One binary operator eml(x,y)=exp(x)-ln(y) plus the constant 1 generates all elementary functions including sin, cos, sqrt, log, arithmetic operations, and constants e, pi, i.
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A taxonomy of SNN training algorithms is presented with the release of NeuroTrain, an open benchmarking framework for reproducible comparisons across datasets and architectures.
Single-cell patterning of bacterial spores shows that parallel initial orientations create highly ordered nematic films that buckle synchronously, while orthogonal seeding yields chaos, enabling macroscopic control of alignment and optical anisotropy in living films.
Ultrafast nonlinear Hall effect is observed in centrosymmetric black phosphorus via femtosecond laser pulses polarized along the armchair direction, persisting beyond 300 fs.
LGS pretrained on 2.5M trajectories across 16 systems matches deterministic baselines at one step and halves 20-step error while using far less compute and adapting to held-out higher-resolution flows.
High-harmonic emission in solids is made programmable by tuning effective nonlinear order and intrinsic emission phase within a photon-pathway framework, unifying modulation types across materials.
ML climate emulators degrade under seasonal distribution shifts that proxy long-term climate change, but physically motivated compositional decompositions improve out-of-distribution performance with modest in-distribution trade-offs.
BOAT optical sensors co-printed into PAM-actuated soft lattices produce repeatable signal changes that discriminate compression from extension over 100 pressure cycles, enabling a digital shadow.
DoLQ employs a sampler agent, parameter optimizer, and LLM-based scientist agent to iteratively propose, refine, and evaluate ODE candidates, yielding higher success rates and better symbolic term recovery than prior symbolic regression methods on multi-dimensional benchmarks.
AMTe4 (A=Ta,Nb; M=Ir,Rh) compounds host Weyl points within a few meV of the Fermi energy, including multiple types such as type-I, II, and III in NbRhTe4, substantially revising the topological electronic structure.
DenSNet learns the Hohenberg-Kohn map to electron density with equivariant networks and delta-learning, then maps density to energy, producing stable MD trajectories whose infrared spectra match experiment and DFT on ethanol, ethanethiol, resorcinol, and polythiophene oligomers.
Continual learning robots form a significantly more stable invariant subnetwork than constant-task controls, and preserving it improves adaptation while damaging it hurts performance.
A Zr-BMG clamp cell delivers higher neutron transmission and clean background for high-pressure INS compared to conventional CuBe cells.
A simplicial set sOb_bullet(M) of Hamiltonian forms in n-plectic geometry is shown to be a Kan complex, supplying an n-groupoid model for observables and a categorified pre-n-Hilbert space via recursive inner products.
MicroDiffuse3D is a foundation model that restores 3D microscopy images under sparse super-resolution, joint degradation, and low-SNR denoising, reporting 10.58% segmentation and 15.59% line-profile gains over baselines.
A material formulation of the cross-sectional warping problem for hyperelastic beams is derived in Voigt notation to compute effective nonlinear beam stiffness efficiently.
ReaxFF simulations find N-carbophenes stable above 1000 K, exhibit negative area thermal expansion that functionalization can flip, and allow a heat-driven transition from graphenylene to gamma-graphyne.
Quantum-chemical bonding descriptors improve machine learning predictions of materials properties and enable symbolic regression to recover intuitive expressions for force constants and thermal conductivity.
Early brokerage in academic networks produces cumulative advantage in later participation and career impact for physicists, equally for men and women.
No single post-Moore technology replaces current HPC for plasma simulations, but FPGA-class accelerators offer near-term kernel offload, non-von Neumann architectures medium-term operator acceleration, and quantum computing long-term potential for warm dense matter microphysics.
FASE pairs a spatiotemporal graph neural network and multivariate Hawkes process for crime prediction with a fairness-constrained linear program for patrol allocation, showing that allocation fairness holds in simulation but a 3.5 percentage point detection gap between minority and non-minority ZIPs
A semi-supervised teacher-student framework enables neural networks to proxy CVaR portfolio optimization using synthetic data augmentation for scarce labels and regime shifts.
A QDMI-based adapter for IQM quantum hardware enables reusable integration with Slurm and Qiskit in HPC centers, with open-source code provided.
A review of SPH modeling for global-scale impacts, emphasizing material properties across size regimes and links to Solar System observations.
citing papers explorer
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All elementary functions from a single binary operator
One binary operator eml(x,y)=exp(x)-ln(y) plus the constant 1 generates all elementary functions including sin, cos, sqrt, log, arithmetic operations, and constants e, pi, i.
-
NeuroTrain: Surveying Local Learning Rules for Spiking Neural Networks with an Open Benchmarking Framework
A taxonomy of SNN training algorithms is presented with the release of NeuroTrain, an open benchmarking framework for reproducible comparisons across datasets and architectures.
-
Shaping nematic order in bacterial films with single-cell resolution patterning
Single-cell patterning of bacterial spores shows that parallel initial orientations create highly ordered nematic films that buckle synchronously, while orthogonal seeding yields chaos, enabling macroscopic control of alignment and optical anisotropy in living films.
-
Ultrafast nonlinear Hall effect in black phosphorus
Ultrafast nonlinear Hall effect is observed in centrosymmetric black phosphorus via femtosecond laser pulses polarized along the armchair direction, persisting beyond 300 fs.
-
Latent Generative Solvers for Generalizable Long-Term Physics Simulation
LGS pretrained on 2.5M trajectories across 16 systems matches deterministic baselines at one step and halves 20-step error while using far less compute and adapting to held-out higher-resolution flows.
