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Manufacturing industries require a right-first-time paradigm to remain competitive. Variation simulation (VS) is a key tool to predict variation of the final shape of flexible assemblies, allowing to reduce defects and waste. VS models involving compliant sheet-metal parts commonly integrate physics-based simulation with statistical approaches (usually Monte Carlo simulation). Although increasingly used as a backbone of synthesis techniques for (stochastic) optimization of assembly systems, the main roadblock of VS methods is the intense computational costs due to time-intensive simulations and high-dimensional design space. Driven by the need of time reduction, this paper presents an innovative real-time physics-based VS model of assembly systems with compliant sheet-metal parts. The proposed methodology involves a non-intrusive reduced-order model (niROM), empowered by a novel adaptive sampling procedure for dataset generation, and a cross-validation-based optimized radial basis function (RBF) formulation for interpolation. Demonstrated through two case studies—(i) a remote laser welding operation to predict mechanical distortions, with two input parameters, and (ii) the assembly of an aircraft vertical stabilizer with five input parameters—the methodology achieves accurate real-time results, with up to a 43% improvement in accuracy compared to traditional sampling techniques. Findings highlight the critical influence of the sampling strategy and the number of input parameters on ROM accuracy. Better results are reached by employing adaptive sampling in combination with optimum RBF, which additionally disengages the user from the choice of the interpolation settings. This study unlocks new avenues in the field of variation simulation and dimensional/quality monitoring by narrowing the gap between any advanced CAE solver and VS models with real-time physics-based simulations.

Physics education applications using augmented reality technology, which has been developed extensively in recent years, have a lot of restrictions in terms of performance and accuracy. The purpose of our research is to develop a real-time simulation system for physics education that is based on parallel processing. In this paper, we present a video see-through AR (Augmented Reality) system that includes an environment recognizer using a depth image of Microsoft’s Kinect V2 and a real-time soft body simulator based on parallel processing using GPU (Graphic Processing Unit). Soft body simulation can provide more realistic simulation results than rigid body simulation, so it can be more effective in systems for physics education. We have designed and implemented a system that provides the physical deformation and movement of 3D volumetric objects, and uses them in education. To verify the usefulness of the proposed system, we conducted a questionnaire survey of 10 students majoring in physics education. As a result of the questionnaire survey, 93% of respondents answered that they would like to use it for education. We plan to use the stand-alone AR device including one or more cameras to improve the system in the future.

This study proposes a GPU-accelerated Position-Based Dynamics (PBD) system for realistic and interactive cloth simulation in Extended Reality (XR) environments, and comprehensively evaluates its performance and functional capabilities on standalone XR devices, such as the Meta Quest 3. To overcome the limitations of traditional CPU-based physics simulations, we designed and optimized highly parallelized algorithms utilizing Unity’s Compute Shader framework. The proposed system achieves real-time performance by implementing efficient collision detection and response handling with complex environmental meshes (RoomMesh) and dynamic hand meshes (HandMesh), as well as capsule colliders based on hand skeleton tracking (OVRSkeleton). Performance evaluations were conducted for both single-sided and double-sided cloth configurations across multiple resolutions. At a 32 × 32 resolution, both configurations maintained stable frame rates of approximately 72 FPS. At a 64 × 64 resolution, the single-sided cloth achieved around 65 FPS, while the double-sided configuration recorded approximately 40 FPS, demonstrating scalable quality adaptation depending on application requirements. Functionally, the GPU-PBD system significantly surpasses Unity’s built-in Cloth component by supporting double-sided cloth rendering, fine-grained constraint control, complex mesh-based collision handling, and real-time interaction with both hand meshes and capsule colliders. These capabilities enable immersive and physically plausible XR experiences, including natural cloth draping, grasping, and deformation behaviors during user interactions. The technical advantages of the proposed system suggest strong applicability in various XR fields, such as virtual clothing fitting, medical training simulations, educational content, and interactive art installations. Future work will focus on extending the framework to general deformable body simulation, incorporating advanced material modeling, self-collision response, and dynamic cutting simulation, thereby enhancing both realism and scalability in XR environments.

The simulation of deformable objects has been the subject of a great deal of work in the field of computer graphics. The constraint-based PBD (Position-Based Dynamics) approach has been proven to be effective in this field for real-time and stable deformable objects simulation. Finite element method with linear tetrahedron discretization is the most widely used in computer graphics despite producing less accurate results than hexahedral or higher-order elements. In this context, our proposal is to integrate higher degree elements within the pbd framework. In addition, we propose a solution to improve convergence of unstable energies (like Neo-Hooke) when used as constraints. We show that our approach improves accuracy compared to linear tetrahedra. We also highlight the time savings, since fewer elements are needed.

Large-scale particle-based fluid simulations present significant computational challenges, particularly in achieving interactive frame rates while maintaining visual quality. Unity3D’s widespread adoption in game development, VR/AR applications, and scientific visualization creates a unique need for efficient fluid simulation within its ecosystem. This paper presents a GPU-accelerated Smoothed Particle Hydrodynamics (SPH) framework implemented in Unity3D that effectively addresses these challenges through several key innovations. Unlike previous GPU-accelerated SPH implementations that typically struggle with scaling beyond 100,000 particles while maintaining real-time performance, we introduce a novel fusion of Count Sort with Parallel Prefix Scan for spatial hashing that transforms the traditionally expensive O(n²) neighborhood search into an efficient O(n) operation, significantly outperforming traditional GPU sorting algorithms in particle-based simulations. Our implementation leverages a Structure of Arrays (SoA) memory layout, optimized for GPU compute shaders, achieving 30–45% improved computation throughput over traditional Array of Structures approaches. Performance evaluations demonstrate that our method achieves throughput rates up to 168,600 particles/ms while maintaining consistent 5.7–6.0 ms frame times across varying particle counts from 10,000 to 1,000,000. The framework maintains interactive frame rates (>30 FPS) with up to 500,000 particles and remains responsive even at 1 million particles. Collision rates approaching 1.0 indicate near-optimal hash distribution, while the adaptive time stepping mechanism adds minimal computational overhead (2–5%) while significantly improving simulation stability. These innovations enable real-time, large-scale fluid simulations with applications spanning visual effects, game development, and scientific visualization.

