Was the paranormal good for physics?
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Visual cognition in multimodal large language models
A chief goal of artificial intelligence is to build machines that think like people. Yet it has been argued that deep neural network architectures fail to accomplish this. Researchers have asserted these models’ limitations in the domains of causal reasoning, intuitive physics and intuitive psychology. Yet recent advancements, namely the rise of large language models, particularly those designed for visual processing, have rekindled interest in the potential to emulate human-like cognitive abilities. This paper evaluates the current state of vision-based large language models in the domains of intuitive physics, causal reasoning and intuitive psychology. Through a series of controlled experiments, we investigate the extent to which these modern models grasp complex physical interactions, causal relationships and intuitive understanding of others’ preferences. Our findings reveal that, while some of these models demonstrate a notable proficiency in processing and interpreting visual data, they still fall short of human capabilities in these areas. Our results emphasize the need for integrating more robust mechanisms for understanding causality, physical dynamics and social cognition into modern-day, vision-based language models, and point out the importance of cognitively inspired benchmarks.
Additive manufacturing of a 3D-segmented plastic scintillator detector for tracking and calorimetry of elementary particles
Plastic scintillators, segmented into small, optically isolated voxels, are used for detecting elementary particles and provide reliable particle identification with nanosecond time resolution. Building large detectors requires the production and precise alignment of millions of individual units, a process that is time-consuming, cost-intensive, and difficult to scale. Here, we introduce an additive manufacturing process chain capable of producing plastic-based scintillator detectors as a single, monolithic structure. Unlike previous manufacturing methods, this approach consolidates all production steps within one machine, creating a detector that integrates and precisely aligns its voxels into a unified structure. By combining fused deposition modeling with an injection process optimized for fabricating scintillation geometries, we produced an additively manufactured fine-granularity plastic scintillator detector with performance comparable to the state of the art, and demonstrated its capabilities for 3D tracking of elementary particles and energy-loss measurement. This work presents an efficient and economical production process for manufacturing plastic-based scintillator detectors, adaptable to various sizes and geometries.
Optical sorting: past, present and future
Optical sorting combines optical tweezers with diverse techniques, including optical spectrum, artificial intelligence (AI) and immunoassay, to endow unprecedented capabilities in particle sorting. In comparison to other methods such as microfluidics, acoustics and electrophoresis, optical sorting offers appreciable advantages in nanoscale precision, high resolution, non-invasiveness, and is becoming increasingly indispensable in fields of biophysics, chemistry, and materials science. This review aims to offer a comprehensive overview of the history, development, and perspectives of various optical sorting techniques, categorised as passive and active sorting methods. To begin, we elucidate the fundamental physics and attributes of both conventional and exotic optical forces. We then explore sorting capabilities of active optical sorting, which fuses optical tweezers with a diversity of techniques, including Raman spectroscopy and machine learning. Afterwards, we reveal the essential roles played by deterministic light fields, configured with lens systems or metasurfaces, in the passive sorting of particles based on their varying sizes and shapes, sorting resolutions and speeds. We conclude with our vision of the most promising and futuristic directions, including AI-facilitated ultrafast and bio-morphology-selective sorting. It can be envisioned that optical sorting will inevitably become a revolutionary tool in scientific research and practical biomedical applications.
Frequency shift caused by nonuniform field and boundary relaxation in magnetic resonance and comagnetometers
In magnetic resonance experiments, it is widely recognized that a nonuniform magnetic field can lead to an increase in the resonance line width, as well as a reduction in sensitivity and spectral resolution. However, a nonuniform magnetic field can also cause shifts in resonance frequency, which has received far less attention. In this work, we investigate the frequency shift caused by boundary relaxation and nonuniform magnetic field with arbitrary spatial distribution. We find that this frequency shift is spin-species dependent, implying a systematic error in NMR gyroscopes and comagnetometers. The first order correction to this systematic error is proportional to the difference of boundary relaxation rate, and dominates for small cells. In contrast, the third and higher order corrections arise from the difference of gyromagnetic ratios of spin species, and dominates for large cells. This insight helps understanding the unexplained isotope shifts in recent NMR gyroscopes and new physics searching experiments that utilize comagnetometers. Finally, we propose a tool for wall interaction research based on the frequency shift’s dependency on boundary relaxation.
Observation of non-Hermitian topological synchronization
Non-Hermitian topology plays a pivotal role in physical science and technology, exerting a profound impact across various scientific disciplines. Recently, the interplay between topological physics and nonlinear synchronization has aroused a great interest, leading to the emergence of an intriguing phenomenon known as topological synchronization, wherein nonlinear oscillators at boundaries synchronize through topological boundary states. To the best of our knowledge, however, this phenomenon has yet to be experimentally validated, and the study of non-Hermitian topological synchronization remains in its infancy. Here, we investigate non-Hermitian topological synchronization, uncovering the influence of system size and boundary site geometry on synchronization effects. We demonstrate that simply varying the lattice size allows transitions between three distinct types of non-Hermitian topological synchronization. Furthermore, we reveal that the geometry of the boundary sites introduces a degree of freedom, enabling the control over the configuration of non-Hermitian topological synchronization. These findings are experimentally validated using non-Hermitian nonlinear topological circuits. This work significantly broadens the scope of nonlinear non-Hermitian topological physics and opens new avenues for the application of synchronization phenomena in future technologies.
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