{"total":15,"items":[{"citing_arxiv_id":"2606.29523","ref_index":23,"ref_count":1,"confidence":0.88,"is_internal_anchor":false,"paper_title":"Stable Positive Integral Deferred Correction Methods for Positive Dynamical Systems","primary_cat":"math.NA","submitted_at":"2026-06-28T17:33:01+00:00","verdict":"UNVERDICTED","verdict_confidence":"LOW","novelty_score":7.0,"formal_verification":"none","one_line_summary":"SPIDeC methods achieve arbitrarily high-order accuracy for positive dynamical systems while unconditionally preserving positivity and equilibria via a multiplicative Volterra structure, and they are L-stable with asymptotic logarithmic contractivity under Gauss-Radau nodes.","context_count":0,"top_context_role":null,"top_context_polarity":null,"context_text":null},{"citing_arxiv_id":"2606.25934","ref_index":28,"ref_count":1,"confidence":0.88,"is_internal_anchor":false,"paper_title":"Error estimates for $A$-stable backward difference full discretizations of Willmore flow of closed surfaces","primary_cat":"math.NA","submitted_at":"2026-06-24T15:08:39+00:00","verdict":"UNVERDICTED","verdict_confidence":"LOW","novelty_score":5.0,"formal_verification":"none","one_line_summary":"Proof of optimal H1-norm error estimates for A-stable BDF1/BDF2 full discretizations of Willmore flow using surface finite elements of degree at least 2.","context_count":0,"top_context_role":null,"top_context_polarity":null,"context_text":null},{"citing_arxiv_id":"2606.25908","ref_index":2,"ref_count":1,"confidence":0.88,"is_internal_anchor":false,"paper_title":"Spectral deferred corrections parallelized across the method for differential-algebraic equations","primary_cat":"math.NA","submitted_at":"2026-06-24T14:56:17+00:00","verdict":"UNVERDICTED","verdict_confidence":"LOW","novelty_score":5.0,"formal_verification":"none","one_line_summary":"Parallel SDC with optimal coefficients solves index-1 DAEs faster than sequential SDC while retaining high accuracy in small-scale parallelism.","context_count":0,"top_context_role":null,"top_context_polarity":null,"context_text":null},{"citing_arxiv_id":"2606.23886","ref_index":48,"ref_count":1,"confidence":0.88,"is_internal_anchor":false,"paper_title":"DISPCA : A hybrid iterative-sequential approach for the identification of errors-in-variables model of linear DAE systems","primary_cat":"eess.SY","submitted_at":"2026-06-22T19:32:57+00:00","verdict":"UNVERDICTED","verdict_confidence":"LOW","novelty_score":5.0,"formal_verification":"none","one_line_summary":"A hybrid iterative-sequential method identifies linear DAE systems from errors-in-variables data by partial lagged-data stacking and iterative diagonal error-covariance estimation.","context_count":0,"top_context_role":null,"top_context_polarity":null,"context_text":null},{"citing_arxiv_id":"2606.21523","ref_index":25,"ref_count":1,"confidence":0.88,"is_internal_anchor":false,"paper_title":"Accelerating Simulation and Optimisation of Cyclic Adsorption Processes with Differentiable Programming","primary_cat":"cs.CE","submitted_at":"2026-06-19T15:21:10+00:00","verdict":"UNVERDICTED","verdict_confidence":"LOW","novelty_score":7.0,"formal_verification":"none","one_line_summary":"A JAX-based differentiable model of pressure vacuum swing adsorption accelerates cyclic steady-state simulation by 20x via Newton iteration and produces a better Pareto front with IPOPT than NSGA-II in two orders of magnitude less time on a post-combustion capture benchmark.","context_count":1,"top_context_role":"background","top_context_polarity":"background","context_text":"Periodic states of adsorption cycles-I. Direct determination and stability.Chemical Engineering Science1994,49, 1821-1829. (24) Deb, K.; Agrawal, S.; Pratap, A.; Meyarivan, T. A Fast Elitist Non-dominated Sort- ing Genetic Algorithm for Multi-objective Optimization: NSGA-II. Parallel Problem Solving from Nature PPSN VI. Berlin, Heidelberg, 2000; pp 849-858. (25) Pai, K. N.; Prasad, V.; Rajendran, A. Generalized, Adsorbent-Agnostic, Artificial Neu- ral Network Framework for Rapid Simulation, Optimization, and Adsorbent Screen- ing of Adsorption Processes.Industrial & Engineering Chemistry Research2020,59, 16730-16740. (26) Beck, J. H. Efficient Targeted Optimisation for the Design of Pressure Swing Adsorption"},{"citing_arxiv_id":"2606.05327","ref_index":34,"ref_count":1,"confidence":0.88,"is_internal_anchor":false,"paper_title":"Multimarginal flow matching with optimal transport potentials","primary_cat":"cs.LG","submitted_at":"2026-06-03T18:11:44+00:00","verdict":"UNVERDICTED","verdict_confidence":"LOW","novelty_score":7.0,"formal_verification":"none","one_line_summary":"OTP-FM