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We investigate hysteresis in a generalized Kuramoto model with identical oscillators, focusing on coupling strength inhomogeneity, which results in oscillators being coupled to others with varying strength, and a simplified, more realistic coupling function. With the more realistic coupling function and the coupling strength inhomogeneity, each oscillator acquires an effective intrinsic frequency proportional to its individual coupling strength. This is analogous to the positive coupling strength-frequency correlation introduced explicitly or implicitly in some previous models with nonidentical oscillators that show explosive synchronization and hysteresis. Through numerical simulations and analysis using truncated Gaussian, uniform, and truncated power-law coupling strength distributions, we observe that the system can exhibit abrupt phase transitions and hysteresis. The distribution of coupling strengths significantly affects the hysteresis regions within the parameter space of the coupling function. Additionally, numerical simulations of models with weighted networks including a brain network confirm the existence of hysteresis due to the realistic coupling function and coupling strength inhomogeneity, suggesting the broad applicability of our findings to complex real-world systems., Comment: 19 pages, 8 figures

We present measurements on Fe$_2$O$_3$ amorphization and melt under laser-driven shock compression up to 209(10) GPa via time-resolved in situ x-ray diffraction. At 122(3) GPa, a diffuse signal is observed indicating the presence of a non-crystalline phase. Structure factors have been extracted up to 182(6) GPa showing the presence of two well-defined peaks. A rapid change in the intensity ratio of the two peaks is identified between 145(10) and 151(10) GPa, indicative of a phase change. Present DFT+$U$ calculations of temperatures along Fe$_2$O$_3$ Hugoniot are in agreement with SESAME 7440 and indicate relatively low temperatures, below 2000 K, up to 150 GPa. The non-crystalline diffuse scattering is thus consistent with the - as yet unreported - shock amorphization of Fe$_2$O$_3$ between 122(3) and 145(10) GPa, followed by an amorphous-to-liquid transition above 151(10) GPa. Upon release, a non-crystalline phase is observed alongside crystalline $\alpha$-Fe$_2$O$_3$. The extracted structure factor and pair distribution function of this release phase resemble those reported for Fe$_2$O$_3$ melt at ambient pressure., Comment: 11 pages, 4 figures, under review

In this paper, we address the problem of cost-sensitive multi-fidelity Bayesian Optimization (BO) for efficient hyperparameter optimization (HPO). Specifically, we assume a scenario where users want to early-stop the BO when the performance improvement is not satisfactory with respect to the required computational cost. Motivated by this scenario, we introduce utility, which is a function predefined by each user and describes the trade-off between cost and performance of BO. This utility function, combined with our novel acquisition function and stopping criterion, allows us to dynamically choose for each BO step the best configuration that we expect to maximally improve the utility in future, and also automatically stop the BO around the maximum utility. Further, we improve the sample efficiency of existing learning curve (LC) extrapolation methods with transfer learning, while successfully capturing the correlations between different configurations to develop a sensible surrogate function for multi-fidelity BO. We validate our algorithm on various LC datasets and found it outperform all the previous multi-fidelity BO and transfer-BO baselines we consider, achieving significantly better trade-off between cost and performance of BO.

Analog Compute-in-Memory (CiM) accelerators use analog-digital converters (ADCs) to read the analog values that they compute. ADCs can consume significant energy and area, so architecture-level ADC decisions such as ADC resolution or number of ADCs can significantly impact overall CiM accelerator energy and area. Therefore, modeling how architecture-level decisions affect ADC energy and area is critical for performing architecture-level design space exploration of CiM accelerators. This work presents an open-source architecture-level model to estimate ADC energy and area. To enable fast design space exploration, the model uses only architecture-level attributes while abstracting circuit-level details. Our model enables researchers to quickly and easily model key architecture-level tradeoffs in accelerators that use ADCs.

Shock-bubble interactions (SBI) are important across a wide range of physical systems. In inertial confinement fusion, interactions between laser-driven shocks and micro-voids in both ablators and foam targets generate instabilities that are a major obstacle in achieving ignition. Experiments imaging the collapse of such voids at high energy densities (HED) are constrained by spatial and temporal resolution, making simulations a vital tool in understanding these systems. In this study, we benchmark several radiation and thermal transport models in the xRAGE hydrodynamic code against experimental images of a collapsing mesoscale void during the passage of a 300 GPa shock. We also quantitatively examine the role of transport physics in the evolution of the SBI. This allows us to understand the dynamics of the interaction at timescales shorter than experimental imaging framerates. We find that all radiation models examined reproduce empirical shock velocities within experimental error. Radiation transport is found to reduce shock pressures by providing an additional energy pathway in the ablation region, but this effect is small ($\sim$1\% of total shock pressure). Employing a flux-limited Spitzer model for heat conduction, we find that flux limiters between 0.03 and 0.10 produce agreement with experimental velocities, suggesting that the system is well-within the Spitzer regime. Higher heat conduction is found to lower temperatures in the ablated plasma and to prevent secondary shocks at the ablation front, resulting in weaker primary shocks. Finally, we confirm that the SBI-driven instabilities observed in the HED regime are baroclinically driven, as in the low energy case., Comment: 14 pages, 12 figures

The last decade has shown the great potential that X-ray Free Electron Lasers (FEL) have to study High Energy Density matter. Experiments at FELs have made significant breakthroughs in Shock Physics and Dynamic Diffraction, Dense Plasma Physics and Warm Dense Matter Science, using techniques such as isochoric heating, inelastic scattering, small angle scattering and x-ray diffraction. In addition, and complementary to these techniques, the coherent properties of the FEL beam can be used to image HED samples with high fidelity. We present new imaging diagnostics and techniques developed at the Matter in Extreme Conditions (MEC) instrument at Linac Coherent Light Source (LCLS) over the last few years. We show result of a previously used Phase Contrast Imaging setup, where the X-ray beam propagates from the target to a camera some distance away revealing its phase, as well as a imaging approach where the target is re-imaged on the camera with 300nm resolution. Last, we show a new Talbot Imaging method allowing both x-ray phase and intensity measurements change introduced by a target with sub-micron resolution.

