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At least 1,135 records · Page 63

Shape-driven, emergent behavior in active particle mixtures

Abstract Active particle systems can vary greatly from one-component systems of spheres to mixtures of particle shapes at different composition ratios. We investigate computationally the combined effect of anisotropy and stoichiometry on the collective behavior of two-dimensional active colloidal mixtures of polygons. We uncover three emergent phenomena not yet reported in active Brownian particle systems. First, we find that mixtures containing hexagons exhibit micro-phase separation with large grains of hexagonal symmetry. We quantify a measurable, implicit ‘steric attraction’ between the active particles as a result of shape anisotropy and activity. This calculation provides further evidence that implicit interactions in active systems, even without explicit attraction, can lead to an effective preferential attraction between particles. Next, we report stable fluid clusters in mixtures containing one triangle or square component. We attribute the fluidization of the dense cluster to the interplay of cluster destabilizing particles, which introduce grain boundaries and slip planes into the system, causing solid-like clusters to break up into fluid clusters. Third, we show that fluid clusters can coexist with solid clusters within a sparse gas of particles in a steady state of three coexisting phases. Our results highlight the potential for a wide variety of behavior to be accessible to active matter systems and establish a route to control active colloidal systems through simple parameter designs.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Widen the resonance at ultra-high energies: novel probes of neutrino self-interactions in the high-mass regime

Neutrino self-interactions beyond the Standard Model are well motivated by the nonzero masses of neutrinos, which are the only known particles guaranteed to have new physics. Meanwhile, cosmic messengers, especially neutrinos, play a central role in probing new physics, as they provide experimental conditions far beyond the reach of laboratories and serve as the link between laboratory fundamental-physics discoveries and their roles in the Universe, where many new physics motivations originate.In this work, we propose a novel probe of neutrino self-interactions through ultrahigh-energy neutrinos scattering off the cosmic neutrino background when the lightest neutrino species remains relativistic today.This allows us to “Widen the Resonance” of such scattering [1].In addition, we also provide a semi-analytic framework for cosmogenic ultrahigh-energy neutrino production, avoiding computationally intensive simulations and yielding results precise enough for beyond-the-standard-model studies.The widened resonance enables future ultrahigh-energy neutrino telescopes,in particular GRAND, to probe mediator masses from MeV to GeV, reaching couplings down to g ∼ 10$^{-3}$ — up to two orders of magnitude beyond current bounds.Our results enhance the discovery potential of neutrino self-interactions in the high-mass regime, potentially offering crucial insights into the connections between the neutrino sector and dark sector.

Machado, Pedro A.N. [Fermilab] (ORCID:000000029118↗

Data-driven profile prediction for DIII-D

A new, fully data-driven algorithm has been developed that uses neural networks to predict plasma pro les on a scale of τ E into the future given actuators and the present plasma state. The model was trained and tested on DIII-D data from the 2013-2018 experimental campaigns. The model is accurate on average, with q predictions the worst and pressure predictions the best. The model can run in milliseconds and is very simple to use. This makes it a potentially useful tool for operators and physicists when planning plasma scenarios. It also is a candidate for doing phase-space exploration without going through the DIIID database or complicated and computationally expensive simulation codes. Here, a reduced model using only realtime diagnostics has also been developed and formed the basis for a model-predictive control algorithm implemented and successfully tested on DIII-D.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Validation of a synthetic fast ion loss detector model for Wendelstein 7-X

Abstract We present the first validated synthetic diagnostic for fast ion loss detectors (FILDs) in the Wendelstein 7-X (W7-X) stellarator. This model has been developed on, and validated against experimental data from, a FILD provided by the National Institute for Fusion Science (NIFS-FILD), with potential future applicability to the existing Faraday Cup FILD (FC-FILD) on W7-X as well as the scintillating FILD (S-FILD) currently under development. A workflow combining Monte Carlo codes BEAMS3D and ASCOT5 is used to track fast ions produced by neutral beam injection from the moment of ionization until they are thermalized or lost from the last closed flux surface, and from there to a virtual plane which serves as a projection of the entrance aperture to the FILD. Simulations in ASCOT5 are analyzed via a geometric method to determine the probability of transmission through the FILD aperture and onto the detector as a function of normalized momentum, pitch angle, gyrophase, and position at the virtual plane. This probability is then applied to the simulated ions arriving from the plasma, producing a simulated signal from a computationally tractable number of simulated fast ions. Simulated signals are presented for two W7-X experiments with neutral beam injection and quantitatively compared with experimental measurements from the NIFS-FILD diagnostic. An estimate of the frequency of charge-exchange with neutral particles in the edge is performed, and it is found that this process may have a significant impact on the measured signals.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Pandemic drugs at pandemic speed: infrastructure for accelerating COVID-19 drug discovery with hybrid machine learning- and physics-based simulations on high-performance computers

