arXiv Physics @arxiv_physics@qoto.org

Fluid-structure interaction (FSI) plays a crucial role in cardiac mechanics, where the strong coupling between fluid flow and deformable structures presents significant computational challenges. The immersed boundary (IB) method efficiently handles large deformations and contact without requiring mesh regeneration. However, solving complex FSI problems demands high computational efficiency, making GPU acceleration essential to leverage massive parallelism, high throughput, and memory bandwidth. We present a fully GPU-accelerated algorithm for the IB method to solve FSI problems in complex cardiac models. The Navier-Stokes equations are discretized using the finite difference method, while the finite element method is employed for structural mechanics. Traditionally, IB methods are not GPU-friendly due to irregular memory access and limited parallelism. The novelty of this work lies in eliminating sparse matrix storage and operations entirely, significantly improving memory access efficiency and fully utilizing GPU computational capability. Additionally, the structural materials can be modeled using general hyperelastic constitutive laws, including fiber-reinforced anisotropic biological tissues such as the Holzapfel-Ogden (HO) model. Furthermore, a combined geometric multigrid solver is used to accelerate the convergence. The full FSI system, consisting of millions of degrees of freedom, achieves a per-timestep computation time of just 0.1 seconds. We conduct FSI simulations of the left ventricle, mitral valve, and aortic valve, achieving results with high consistency. Compared to single-core CPU computations, our fully GPU-accelerated approach delivers speedups exceeding 100 times.

Concepts on quantum physics are generally difficult for the general public to understand and grasp due to its counter-intuitive nature and requirement for higher level of mathematical literacy. With categorical quantum mechanics (CQM), quantum theory is re-formalized into a more intuitive diagrammatic approach, which we will refer to as the first level of transformation, to improve the accessibility and readability of quantum theory to a broader audience since the mathematical details are embedded into diagrammatic rules. Taking inspiration from this diagrammatic approach, we propose the second level of transformation by gamifying the diagrammatic rules of quantum teleportation into a quantum card game called Quantum Port. In this work, we discuss the gamification process of quantum teleportation and provide a printable version of Quantum Port for public engagement.

In this paper, we propose the regularization principle that resolves the temporal paradoxes associated with faster-than-light particles or tachyons at the macroscopic scale. The principle involves using the properties of the ζ-function to regularize the unphysical momenta of tachyons that moves backwards in-time as an infinite sum of physical tachyon momenta that travel forwards in-time. Since, the tachyon moves forward in-time in all interial frames, this ensures that the tachyon processes are paradox-free without invoking the Reinterpretation Principle (RIP). Apart from resolving these paradoxes associated with faster-than-light particles, its other notable consequences especially pertaining to the censorship of naked singularities and faster-than-light communication are also discussed.

The study of magnetic phenomena in low-dimensional systems has largely explored after the discovery of two-dimensional (2D) magnetic materials, such as CrI3 and Cr2Ge2Te6 in 2017. These materials presents intrinsic magnetic order, overcoming the limitations predicted by the Mermin-Wagner theorem, due to magnetic crystalline anisotropy energy. Among these, CrTe2, a van der Waals 2D magnet, has gather significant interest due to its in-plane anisotropic magnetoresistance (AMR) and high Curie temperature. This study investigates the magnetic field-regulated resistance of CrTe2 monolayers in the context of spintronics applications. Utilizing the zigzag-ordered parameters obtained from prior simulations, we examine how external magnetic fields influence resistance states and control the ON/OFF state of nano-devices. The analysis demonstrates that specific magnetic field configurations, particularly those in the form of (0, 0, Bz), which is out-of-plane directed field, gives a non-zero root mean square resistance, indicating a functional ON state. This provides a novel method for magnetically controlled current regulation in spintronic devices. The experimental results also reveal an interesting spin-flop transition in CrTe2 under a z-directed magnetic field, leading to y-directional magnetization. This phenomenon, combined with the material's robust magnetic properties, positions CrTe2 as a promising candidate for next-generation memory and logic devices. By advancing the understanding of magnetic field manipulation in 2D magnetic materials, this research opens new pathways in the development of energy-efficient spintronics technology.

