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Differentiable Particle-Mesh Ewald with Cartesian Tensor Message Passing for Learning Long-Range Electrostatics and Dipole Response
Announce Type: new Abstract: Machine learning interatomic potentials (MLIPs) can approach quantum accuracy for short-range chemistry, but most architectures remain local and fail to capture the long-range electrostatic and polarization interactions essential for ionic, polar, and interfacial systems. Recent Ewald-based MLIPs show that locally predicted electrostatic variables can recover important long-range physics, including multipolar response. However, many energy-based implementations...
B&M's 'perfect' £4 item 'helps keep home tidy' similar to £24 one at The Range
B&M's 'perfect' £4 item 'helps keep home tidy' similar to £24 one at The Range B&M's budget-friendly £4 Spaceways 3 Tier Storage Unit is an affordable storage solution Homeowners searching for extra storage on a tight budget may well have found their answer at B&M right now. The discount retailer, well known for its ever-growing range of cut-price homeware and furniture, promises the bargain item will "help keep your home tidy". Describing the Spaceways 3 Tier Storage Unit on its website, a...
'Gardens come to life' thanks to B&M £5 item similar to £21 The Range option
'Gardens come to life' thanks to B&M £5 item similar to £21 The Range option The solar-powered garden accessory lights up with a warm glow at dusk and is over £15 cheaper than a similar item at The Range Summer is just around the corner and plenty of shoppers are focusing on refreshing their gardens before the warmer weather arrives. B&M is currently offering an expanding selection of outdoor furniture, lighting and decorative accessories alongside its regular homeware deals - but one...
A Cluster Expansion and the Decay of Correlations of the 1D Long-Range Ising Model at Low Temperatures
Mathematical Physics [Submitted on 12 Feb 2026 (v1), last revised 29 May 2026 (this version, v2)] Title:A Cluster Expansion and the Decay of Correlations of the 1D Long-Range Ising Model at Low Temperatures View PDF HTML (experimental)Abstract:In this work, a convergent low-temperature cluster expansion of the one-dimensional long-range ferromagnetic Ising model with polynomial decay $\alpha\in (1,2]$ is developed; that is, $J(r)=r^{-\alpha}$. As an application, the $n$-point correlations...
Fears Russia could threaten Arctic chokepoint that puts London within range of hypersonic missiles
Fears Russia could threaten Arctic chokepoint that puts London within range of hypersonic missiles UK’s defence secretary has warned Russia poses ‘greatest threat to Arctic and High North security since the Cold War’ amid growing military presence - Bookmark - CommentsGo to comments Russia is threatening a strategic chokepoint in the Arctic, control of which would place it within missile range of London, Norway’s defence minister has warned. Tore Sandvik told The Times that he was concerned...
'Absolute shocker!' | Ecclestone misses the stumps from close range!
England vs India, third women's T20: Sophie Ecclestone misses the stumps from close range Tuesday 2 June 2026 20:33, UK Please use Chrome browser for a more accessible video player Sophie Ecclestone endures a rare lapse in the field, missing the non-striker’s stumps from close range with an underarm attempt to run out Richa Ghosh.
Prolate spheroidal wave functions enable fast and exponent-aware long-range machine learning interatomic potentials
arXiv:2606.06617v1 Announce Type: cross Abstract: Long-range interactions such as electrostatics and dispersion remain a central bottleneck for machine learning interatomic potentials (MLIPs), especially in ionic, polar and interfacial systems. Ewald-based reciprocal-space mechanisms provide a physically grounded route for capturing these nonlocal effects, but often require dense Fourier grids and can become memory-limited at scale.
Prolate spheroidal wave functions enable fast and exponent-aware long-range machine learning interatomic potentials
arXiv:2606.06617v1 Announce Type: new Abstract: Long-range interactions such as electrostatics and dispersion remain a central bottleneck for machine learning interatomic potentials (MLIPs), especially in ionic, polar and interfacial systems. Ewald-based reciprocal-space mechanisms provide a physically grounded route for capturing these nonlocal effects, but often require dense Fourier grids and can become memory-limited at scale. This problem is particularly pronounced in molecular...
SHARP: Sleep-based Hierarchical Accelerated Replay for Long Range Non-Stationary Temporal Pattern Recognition
Announce Type: replace Abstract: Learning long-range non-stationary temporal patterns remains a core challenge for modern sequence models, particularly in strict streaming settings. In these settings, data arrive sequentially and must be processed in a single pass without simultaneously revisiting past observations. Standard architectures, including recurrent neural networks and transformers, are constrained by either truncated backpropagation through time horizon or explicit input window...
ReciNet: Reciprocal Space-Aware Long-Range Modeling for Crystalline Property Prediction
Announce Type: replace Abstract: Predicting properties of crystals from their structures is a fundamental yet challenging task in materials science. Unlike molecules, crystal structures exhibit infinite periodic arrangements of atoms, requiring methods capable of capturing both local and global information effectively. However, current works fall short of capturing long-range interactions within periodic structures.