Hasil untuk "Physics"

Shengze Cai, Zhicheng Wang, Sifan Wang et al.

Physics-informed neural networks (PINNs) have gained popularity across different engineering fields due to their effectiveness in solving realistic problems with noisy data and often partially missing physics. In PINNs, automatic differentiation is leveraged to evaluate differential operators without discretization errors, and a multitask learning problem is defined in order to simultaneously fit observed data while respecting the underlying governing laws of physics. Here, we present applications of PINNs to various prototype heat transfer problems, targeting in particular realistic conditions not readily tackled with traditional computational methods. To this end, we first consider forced and mixed convection with unknown thermal boundary conditions on the heated surfaces and aim to obtain the temperature and velocity fields everywhere in the domain, including the boundaries, given some sparse temperature measurements. We also consider the prototype Stefan problem for two-phase flow, aiming to infer the moving interface, the velocity and temperature fields everywhere as well as the different conductivities of a solid and a liquid phase, given a few temperature measurements inside the domain. Finally, we present some realistic industrial applications related to power electronics to highlight the practicality of PINNs as well as the effective use of neural networks in solving general heat transfer problems of industrial complexity. Taken together, the results presented herein demonstrate that PINNs not only can solve ill-posed problems, which are beyond the reach of traditional computational methods, but they can also bridge the gap between computational and experimental heat transfer.

S. Udrescu, Max Tegmark

Our physics-inspired algorithm for symbolic regression is able to discover complex physics equations from mere tables of numbers. A core challenge for both physics and artificial intelligence (AI) is symbolic regression: finding a symbolic expression that matches data from an unknown function. Although this problem is likely to be NP-hard in principle, functions of practical interest often exhibit symmetries, separability, compositionality, and other simplifying properties. In this spirit, we develop a recursive multidimensional symbolic regression algorithm that combines neural network fitting with a suite of physics-inspired techniques. We apply it to 100 equations from the Feynman Lectures on Physics, and it discovers all of them, while previous publicly available software cracks only 71; for a more difficult physics-based test set, we improve the state-of-the-art success rate from 15 to 90%.

M. Tanabashi, Peter J. Richardson, A. Bettini et al.

A. Fert, N. Reyren, V. Cros

Magnetic skyrmions are small swirling topological defects in the magnetization texture. Their stabilization and dynamics depend strongly on their topological properties. In most cases, they are induced by chiral interactions between atomic spins in non-centrosymmetric magnetic compounds or in thin films with broken inversion symmetry. Skyrmions can be extremely small, with diameters in the nanometre range, and behave as particles that can be moved, created and annihilated, which makes them suitable for ‘abacus’-type applications in information storage and logic technologies. Until recently, skyrmions had been observed only at low temperature and, in most cases, under large applied magnetic fields. An intense research effort has led to the identification of thin-film and multilayer structures in which skyrmions are now stable at room temperature and can be manipulated by electrical currents. The development of skyrmion-based topological spintronics holds promise for applications in the mid-term furure, even though many challenges, such as the achievement of writing, processing and reading functionalities at room temperature and in all-electrical manipulation schemes, still lie ahead. Magnetic skyrmions are topologically protected spin whirls that hold promise for applications because they can be controllably moved, created and annihilated. In this Review, the underlying physics of the stabilization of skyrmions at room temperature and their prospective use for spintronic applications are discussed.

W. Kruer

Based on a graduate course in plasma physics taught at University of California, Davis, this classic book provides a concise overview and a physically-motivated treatment of the major plasma processes which determine the interaction of intense light waves with plasmas. It also includes a discussion of basic plasma concepts, plasma simulation using particle codes, and laser plasma experiments. This is the most elementary book currently available that successfully blends theory, simulation, and experiment, and presents a clear exposition of the major physical processes involved in laser-plasma interactions. This was also the first book on the topic by anyone involved in the United States Laser Fusion Program. Dr. Kruer has more than 30 years of active participation in this field.

M. Grunwald

M. J. Savage

THE British Association discussion at Norwich on nuclear physics on September 5 was opened by Lord Rutherford. After a review of progress resulting from the application of high voltages to nuclear transmutation, he passed on to discuss the rapid development of our knowledge of artificial radioactivity and in particular the production of such radioactivity by neutron bombardment. Neutrons, being uncharged, penetrate the heaviest nuclei without difficulty, and radioactive isotopes of the great majority of the elements have already been discovered. The effectiveness of neutrons in producing some types of transmutation is increased largely by slowing them down by passage through paraffin, water or other substances containing hydrogen, the neutrons losing energy by collision with the protons. By slowing them down in this way to thermal velocities, their adsorption by boron is increased 350 times, by cadmium 3,000 times, and by gadolinium 30,000 times, the effective cross-section for capture then being of the order of 10-20 sq. cm. A demonstration that neutrons actually obtain thermal velocities is afforded by slowing them down in paraffin wax cooled to liquid air or liquid hydrogen temperatures. This extra cooling reduces the velocity still further, and an increase in the efficiency of disintegration has been observed by P. B. Moon and others.