-
Programmable high-harmonic emission in solids through photon pathways
High-harmonic emission in solids is made programmable by tuning effective nonlinear order and intrinsic emission phase within a photon-pathway framework, unifying modulation types across materials.
-
No Epoch Like the Present: Robust Climate Emulation Requires Out-of-Distribution Generalisation
ML climate emulators degrade under seasonal distribution shifts that proxy long-term climate change, but physically motivated compositional decompositions improve out-of-distribution performance with modest in-distribution trade-offs.
-
Bidirectional Optical sensors for Actuation Tracking (BOAT) in soft lattice systems
BOAT optical sensors co-printed into PAM-actuated soft lattices produce repeatable signal changes that discriminate compression from extension over 100 pressure cycles, enabling a digital shadow.
-
Discovering Ordinary Differential Equations with LLM-Based Qualitative and Quantitative Evaluation
DoLQ employs a sampler agent, parameter optimizer, and LLM-based scientist agent to iteratively propose, refine, and evaluate ODE candidates, yielding higher success rates and better symbolic term recovery than prior symbolic regression methods on multi-dimensional benchmarks.
-
Fermi energy Weyl nodes in $\mathbf{AM}$Te$_4$ ($\mathbf{A}$=Ta, Nb, $\mathbf{M}$=Ir, Rh)
AMTe4 (A=Ta,Nb; M=Ir,Rh) compounds host Weyl points within a few meV of the Fermi energy, including multiple types such as type-I, II, and III in NbRhTe4, substantially revising the topological electronic structure.
-
Enhancing molecular dynamics with equivariant machine-learned densities
DenSNet learns the Hohenberg-Kohn map to electron density with equivariant networks and delta-learning, then maps density to energy, producing stable MD trajectories whose infrared spectra match experiment and DFT on ethanol, ethanethiol, resorcinol, and polythiophene oligomers.
-
Evidence of an Emergent "Self" in Continual Robot Learning
Continual learning robots form a significantly more stable invariant subnetwork than constant-task controls, and preserving it improves adaptation while damaging it hurts performance.
-
Zr-based bulk metallic glass clamp cell for high-pressure inelastic neutron scattering
A Zr-BMG clamp cell delivers higher neutron transmission and clean background for high-pressure INS compared to conventional CuBe cells.
-
A Simplicial Approach to Higher Geometric Quantization
A simplicial set sOb_bullet(M) of Hamiltonian forms in n-plectic geometry is shown to be a Kan complex, supplying an n-groupoid model for observables and a categorified pre-n-Hilbert space via recursive inner products.
-
MicroDiffuse3D: A Foundation Model for 3D Microscopy Imaging Restoration
MicroDiffuse3D is a foundation model that restores 3D microscopy images under sparse super-resolution, joint degradation, and low-SNR denoising, reporting 10.58% segmentation and 15.59% line-profile gains over baselines.
-
The cross-sectional warping problem for hyperelastic beams: An efficient formulation in Voigt notation
A material formulation of the cross-sectional warping problem for hyperelastic beams is derived in Voigt notation to compute effective nonlinear beam stiffness efficiently.
-
A ReaxFF-based thermomechanical analysis of N-carbophenes: phase-change, thermal expansion, and high temperature synthesis pathway
ReaxFF simulations find N-carbophenes stable above 1000 K, exhibit negative area thermal expansion that functionalization can flip, and allow a heat-driven transition from graphenylene to gamma-graphyne.
-
A critical assessment of bonding descriptors for predicting materials properties
Quantum-chemical bonding descriptors improve machine learning predictions of materials properties and enable symbolic regression to recover intuitive expressions for force constants and thermal conductivity.
-
Cumulative Advantage of Brokerage in Academia
Early brokerage in academic networks produces cumulative advantage in later participation and career impact for physicists, equally for men and women.
-
Post-Moore Technologies for Plasma Simulation: A Community Roadmap
No single post-Moore technology replaces current HPC for plasma simulations, but FPGA-class accelerators offer near-term kernel offload, non-von Neumann architectures medium-term operator acceleration, and quantum computing long-term potential for warm dense matter microphysics.
-
FASE : A Fairness-Aware Spatiotemporal Event Graph Framework for Predictive Policing
FASE pairs a spatiotemporal graph neural network and multivariate Hawkes process for crime prediction with a fairness-constrained linear program for patrol allocation, showing that allocation fairness holds in simulation but a 3.5 percentage point detection gap between minority and non-minority ZIPs
-
Portfolio Optimization Proxies under Label Scarcity and Regime Shifts via Bayesian and Deterministic Students under Semi-Supervised Sandwich Training
A semi-supervised teacher-student framework enables neural networks to proxy CVaR portfolio optimization using synthetic data augmentation for scarce labels and regime shifts.
-
Practical HPCQC Integration with QDMI: A Real-Hardware Case Study with IQM Systems
A QDMI-based adapter for IQM quantum hardware enables reusable integration with Slurm and Qiskit in HPC centers, with open-source code provided.
-
Recent advances in modelling of global-scale collisions using smoothed particle hydrodynamics
A review of SPH modeling for global-scale impacts, emphasizing material properties across size regimes and links to Solar System observations.
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Human Ancestries Simulation and Inference: a Review of Ancestral Recombination Graph-Based Approaches
A review of ARG-based simulation and inference methods in population genetics, evaluating their performance, usability, and biological realism with links to software.