Classical Simulations Research Articles

Accelerated quantum circuit Monte Carlo simulation for heavy quark thermalization

Thermalization of heavy quarks in the quark-gluon plasma is one of the most promising phenomena for understanding the strong interaction. The energy loss and momentum broadening at low momentum can be well described by a stochastic process with drag and diffusion terms. Recent advances in quantum computing, in particular, quantum amplitude estimation (QAE), promise to provide a quadratic speedup in simulating stochastic processes. We introduce and formalize an accelerated quantum circuit Monte Carlo (aQCMC) framework to simulate heavy quark thermalization. With simplified drag and diffusion coefficients connected by Einstein’s relation, we simulate the thermalization of a heavy quark in isotropic and anisotropic mediums using an ideal quantum simulator and compare that to thermal expectations. With Grover-like QAE, we calculate physical observables with quadratically fewer resources, which is a boost over the classical MC simulation that usually requires a large sampling number at the same estimation accuracy. Published by the American Physical Society 2024

Ternary Solid Polymer Electrolytes at the Electrochemical Interface: A Computational Study.

Polymer-based solid-like gel electrolytes have emerged as a promising alternative to improve battery performance. However, there is a scarcity of studies on the behavior of these media at the electrochemical interface. In this work, we report classical MD simulations of ternary polymer electrolytes composed of poly(ethylene oxide), a lithium salt [lithium bis(trifluoromethanesulfonyl)imide], and different ionic liquids [1-butyl-1-methylpyrrolidinium bis(trifluoromethanesulfonyl)imide and 1-ethyl-3-methylimidazolium bis(trifluoromethanesulfonyl)imide] confined between two charged and uncharged graphene-like surfaces. The molecular solvation of Li+ ions and their diffusion as well as the polymer conformational picture were characterized in terms of the radial distribution functions, coordination numbers, number density profiles, orientations, displacement variance, polymer radius of gyration, and polymer end-to-end distance. Our results show that the layering behavior of the ternary electrolyte in the interfacial region leads to a decrease of Li+ mobility in the direction perpendicular to the electrodes and high energy barriers that hinder lithium cations from coming into direct contact with the graphene-like surface. The nature of the ionic liquid and its concentration were found to influence the structural and dynamic properties at the electrode/electrolyte interface, the electrolyte with low amounts of the pyrrolidinium-based ionic liquid being that with the best performance since it favors the migration of Li+ cations toward the negative electrode when compared to the imidazolium-based one.

Molecular dynamics simulations for the prediction of thermophysical properties of plutonium-based molten salts

Molten salt nuclear reactors are promising technologies for sustainable energy sources. In this context, understanding the physicochemical properties of molten salts is essential to the development, usage, and maintenance of reactors. Classical molecular simulations allow estimating the macroscopic properties of molten salts at a relatively low computational cost. In this work, we develop a new force field for plutonium-based molten salts. We validate our classical model by comparing molecular dynamics results with experimental measurements, obtaining a quantitative agreement. Our work demonstrates the reliability and transferability of classical force fields to represent the physicochemical properties of molten salts.

Estimating Posterior Sensitivities with Application to Structural Analysis of Bayesian Vector Autoregressions

The inherent feature of Bayesian empirical analysis is the dependence of posterior inference on prior parameters, which researchers typically specify. However, quantifying the magnitude of this dependence remains difficult. This article extends Infinitesimal Perturbation Analysis, widely used in classical simulation, to compute asymptotically unbiased and consistent sensitivities of posterior statistics with respect to prior parameters from Markov chain Monte Carlo inference via Gibbs sampling. The method demonstrates the possibility of efficiently computing the complete set of prior sensitivities for a wide range of posterior statistics, alongside the estimation algorithm using Automatic Differentiation. The method’s application is exemplified in Bayesian Vector Autoregression analysis of fiscal policy in U.S. macroeconomic time series data. The analysis assesses the sensitivities of posterior estimates, including the Impulse response functions and Forecast error variance decompositions, to prior parameters under common Minnesota shrinkage priors. The findings illuminate the significant and intricate influence of prior specification on the posterior distribution. This effect is particularly notable in crucial posterior statistics, such as the substantial absolute eigenvalue of the companion matrix, ultimately shaping the structural analysis.