We present an analysis of the Dirac equation when the spin symmetry is changed from SU(2) to the quaternion group, $Q_8$, achieved by multiplying one of the gamma matrices by the imaginary number, $i$. The reason for doing this is to introduce a bivector into the spin algebra, which complexifies the Dirac field. It then separates into two distinct and complementary spaces: one describing polarization and the other coherence. The former describes a 2D structured spin, and the latter its helicity, generated by a unit quaternion.

Nuclear orbiting resonances have been revealed at the sub-barrier energies as an atomic phenomenon by means of x-ray spectroscopy experiments. This interpretation is supported by several phenomenological models and theoretical estimates of the nuclear orbiting timescale and cross-section, inelastic scattering cross section including both nuclear and Coulomb excitation, and the Wigner-Smith time delay. We demonstrate that a multi-photon exchange during nuclear orbiting is responsible for an atomic excitation. Furthermore, proximity of the projectile and target nucleus during the nuclear orbiting modifies the effective charge of the projectile. Even though this orbiting induced excitation is triggered in zeptoseconds, it can still be observed in the attosecond time scale because of the Wigner-Smith time delay inherent to autoionization. Thus, we demonstrate the crossover between the zeptosecond and attosecond time scales which are native to nuclear and atomic physics, respectively. Markedly, this crossover may be the reason for x-ray production from ultra short nuclear processes ($\leq 10^{-21}$ sec). This explanation is likely to resolve the fission time scale anomaly and can stimulate cross-disciplinary research ranging from solid state to high-energy physics.

The Cooling-Storage-Ring External-target Experiment (CEE) at Heavy Ion Research Facility in Lanzhou (HIRFL) is designed to study the properties of nuclear matter created in heavy-ion collisions at a few hundred MeV/$u$ to 1 GeV/$u$ beam energies, facilitating the research of quantum chromodynamics phase structure in the high-baryon-density region. Collective flow is one of the most important observables in heavy-ion collision experiments to study the bulk behavior of the created matter. Even though the standard event plane method has been widely used for collective flow measurements, it remains crucial to validate and optimize this method for the CEE spectrometer. In this paper, we study the experimental procedures of measuring directed flow in $^{238}$U+$^{238}$U collisions at 500 MeV/$u$ using event planes reconstructed by Multi Wire Drift Chamber and Zero Degree Calorimeter, respectively. Jet AA Microscopic (JAM) transport generator is used to generate events, and the detector response is simulated by the CEE Fast Simulation (CFS) package. Finally, the optimal kinetic region for proton directed flow measurements is discussed for the future CEE experiment.

The joint expertise of ANL and FNAL has led to the production of Nb3Sn undulator magnets in operation in the ANL Advanced Photon Source (APS). These magnets showed performance reproducibility close to the short sample limit, and a design field increase of 20% at 820A. However, the long training did not allow obtaining the expected 50% increase of the on-axis magnetic field with respect to the ~1 T produced at 450 A current in the ANL NbTi undulator. To address this, 10-pole long undulator prototypes were fabricated, and CTD-101K was replaced as impregnation material with TELENE, an organic olefin-based thermosetting dicyclopentadiene resin produced by RIMTEC Corporation, Japan. Training and magnet retraining after a thermal cycle were nearly eliminated, with only a couple of quenches needed before reaching short sample limit at over 1,100 A. TELENE will enable operation of Nb3Sn undulators much closer to their short sample limit, expanding the energy range and brightness intensity of light sources. TELENE is Co-60 gamma radiation resistant up to 7-8 MGy, and therefore already applicable to impregnate planar, helical and universal devices operating in lower radiation environments than high energy colliders.

This work assess the accuracy of standard profile beam symmetry metrics used in radiotherapy quality assurance and compare them to the proposed correlative symmetric index metric and Structural similarity index. The objective is to propose a new method based on cross correlation, named correlative symmetric index, that we show is less susceptible to noise than traditional methods. In addition, a supplemental method called Structural Similarity Index is presented.Simulations of non symmetric beams with similar left and right areas were used to compare the effectiveness of quantifying beam symmetry through proposed and standard methods. To assess each metric dependence on noise, an assessment was performed on all metrics using a noisy, simulated, non symmetric beam profile. A comparison of standard and proposed methods was also performed to characterize beam symmetry of roughly symmetric beam profiles measures at different depths in a water tank.In quantifying beam symmetry, the proposed correlative index metric and Structural Similarity Index method resulted in values 0.387, 0.5401, respectively for the non symmetric noisy scenario. More traditional approaches of PDQ and area based symmetry resulted in values of 0.312 and 0.400, respectively, for the non symmetric noisy scenario. The corresponding percentage change between the non symmetric no noise and the non symmetric with noise for the Point Difference Quotient, area based symmetric value, Structural Similarity Index Measurement, and Correlative symmetric index were 0.111, 0.056, 0.1625, 0.008, respectively. For the clinical measured symmetric profiles all methods achieved values above 0.9. Comparisons of quantitative and qualitative metrics demonstrate that the proposed correlative symmetry index method outperforms both the pointwise and area based symmetric metrics for when beam profiles are noisy.