The race to meet the challenges of the global pandemic has served as a reminder that the existing drug discovery process is expensive, inefficient and slow. There is a major bottleneck screening the vast number of potential small molecules to shortlist lead compounds for antiviral drug development. New opportunities to accelerate drug discovery lie at the interface between machine learning methods, in this case, developed for linear accelerators, and physics-based methods. The two in silico methods, each have their own advantages and limitations which, interestingly, complement each other. Here, we present an innovative infrastructural development that combines both approaches to accelerate drug discovery. The scale of the potential resulting workflow is such that it is dependent on supercomputing to achieve extremely high throughput. We have demonstrated the viability of this workflow for the study of inhibitors for four COVID-19 target proteins and our ability to perform the required large-scale calculations to identify lead antiviral compounds through repurposing on a variety of supercomputers.

97 MATHEMATICS AND COMPUTING↗

Signaling and scrambling with strongly long-range interactions

Strongly long-range interacting quantum systems—those with interactions decaying as a power law 1/$r^α$ in the distance $\textit{r}$ on a $\textit{D}$-dimensional lattice for $\textit{α ≤ D}$—have received significant interest in recent years. They are present in leading experimental platforms for quantum computation and simulation, as well as in theoretical models of quantum-information scrambling and fast entanglement creation. Since no notion of locality is expected in such systems, a general understanding of their dynamics is lacking. In a step towards rectifying this problem, we prove two Lieb-Robinson-type bounds that constrain the time for signaling and scrambling in strongly long-range interacting systems, for which no tight bounds were previously known. In this work, our first bound applies to systems mappable to free-particle Hamiltonians with long-range hopping, and is saturable for $\textit{α ≤ D/2}$. Our second bound pertains to generic long-range interacting spin Hamiltonians and gives a tight lower bound for the signaling time to extensive subsets of the system for all $\textit{α < D}$. This many-site signaling time lower bounds the scrambling time in strongly long-range interacting systems.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Spin dynamics of the antiferromagnetic Heisenberg model on a kagome bilayer

We research the spin dynamics of a classical Heisenberg antiferromagnet with nearest-neighbor interactions on a quasi-two-dimensional kagome bilayer. This geometrically frustrated lattice consists of two kagome layers connected by a triangular-lattice linking layer. By combining Monte Carlo with precessional spin dynamics simulations, we compute the dynamical structure factor of the classical spin liquid in the kagome bilayer and investigate the thermal and dilution effects. While the low-frequency and long-wavelength dynamics of the cooperative paramagnetic phase is dominated by spin diffusion, weak magnon excitations persist at higher energies, giving rise to the half-moon pattern in the dynamical structure factor. In the presence of spin vacancies, the dynamical properties of the diluted system can be understood within the two-population picture. The spin diffusion of the “correlated” spin clusters is mainly driven by the zero-energy weather-vane modes, giving rise to an autocorrelation function that decays exponentially with time. On the other hand, the diffusive dynamics of the quasifree “orphan” spins leads to a distinctive longer-time power-law tail in the autocorrelation function. We discuss the implications of our work for the glassy behaviors observed in the archetypal frustrated magnet SrCr 9p Ga 12-9 pO 19 (SCGO).

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Scale-dependent halo bias and the squeezed limit bispectrum in the presence of radiation

Here, we investigate the gravitational effect of large-scale radiation perturbations on small-scale structure formation. In addition to making the growth of matter perturbations scale dependent, the free streaming of radiation also affects the coupling between structure formation at small and large scales. We study this using separate universe N -body simulations to compute the (isotropized) squeezed limit matter bispectrum and the linear halo bias. Our results show that the scale dependence in the growth of long-wavelength matter perturbations, caused by radiation, translates into these quantities acquiring a nontrivial scale dependence at k ≲ 0.05 Mpc -1 . In a universe with radiation composed of cosmic microwave background photons and three species of massless neutrinos, the bias of halos with b = 2 at high k will decrease by 0.29%, 0.45%, and 0.8% between k = 0.05 Mpc -1 and k = 0.0005 Mpc -1 at redshifts z = 0, 1, and 3, respectively. For objects with b >> 1 , these differences approach 0.43%, 0.68%, and 1.2%, respectively.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Advection algorithms for quantum neutrino moment transport