Scalable Circuits for Preparing Ground States on Digital Quantum Computers: The Schwinger Model Vacuum on 100 Qubits

The vacuum of the lattice Schwinger model is prepared on up to 100 qubits of IBM’s Eagle-processor quantum computers. A new algorithm to prepare the ground state of a gapped translationally invariant system on a quantum computer is presented, which we call “scalable circuits ADAPT-VQE” (SC-ADAPT-VQE). This algorithm uses the exponential decay of correlations between distant regions of the ground state, together with ADAPT-VQE, to construct quantum circuits for state preparation that can be scaled to arbitrarily large systems. These scalable circuits can be determined with use of classical computers, avoiding the challenging task of optimizing parameterized circuits on a quantum computer. SC-ADAPT-VQE is applied to the Schwinger model, and is shown to be systematically improvable, with an accuracy that converges exponentially with circuit depth. Both the structure of the circuits and the deviations of prepared wave functions are found to become independent of the number of spatial sites, L. This allows a controlled extrapolation of the circuits, determined with use of small or modest-sized systems, to arbitrarily large L. The circuits for the Schwinger model are determined on lattices up to L=14 (28 qubits) with the Qiskit classical simulator, and are subsequently scaled up to prepare the L=50 (100 qubits) vacuum on IBM’s 127-superconducting-qubit quantum computers ibm_brisbane and ibm_cusco. After introduction of an improved error-mitigation technique, which we call “operator decoherence renormalization”, the chiral condensate and charge-charge correlators obtained from the quantum computers are found to be in good agreement with classical matrix product state simulations. Published by the American Physical Society 2024

Quantum dynamics of a fully blockaded Rydberg atom ensemble

Classical simulation of quantum systems plays an important role in the study of many-body phenomena and in the benchmarking and verification of quantum technologies. Exact simulation is often limited to small systems because the dimension of the Hilbert space increases exponentially with the size of the system. For systems that possess a high degree of symmetry, however, classical simulation can reach much larger sizes. Here we consider an ensemble of strongly interacting atoms with permutation symmetry, enabling the computation of certain collective observables for hundreds of atoms at arbitrarily long evolution times. The system is realized by an ensemble of three-level atoms, where one of the levels corresponds to a highly excited Rydberg state. In the limit of all-to-all Rydberg blockade, the Hamiltonian is invariant under permutation of the atoms. Using techniques from representation theory, we construct a block-diagonal form of the Hamiltonian, where the size of the largest block increases only linearly with the system size. We apply this formalism to derive efficient pulse sequences to prepare arbitrary permutation-invariant quantum states. Moreover, we study the quantum dynamics following a quench, uncovering a parameter regime in which the system thermalizes slowly and exhibits pronounced revivals. Our results create opportunities for the experimental and theoretical study of large interacting and nonintegrable quantum systems. Published by the American Physical Society 2024

SQUWALS: A Szegedy QUantum WALks Simulator

AbstractSzegedy's quantum walk is an algorithm for quantizing a general Markov chain. It has plenty of applications, such as many variants of optimizations. In order to check its properties in an error‐free environment, it is important to have a classical simulator. However, the current simulation algorithms require a great deal of memory due to the particular formulation of this quantum walk. In this paper, a memory‐saving algorithm is proposed that scales as with the size of the graph. Additional procedures are provided for simulating Szegedy's quantum walk over mixed states and also the Semiclassical Szegedy walk. With these techniques, a classical simulator in Python called SQUWALS (Szegedy QUantum WALks Simulator) has been built. It is shown that the simulator scales as in both time and memory resources. This package provides some high‐level applications for algorithms based on Szegedy's quantum walk, as for example the quantum PageRank.

Extreme terahertz magnon multiplication induced by resonant magnetic pulse pairs

Nonlinear interactions of spin-waves and their quanta, magnons, have emerged as prominent candidates for interference-based technology, ranging from quantum transduction to antiferromagnetic spintronics. Yet magnon multiplication in the terahertz (THz) spectral region represents a major challenge. Intense, resonant magnetic fields from THz pulse-pairs with controllable phases and amplitudes enable high order THz magnon multiplication, distinct from non-resonant nonlinearities such as the high harmonic generation by below-band gap electric fields. Here, we demonstrate exceptionally high-order THz nonlinear magnonics. It manifests as 7th-order spin-wave-mixing and 6th harmonic magnon generation in an antiferromagnetic orthoferrite. We use THz two-dimensional coherent spectroscopy to achieve high-sensitivity detection of nonlinear magnon interactions up to six-magnon quanta in strongly-driven many-magnon correlated states. The high-order magnon multiplication, supported by classical and quantum spin simulations, elucidates the significance of four-fold magnetic anisotropy and Dzyaloshinskii-Moriya symmetry breaking. Moreover, our results shed light on the potential quantum fluctuation properties inherent in nonlinear magnons.