extends conditional flow matching by incorporating dynamic optimal transport potentials to enable efficient multimarginal transport learning with intermediate observed marginals.","context_count":0,"top_context_role":null,"top_context_polarity":null,"context_text":null},{"citing_arxiv_id":"2605.16684","ref_index":36,"ref_count":1,"confidence":0.88,"is_internal_anchor":false,"paper_title":"GPU Performance of an Entropy-Stable Discontinuous Galerkin Euler Solver with Non-Conservative Terms","primary_cat":"math.NA","submitted_at":"2026-05-15T22:43:11+00:00","verdict":"UNVERDICTED","verdict_confidence":"LOW","novelty_score":4.0,"formal_verification":"none","one_line_summary":"GPU port of entropy-stable DG Euler solver with non-conservative buoyancy terms reaches nearly 70% of 64-bit peak on A100 volume kernels, delivers 10x speedup and 13x better energy efficiency versus CPU, and preserves symmetry-based flux savings.","context_count":1,"top_context_role":"background","top_context_polarity":"background","context_text":"Gassner, A provablystable discontinuous Galerkin spectral element approximation for moving hexahedral meshes, Computers & Fluids, 139 (2016), pp. 148-160. [35]F.-A. Kuo, M. R. Smith, C.-W. Hsieh, C.-Y. Chou, and J.-S. Wu, GPU acceleration for general conservationequations and its application to severalengineering problems, Computers & Fluids, 45 (2011), pp. 147-154. [36]M. Kurz, D. Kempf, M. P. Blind, P. Kopper, P. Offenhäuser, A. Schw arz, S. Starr, J. Keim, and A. Beck, GALÆXI: Solving complex compressible flowswith high-order discontinuous Galerkin methods on accelerator-based systems, Computer Physics Communications, 306 (2025), p. 109388. [37]M. Lefebvre, P. Guillen, J.-M. Le Gouez, and C. Basdev ant, Optimizing 2D and 3D structured Euler CFD solvers on Graphical Processing Units,"},{"citing_arxiv_id":"2605.05129","ref_index":11,"ref_count":1,"confidence":0.88,"is_internal_anchor":false,"paper_title":"BDF2-type integrator for Landau-Lifshitz-Gilbert equation in micromagnetics: a-priori error estimates","primary_cat":"math.NA","submitted_at":"2026-05-06T16:56:38+00:00","verdict":"UNVERDICTED","verdict_confidence":"LOW","novelty_score":7.0,"formal_verification":"none","one_line_summary":"A linear BDF2 finite-element integrator for the LLG equation achieves first-order spatial and second-order temporal convergence rates and converges to both weak and strong solutions.","context_count":0,"top_context_role":null,"top_context_polarity":null,"context_text":null},{"citing_arxiv_id":"2605.04561","ref_index":8,"ref_count":1,"confidence":0.88,"is_internal_anchor":false,"paper_title":"IRON: Implicit Resolvent Optimization under Noise","primary_cat":"math.OC","submitted_at":"2026-05-06T07:04:22+00:00","verdict":"UNVERDICTED","verdict_confidence":"LOW","novelty_score":6.0,"formal_verification":"none","one_line_summary":"Fully implicit resolvent discretization of noisy accelerated gradient dynamics produces a Lyapunov mean-square recursion whose contraction factor improves and stationary error scales as O(1/α), vanishing for large α under accurate inner solves.","context_count":0,"top_context_role":null,"top_context_polarity":null,"context_text":null},{"citing_arxiv_id":"2604.15850","ref_index":1,"ref_count":1,"confidence":0.88,"is_internal_anchor":false,"paper_title":"Benchmarking Two Chemical Networks used in General Circulation Models of Hot Jupiters","primary_cat":"astro-ph.EP","submitted_at":"2026-04-17T08:59:17+00:00","verdict":"CONDITIONAL","verdict_confidence":"LOW","novelty_score":5.0,"formal_verification":"none","one_line_summary":"Benchmarking reveals that a numerical escape criterion in hot Jupiter chemical kinetics solvers causes artificial quenching overestimating HCN, CH4, and NH3 by factors of 1.5-3, with remaining discrepancies traced to specific reaction rates and absent species.","context_count":0,"top_context_role":null,"top_context_polarity":null,"context_text":null},{"citing_arxiv_id":"2604.09543","ref_index":29,"ref_count":3,"confidence":0.88,"is_internal_anchor":false,"paper_title":"ANTIC: Adaptive Neural Temporal In-situ Compressor","primary_cat":"cs.LG","submitted_at":"2026-04-10T17:58:16+00:00","verdict":"UNVERDICTED","verdict_confidence":"LOW","novelty_score":6.0,"formal_verification":"none","one_line_summary":"ANTIC reduces storage for large-scale PDE simulations by orders of magnitude through adaptive temporal snapshot selection combined with continual neural-field residual compression while preserving