We investigate a composite elastic meta-slab with exceptional transmission properties, particularly the presence of a W-shaped bandgap. A comprehensive study, utilizing experimental measurements, the finite element method, and an analytical approach, identifies this specific bandgap. The meta-slab design involves cutting an array of composite materials arranged in parallel with strategically placed incisions. This configuration ensures that the materials between the slits act as plate-like waveguides within the surrounding medium. The incorporation of steel into ABS-based Fabry-Perot cavities induces a notable coupling effect between longitudinal waves and localized modes traversing the structure, leading to the formation of two distinct Fabry-Perot resonators. These coupling effects generate a series of resonances and antiresonances, ultimately producing the W-band gap through the interaction of two symmetric Fano resonances.

Due to limitations such as geographic, physical, or economic factors, collected seismic data often have missing traces. Traditional seismic data reconstruction methods face the challenge of selecting numerous empirical parameters and struggle to handle large-scale continuous missing traces. With the advancement of deep learning, various diffusion models have demonstrated strong reconstruction capabilities. However, these UNet-based diffusion models require significant computational resources and struggle to learn the correlation between different traces in seismic data. To address the complex and irregular missing situations in seismic data, we propose a latent diffusion transformer utilizing representation learning for seismic data reconstruction. By employing a mask modeling scheme based on representation learning, the representation module uses the token sequence of known data to infer the token sequence of unknown data, enabling the reconstructed data from the diffusion model to have a more consistent data distribution and better correlation and accuracy with the known data. We propose the Representation Diffusion Transformer architecture, and a relative positional bias is added when calculating attention, enabling the diffusion model to achieve global modeling capability for seismic data. Using a pre-trained data compression model compresses the training and inference processes of the diffusion model into a latent space, which, compared to other diffusion model-based reconstruction methods, reduces computational and inference costs. Reconstruction experiments on field and synthetic datasets indicate that our method achieves higher reconstruction accuracy than existing methods and can handle various complex missing scenarios.

We introduce PHYSICS, a comprehensive benchmark for university-level physics problem solving. It contains 1297 expert-annotated problems covering six core areas: classical mechanics, quantum mechanics, thermodynamics and statistical mechanics, electromagnetism, atomic physics, and optics. Each problem requires advanced physics knowledge and mathematical reasoning. We develop a robust automated evaluation system for precise and reliable validation. Our evaluation of leading foundation models reveals substantial limitations. Even the most advanced model, o3-mini, achieves only 59.9% accuracy, highlighting significant challenges in solving high-level scientific problems. Through comprehensive error analysis, exploration of diverse prompting strategies, and Retrieval-Augmented Generation (RAG)-based knowledge augmentation, we identify key areas for improvement, laying the foundation for future advancements.

The variation of the oxygen enhancement ratio (OER) across different values of Linear Energy Transfer (LET) currently lacks a comprehensive mechanistic interpretation and a mechanistic model. Our earlier research revealed a significant correlation between the distribution of double-strand breaks (DSBs) within the 3D genome and radiation-induced cell death, which offers valuable insights into the oxygen effect. In this study, we formulate a model where the reaction of oxygen is represented as the probability of inducing DNA strand breaks. Then it is integrated into a track-structure Monte Carlo simulation to investigate the impact of oxygen on the spatial distribution of DSBs within the 3D genome. Results show that the incidence ratios of clustered DSBs in a single topologically associating domain (TAD) (case 2) and DSBs in frequently-interacting TADs (case 3) under aerobic and hypoxic conditions closely align with the trend of the OER of cell survival across various LET values. By utilizing the parameters derived from our previous study, we calculate the OER values related to cell survival. Our OER curves exhibit good correspondence with experimental data. This study provides a potentially mechanistic explanation for the changes in OER across different LET levels. High-LET irradiation leads to dense ionization events, resulting in an overabundance of lesions that readily induce case 2 and case 3. The probabilities of cell death associated with case 2 and case 3 are substantially higher than other damage patterns. This may contribute to the main mechanism governing the variation of OER for high LET. Our study further underscores the importance of the DSB distribution within the 3D genome in the context of radiation-induced cell death. This study also provides valuable reference points for establishing a mechanistic model of OER.

