Introduces graph-to-image prediction of per-node dynamic stability landscapes in oscillator networks from topology, releases two 10k-graph datasets, and shows GNN-CNN models achieve good accuracy with cross-size generalization.
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PEPSKit.jl is a new Julia software package providing high-level algorithms for iPEPS tensor-network simulations of 2D quantum systems with symmetry support.
Linear estimators point-identify parameters of dynamic fixed effects logit models with only time effects when at least five time periods are available, enabling root-N consistent estimation.
Finite fixed-point iterations in implicit symplectic integrators induce a perturbed symplectic matrix that remains skew-symmetric, with one diagonal block vanishing and others showing O(h^{M+1}) perturbations, leading to controlled volume and energy errors.
fixest is an R package that delivers fast fixed-effects and other econometric estimations through a novel fixed-point acceleration algorithm in C++.
DenseAMs show tradeoffs between entropy production, retrieval accuracy, and speed at intermediate loads, with a new failure mode in higher-order networks at finite temperature.
The paper presents ModelPredictiveControl.jl, an open-source Julia toolkit for model predictive control including nonlinear, economic, and successive linearization variants, illustrated with CSTR and inverted pendulum simulations and benchmarked against MATLAB.
A Gauss-Newton-based parallel 3-D TEM inversion method employs rational near-best approximations of the matrix exponential to make time-dependent computations independent of the number of observation times.
An amortized reinforcement learning method enables immediate, observation-driven sequential optimization of genetic circuits while accounting for both intrinsic stochasticity and cross-laboratory variability without repeated inference steps.
An adaptive anisotropic composite quadrature strategy combined with refresh-based training narrows the gap between training and reference losses in neural residual minimization for PDEs while using quadrature points more efficiently.
A new Bayesian multiscale framework with cut inference jointly models heterogeneous viral load trajectories and household transmission, recovering parameters without bias on simulated data when viral sampling is frequent.
Gradient-based optimization of SUPER and FTPE pulse protocols via auto-differentiation and uniTEMPO yields higher preparation fidelities than resonant pi-pulses or standard two-photon excitation, with the advantage increasing at higher temperatures.
Reformulating DRL in a moving reference frame enables reliable control of rapid transitions between mode-locked states in a 1D RDE model by separating fast detonation propagation from slower operating-mode dynamics.
A distributionally robust PAC-Bayesian approach derives sub-Gaussian loss proxies and performance bounds tied to closed-loop operator norms via system level synthesis, enabling optimization-based safety certificates for controllers facing sim-to-real gaps.
Adaptive multi-criteria scoring with online logistic regression for Benders subproblem selection yields statistically significant runtime and integral improvements on 135 survivable network design instances.
Extends linear response theory to nonautonomous systems and applies it to optimal fingerprinting for attributing changes to multiple forcings in time-dependent backgrounds, with numerical tests on a climate model.
High-order essentially explicit discretizations using Fourier Galerkin plus projection-relaxation conserve mass, momentum, and energy for BBM, KdV, and NLS equations.
An algebraic approach defines semi-algebraic parameter sets from underlying polynomial structures in evolutionary processes before likelihood maximization, showing compatibility with existing statistical EvAM models while adding parameter-space information.
A parallel two-level stepping method for athermal quasistatic deformation achieves average computational speed-ups of 2.02 to 6.33 times with 4 to 32 threads.
A two-level HPRNN framework is proposed that embeds physical properties into latent spaces to surrogate nonlinear elasto-plastic yarn behavior and meso-to-macro transitions for woven composites.
Simulations demonstrate that sinusoidal thermal boundary conditions reduce entropy generation in power-law fluid natural convection relative to uniform heating, with shear-thinning fluids producing stronger buoyancy-driven flow and higher Nusselt numbers.
A 3D mechano-geometric multicellular model integrates cell mechanics, irreversible wall growth, and deformable geometry to simulate apical stem-cell-driven plant morphogenesis.
Methods estimate multiplicative and additive noise in AEM data from repeat lines with non-linear altitude correction, Gaussianise the noise, estimate time-channel correlations in the covariance matrix, and conclude that a diagonal covariance suffices for regularised time-domain AEM imaging.
Extension of GSM2 model to cell population level for mechanistic TCP and NTCP modeling in particle therapy accounting for physical and environmental factors.
citing papers explorer
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Learning Dynamic Stability Landscapes in Synchronization Networks
Introduces graph-to-image prediction of per-node dynamic stability landscapes in oscillator networks from topology, releases two 10k-graph datasets, and shows GNN-CNN models achieve good accuracy with cross-size generalization.
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PEPSKit.jl: A Julia package for projected entangled-pair state simulations
PEPSKit.jl is a new Julia software package providing high-level algorithms for iPEPS tensor-network simulations of 2D quantum systems with symmetry support.