Neutrino transport in compact objects is an inherently challenging multidimensional problem. Here, this difficulty is compounded if one includes flavor transformation—an intrinsically quantum phenomenon requiring one to follow the coherence between flavors and thus necessitating the introduction of complex numbers. To reduce the computational burden, simulations of compact objects that include neutrino transport often make use of momentum-angle-integrated moments (the lowest order ones being commonly referred to as the energy density and flux) and these quantities can be generalized to include neutrino flavor, i.e., they become quantum moments. Numerous finite-volume approaches to solving the moment evolution equations for classical neutrino transport have been developed based on solving a Riemann problem at cell interfaces. In this paper we describe our generalization of a Riemann solver for quantum moments, specifically decomposing complex numbers in terms of a (signed) magnitude and phase instead of real and imaginary parts. We then test our new algorithm in numerous cases showing a neutrino fast flavor instability, varying from toy models with analytic solutions to snapshots from neutron star merger simulations. Compared to previous algorithms for neutrino transport with flavor mixing, we find uniformly smaller growth rates of the flavor transformation along with concomitantly larger length-scales, and that the results are a better match with the growth rates seen from multiangle codes.

79 ASTRONOMY AND ASTROPHYSICS↗

Anharmonicity and Phase Diagram of Magnesium Oxide in the Megabar Regime

With density functional molecular dynamics simulations, we computed the phase diagram of MgO from 50 to 2000 GPa up to 20000 K. Via thermodynamic integration (TDI), we derive the Gibbs free energies of the B1, B2, and liquid phases and determine their phase boundaries. With TDI and a pseudo-quasi-harmonic approach, we show that anharmonic effects are important and stabilize the B1 phase in particular. As a result, the B1-B2 transition boundary in the pressure-temperature plane exhibits a steep slope. We predict the B1-B2-liquid triple point to occur at approximately T= 10000 K and P = 370 GPa, which is higher in pressure than was inferred with quasi-harmonic methods alone. We predict the principal shock Hugoniot curve to enter the B2 phase stability domain but only over a very small range of parameters. Here, this may render it difficult to observe this phase with shock experiments because of kinetic effects.

3-dimensional systems↗

Radial Two-Dimensional Ion Crystals in a Linear Paul Trap

We experimentally study two-dimensional (2D) Coulomb crystals in the “radial-2D” phase of a linear Paul trap. This phase is identified by a 2D ion lattice aligned entirely with the radial plane and is created by imposing a large ratio of axial to radial trapping potentials. Using arrays of up to 19 171 Yb + ions, we demonstrate that the structural phase boundaries of such crystals are well described by the pseudopotential approximation, despite the time-dependent ion positions driven by intrinsic micromotion. We further observe that micromotion-induced heating of the radial-2D crystal is confined to the radial plane. Finally, we verify that the transverse motional modes, which are used in most ion-trap quantum simulation schemes, are well-predictable numerically and remain decoupled and cold in this geometry. Our results establish radial-2D ion crystals as a robust experimental platform for realizing a variety of theoretical proposals in quantum simulation and computation.

74 ATOMIC AND MOLECULAR PHYSICS↗

Monolayer CrCl 3 as an Ideal Test Bed for the Universality Classes of 2D Magnetism

The monolayer halides CrX 3 (X=Cl, Br, I) attract significant attention for realizing 2D magnets with genuine long-range order (LRO), challenging the Mermin-Wagner theorem. In this work, we show that monolayer CrCl 3 has the unique benefit of exhibiting tunable magnetic anisotropy upon applying a compressive strain. This opens the possibility to use CrCl 3 for producing and studying both ferromagnetic and antiferromagnetic 2D Ising-type LRO as well as the Berezinskii-Kosterlitz-Thouless (BKT) regime of 2D magnetism with quasi-LRO. Using state-of-the-art density functional theory, we explain how realistic compressive strain could be used to tune the monolayer's magnetic properties so that it could exhibit any of these phases. Building on large-scale quantum Monte Carlo simulations, we compute the phase diagram of strained CrCl 3 , as well as the magnon spectrum with spin-wave theory. Our results highlight the eminent suitability of monolayer CrCl 3 to achieve very high BKT transition temperatures, around 50 K, due to their singular dependence on the weak easy-plane anisotropy of the material.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Circuit Quantum Electrodynamics in Hyperbolic Space: From Photon Bound States to Frustrated Spin Models

Circuit quantum electrodynamics is one of the most promising platforms for efficient quantum simulation and computation. In recent groundbreaking experiments, the immense flexibility of superconducting microwave resonators was utilized to realize hyperbolic lattices that emulate quantum physics in negatively curved space. Here we investigate experimentally feasible settings in which a few superconducting qubits are coupled to a bath of photons evolving on the hyperbolic lattice. We compare our numerical results for finite lattices with analytical results for continuous hyperbolic space on the Poincaré disk. We find good agreement between the two descriptions in the long-wavelength regime. We show that photon-qubit bound states have a curvature-limited size. We propose to use a qubit as a local probe of the hyperbolic bath, for example, by measuring the relaxation dynamics of the qubit. We find that, although the boundary effects strongly impact the photonic density of states, the spectral density is well described by the continuum theory. We show that interactions between qubits are mediated by photons propagating along geodesics. We demonstrate that the photonic bath can give rise to geometrically frustrated hyperbolic quantum spin models with finite-range or exponentially decaying interaction.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Prediction of defect properties in concentrated solid solutions using a Langmuir-like model

