SLayerGen generates crystals invariant to any space or layer group via autoregressive lattice and Wyckoff sampling plus equivariant diffusion, achieving gains over bulk models on diperiodic materials after correcting a prior loss inconsistency for hexagonal groups.
super hub Canonical reference
Pattern Recognition 127 (2022), 108611
Canonical reference. 70% of citing Pith papers cite this work as background.
394
Pith papers citing it
1
external citations · Crossref
Background
70% of classified citations
hub tools
citation-role summary
background 7
method 3
citation-polarity summary
authors
co-cited works
representative citing papers
Every proper minor-closed graph class admits an optimal (1+o(1)) log n bit adjacency labeling scheme.
A directed weighted two-graph model separates feasibility from movement in solution discovery and yields a detailed complexity classification for path and shortest-path discovery.
The method reformulates ALE mesh motion as independent multi-patch spline parameterizations per time step, using barrier functions, tangential-slip reparameterization, and constant-preserving quasi-interpolation to enable large-rotation FSI simulations.
Superconductivity in high-pressure MnB4 is induced by altermagnetic spin fluctuations, yielding extended-s pairing symmetry.
A new qubit-efficient HUBO encoding for graph partitioning problems like minimum coloring uses logarithmic bits and a lexicographic penalty to cut resources while providing provable optimality conditions.
GHGbench is a new multi-entity benchmark for company- and building-level carbon emission prediction that shows building tasks are harder, out-of-distribution gaps dominate, and multimodal data aids generalization.
A flow-adaptive ergodic coverage formulation using MMD that preserves guarantees over evolving domains and supports open-loop planning for robots in flows.
IfcLLM combines relational and graph representations of IFC models with iterative LLM reasoning to deliver 93.3-100% first-attempt accuracy on natural language queries across three test models.
Introduces the Mechanism Plausibility Scale to distinguish generative sufficiency from mechanistic plausibility in LLM-based agent-based models.
Human face perception aligns with neural networks trained on inverse-generative and naturalistic discriminative tasks, as these best predict human dissimilarity judgments on controversial and random face pairs.
A geometry-aligned bi-fidelity surrogate maps low- and high-fidelity wildfire solutions to a common domain for improved reduced-basis reconstruction, lower error near fronts, and practical uncertainty quantification.
A non-trivial UV fixed point for the scalar matter form factor exists in asymptotically safe quantum gravity, with a discrete spectrum of critical exponents and infrared locality restored.
MulTaBench is a new collection of 40 image-tabular and text-tabular datasets designed to test target-aware representation tuning in multimodal tabular models.
Statistical model checking on the K+S model shows macro-financial and structural parameters produce stronger transient effects on unemployment and GDP growth than heuristic-rule parameters under fixed precision policies.
A differentiable physics engine inside a neural network discovers non-Hertzian asperity shapes that produce programmable nonlinear friction-area relations, validated by BEM simulations.
Users experience fast-food intimacy with Soul's AI boyfriend that conflicts with gradual cultural expectations, introduces technical uncertainty, and shifts emotional labor onto women.
A dual-polarity representation in Ising/QUBO models enables computation of short SAT implicants by treating some variables as unassigned, with parameter regimes guaranteeing minimality.
ProtoSSL discovers generalizable prototypes from unlabeled time-series via self-supervision and assigns them to new tasks for interpretable predictions, outperforming supervised baselines in low-data regimes on ECG datasets.
AI CFD Scientist autonomously discovers a Spalart-Allmaras runtime correction reducing lower-wall Cf RMSE by 7.89% on the periodic hill at Reh=5600 while using a vision-language gate to detect 14 of 16 silent failures missed by solver checks.
Electrochemical reduction of hydrogen-capped polyynes yields stable amorphous sp-sp2 carbon nanoparticles with tunable diameters, >60% retained sp fraction, and ambient stability exceeding six months.