Two-Dimensional Projected-Momentum Covariance Mapping for Coulomb Explosion Imaging.

We introduce projected-momentum covariance mapping, an extension of recoil-frame covariance mapping for 2D ion imaging studies. By considering the two-dimensional projection of the ion momenta as recorded by the detector, one opens the door to a complex suite of analysis tools adapted from three-dimensional momentum imaging studies. This includes the use of different frames of reference to unravel the dynamics of fragmentation and the application of fragment momentum constraints to isolate specific fragmentation channels. The technique is demonstrated on data from a two-dimensional ion imaging study of the Coulomb explosion of the cis and trans isomers of 1,2-dichloroethene, following strong-field ionization by an intense near-infrared femtosecond laser pulse. Classical simulations are used to guide the interpretation of projected-momentum covariance maps. The results offer a detailed insight into the distinct Coulomb explosion dynamics for this pair of isomers and lay the groundwork for future time-resolved studies of photoisomerization dynamics in this molecular system.

Brain-inspired spiking neural networks in Engineering Mechanics: a new physics-based self-learning framework for sustainable Finite Element analysis

AbstractThe present study aims to develop a sustainable framework employing brain-inspired neural networks for solving boundary value problems in Engineering Mechanics. Spiking neural networks, known as the third generation of artificial neural networks, are proposed for physics-based artificial intelligence. Accompanied by a new pseudo-explicit integration scheme based on spiking recurrent neural networks leading to a spike-based pseudo explicit integration scheme, the underlying differential equations are solved with a physics-informed strategy. We propose additionally a third-generation spike-based Legendre Memory Unit that handles large sequences. These third-generation networks can be implemented on the coming-of-age neuromorphic hardware resulting in less energy and memory consumption. The proposed framework, although implicit, is viewed as a pseudo-explicit scheme since it requires almost no or fewer online training steps to achieve a converged solution even for unseen loading sequences. The proposed framework is deployed in a Finite Element solver for plate structures undergoing cyclic loading and a Xylo-Av2 SynSense neuromorphic chip is used to assess its energy performance. An acceleration of more than 40% when compared to classical Finite Element Method simulations and the capability of online training is observed. We also see a reduction in energy consumption down to the thousandth order.

Experimental post-selection loophole-free time-bin and energy-time nonlocality with integrated photonics

Time-bin (TB) and energy-time (ET) entanglements are crucial resources for long-distance quantum information processing. However, their standard implementations suffer from the so-called post-selection loophole that allows for classical simulation and thus prevents quantum advantage. The post-selection loophole has been addressed in proof-of-principle experiments. An open problem though is to close it in real-life applications based on integrated technologies. This is especially important since, so far, all integrated sources of TB and ET entanglements suffer from the post-selection loophole. Here, we report post-selection loophole-free certification of TB or ET entanglement in integrated technologies, by implementing in a silicon nitride chip the “hug” scheme [Phys. Rev. Lett. 102, 040401 (2009)PRLTAO0031-900710.1103/PhysRevLett.102.040401] and certifying genuine TB entanglement through the violation of a Bell inequality.

Digging into the friction reduction mechanism of organic friction modifiers on steel surfaces: Chains packing vs. molecule–metal interactions

We present a study of five commercially available Organic Friction Modifiers (OFMs) that combines micro-Infrared reflection absorption spectroscopy (IRRAS), classical MD, and DFT/DFT-MD computational methods. We investigate the relation between the molecular structure of the OFMs and their temperature-dependent friction performance. Classical dynamics simulations show that at low temperatures, the OFM molecules, arranged in self-assembled monolayers, undergo collective torsional motion during a friction event. This becomes progressively easier as temperature increases, resulting in lower friction coefficients, until a temperature where these collective motions cannot be maintained anymore, leading to an increase of the friction coefficient. Static DFT calculations indicate that the strength of the packing between OFM molecules determines the friction performance. The temperature at which the collective behavior fails coincides with the temperature at which the packing-free energy is found to diminish.

Microscopic self-dynamics in liquid Ne-D_{2} mixtures: Quantum features and itinerant oscillators reexamined.