The alleged existence of sluggish diffusion in high-entropy alloys has drawn controversy. In high-entropy alloys and, in general, in all solids, transport properties are controlled by point defect concentration, which must be known before performing atomistic simulations to compute transport coefficients. In this work, we present a general Langmuir-like model for defect concentration in an arbitrarily complex solid solution and apply this model to generate expressions for concentrations of vacancies and small interstitial atoms. We then calculate the vacancy concentration as a function of temperature in the equiatomic CoNiCrFeMn and FeAl alloys with modified embedded-atom-method potentials for various chemical orderings, showing there is no clear correlation between vacancy thermodynamics and chemical ordering in the CoNiCrFeMn alloy, but clear systematic patterns for FeAl. We believe this is due to the high stability of disordered, random, and ordered intermetallic phases, respectively, in the CoNiCrFeMn and FeAl systems. Finally, this work provides future avenues to the prediction of thermal interstitials and vacancies in solid solutions, which is necessary for models of nonequilibrium behavior of solid solutions.

composition↗

Raman Sideband Cooling of Molecules in an Optical Tweezer Array to the 3D Motional Ground State

Ultracold polar molecules are promising for quantum information processing and searches for physics beyond the standard model. Laser cooling to ultracold temperatures is an established technique for trapped diatomic and triatomic molecules. Further cooling of the molecules to near the motional ground state is crucial for reducing various dephasings in quantum and precision applications. In this work, we demonstrate Raman sideband cooling (RSC) of CaF molecules in optical tweezers to near their motional ground state, with average motional occupation quantum numbers of n ¯ x = 0.16 ( 12 ) , n ¯ y = 0.17 ( 17 ) (radial directions), and n ¯ z = 0.22 ( 16 ) (axial direction), and a 3-D motional-ground-state probability of 54 ± 18 % of the molecules that survive the RSC. This process paves the way to increase molecular coherence times in optical tweezers for robust quantum computation and simulation applications. Published by the American Physical Society 2024

Physics↗

Many-Body Physics in the NISQ Era: Quantum Programming a Discrete Time Crystal

Recent progress in the realm of noisy intermediate-scale quantum (NISQ) devices represents an exciting opportunity for many-body physics by introducing new laboratory platforms with unprecedented control and measurement capabilities. We explore the implications of NISQ platforms for many-body physics in a practical sense: we ask which physical phenomena, in the domain of quantum statistical mechanics, they may realize more readily than traditional experimental platforms. While a universal quantum computer can simulate any system, the eponymous noise inherent to NISQ devices practically favors certain simulation tasks over others in the near term. As a particularly well-suited target, we identify discrete time crystals (DTCs), novel nonequilibrium states of matter that break time translation symmetry. These can only be realized in the intrinsically out-of-equilibrium setting of periodically driven quantum systems stabilized by disorder-induced many-body localization. While promising precursors of the DTC have been observed across a variety of experimental platforms—ranging from trapped ions to nitrogen-vacancy centers to NMR crystals—none have all the necessary ingredients for realizing a fully fledged incarnation of this phase, and for detecting its signature long-range spatiotemporal order. We show that a new generation of quantum simulators can be programmed to realize the DTC phase and to experimentally detect its dynamical properties, a task requiring extensive capabilities for programmability, initialization, and readout. Specifically, the architecture of Google’s Sycamore processor is a remarkably close match for the task at hand. We also discuss the effects of environmental decoherence, and how they can be distinguished from ‘internal’ decoherence coming from closed-system thermalization dynamics. Already with existing technology and noise levels, we find that DTC spatiotemporal order would be observable over hundreds of periods, with parametric improvements to come as the hardware advances.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Hybrid Approaches for Data Reduction of Spatiotemporal Scientific Applications

Scientists conduct large-scale simulations to compute derived quantities from primary data. Thus, it is crucial that data compression techniques maintain bounded errors on these derived quantities or quantities of interest (QOI). For many spatiotemporal applications, these QOIs are binary in nature and represent presence or absence of a physical phenomenon. In this work, we propose to use a hybrid approah for differential compression for such applications. We use a neural network (NN) approach to determine regions-of-interest (ROIs) where the binary QOIs are going to be prevalent. This is then used with traditional approaches that compress at a lower level (and higher accuracy) for these ROIs as compared to other regions.

Li, Xiao↗