A physics-aware meta-learning framework retrieves coastal biogeochemical parameters from hyperspectral Rrs by pretraining a base model on synthetic data from a bio-optical forward model and fine-tuning on regional in situ samples, outperforming benchmarks with good temporal agreement.
Establishes the Riesz property for spectral projections of the multi-dimensional harmonic oscillator, Landau Hamiltonian, and Laplace-Beltrami operator on a sphere perturbed by complex L^r potentials when d/2 < r < infinity.
Researchers derived 19 design guidelines for AI-supported adult learning from thematic analysis of real deployments and demonstrated their use via heuristic evaluation and an ideation tool.
citing papers explorer
-
Qubit-efficient and gate-efficient encodings of graph partitioning problems for quantum optimization
A new qubit-efficient HUBO encoding for graph partitioning problems like minimum coloring uses logarithmic bits and a lexicographic penalty to cut resources while providing provable optimality conditions.
-
2D quantum-path interference in high-harmonic generation driven by highly-bichromatic fields
A new 2D quantum-path interference is observed in HHG driven by highly-bichromatic orthogonal fields, producing monomodal modulations in odd harmonics and bimodal modulations in even harmonics.
-
Qurator: Scheduling Hybrid Quantum-Classical Workflows Across Heterogeneous Cloud Providers
Qurator jointly optimizes queue time and fidelity for hybrid quantum-classical workflows across providers using quantum-aware DAG scheduling and a unified logarithmic fidelity score, achieving 30-75% wait reduction at high load with bounded accuracy cost.
-
Probabilistic Condition, Decision and Path Coverage of Circuit-based Quantum Programs
Quantum circuits show high average condition (97.56%) and decision (97.63%) coverage but lower path coverage (71.84%), with probabilistic versions adding confidence levels (averages 88.87%, 88.65%, 37.18%); mutation testing reveals weak or no correlation between structural coverage and fault finding
-
The Fock-Darwin-Darboux system: eigenstates, information entropies and dispersion-like measures
The FDD system yields analytical entropies matching the harmonic oscillator with effective frequency for the flat case, but requires numerical momentum-space analysis on curved space where Landau levels lose infinite degeneracy.
-
Quantum-Accelerated Gowers $U_2$ Norm for Bent Boolean Functions
A quantum circuit computes the Gowers U2 norm using 3n qubits and O(n^2) gates to accelerate genetic search for bent Boolean functions, providing exponential advantage over classical O(2^{2n}) evaluation for n greater than 25.
-
Sector-dominant graph-local drivers for path-window barrier Hamiltonians on the Boolean hypercube
Hybrid sector and path-window drivers achieve approximately 0.98 fidelity in centered barrier instances on hypercubes, outperforming standard transverse-field annealing for specific target Hamiltonians.
-
Physics-Informed Neural Networks for Maximizing Quantum Fisher Information in Time-Dependent Many-Body Systems
PINNs combined with Magnus expansion learn scheduling functions and adiabatic gauge potentials that yield higher normalized QFI than Euler-Lagrange baselines in nearest-neighbor, dipolar, and trapped-ion spin models up to six qubits.
-
Three ways to share a QPU: Scheduling strategies for hybrid Quantum-HPC applications
Three scheduling strategies for hybrid quantum-HPC systems cut classical resource use by up to 64% or boost QPU utilization depending on workload balance, validated on real hardware.
-
Hybrid Quantum-HPC Middleware Systems for Adaptive Resource, Workload and Task Management
The authors present Pilot-Quantum, a middleware for adaptive resource management in hybrid quantum-HPC systems, along with execution motifs and a performance modeling toolkit called Q-Dreamer.
-
Entanglement is Half the Story: Post-Selection vs. Partial Traces
A hybrid tensor network framework interpolates between classical and quantum models via controllable post-selection, with a trainable hyperparameter that complements bond dimension to enhance quantum machine learning.
-
Quantum Complexity and New Directions in Nuclear Physics and High-Energy Physics Phenomenology
A review of how quantum information science is expected to provide new tools and insights for nuclear and high-energy physics phenomenology and quantum simulations.