-
Linear estimations of dynamic fixed effects logit models only with time effects
Linear estimators point-identify parameters of dynamic fixed effects logit models with only time effects when at least five time periods are available, enabling root-N consistent estimation.
-
Symplectic Error of Implicit Symplectic Integrators: A Qualitative Structural Analysis
Finite fixed-point iterations in implicit symplectic integrators induce a perturbed symplectic matrix that remains skew-symmetric, with one diagonal block vanishing and others showing O(h^{M+1}) perturbations, leading to controlled volume and energy errors.
-
fixest: A fast and feature-rich framework for econometric estimations in R
fixest is an R package that delivers fast fixed-effects and other econometric estimations through a novel fixed-point acceleration algorithm in C++.
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Stochastic Thermodynamics of Associative Memory
DenseAMs show tradeoffs between entropy production, retrieval accuracy, and speed at intermediate loads, with a new failure mode in higher-order networks at finite temperature.
-
ModelPredictiveControl.jl: advanced process control made easy in Julia
The paper presents ModelPredictiveControl.jl, an open-source Julia toolkit for model predictive control including nonlinear, economic, and successive linearization variants, illustrated with CSTR and inverted pendulum simulations and benchmarked against MATLAB.
-
Scalable parallel 3-D TEM inversion via rational approximation of the matrix exponential
A Gauss-Newton-based parallel 3-D TEM inversion method employs rational near-best approximations of the matrix exponential to make time-dependent computations independent of the number of observation times.
-
Sequential Design of Genetic Circuits Under Uncertainty With Reinforcement Learning
An amortized reinforcement learning method enables immediate, observation-driven sequential optimization of genetic circuits while accounting for both intrinsic stochasticity and cross-laboratory variability without repeated inference steps.
-
Adaptive anisotropic composite quadratures for residual minimisation in neural PDE approximations
An adaptive anisotropic composite quadrature strategy combined with refresh-based training narrows the gap between training and reference losses in neural residual minimization for PDEs while using quadrature points more efficiently.
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Bayesian inference for disease transmission models informed by viral dynamics
A new Bayesian multiscale framework with cut inference jointly models heterogeneous viral load trajectories and household transmission, recovering parameters without bias on simulated data when viral sampling is frequent.
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Efficient optimisation of multi-parameter quantum control protocols for strongly-coupled systems
Gradient-based optimization of SUPER and FTPE pulse protocols via auto-differentiation and uniTEMPO yields higher preparation fidelities than resonant pi-pulses or standard two-photon excitation, with the advantage increasing at higher temperatures.
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Timescale Separation Enables Deep Reinforcement Learning Control of Rotating Detonation Engine Mode Transitions
Reformulating DRL in a moving reference frame enables reliable control of rapid transitions between mode-locked states in a 1D RDE model by separating fast detonation propagation from slower operating-mode dynamics.
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Distributionally Robust PAC-Bayesian Control
A distributionally robust PAC-Bayesian approach derives sub-Gaussian loss proxies and performance bounds tied to closed-loop operator norms via system level synthesis, enabling optimization-based safety certificates for controllers facing sim-to-real gaps.
-
Adaptive Subproblem Selection in Benders Decomposition for Survivable Network Design Problems
Adaptive multi-criteria scoring with online logistic regression for Benders subproblem selection yields statistically significant runtime and integral improvements on 135 survivable network design instances.
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Linear Response and Optimal Fingerprinting for Nonautonomous Systems
Extends linear response theory to nonautonomous systems and applies it to optimal fingerprinting for attributing changes to multiple forcings in time-dependent backgrounds, with numerical tests on a climate model.
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Conserving mass, momentum, and energy for the Benjamin-Bona-Mahony, Korteweg-de Vries, and nonlinear Schr\"odinger equations
High-order essentially explicit discretizations using Fourier Galerkin plus projection-relaxation conserve mass, momentum, and energy for BBM, KdV, and NLS equations.
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An Algebraic Approach to Evolutionary Accumulation Models
An algebraic approach defines semi-algebraic parameter sets from underlying polynomial structures in evolutionary processes before likelihood maximization, showing compatibility with existing statistical EvAM models while adding parameter-space information.
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Parallel athermal quasistatic deformation stepping of molecular systems
A parallel two-level stepping method for athermal quasistatic deformation achieves average computational speed-ups of 2.02 to 6.33 times with 4 to 32 threads.
-
Multiscale Analysis of Woven Composites Using Hierarchical Physically Recurrent Neural Networks
A two-level HPRNN framework is proposed that embeds physical properties into latent spaces to surrogate nonlinear elasto-plastic yarn behavior and meso-to-macro transitions for woven composites.