We present direct observations of acoustic waves in warm dense matter. We analyze wave-number- and energy-resolved x-ray spectra taken from warm dense methane created by laser heating a cryogenic liquid jet. X-ray diffraction and inelastic free-electron scattering yield sample conditions of 0.3$\pm$0.1 eV and 0.8$\pm$0.1 g/cm$^3$, corresponding to a pressure of $\sim$13 GPa. Inelastic x-ray scattering was used to observe the collective oscillations of the ions. With a highly improved energy resolution of $\sim$50 meV, we could clearly distinguish the Brillouin peaks from the quasielastic Rayleigh feature. Data at different wave numbers were utilized to derive a sound speed of 5.9$\pm$0.5 km/s, marking a high-temperature data point for methane and demonstrating consistency with Birch's law in this parameter regime., Comment: 7 pages, 4 figures

The traditional picture of solid-solid phase transformations assumes an ordered parent phase transforms into an ordered daughter phase via a single unique pathway. Zirconium and its prototypical phase transition from hexagonal close-packed (hcp) to simple hexagonal (hex-3) structure has generated considerable controversy over several decades regarding which mechanism mediates the transformation. However, a lack of in situ measurements over the relevant atomistic timescales has hindered our ability to identify the true pathway. In this study, we exploit femtosecond X-ray diffraction coupled with nanosecond laser compression to give unprecedented insights into the complexities of how materials transform at the lattice level. We observe single-crystal zirconium changing from hcp to a hex-3 structure via not one but three competing pathways simultaneously. Concurrently, we also observe a broad diffuse background underlying the sharp Bragg diffraction during the transition. We corroborate our observation of the diffuse signal with multimillion-atom molecular dynamics simulations using a machine-learned interatomic potential. Our study demonstrates that the traditional mechanistic view of transitions may fail for even an elemental metal and that the mechanisms by which materials transform are far more intricate than generally thought.

We present a new algorithm for amortized inference in sparse probabilistic graphical models (PGMs), which we call $\Delta$-amortized inference ($\Delta$-AI). Our approach is based on the observation that when the sampling of variables in a PGM is seen as a sequence of actions taken by an agent, sparsity of the PGM enables local credit assignment in the agent's policy learning objective. This yields a local constraint that can be turned into a local loss in the style of generative flow networks (GFlowNets) that enables off-policy training but avoids the need to instantiate all the random variables for each parameter update, thus speeding up training considerably. The $\Delta$-AI objective matches the conditional distribution of a variable given its Markov blanket in a tractable learned sampler, which has the structure of a Bayesian network, with the same conditional distribution under the target PGM. As such, the trained sampler recovers marginals and conditional distributions of interest and enables inference of partial subsets of variables. We illustrate $\Delta$-AI's effectiveness for sampling from synthetic PGMs and training latent variable models with sparse factor structure., Comment: ICLR 2024; 19 pages, code: https://github.com/GFNOrg/Delta-AI/

X-ray laser-induced structural changes in silicon undergoing femtosecond melting have been investigated by using an x-ray pump-x-ray probe technique. The experimental results for different initial sample temperatures reveal that the onset time and the speed of the atomic disordering are independent of the initial temperature, suggesting that equilibrium atomic motion in the initial state does not play a pivotal role in the x-ray-induced ultrafast melting. By comparing the observed time-dependence of the atomic disordering and the dedicated theoretical simulations, we interpret that the energy transfer from the excited electrons to ions via electron-ion coupling (thermal effect) as well as a strong modification of the interatomic potential due to electron excitations (non-thermal effect) trigger the ultrafast atomic disordering. Our finding of the interplay of thermal and non-thermal effects in the x-ray-induced melting demonstrates that accurate modeling of intense x-ray interactions with matter is essential to ensure a correct interpretation of experiments using intense x-ray laser pulses.

We present the first experimental observation of K$_{\beta}$ emission from highly charged Mg ions at solid density, driven by intense x-rays from a free electron laser. The presence of K$_{\beta}$ emission indicates the $n=3$ atomic shell is relocalized for high charge states, providing an upper constraint on the depression of the ionization potential. We explore the process of state relocalization in dense plasmas from first principles using finite-temperature density functional theory alongside a wavefunction localization metric, and find excellent agreement with experimental results., Comment: 22 pages, 13 figures

In this paper, we present an experiment that explores the plasma dynamics of a 7 micron diameter carbon wire after being irradiated with a near-relativistic-intensity short pulse laser. Using an X-ray Free Electron Laser pulse to measure the small angle X-ray scattering signal, we observe that the scattering surface is bent and prone to instability over tens of picoseconds. The dynamics of this process are consistent with the presence of a sharp, propagating shock front inside the wire, moving at a speed close to the hole boring velocity.