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Related Articles from SNS
Co-condensation and multivalency enable acetylation-sensitive, concentration-robust assembly of BRD4 condensates
Announce Type: new Abstract: Biomolecular condensates must assemble at specific locations and times inside living cells to perform their biological functions. However, it remains unclear how condensate formation achieves high spatiotemporal precision, responding sensitively to local chemical modifications while remaining robust to fluctuations in protein concentration. Here we study chromatin-associated BRD4 condensates to identify a physical mechanism that enables this combination of...
Physicists discover attractive forces between molecular condensates may cause running off
Inside cells, certain functions are carried out by locally adjusting molecular composition. This condensation of material results in the formation of dense droplets that can dynamically rearrange. Because of this, interactions between such dense regions determine the shaping of condensates.
Energy spectra and cascade in the spin turbulence of a driven spinor Bose-Einstein condensate
arXiv:2606.00766v1 Announce Type: cross Abstract: We investigate the spin-interaction energy spectrum of spin turbulence in a driven spinor Bose-Einstein condensate. Continuous spin driving of a spin-1 condensate produces a nonequilibrium steady state with spatially fluctuating magnetization. We observe a power-law scaling consistent with the $-7/3$ exponent predicted for spin-wave turbulence, which persists across our full range of drive strengths despite substantial changes in the spectral...
Distilling first-principles accuracy into compact machine learning potentials for condensed-phase chemistry
Announce Type: new Abstract: Accurate machine learning interatomic potentials (MLIPs) have made first-principles-quality potential energy surfaces increasingly accessible for condensed-phase chemistry, but their inference cost can still limit the sampling needed to compute experimentally relevant observables. In this work, we combine transfer learning and knowledge distillation to construct compact "student" models that retain the accuracy of much larger "teacher" models obtained by applying...
Comment on "Specific heat of an ideal Bose gas above the Bose condensation temperature," [Am. J. Phys. 72(9), 1193--1194 (2004)]
Physics > History and Philosophy of Physics [Submitted on 20 Apr 2026 (v1), last revised 8 Jun 2026 (this version, v3)] Title:Comment on "Specific heat of an ideal Bose gas above the Bose condensation temperature," [Am. J. Phys. 72(9), 1193--1194 (2004)]
An Efficient and Scalable Graph Condensation with Structure-Preserving
arXiv:2605.31016v1 Announce Type: new Abstract: Graph condensation (GC) is pivotal for enabling Graph Neural Networks (GNNs) deployment in resource-constrained scenarios by compressing large-scale graphs into compact synthetic counterparts. Existing GC methods commonly suffer from computational inefficiency due to coupled optimization as well as encountering poor generalization across GNN architectures. To address these challenges, this study proposes an Efficient and Scalable Graph...
Text-attributed Graph Condensation via Text Selection and Attribute Matching
Announce Type: new Abstract: Text-Attributed Graph (TAG) is an important type of graph structured data, where each node has a text description. TAG models usually train a Graph Neural Network (GNN) and language model jointly, which leads to high space and time consumption, especially on large datasets. To mitigate this, we propose TAGSAM, a condensation method that compresses TAGs while preserving training accuracy.
Polalrized reservoirs in dynamics of polariton condensation
arXiv:2606.04808v1 Announce Type: new Abstract: We review the problem of description of the dynamics of driven-disspipative spinor polariton condensates, focusing on the terms corresponding to the coupling between a macroscopic wavefunction of the condensdate and incoherent excitonic reservoir created by a non-resonant pump. We demonstrate that the existing version of the theory breaks down in case, when reservoir has non-zero components of the Stokes vector corresponding to in-plane linear...
Comment on "Possibility of superradiant neutrino emission by atomic condensate" by M. Blasone, L. Gastaldo and F. Romeo, Phys. Rev. D 113, 053010 (2026)
Quantum Physics [Submitted on 3 Jun 2026] Title:Comment on "Possibility of superradiant neutrino emission by atomic condensate" by M. Blasone, L. Gastaldo and F. Romeo, Phys. Rev. D 113, 053010 (2026) View PDF HTML (experimental)Abstract:We show that the recent proposal for superradiant emission of neutrinos cannot evade our proof that superradiant neutrino emission is fundamentally impossible.
Geometry-Aware Dataset Condensation for Diffusion Model Training
Announce Type: new Abstract: Dataset condensation aims to construct compact datasets from real data via synthesis or selection. However, existing approaches are ill-suited for diffusion model training: synthetic data generation often yields low-fidelity samples unsuitable for authentic modeling, while real subset selection typically fails to preserve the distributional geometry required by diffusion likelihood objectives.