The topological θ -angle is central to several gauge theories in condensed-matter and high-energy physics. For example, it is responsible for the strong CP problem in quantum chromodynamics and can emerge in effective theories of electrodynamics in topological insulators. Although analogue quantum simulators potentially offer a venue for realizing and controlling the θ -angle, doing so has hitherto remained an outstanding challenge. Here, we describe the experimental realization of a tunable topological θ -angle in a Bose–Hubbard gauge-theory quantum simulator, which was implemented through a tilted superlattice potential that induces an effective background electric field. We demonstrate the emerging physics through the direct observation of the confinement–deconfinement transition of (1 + 1)-dimensional quantum electrodynamics. Using an atomic-precision quantum gas microscope, we distinguish between the confined and deconfined phases by monitoring the real-time evolution of particle–antiparticle pairs. Our work provides a step forward in the realization of topological terms on modern quantum simulators. Topological terms arise naturally in gauge theories but have been difficult to implement in quantum simulators. Now, a tunable topological θ -angle is demonstrated with a cold-atom platform.

Confinement plays an important role in many-body physics from high energy to condensed matter. New results show that it strongly affects the non-equilibrium dynamics after a quantum quench with possible implications from ultracold atoms to QCD. Quarks cannot be observed as free particles in nature because they are confined into baryons and mesons, as a result of the fact that the strong interaction between them increases with their separation. However, it is less known that this phenomenon also occurs in condensed matter and statistical physics as experimentally proved in several quasi-1D compounds 1 , 2 . Most of the theoretical and experimental studies so far concentrated on understanding the consequences of confinement for the equilibrium physics of both high-energy and condensed matter systems. Here, instead we show that confinement has dramatic consequences for the non-equilibrium dynamics following a quantum quench and that these effects could be exploited as a quantitative probe of confinement.

Linear response theory lies at the heart of studying quantum matters, because it connects the dynamical response of a quantum system to an external probe to correlation functions of the unprobed equilibrium state. Thanks to linear response theory, various experimental probes can be used for determining equilibrium properties. However, so far, both the unprobed system and the probe operator are limited to Hermitian ones. Here, we develop a non-Hermitian linear response theory that considers the dynamical response of a Hermitian system to a non-Hermitian probe, and we can also relate such a dynamical response to the properties of an unprobed Hermitian system at equilibrium. As an application of our theory, we consider the real-time dynamics of momentum distribution induced by one-body and two-body dissipations. Remarkably, for a critical state with no well-defined quasi-particles, we find that the dynamics are slower than the normal state with well-defined quasi-particles, and our theory provides a model-independent way to extract the critical exponent in the real-time correlation function. We find surprisingly good agreement between our theory and a recent cold atom experiment on the dissipative Bose–Hubbard model. We also propose to further quantitatively verify our theory by performing experiments on dissipative one-dimensional Luttinger liquid. Generalization of linear response theory to the non-Hermitian case turns dissipation into a new tool for detecting equilibrium phases. The prediction from this theory remarkably agrees with a recent cold atom experiment.

The COVID-19 pandemic is impacting human activities, and in turn energy use and carbon dioxide (CO 2 ) emissions. Here we present daily estimates of country-level CO 2 emissions for different sectors based on near-real-time activity data. The key result is an abrupt 8.8% decrease in global CO 2 emissions (−1551 Mt CO 2 ) in the first half of 2020 compared to the same period in 2019. The magnitude of this decrease is larger than during previous economic downturns or World War II. The timing of emissions decreases corresponds to lockdown measures in each country. By July 1st, the pandemic’s effects on global emissions diminished as lockdown restrictions relaxed and some economic activities restarted, especially in China and several European countries, but substantial differences persist between countries, with continuing emission declines in the U.S. where coronavirus cases are still increasing substantially. The COVID-19 pandemic has stopped many human activities, which has had significant impact on emissions of greenhouse gases. Here, the authors present daily estimates of country-level CO 2 emissions for different economic sectors and show that there has been a 8.8% decrease in global CO2 emissions in the first half of 2020.

A laser frequency comb is a broad spectrum composed of equidistant narrow lines. Initially invented for frequency metrology, such combs enable new approaches to spectroscopy over broad spectral bandwidths, of particular relevance to molecules. The performance of existing spectrometers — such as crossed dispersers employing, for example, virtual imaging phase array étalons, or Michelson-based Fourier transform interferometers — can be dramatically enhanced with optical frequency combs. A new class of instruments, such as dual-comb spectrometers without moving parts, enables fast and accurate measurements over broad spectral ranges. The direct self-calibration of the frequency scale of the spectra within the accuracy of an atomic clock and the negligible contribution of the instrumental line-shape will enable determinations of all spectral parameters with high accuracy for stringent comparisons with theories in atomic and molecular physics. Chip-scale frequency comb spectrometers promise integrated devices for real-time sensing in analytical chemistry and biomedicine. This Review gives a summary of the developments in the emerging and rapidly advancing field of atomic and molecular broadband spectroscopy with frequency combs.Frequency comb spectroscopy is a recent field of research that has blossomed in the past five years. This Review discusses developments in the emerging and rapidly advancing field of atomic and molecular broadband spectroscopy with frequency combs.