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Matrix-multiply-accumulate (MMA) units, or tensor cores, are now widespread across modern computing architectures. Yet, their use for particle-grid operators remains limited. In implicit particle methods, mass-matrix assembly is a…

Computational Engineering, Finance, and Science · Computer Science 2026-04-22 Luca Pennati , Stefano Markidis

Fast matrix-by-matrix multiplication (hereafter MM) is a highly recognized research subject. The record upper bound 3 of 1968 on the exponent of the complexity MM decreased below 2.38 by 1987, applies to celebrated problems in many areas of…

Data Structures and Algorithms · Computer Science 2018-04-12 Victor Y. Pan

Leveraging a general framework adapted from symbolic integration, a unified reduction-based algorithm for computing telescopers of minimal order for hypergeometric and q-hypergeometric terms has been recently developed. In this paper, we…

Symbolic Computation · Computer Science 2026-02-24 Hui Huang

The double scaling limit of a new class of the multi-matrix models proposed in \cite{MMM91}, which possess the $W$-symmetry at the discrete level, is investigated in details. These models are demonstrated to fall into the same universality…

High Energy Physics - Theory · Physics 2009-10-22 A. Mironov , S. Pakuliak

Karppa & Kaski (2019) proposed a novel ``broken" or ``opportunistic" matrix multiplication algorithm, based on a variant of Strassen's algorithm, and used this to develop new algorithms for Boolean matrix multiplication, among other tasks.…

Data Structures and Algorithms · Computer Science 2024-09-05 David G. Harris

In this paper, we propose a general algorithmic framework to solve a class of optimization problems on the product of complex Stiefel manifolds based on the matrix polar decomposition. We establish the weak convergence, global convergence…

Numerical Analysis · Mathematics 2020-06-16 Jianze Li , Shuzhong Zhang

The Matrix Element Method is a promising multi-variate analysis tool which offers an optimal approach to compare theory and experiment according to the Neyman-Pearson lemma. However, until recently its usage has been limited by the fact…

High Energy Physics - Phenomenology · Physics 2020-10-01 Till Martini , Manfred Kraus , Sascha Peitzsch , Peter Uwer

The aim of this paper is to implement some new techniques, based on conjugate duality in convex optimization, for proving the existence of global error bounds for convex inequality systems. We deal first of all with systems described via…

Optimization and Control · Mathematics 2010-07-13 Radu Ioan Bot , Ernö Robert Csetnek

We determine the border subrank of higher order structure tensors of several families of algebras, and in particular obtain the following results. (1) We determine tight bounds on the border subrank of $k$-fold matrix multiplication and…

Algebraic Geometry · Mathematics 2026-04-23 Chia-Yu Chang , Fulvio Gesmundo , Jeroen Zuiddam

We provide a unified ultraproduct approach for constructing Wick words in mixed $q$-Gaussian algebras, which are generated by $s_j=a_j+a_j^*$, $j=1,\cdots,N$, where $a_ia^*_j - q_{ij}a^*_ja_i =\delta_{ij}$. Here we also allow equality in…

Operator Algebras · Mathematics 2016-12-09 Marius Junge , Qiang Zeng

High-order methods for convex and nonconvex optimization, particularly $p$th-order Adaptive Regularization Methods (AR$p$), have attracted significant research interest by naturally incorporating high-order Taylor models into adaptive…

Optimization and Control · Mathematics 2025-04-30 Wenqi Zhu , Coralia Cartis

We study the resources required to achieve universal quantum computing via the gate sets that provide the fundamental instructions from which quantum algorithms are built. While single-gate universal sets are known, they rely on precisely…

Quantum Physics · Physics 2026-02-24 Robin Kaarsgaard

In this paper, we give a short Bayesian proof of Talagrand's celebrated majorizing-measure theorem (MMT). While the upper-bound direction of MMT follows relatively directly from standard arguments, the lower-bound direction is widely…

Probability · Mathematics 2026-05-29 Ilias Zadik

We consider the problem of multiplying sparse matrices (over a semiring) where the number of non-zero entries is larger than main memory. In the classical paper of Hong and Kung (STOC '81) it was shown that to compute a product of dense $U…

Data Structures and Algorithms · Computer Science 2014-03-17 Rasmus Pagh , Morten Stöckel

Since Kilmer et al. introduced the new multiplication method between two third-order tensors around 2008 and third-order tensors with such multiplication structure are also called as T-product tensors, T-product tensors have been applied to…

Probability · Mathematics 2021-10-06 Shih Yu Chang , Yimin Wei

A fundamental class of matrix optimization problems that arise in many areas of science and engineering is that of quadratic optimization with orthogonality constraints. Such problems can be solved using line-search methods on the Stiefel…

Optimization and Control · Mathematics 2015-10-06 Huikang Liu , Weijie Wu , Anthony Man-Cho So

We show that computing the Tutte polynomial of a linear matroid of dimension $k$ on $k^{O(1)}$ points over a field of $k^{O(1)}$ elements requires $k^{\Omega(k)}$ time unless the \#ETH---a counting extension of the Exponential Time…

Computational Complexity · Computer Science 2020-07-29 Andreas Björklund , Petteri Kaski

We give a formula for the universal R-matrix of the quantized universal enveloping algebra $U_q(\g).$ This is similar to a previous formula due to Kirillov-Reshetikhin and Levendorskii-Soibelman, except that where they use the action of the…

Representation Theory · Mathematics 2010-08-23 Peter Tingley

The classical Brun--Titchmarsh theorem gives an upper bound, which is of correct order of magnitude in the full range, for the number of primes $p\leqslant x$ satisfying $p\equiv a\bmod q$. We strengthen this inequality for different ranges…

Number Theory · Mathematics 2025-12-30 Ping Xi , Junren Zheng

With the advent of deep learning application on edge devices, researchers actively try to optimize their deployments on low-power and restricted memory devices. There are established compression method such as quantization, pruning, and…

Machine Learning · Computer Science 2022-12-23 Xinlin Li , Mariana Parazeres , Adam Oberman , Alireza Ghaffari , Masoud Asgharian , Vahid Partovi Nia