physics accuracy.","context_count":0,"top_context_role":null,"top_context_polarity":null,"context_text":null},{"citing_arxiv_id":"2604.09166","ref_index":25,"ref_count":1,"confidence":0.88,"is_internal_anchor":false,"paper_title":"Automated Batch Distillation Process Simulation for a Large Hybrid Dataset for Deep Anomaly Detection","primary_cat":"cs.LG","submitted_at":"2026-04-10T09:51:33+00:00","verdict":"UNVERDICTED","verdict_confidence":"LOW","novelty_score":6.0,"formal_verification":"none","one_line_summary":"An automated Python simulator, calibrated to one experimental run, generates consistent time-series data for many batch distillation scenarios including anomalies, forming an openly released hybrid dataset for deep anomaly detection.","context_count":1,"top_context_role":"background","top_context_polarity":"background","context_text":"data, Processes 10 (2) (2022).doi:10.3390/pr10020335. [23] Y.-J. Park, S.-K. S. Fan, C.-Y. Hsu, A review on fault detection and process diagnostics in industrial processes, Processes 8 (9) (2020).doi:10.3390/pr8091123. [24] U. M. Ascher, L. R. Petzold, Computer methods for ordinary differential equations and differential-algebraic equations, SIAM, 1998. [25] E. Hairer, G. Wanner, Solving ordinary differential equations II: Stiff and differential-algebraic problems, Springer Berlin Heidelberg, 1991.doi:10.1007/978-3-642-05221-7. [26] P. Kunkel, Differential-algebraic equations: analysis and numerical solution, Vol. 2, European Mathematical Society, 2006. [27] S. Campbell, A. Ilchmann, V. Mehrmann, T. Reis, Applications of Differential-Algebraic Equations: Examples"},{"citing_arxiv_id":"2604.03013","ref_index":32,"ref_count":1,"confidence":0.88,"is_internal_anchor":false,"paper_title":"Spectral Deferred Corrections in the framework of Runge-Kutta methods","primary_cat":"math.NA","submitted_at":"2026-04-03T12:55:58+00:00","verdict":"UNVERDICTED","verdict_confidence":"LOW","novelty_score":7.0,"formal_verification":"none","one_line_summary":"Spectral Deferred Correction methods achieve at least order p after p iterations when viewed as Runge-Kutta methods, with order jumps of two possible for collocation methods using specific implicit error discretizations.","context_count":1,"top_context_role":"background","top_context_polarity":"background","context_text":"Lobatto IIIA methods which are implicit Runge-Kutta methods of order 2s, 2s−1, and 2s−2 with the favourable A-stability property which is desirable for stiff problems. Consider the Dahlquist's test equation du(t) dt =λu(t) withλ∈CandRe(λ)≤0. For any method, we can find the stability functionR(z), withz=λ∆t, that advances the numerical solution of the Dahlquist equation forward in timeu n+1 =R(z)u n. Following [32] (Definition 2.1) we introduce the setS={z∈C:|R(z)| ≤1}as the stability domain of a given method. Ifz∈S, then the numerical solution{u n}is bounded and is called stable. A method is called A(α) stable if{z:|arg(−z)| ≤α} ∈S withα∈[0, π/2] ([32] Definition 3.9, [33]). A method is called A-stable if it is A(α)- stable withα=π/2 [34] [32] (Definition 3."},{"citing_arxiv_id":"2512.04592","ref_index":40,"ref_count":1,"confidence":0.88,"is_internal_anchor":false,"paper_title":"Stable self-adaptive timestepping for Reduced Order Models for incompressible flows","primary_cat":"math.NA","submitted_at":"2025-12-04T09:13:31+00:00","verdict":"UNVERDICTED","verdict_confidence":"LOW","novelty_score":7.0,"formal_verification":"none","one_line_summary":"RedEigCD enables stable timestep increases up to 40 times larger than full-order models for projection-based ROMs of incompressible flows by using exact spectral bounds on reduced convective and diffusive operators together with a proof that ROM stable timesteps are at least as large as FOM ones.","context_count":0,"top_context_role":null,"top_context_polarity":null,"context_text":null},{"citing_arxiv_id":"2511.21597","ref_index":18,"ref_count":1,"confidence":0.88,"is_internal_anchor":false,"paper_title":"Low-Rank Solvers for Energy-Conserving Hamiltonian Boundary Value Methods","primary_cat":"math.NA","submitted_at":"2025-11-26T17:13:49+00:00","verdict":"UNVERDICTED","verdict_confidence":"LOW","novelty_score":5.0,"formal_verification":"none","one_line_summary":"Low-rank structure in HBVM stage equations is exploited via Krylov projection for linear cases and Newton-Krylov with adaptive time-stepping for nonlinear cases, shown efficient on semi-discretized wave equations.","context_count":0,"top_context_role":null,"top_context_polarity":null,"context_text":null}],"limit":50,"offset":0}