Applied & Human-Centered · Computer Science & AI
Mathematical Software
The newest papers in Mathematical Software that ReadSearch has read, newest first. Each links to its own page, with its authors, date, where it was published and the original.
26 papers, from 5 September 2026 to 2 November 2026: 26 arXiv preprints.
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Newest papers
A GPU Engine for Sparse Matrix-Vector Products on $k^2$-Tree-Compressed Graphs
The $k^2$-tree is a compact representation of Boolean matrices: it stores the recursive hierarchy of their non-empty submatrices, with neither values nor coordinates, and serves rows and columns…Extensible Programmatic Specification of Finite Element Methods
Finite element methods (FEMs) are a powerful and ubiquitous tool for solving engineering problems.The Rise of Low Precision Floating Point
Floating point computing has dominated scientific computations since the 1950s because of its versatile ability to approximate real numbers with both sufficiently high precision and sufficiently…Integer-Quantized Hierarchical Matrices with Adaptive Bit Allocation
We present an adaptive bitwidth allocation method for quantizing low-rank factors in hierarchical matrices in order to decrease storage while meeting a given constraint on their reconstruction error.Beyond atol and rtol: Sound Test Oracles for Low-Precision GPU Kernels
Low-precision GPU kernels are commonly tested against a reference using hand-picked absolute and relative tolerances.diff-soup: GPU-native Differentiable Simulation and Inference for Large-scale Stiff Dynamical Systems
Learning physical models from spatiotemporal data requires simulating systems of partial differential equations (PDEs) and differentiating through their solution.Building Mathematical Software -- Lessons from the Development of GAP
Mathematical software has particular needs that are not all covered by the existing literature on software engineering or algorithm design.ArcTN: Efficient Tensor-Network Contraction Planning for Quantum Circuit Simulation
Tensor-network simulation of quantum circuits depends on contraction orders with low computational cost and small intermediate tensors, found without excessive planning time.A 55-Addition Rank-23 Scheme for $3\times3$ Matrix Multiplication via Exact Two-Sided Minimization
We give a scheme that multiplies two $3\times3$ matrices with 23 multiplications and 55 additions over any ring, one addition below the previous record of 56 (Sun, 2026) and the first below 56 for…PADO-Pauli: A GPU-Accelerated Implementation of Pauli Propagation
Variational quantum algorithms utilize parameterized circuits many times during training, at new parameter values, over batches of data, and with gradients.GpFlash: Maximizing Speed and Minimizing Memory for Gaussian Process Training and Prediction
This paper presents GpFlash, a Gaussian process library that is focused on fast training and posterior evaluations, minimal memory usage, and scalability to high-dimensional problems.Learning to Design Convex Relaxations for Nonconvex Optimization
Convex relaxations make nonconvex optimization tractable by replacing hard nonconvex problems with convex surrogates that give valid bounds.Separating Statistical Inference from Experimental Runtime: An Architecture for Sequential Scientific Analysis
Sequential statistical procedures are increasingly embedded in scientific systems in which observations arrive incrementally from heterogeneous sources.asdex: Automatic Sparse Differentiation in JAX
Many tasks in scientific computing and machine learning require the Jacobian or Hessian matrix of a function.Coordinate-Free Automatic Differentiation
Automatic differentiation (AD) is a cornerstone of modern machine learning.Scen-Opt: A Scenario Optimization Toolbox for Data-Driven Convex Programming
The scenario approach is a well-established statistical framework for data-driven decision-making.CNet: A Complex-Valued Deep Learning Framework with Wirtinger Autodifferentiation and FFT--Hadamard Convolution
CNet is a C++/CUDA framework for building deep complex-valued neural networks (CVNNs) and optimizing complex functions by gradient descent with Wirtinger derivatives.Robust Local Optimization Done Right
RANSAC scoring and local optimization (LO) impose different robustness requirements, motivating the separation of hypothesis selection from refinement.A Flexible and Generic Approach for Explainable Landscape Analysis and the pyXla Toolbox
Landscape analysis has been successfully applied to understand complex optimisation problems, gain insights into algorithm behaviour, and automate algorithm selection and configuration.Interactive Power Flow in the Browser
This paper introduces tellegen, an open source framework for interactive power flow (PF) and optimal power flow (OPF) studies that run in the browser.