High-Dimensional Partial Differential Equations in Science and Engineering
Bibliographic record
Abstract
Singularity-free methods for the time-dependent Schrodinger equation for nonlinear molecules in intense laser fields--A non-perturbative approach by A. D. Bandrauk and H. Lu Feasibility and competitiveness of a reduced basis approach for rapid electronic structure calculations in quantum chemistry by E. Cances, C. Le Bris, Y. Maday, N. C. Nguyen, A. T. Patera, and G. S. H. Pau Some fundamental mathematical properties in atomic and molecular quantum mechanics by G. Chen, Z. Ding, A. Perronnet, M. O. Scully, R. Xie, and Z. Zhang Sparse tensor-product Fokker-Planck-based methods for nonlinear bead-spring chain models of dilute polymer solutions by P. Delaunay, A. Lozinski, and R. G. Owens A partial differential equation for credit derivatives pricing by M. Escobar and L. Seco A short review on computational issues arising in relativistic atomic and molecular physics by M. J. Esteban Model Hamiltonians in density functional theory by P. Gori-Giorgi, J. Toulouse, and A. Savin Simulation of quantum-classical dynamics by surface-hopping trajectories by H. Kim and R. Kapral Simulating realistic and nonadiabatic chemical dynamics: Application to photochemistry and electron transfer reactions by D. M. Koch, Q. K. Timerghazin, and G. H. Peslherbe A Maxwell-Schrodinger model for non-perturbative laser-molecule interaction and some methods of numerical computation by E. Lorin, S. Chelkowski, and A. Bandrauk Parareal in time algorithm for kinetic systems based on model reduction by Y. Maday.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".