In this paper, we report the results of a centroid molecular dynamics (CMD) study of the canonical velocity autocorrelation functions (VACFs) in liquid Ne-D_{2} mixtures at a temperature of T=30K and in the full D_{2}-concentration range (0%≤x_{D_{2}}≤100%). This binary system was selected because of its moderate, although sizable, quantum effects which, as far as its equilibrium properties are concerned, are fully described by the path integral Monte Carlo (PIMC) simulations that have been also implemented. A comprehensive test of the VACF spectral moments carried out using three physical quantities (namely, mean kinetic energy, Einstein frequency, and mean-squared force) obtained from PIMC was performed revealing the potentialities, as well as the limitations, of the CMD approach to the single-particle dynamics in these low-T liquid mixtures. Additional physical information was extracted from the canonical VACFs by fitting their spectra via two distinct methods: the Levesque-Verlet model (LV, very flexible but highly heuristic) and the itinerant oscillator model (IO, based on the physical ground of a single particle rattling inside a short-lived diffusing pseudocage). Both provided good fits of the CMD outputs, with LV being always more adequate than IO in the case of the Ne VACFs, while, as for the D_{2} VACFs, the LV superiority is evident only at high x_{D_{2}} values. However, a peculiar and systematic effect was found after analyzing the IO-fitted parameters: the estimated pseudocage masses turned out to be at least one order of magnitude lower than the corresponding values inferred from the PIMC simulations. This outcome concerns both the Ne and the D_{2} rattling molecule and, as we also discovered, had already been observed (but promptly forgotten) in purely classical simulations of liquid Ar. The possible physical origins of this finding have been finally discussed in some detail, also in connection with the result of the more recent exponential expansion theory (EET), which manages to shed more light on the concept of single particles rattling inside short-lived pseudocages, ultimately demonstrating its untenability.

Quantum simulations for strong-field QED

Quantum field theory in the presence of strong background fields contains interesting problems where quantum computers may someday provide a valuable computational resource. In the noisy intermediate-scale quantum era it is useful to consider simpler benchmark problems in order to develop feasible approaches, identify critical limitations of current hardware, and build new simulation tools. Here we perform quantum simulations of strong-field QED (SFQED) in 3+1 dimensions, using real-time nonlinear Breit-Wheeler pair production as a prototypical process. The strong-field QED Hamiltonian is derived and truncated in the Furry-Volkov mode expansion, and the interactions relevant for Breit-Wheeler are transformed into a quantum circuit. Quantum simulations of a “null double slit” experiment are found to agree well with classical simulations following the application of various error mitigation strategies, including an asymmetric depolarization algorithm which we develop and adapt to the case of Trotterization with a time-dependent Hamiltonian. We also discuss longer-term goals for the quantum simulation of SFQED. Published by the American Physical Society 2024

Conserved energy–momentum tensor for real-time lattice simulations

We derive an expression for the energy–momentum tensor in the discrete lattice formulation of pure glue QCD. The resulting expression satisfies the continuity equation for energy conservation up to numerical errors with a symmetric procedure for the time discretization. In the case of the momentum conservation equation, we obtain an expression that is of higher accuracy in lattice spacing (O(a2)\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${\\mathcal {O}}(a^2)$$\\end{document}) than the naive discretization where fields in the continuum expressions are replaced by discretized counterparts. The improvements are verified by performing numerical tests on the derived expressions using classical real-time lattice gauge theory simulations. We demonstrate substantial reductions in relative error of one to several orders of magnitude compared to a naive discretization for both energy and momentum conservation equations. We expect our formulation to have applications in the area of pre-equilibrium dynamics in ultrarelativistic heavy ion collisions, in particular for the extraction of transport coefficients such as shear viscosity.

Probability density evolution method based stochastic simulation of near-fault pulse-like ground motions

Quantifying the near-fault effect and establishing a reasonable model of near-fault pulse-like ground motions are particularly important for seismic design of structures in near-fault regions. Given the pronounced randomness associated with earthquakes, this study first proposes a novel stochastic model of near-fault pulse-like ground motions by combining the improved finite-fault model (IFFM) and the multivariate copula-based velocity-pulse model (CVPM). Further, a probability density evolution method (PDEM) based stochastic simulation method is developed, by which the model parameters can be determined in a unified probability space so as to ensure the consistency of two independent models. For illustrative purposes, the observed records collected from the 1999 Chi-Chi earthquake are used to generate new stochastic ground motions set. Two ground motions sets based on classical stochastic simulation methods are also presented for comparison. Numerical results show that the proposed method for stochastic simulation of near-fault pulse-like ground motions is reliable; the statistics of peak ground accelerations and spectral characteristics of simulated samples are consistent with station records. Besides, the proposed method accommodates the noteworthy randomness and proportion consistency of components associated with near-fault pulse-like ground motions, making it suitable for the stochastic response and reliability analysis of seismic structures in near-fault regions. This superiority is challenging to classical stochastic simulation methods that lack reasonable consideration of randomness and correlation associated with model parameters.