Francis F. Chen

K. Olive, K. Agashe, C. Amsler et al.

Niklas Wahlström, A. Wills, J. Hendriks et al.

G. Catalán, J. Scott

Younan Xia, Y. Xiong, Byungkwon Lim et al.

F. Kondev, Mu-Yuan Wang, W. Huang et al.

The NUBASE2020 evaluation contains the recommended values of the main nuclear physics properties for all nuclei in their ground and excited, isomeric (T1/2 100 ns) states. It encompasses all experimental data published in primary (journal articles) and secondary (mainly laboratory reports and conference proceedings) references, together with the corresponding bibliographical information. In cases where no experimental data were available for a particular nuclide, trends in the behavior of specific properties in neighboring nuclei were examined and estimated values are proposed. Evaluation procedures and policies that were used during the development of this evaluated nuclear data library are presented, together with a detailed table of recommended values and their uncertainties.

J. Nelson

S. Sze, K. Ng

M. Newman, G. Barkema

P. Lee, N. Nagaosa, X. Wen

This article reviews the physics of high-temperature superconductors from the point of view of the doping of a Mott insulator. The basic electronic structure of cuprates is reviewed, emphasizing the physics of strong correlation and establishing the model of a doped Mott insulator as a starting point. A variety of experiments are discussed, focusing on the region of the phase diagram close to the Mott insulator (the underdoped region) where the behavior is most anomalous. The normal state in this region exhibits pseudogap phenomenon. In contrast, the quasiparticles in the superconducting state are well defined and behave according to theory. This review introduces Anderson's idea of the resonating valence bond and argues that it gives a qualitative account of the data. The importance of phase fluctuations is discussed, leading to a theory of the transition temperature, which is driven by phase fluctuations and the thermal excitation of quasiparticles. However, an argument is made that phase fluctuations can only explain pseudogap phenomenology over a limited temperature range, and some additional physics is needed to explain the onset of singlet formation at very high temperatures. A description of the numerical method of the projected wave function is presented, which turns out to be a very useful technique for implementing the strong correlation constraint and leads to a number of predictions which are in agreement with experiments. The remainder of the paper deals with an analytic treatment of the $t\text{\ensuremath{-}}J$ model, with the goal of putting the resonating valence bond idea on a more formal footing. The slave boson is introduced to enforce the constraint againt double occupation and it is shown that the implementation of this local constraint leads naturally to gauge theories. This review follows the historical order by first examining the U(1) formulation of the gauge theory. Some inadequacies of this formulation for underdoping are discussed, leading to the SU(2) formulation. Here follows a rather thorough discussion of the role of gauge theory in describing the spin-liquid phase of the undoped Mott insulator. The difference between the high-energy gauge group in the formulation of the problem versus the low-energy gauge group, which is an emergent phenomenon, is emphasized. Several possible routes to deconfinement based on different emergent gauge groups are discussed, which leads to the physics of fractionalization and spin-charge separation. Next the extension of the SU(2) formulation to nonzero doping is described with a focus on a part of the mean-field phase diagram called the staggered flux liquid phase. It will be shown that inclusion of the gauge fluctuation provides a reasonable description of the pseudogap phase. It is emphasized that $d$-wave superconductivity can be considered as evolving from a stable U(1) spin liquid. These ideas are applied to the high-${T}_{c}$ cuprates, and their implications for the vortex structure and the phase diagram are discussed. A possible test of the topological structure of the pseudogap phase is described.

C. Gough

C. Dafermos

Ye Yuan, Jiaming Song, Umar Iqbal et al.

Denoising diffusion models hold great promise for generating diverse and realistic human motions. However, existing motion diffusion models largely disregard the laws of physics in the diffusion process and often generate physically-implausible motions with pronounced artifacts such as floating, foot sliding, and ground penetration. This seriously impacts the quality of generated motions and limits their real-world application. To address this issue, we present a novel physics-guided motion diffusion model (PhysDiff), which incorporates physical constraints into the diffusion process. Specifically, we propose a physics-based motion projection module that uses motion imitation in a physics simulator to project the denoised motion of a diffusion step to a physically-plausible motion. The projected motion is further used in the next diffusion step to guide the denoising diffusion process. Intuitively, the use of physics in our model iteratively pulls the motion toward a physically-plausible space, which cannot be achieved by simple post-processing. Experiments on large-scale human motion datasets show that our approach achieves state-of-the-art motion quality and improves physical plausibility drastically (>78% for all datasets).