CERN's strategic R&D programme on technologies for future experiments recently started investigating the TPSCo 65nm ISC CMOS imaging process for monolithic active pixels sensors for application in high energy physics. In collaboration with the ALICE experiment and other institutes, several prototypes demonstrated excellent performance, qualifying the technology. The Hybrid-to-Monolithic (H2M), a new test-chip produced in the same process but with a larger pixel pitch than previous prototypes, exhibits an unexpected asymmetric efficiency pattern. This contribution describes a simulation procedure combining TCAD, Monte Carlo and circuit simulations to model and understand this effect. It proved able to reproduce measurement results and attribute the asymmetric efficiency drop to a slow charge collection due to low amplitude potential wells created by the circuitry layout and impacting efficiency via ballistic deficit.

Nonreciprocity is most commonly associated with a large difference in the transmitted energy when the locations of the source and receiver are interchanged. This energy bias is accompanied by a difference in the transmitted phase. We highlight the role of this phase bias in breaking reciprocity in the steady-state vibration transmission characteristics of coupled nonlinear systems to external harmonic excitation. We show that breaking of reciprocity is most commonly accompanied by a simultaneous bias in the transmitted energy and phase. Energy bias alone, without any contribution from phase, can still lead to nonreciprocity, but only at very finely tuned system parameters. We provide a methodology for realizing response regimes of phase-preserving nonreciprocity using two independent symmetry-breaking parameters in the system. Our findings highlight the key contribution of phase in nonlinear nonreciprocity.

This study investigates how variations in freestream turbulence (FST) and the thrust coefficient ($C_T$) influence wind turbine wakes. Wakes generated at $C_T \in \{0.5, 0.7,0.9\}$ are exposed to turbulent inflows with varying FST intensity ($1\% \lesssim TI_{\infty} \lesssim 11\%$) and integral length scale ($0.1 \lesssim \mathcal{L}_x/D \lesssim 2$, $D$ is the rotor diameter). For high-$TI_{\infty}$ inflows, a flow region within the wake is observed several diameters downstream, where a mean momentum deficit persists despite the turbulence intensity having already homogenised with the freestream, challenging traditional wake definitions. A ``turning point'' in the mean wake width evolution is identified, beyond which wakes spread at slower rates. Near-field ($x/D \lesssim 7$) wake growth rate increases with higher $TI_{\infty}$ and $C_T$, while far-field ($x/D \gtrsim 15$) wake growth rate decreases with higher $TI_{\infty}$ -- a finding with profound implications for wind turbine wake modelling that also bridges the gap with entrainment behaviours observed in bluff and porous body wakes exposed to FST. Increasing $\mathcal{L}_x$ delays wake recovery onset and reduces the mean wake width, with minimal effect on the spreading rate. Both $C_T$ and FST influence high- and low-frequency wake dynamics, with varying contributions in the near and far fields. For low-$TI_{\infty}$ and small-$\mathcal{L}_x$ inflows, wake meandering is minimal, sensitive to $C_T$, and appears to be triggered by shear layer instabilities. Wake meandering is enhanced for high-$TI_{\infty}$ and large-$\mathcal{L}_x$ inflows and is dominated by background turbulence. This emphasises the complex role of FST integral length scale: while increasing $\mathcal{L}_x$ amplifies meandering, it does not necessarily translate to larger mean wake width due to the concurrent suppression of entrainment rate.