Quantum dueling: an efficient solution for combinatorial optimization

In this paper, we present a new algorithm for generic combinatorial optimization, which we term quantum dueling. Traditionally, potential solutions to the given optimization problems were encoded in a ‘register’ of qubits. Various techniques are used to increase the probability of finding the best solution upon measurement. Quantum dueling innovates by integrating an additional qubit register, effectively creating a ‘dueling’ scenario where two sets of solutions compete. This dual-register setup allows for a dynamic amplification process: in each iteration, one register is designated as the ‘opponent,’ against which the other register’s more favorable solutions are enhanced through a controlled quantum search. This iterative process gradually steers the quantum state within both registers toward the optimal solution. With a quantitative contraction for the evolution of the state vector, classical simulation under a broad range of scenarios and hyper-parameter selection schemes shows that a quadratic speedup is achieved, which is further tested in more real-world situations. In addition, quantum dueling can be generalized to incorporate arbitrary quantum search techniques and as a quantum subroutine within a higher-level algorithm. Our work demonstrates that increasing the number of qubits allows the development of previously unthought-of algorithms, paving the way for advancement of efficient quantum algorithm design.

On the Brownian motion of a colloid trapped in optical tweezers: Experiments and simulations

The trapping potential induced by the interaction of a highly focused laser light with a spherical dielectric particle can be accurately approximated by a parabolic potential. In this work, we revisit experimental and numerical methodologies used to characterize the Brownian motion of a colloidal particle under the influence of a simple harmonic potential produced by optical tweezers. A classic Brownian dynamics simulation is used to model the experimental results, focusing on statistical properties that can be measured by direct visualization of the system using videomicroscopy. This work represents a useful insight into the underlying physics behind the optical tweezers technique, also giving guidelines regarding programming protocols and experimental analysis methodologies, that may be of help for students working with such techniques, as well as for professors teaching undergraduate advanced optics courses.

Mechanical behavior of Ni/Ti bilayer-based shape memory alloys: Endorsement via atomistic simulations

To gain a structural and thermodynamic understanding along with the interpretation of atomic diffusion in a Ni/Ti bilayer, detailed first-principles simulations using density functional theory (DFT) and molecular dynamics (MD) simulations have been carried out. The interface energies and electronic structure of the Ni/Ti bilayer have been calculated using DFT. The MD simulations of interface atomic diffusion in the Ni/Ti bilayer were performed at 773 K for different annealing times to investigate the formation of Ni–Ti alloy. The simulated results indicate that Ni atoms predominantly diffuse into the Ti side. The radial distribution functions (RDFs) have been plotted to understand the nature of bonding that exists between the Ni and Ti atoms in the bilayer. The shape of the RDFs reveals information about the extent to which Ni and Ti atoms mix together. Classical MD simulations have been used to simulate the deformation behavior of the material under tension and to investigate the effects of annealing time on the mechanical properties of the materials.

Green Enzymatic Synthesis of Geranyl Butyrate: Process Optimization and Mechanistic Insights.

Flavor esters are organic compounds widely used in the food industry to enhance the aroma and taste of products. However, most chemical processes for the production of these flavoring compounds use toxic organic solvents. Some organic solvents derived from petroleum can leave behind residual traces in food products, which may raise concerns about potential health risks and contamination. In this study, we employ Eversa Transform 2.0, a commercial lipase derived from the lipase from Thermomyces lanuginosus, to produce geranyl butyrate in aqueous media. The chemical process was optimized using the Taguchi method, and a conversion of 93% was obtained at the optimal reaction conditions of: 1:5 molar ratio (v/v), 15% biocatalyst load (w/w), at 50 °C, in 6 h. Classic (molecular dynamics) and quantum (density functional theory) simulations unveiled amino acid residues involved in the stabilization of the enzyme-substrate complex. Detailed QM/MM mechanistic studies identified the nucleophilic attack of the deacylation reaction as the rate-limiting step of the entire mechanism, which has a free energy barrier of 14.0 kcal/mol.