Wigner
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Related Articles from SNS
Feasibility study of continuous electronic Pomeranchuk cooling with a flavor-degenerate Wigner crystal
arXiv:2605.31307v1 Announce Type: cross Abstract: Achieving sub-millikelvin electron temperatures in nanoelectronic devices could unveil new transport phenomena, extend quantum coherence times, and enhance the precision of quantum metrology. However, maintaining such low temperatures continuously remains a long-standing challenge. Here, we propose and simulate an on-chip cooling cycle that harnesses the entropy difference between an electron liquid (EL) and a Wigner crystal (WC) in...
On the Role of the Double Fourier Sphere Method in Fast Algorithms on SO(3)
arXiv:2602.06677v3 Announce Type: replace Abstract: We analyze the Double Fourier Sphere (DFS) method on the rotation group $\mathcal{SO}(3)$ in the frequency domain and demonstrate its central role in fast algorithms. Fast Fourier algorithms on $\mathcal{SO}(3)$ are commonly formulated as a Wigner transform - mapping harmonic to Fourier coefficients - followed by a Fourier transform. We revisit this formulation and interpret the Wigner transform as an explicit realization of the DFS method,...
Robust Random Graph Matching in Dense Graphs via an Approximate Message Passing Type Algorithm
arXiv:2412.16457v3 Announce Type: replace-cross Abstract: In this paper, we focus on the matching recovery problem between a pair of correlated Gaussian Wigner matrices with a latent vertex correspondence. We are particularly interested in a robust version of this problem such that our observation is a perturbed input $(A+E,B+F)$ where $(A,B)$ is a pair of correlated Gaussian Wigner matrices and $E,F$ are adversarially chosen matrices supported on an unknown $\epsilon n * \epsilon n$...
Guided progressive reconstructive imaging: a new quantization-based framework for low-dose, high-throughput and real-time analytical ptychography
Announce Type: replace Abstract: By profiting from recent developments in detector technologies, making it possible to access a stream of detection events with few-ns time resolutions, a new ptychographic workflow is established. This methodological framework, referred to as guided progressive reconstructive imaging, relies on a quantization-based description of the acquired intensity, through an elementary derivation. Established direct phase retrieval solutions, such as the Wigner...
A Husserlian ontology of the science of physics
Announce Type: new Abstract: Since 1939, when Wigner published his proposal to define particles via symmetries expressed as algebraic groups, we have seen a long stream of attempts to formulate an ontology of matter based on mathematics. It has become apparent that such attempts must fail, and more particularly that we cannot derive an ontology of matter from the Standard Model on the basis of quantum field theory. We briefly recapitulate the reasons for this and demonstrate how the...
A Cartesian-3j Framework for Machine Learning Interatomic Potentials
Announce Type: replace Abstract: Machine learning interatomic potentials (MLIPs) have brought substantial gains in the extrapolation capability in computational chemistry. However, most equivariant models are typically built with spherical tensors (STs), while Cartesian tensor formulations remain less developed despite their natural alignment with atomic coordinates and tensorial targets. In this work, we develop a Cartesian framework for irreducible Cartesian tensors (ICTs) by introduce the...
How heavy can a neutron star get?
How heavy can a neutron star get? Sadie Harley Scientific Editor Andrew Zinin Lead Editor The physics of neutron stars are almost too fantastic to believe: something the weight of two suns compacted to a sphere the size of a city.
A Cartesian-3j Framework for Machine Learning Interatomic Potentials
Announce Type: replace-cross Abstract: Machine learning interatomic potentials (MLIPs) have brought substantial gains in the extrapolation capability in computational chemistry. However, most equivariant models are typically built with spherical tensors (STs), while Cartesian tensor formulations remain less developed despite their natural alignment with atomic coordinates and tensorial targets. In this work, we develop a Cartesian framework for irreducible Cartesian tensors (ICTs) by...
Human-Like Neural Nets by Catapulting
Human-like Neural Nets by Catapulting Speculative proposal to create artificial neural nets with human-like performance by high-learning-rate/regularization training of overparameterized NNs to trigger catapulting/grokking. Over-parameterization as a route to true generalization would resolve many outstanding mysteries of artificial versus natural intelligence. There are many mysteries about deep learning and human intelligence, but we could describe the biggest anomaly this way: why are...
Enhancing Neural-Network Variational Monte Carlo through Basis Transformation
arXiv:2604.15888v2 Announce Type: replace-cross Abstract: Neural-network variational Monte Carlo (NNVMC) has emerged as a powerful tool for solving quantum many-body problems, yet systematic pathways for improving its accuracy remain largely heuristic. Here, we introduce a physically motivated basis transformation for NNVMC that enhances variational expressivity without increasing the complexity of the neural-network ansatz itself. By formulating the many-body wave function in a Gaussian...