This chapter explores the key carbon compounds that shaped the Archean biogeochemical cycle, delineating their substantial impact on Earth's primordial atmospheric and biospheric evolution. At the heart of the Archean carbon cycle were carbon dioxide and methane, which served as key regulators of Earth's early climate. Particular emphasis is placed on methane cycling, encompassing both abiotic methane production and consumption, as well as their biotic counterparts-methanogenesis and methanotrophy. These ancient microbial pathways not only shaped methane fluxes but were also tightly interwoven with Earth's evolving redox state. We provide a comprehensive exploration of the intertwined evolution of Earth's geochemical environment and microbial life. The interdisciplinary approach of this chapter not only sheds light on the complex dynamics of Earth's early methane cycling but also offers critical insights that could inform the search for life beyond our planet, thereby marking a contribution to Earth sciences, astrobiology, and related fields.

Below critical temperature, turbulence prevents the spontaneous phase separation of binary mixtures, resulting in a phase arrested state of emulsion which is of significant interest for scientific and industrial applications. The current work is an extensive continuation of our initial theoretical investigation into the nature and universality of associated energy cascade (Pan and Banerjee, PRE, 2022). In addition to the previously derived divergence and correlator forms of the exact relations, a Banerjee-Galtier type divergence-free form of the exact relation is derived under the explicit assumption of homogeneity. By performing three-dimensional direct numerical simulations with up to $1024^3$ grid points, we show that the sum of the kinetic and active energy associates a Kolmogorov-like universal cascade with constant flux rate across inertial scales. Despite term-by-term deviations, the cascade rates computed from all three exact laws show excellent agreement, thereby confirming the equivalence of different exact relations and hence the feasibility of determining the net cascade rate from any of the three formulations. Notably, the two dominant flux rates of the divergence form are found to cross each other roughly at the domain size, which also serves as an infrared cut-off for the inverse cascade of the small scale active energy. This behaviour is phenomenologically justified based on the interplay between the flow and surface dynamics of a phase arrested binary fluid.

Obtaining a group velocity higher than the speed of sound in a waveguide is a challenging task in acoustic wave engineering. Even more challenging is to achieve this velocity increase without any intervention with the waveguide profile, such as narrowing or widening, and particularly without interfering with the passage by flexible inclusions, either passive or active. Here, we approach this problem by invoking concepts from non- Hermitian physics, and imposing them using active elements that are smoothly sealed within the waveguide wall. In a real-time feedback operation, the elements induce local pressure gain and loss, as well as non-local pressure integration couplings. We employ a dedicated balancing between the control parameters, derived from lattice theory and adjusted to the waveguide system, to drive the dynamics into a stable parity-time-symmetric regime. We demonstrate the accelerated propagation of a wave packet both numerically and experimentally in an air-filled waveguide and discuss the trade-off between stabilization and the achievable velocity increase. Our work prepares the grounds for advanced forms of wave transmission in continuous media, enabled by short and long range active couplings, created via embedded real-time feedback control.

Uncertainties in the subsurface challenge reliable leakage risk assessments and long-term integrity of CO2 storage. Fault zones, characterised by multi-scale heterogeneities, are critical pathways for leakage and suffer from significant data uncertainties due to unresolved features. Understanding the multi-scale uncertainties in estimating fracture network conductivity is essential for mitigating leakage risks and ensuring reliable modelling of upscaled fault leakage rates. However, current models fail to capture all fault zone heterogeneity, particularly fracture surface roughness effects on fluid migration. Simplified assumptions, such as the Cubic Law based on mechanical aperture measurements, lead to erroneous models known as model misspecifications and introduce modelling uncertainty in leakage predictions. Here, we develop an AI-driven framework to address data uncertainties and correct model misspecifications in estimating fracture conductivities. By automatically integrating small-scale uncertainties, including fracture surface roughness, and leveraging their interactions across scales, we improve upon traditional empirical corrections. We combine physics-based constraints with adaptive, data-driven and geometric corrections to infer the hydraulic aperture governing fluid flow in fractures with varying roughness. This approach generates reliable local permeability maps that account for roughness effects and discrepancies between mechanical and hydraulic apertures, accurately reflecting overall fracture conductivity. By propagating uncertainties from individual fractures to network scales, our approach will support robust calibration of conductivity ranges for fault leakage sensitivity analyses, not only resolving uncertainties in fracture-scale modelling but also enabling efficient integration into larger-scale simulations to enhance predictions for subsurface CO2 storage.