Evaluating the permanent of a matrix is a fundamental computation that emerges in many domains, including traditional fields like computational complexity theory, graph theory, many-body quantum theory and emerging disciplines like machine learning and quantum computing. While conceptually simple, evaluating the permanent is extremely challenging: no polynomial-time algorithm is available (unless $\textsc{P} = \textsc{NP}$). To the best of our knowledge there is no publicly available software that automatically uses the most efficient algorithm for computing the permanent. In this work we designed, developed, and investigated the performance of our software package which evaluates the permanent of an arbitrary rectangular matrix, supporting three algorithms generally regarded as the fastest while giving the exact solution (the straightforward combinatoric algorithm, the Ryser algorithm, and the Glynn algorithm) and, optionally, automatically switching to the optimal algorithm based on the type and dimensionality of the input matrix. To do this, we developed an extension of the Glynn algorithm to rectangular matrices. Our free and open-source software package is distributed via Github, at https://github.com/theochem/matrix-permanent.
Optimizing quantum error correction through error attribution
Yau Mathematical Sciences Center, Tsinghua University（丘成桐数学科学中心，清华大学）；Yanqi Lake Beijing Institute of Mathematical Sciences and Applications（燕京数学科学与应用研究院）
Optimizing QAOA circuit transpilation with parity twine and SWAP network encodings
Jülich Supercomputing Centre, Institute for Advanced Simulation, Forschungszentrum Jülich（于利希研究中心先进模拟研究所超级计算中心）；Institute for Quantum Computing Analytics (PGI-12), Forschungszentrum Jülich（于利希研究中心量子计算分析研究所）；Department of Mechanical Engineering, Virginia Tech（弗吉尼亚理工大学机械工程系）；Davidson School of Chemical Engineering, Purdue University（普渡大学戴维森化学工程学院）；AIDAS；RWTH Aachen University（亚琛工业大学）
