Result artifacts are organized by the five scientific domains used in the paper. Each benchmark problem has one subdirectory for its evolved program (*_best.py, *_best.cpp, or *_best.rs) and, where applicable, its concrete evaluated artifact (*_best_construction.json).
| Task |
What it is |
quantum_compilation/qubit_routing_on_superconducting_quantum_computer/ |
Routing policy for two-qubit gates on a superconducting chip, minimizing added SWAPs (Rust) |
quantum_compilation/compilation_for_zoned_neutral_atom_quantum_architectures/ |
Compilation policy for a zoned neutral-atom architecture; the paper reports geometric-mean execution time |
| Task |
What it is |
astrodynamics/mariner_10/ |
Gravity-assist trajectory design for Mariner 10 |
astrodynamics/voyager_2/ |
Gravity-assist trajectory design for Voyager 2 |
astrodynamics/galileo/ |
Gravity-assist trajectory design for Galileo |
astrodynamics/cassini/ |
Gravity-assist trajectory design for Cassini |
astrodynamics/rosetta/ |
Gravity-assist trajectory design for Rosetta |
| Task |
What it is |
scientific_algorithms/lasso_regularization_path/ |
LASSO solver along a full regularization path (ms) |
scientific_algorithms/zapbench_forecasting_h1/ |
Whole-brain activity forecasting at horizon 1 |
scientific_algorithms/zapbench_forecasting_h4/ |
Whole-brain activity forecasting at horizon 4 |
scientific_algorithms/zapbench_forecasting_h8/ |
Whole-brain activity forecasting at horizon 8 |
scientific_algorithms/zapbench_forecasting_h16/ |
Whole-brain activity forecasting at horizon 16 |
scientific_algorithms/zapbench_forecasting_h32/ |
Whole-brain activity forecasting at horizon 32 |
scientific_algorithms/single_cell_rna_seq_denoising/ |
Single-cell RNA-seq denoising policy, evaluated with the OpenProblems benchmark |
Additional released artifacts: scientific_algorithms/ahc039_purse_seine_fishing/ and scientific_algorithms/ahc058_apple_production_planning/.
| Task |
What it is |
ai_foundations/trimul/ |
Triton kernel for triangular matrix multiplication (headline result on H100, ms) |
ai_foundations/asymmetric_matrix_multiplication/ |
Triton kernel for asymmetric matmul (H200, ms) |
ai_foundations/batched_cumsum/ |
Triton kernel for batched prefix-sum (H200, ms) |
ai_foundations/parallel_scaling_law/ |
Symbolic scaling-law extrapolation on the parallel split |
ai_foundations/domain_mixture_scaling_law/ |
Scaling law on the domain_mixture split |
ai_foundations/learning_rate_and_batch_size_scaling_law/ |
Scaling law on the lr & bsz split |
ai_foundations/easy_question_u_shaped_scaling_law/ |
Scaling law on the u_shape split |
| Task |
What it is |
mathematics_discovery/erdos_minimum_overlap/ |
Erdős minimum overlap problem — constructions minimizing the overlap statistic |
mathematics_discovery/second_autocorrelation_inequality/ |
Second autocorrelation inequality |
mathematics_discovery/third_autocorrelation_inequality/ |
Third autocorrelation inequality |
mathematics_discovery/sum_difference_problem/ |
Sum-difference set constructions maximizing $ |
mathematics_discovery/circle_packing_in_a_unit_square_n26/ |
26 non-overlapping circles packed in a unit square, maximizing the sum of radii |
mathematics_discovery/circle_packing_in_a_unit_square_n32/ |
Same task at $N = 32$
|
mathematics_discovery/hadamard_maximum_determinant_order_29/ |
$\pm 1$ matrix of order 29 maximizing $ |
Additional released artifact: mathematics_discovery/first_autocorrelation_inequality/.
| File |
What it is |
<task>_best.py |
Evolved Python program (most tasks) |
<task>_best.cpp |
Evolved C++ program (AHC tasks) |
<task>_best.rs |
Evolved Rust program (qubit routing) |
<task>_best_construction.json |
Concrete construction the program was evaluated on, stored as tagged JSON (numpy arrays round-trip via simpletes.construction.decode_construction) |
Older artifacts tag the JSON with __simpleevolve_type__; the current encoder writes __simpletes_type__. The decoder accepts both.