence of the form factors on the momentum transfer, the pion mass, and the lattice spacing using modified 𝑧 expansions that account for subthreshold branch cuts, and apply dispersive bounds and asymptotic behavior constraints to achieve controlled uncertainties in the full semileptonic kinematic region. Using our form factor results, we present standard model predictions for the $Ξ$$^{−}_{𝑏}$ → $Ξ$ − ⁢𝛾 and $Ξ$$^{−}_{𝑏}$ → $Ξ$ − ⁢𝜇 + ⁢𝜇 − branching fractions and two angular observables.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Structural Propensities in Cs2MBiX6 (M=Na, Ag; X=Cl, Br) Bismuth Halide Double Perovskites

A previously unreported low-temperature phase transition in the bismuth halide double perovskite Cs2AgBiCl6 is reported, thereby establishing trends in the structural ground state across Cs2NaBiCl6, Cs2AgBiCl6, and Cs2AgBiBr6. Using the combined toolkit of variable-temperature synchrotron X-ray and neutron powder diffraction, Raman spectroscopy, and density-functional theory–based electronic structure modeling, we demonstrate a cubic Fm¯3m → tetragonal I4/m transition upon cooling with distinct onset temperatures. Neutron powder diffraction refinements permit the unambiguously assignment of the low-temperature phase of Cs2NaBiCl6 to I4/m, correcting prior reports of an I4/mmm ground state. Cs2AgBiCl6 is also found to transforms to a structure crystallizing in the I4/m space group at low temperatures. Temperaturedependent Raman data and density-functional theory-based modeling capture the softening and freezing of out-of-phase octahedral-tilt modes and quantify relative instabilities. Solid-state nuclear magnetic resonance spectroscopy at room temperature completes the characterization and helps underpin the subtle differences in covalency across the compounds. Trends in the phase transition temperature Ts and tilt magnitudes emerge from coupled effects of halide identity, M(I)–site bonding character, and a mismatch between interatomic distances. These results establish the structure– dynamics–bonding framework for tuning tilt-driven instabilities in halide double perovskites.

Tian, Haowen↗

Reconstructing the spatial structure of quantum correlations in materials

Quantum correlations are a fundamental property of quantum many-body states. Yet they remain experimentally elusive, hindering certification of genuine quantum behavior, especially in quantum materials. Here we show that the momentum-dependent dynamical susceptibility measured via inelastic neutron scattering enables the systematic reconstruction of a general family of quantum correlation functions, which express the degree of quantum coherence in the fluctuations of two spins at an arbitrary mutual distance. Using neutron scattering data for the compound KCuF 3 —a system of weakly coupled S = 1 / 2 Heisenberg chains—and numerically exact quantum Monte Carlo data, we show that quantum correlations possess a radically different spatial structure with respect to conventional correlations. Indeed, they exhibit a different emergent length scale—the quantum coherence length—which is finite at any finite temperature (including when long-range magnetic order develops). Moreover, we show theoretically that coupled Heisenberg spin chains exhibit a form of quantum monogamy, with a trade-off between quantum correlations along and transverse to the spin chains. These results highlight real-space quantum correlators as an informative, model-independent means of probing the underlying quantum state of real quantum materials. Published by the American Physical Society 2024

36 MATERIALS SCIENCE↗

A probabilistic graphical model foundation for enabling predictive digital twins at scale

A unifying mathematical formulation is needed to move from one-off digital twins built through custom implementations to robust digital twin implementations at scale. This work proposes a probabilistic graphical model as a formal mathematical representation of a digital twin and its associated physical asset. We create an abstraction of the asset–twin system as a set of coupled dynamical systems, evolving over time through their respective state spaces and interacting via observed data and control inputs. The formal definition of this coupled system as a probabilistic graphical model enables us to draw upon well-established theory and methods from Bayesian statistics, dynamical systems and control theory. The declarative and general nature of the proposed digital twin model make it rigorous yet flexible, enabling its application at scale in a diverse range of application areas. Here, we demonstrate how the model is instantiated to enable a structural digital twin of an unmanned aerial vehicle (UAV). The digital twin is calibrated using experimental data from a physical UAV asset. Its use in dynamic decision-making is then illustrated in a synthetic example where the UAV undergoes an in-flight damage event and the digital twin is dynamically updated using sensor data. The graphical model foundation ensures that the digital twin calibration and updating process is principled, unified and able to scale to an entire fleet of digital twins.

42 ENGINEERING↗

Quantifying Value and Representing Competitiveness of Electricity System Technologies in Economic Models

Evaluating competition between electricity technologies is challenging because it depends on both their costs and their values. While technology costs can typically be estimated from projections of the cost components - capital, fuel, and O&M - estimating a technology's value is more complex due to its dependence on its contributions to multiple different grid services, each with prices that can vary substantially over space and time. In this work, using an electricity model of the contiguous United States, we develop relationships between relative value and share of total generation for major electricity generation technologies which, when paired with projections of technology costs, can be used to estimate technology competitiveness. We identify significant differences in the relationship between relative value and generation share for variable renewable energy (VRE) and non-VRE sources, but we demonstrate that all technologies require consideration of their dynamic values (in addition to cost) when evaluating competitiveness. In addition, we demonstrate that relative value of a technology is substantially impacted by not only its own generation share but also other aspects of the system state, in particular the mix of other technologies present in the system. Finally, we use the developed relative value relationships in combination with projections of future technology costs in a coarse resolution model that competes technologies based on a comprehensive competitiveness metric: profitability-adjusted LCOE (PLCOE). We show that this simple representation of technology competition approximately recovers the generation mix from a detailed model, which is not possible using LCOE alone. Such an approach can be used to improve the representation of technology competition in coarse-resolution models such as integrated assessment models, for which simplified metrics are often needed.

electricity model↗