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Effects of Thermal Boundary Conditions on Natural Convection and Entropy Generation in Non-Newtonian Power-Law Fluids
Simulations demonstrate that sinusoidal thermal boundary conditions reduce entropy generation in power-law fluid natural convection relative to uniform heating, with shear-thinning fluids producing stronger buoyancy-driven flow and higher Nusselt numbers.
-
3D mechano-geometric multicellular model of apical stem cell-driven plant morphogenesis
A 3D mechano-geometric multicellular model integrates cell mechanics, irreversible wall growth, and deformable geometry to simulate apical stem-cell-driven plant morphogenesis.
-
Estimating noise for airborne electromagnetic data from repeat flight lines or inversion residuals
Methods estimate multiplicative and additive noise in AEM data from repeat lines with non-linear altitude correction, Gaussianise the noise, estimate time-channel correlations in the covariance matrix, and conclude that a diagonal covariance suffices for regularised time-domain AEM imaging.
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Mechanistic driven TCP and NTCP modeling for particle therapy accounting for a broad range of physical irradiation parameters and tissue environmental conditions
Extension of GSM2 model to cell population level for mechanistic TCP and NTCP modeling in particle therapy accounting for physical and environmental factors.
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LCS.jl: A High-Performance, Multi-Platform Computational Model in Julia for Turbulent Particle-Laden Flows
LCS.jl delivers a portable Julia implementation of multiphase turbulence simulation with a new GPU particle-communication method that cuts communication time to 10% and achieves up to 18x GPU speedup over CPU while maintaining strong scaling above 85% on hundreds of GPUs.
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StreamSampling.jl: Efficient Sampling from Data Streams in Julia
StreamSampling.jl implements efficient one-pass sampling algorithms for data streams in Julia with constant memory footprint and performance gains over traditional methods.
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D-PDLP: Scaling PDLP to Distributed Multi-GPU Systems
D-PDLP is the first distributed multi-GPU framework for PDLP that uses 2D grid partitioning of the constraint matrix plus nonzero-aware and random-permutation strategies to scale PDHG iterations with low overhead and full FP64 accuracy.
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Basis pursuit by inconsistent alternating projections
New inconsistent alternating projection scheme for basis pursuit with linear convergence proofs and competitive benchmarks.
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The domain-of-dependence stabilization for cut-cell meshes is fully discretely stable
Domain-of-dependence stabilization for cut-cell meshes achieves fully discrete stability for linear advection under a CFL condition independent of arbitrarily small cell sizes.
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Ageing-aware Energy Management for Residential Multi-Carrier Energy Systems
Develops an ageing-aware nonlinear economic MPC for multi-carrier residential energy systems using physics-based battery models, reporting 10% grid cost reduction and 20% less degradation with LFP vs NMC cells plus 10%/5% gains over state-of-the-art in summer conditions.
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Minimalistic Terminal Editor for Julia Programming -- MinTEJ: A Friendly Approach for a Scientific Programmer
MinTEJ is a new terminal editor for Julia that uses Sequential Modal Interaction Architecture to integrate editing, running, and debugging while showing lower memory and CPU use than VS Code or Notepad++.
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Distributed Energy System Design including Unbalanced AC Power Flow for Large LV Networks with ADMM
A hybrid MILP-NLP-complementarity decomposition solved via spatial/temporal ADMM yields up to 13x speedup on unbalanced AC power flow-constrained DES design for networks with 55 loads, with maximum 0.61% optimality gap.
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Sequential topology optimization: SIMP initialization for level-set boundary refinement
A sequential topology optimization approach uses SIMP results to initialize level-set refinement via signed distance function transfer on 3D meshes, achieving comparable compliance with up to 4.6x speedup on benchmarks.
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An Efficient Hybrid Heuristic for the Transmission Expansion Planning under Uncertainty
A progressive hedging hybrid heuristic improves average solution cost by 5.28% over a strong baseline for stochastic transmission expansion planning on systems up to 10,000 nodes within a 2-hour limit.
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Bulk-mediated interaction between impurities in 1D atomic chains
Electron-mediated interaction between two impurities in a 1D atomic chain changes sign and magnitude with adatom separation and system doping.
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Quantum eigenvalues and eigenfunctions of an electron confined between conducting planes
An electron between grounded planes has its eigenvalues and eigenfunctions computed from an image-charge double-well potential, recovering particle-in-a-box behavior at small separation and degenerate bound states at large separation.
- IntegrateUnitary.jl: A Julia package for symbolic integration over Haar measures
- Adaptive Generalized Elliptical Slice Sampling
- Scheduling Electricity Production Units to Mitigate Severe Weather Impact: An Efficient Computational Implementation