The ‘10 Martini’ Proof Connects Quantum Mechanics With Infinitely Intricate Mathematical Structures

The proof, known to be so hard that a mathematician once offered 10 martinis to whoever could figure it out, uses number ...
GitHub

Pauli.to_matrix(sparse=True) return the matrix in CSC format for efficiency with scipy.sparse.linalg.expm

The default sparse matrix format that to_matrix, in the Pauli class, returns is CSR. A very typical operation that is done with Pauli (and in general Hermitian) operators is to exponentiate them.
Women's Health

What Is A One-Rep Max? What It Means—And Why You Should Calculate Yours For Performance Perks

Women's Health may earn commission from the links on this page, but we only feature products we believe in. Why Trust Us? If you’ve ever been posted up at the squat rack, wondering how heavy you can ...
C&EN

The Iso-Inverse: A Contravariant Sparse Approximate Inverse Matrix

Article Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to ...
IEEE

DyLaClass: Dynamic Labeling Based Classification for Optimal Sparse Matrix Format Selection in Accelerating SpMV

Abstract: Sparse matrix-vector multiplication (SpMV) is crucial in many scientific and engineering applications, particularly concerning the effectiveness of different sparse matrix storage formats ...
IEEE

A Balanced Sparse Matrix Convolution Accelerator for Efficient CNN Training

Abstract: Sparse Convolutional Neural Network (CNN) training is well known to be time-consuming due to significant off-chip memory traffic. To effectively deploy sparse training, existing accelerators ...
acm.org

Solving Sparse Linear Systems Faster than Matrix Multiplication

Presenting an algorithm that solves linear systems with sparse coefficient matrices asymptotically faster than matrix multiplication for any ω > 2. Our algorithm can be viewed as an efficient, ...
Frontiers

SWI and CTP fusion model based on sparse representation method to predict cerebral infarction trend

Objective: SWI image signal is related to venous reflux disorder and perfusion defect. Computed tomography perfusion (CTP) contains perfusion information in space and time. There is a complementary ...
marktechpost

Sparse-Matrix Factorization-based Method: Efficient Computation of Latent Query and Item Representations to Approximate CE Scores

Cross-encoder (CE) models evaluate similarity by simultaneously encoding a query-item pair, outperforming the dot-product with embedding-based models at estimating query-item relevance. Current ...