AI Medical Compendium Journal:
Physical review letters

Showing 1 to 10 of 26 articles

Group Velocity Engineering of Confined Ultrafast Magnons.

Physical review letters
Quantum confinement permits the existence of multiple terahertz magnon modes in atomically engineered ultrathin magnetic films and multilayers. By means of spin-polarized high-resolution electron energy-loss spectroscopy, we report on the direct expe...

Dicke simulators with emergent collective quantum computational abilities.

Physical review letters
Using an approach inspired from spin glasses, we show that the multimode disordered Dicke model is equivalent to a quantum Hopfield network. We propose variational ground states for the system at zero temperature, which we conjecture to be exact in t...

Perceptrons with Hebbian learning based on wave ensembles in spatially patterned potentials.

Physical review letters
A general scheme to realize a perceptron for hardware neural networks is presented, where multiple interconnections are achieved by a superposition of Schrödinger waves. Spatially patterned potentials process information by coupling different points ...

Off-diagonal geometric phase for mixed states.

Physical review letters
We extend the off-diagonal geometric phase [Phys. Rev. Lett. 85, 3067 (2000)]] to mixed quantal states. The nodal structure of this phase in the qubit (two-level) case is compared with that of the diagonal mixed state geometric phase [Phys. Rev. Lett...

Biomimetic Synchronization in Biciliated Robots.

Physical review letters
Direct mechanical coupling is known to be critical for establishing synchronization among cilia. However, the actual role of the connections is still elusive-partly because controlled experiments in living samples are challenging. Here, we employ an ...

Schrödinger Dynamics and Berry Phase of Undulatory Locomotion.

Physical review letters
Spectral mode representations play an essential role in various areas of physics, from quantum mechanics to fluid turbulence, but they are not yet extensively used to characterize and describe the behavioral dynamics of living systems. Here, we show ...

One T Gate Makes Distribution Learning Hard.

Physical review letters
The task of learning a probability distribution from samples is ubiquitous across the natural sciences. The output distributions of local quantum circuits are of central importance in both quantum advantage proposals and a variety of quantum machine ...

Asymptotic Self-Similar Blow-Up Profile for Three-Dimensional Axisymmetric Euler Equations Using Neural Networks.

Physical review letters
Whether there exist finite-time blow-up solutions for the 2D Boussinesq and the 3D Euler equations are of fundamental importance to the field of fluid mechanics. We develop a new numerical framework, employing physics-informed neural networks, that d...

Predicting Dynamic Heterogeneity in Glass-Forming Liquids by Physics-Inspired Machine Learning.

Physical review letters
We introduce GlassMLP, a machine learning framework using physics-inspired structural input to predict the long-time dynamics in deeply supercooled liquids. We apply this deep neural network to atomistic models in 2D and 3D. Its performance is better...

Stochastic Gradient Descent Introduces an Effective Landscape-Dependent Regularization Favoring Flat Solutions.

Physical review letters
Generalization is one of the most important problems in deep learning, where there exist many low-loss solutions due to overparametrization. Previous empirical studies showed a strong correlation between flatness of the loss landscape at a solution a...