Some of the new unique features of the MOLCAS quantum chemistry package version 7 are presented in this report. In particular, the Cholesky decomposition method applied to some quantum chemical methods is described. This approach is used both in the context of a straight forward approximation of the two-electron integrals and in the generation of so-called auxiliary basis sets. The article describes how the method is implemented for most known wave functions models: self-consistent field, density functional theory, 2nd order perturbation theory, complete-active space self-consistent field multiconfigurational reference 2nd order perturbation theory, and coupled-cluster methods. The report further elaborates on the implementation of a restricted-active space self-consistent field reference function in conjunction with 2nd order perturbation theory. The average atomic natural orbital basis for relativistic calculations, covering the whole periodic table, are described and associated unique properties are demonstrated. Furthermore, the use of the arbitrary order Douglas-Kroll-Hess transformation for one-component relativistic calculations and its implementation are discussed. This section especially focuses on the implementation of the so-called picture-change-free atomic orbital property integrals. Moreover, the ElectroStatic Potential Fitted scheme, a version of a quantum mechanics/molecular mechanics hybrid method implemented in MOLCAS, is described and discussed. Finally, the report discusses the use of the MOLCAS package for advanced studies of photo chemical phenomena and the usefulness of the algorithms for constrained geometry optimization in MOLCAS in association with such studies.

to be used for computations of large systems. In addition, the report includes the description of a computational machinery for nonlinear optical spectroscopy through an interface to the QM/MM package Cobramm. Further, a module to run molecular dynamics simulations is added and two surface hopping algorithms are included to enable nonadiabatic calculations. Finally, we report on the subject of improvements with respects to alternative file options and parallelization.

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With rapid recent advances in quantum technology, we are close to the threshold of quantum devices whose computational powers can exceed those of classical supercomputers. Here, we show that a quantum computer can be used to elucidate reaction mechanisms in complex chemical systems, using the open problem of biological nitrogen fixation in nitrogenase as an example. We discuss how quantum computers can augment classical computer simulations used to probe these reaction mechanisms, to significantly increase their accuracy and enable hitherto intractable simulations. Our resource estimates show that, even when taking into account the substantial overhead of quantum error correction, and the need to compile into discrete gate sets, the necessary computations can be performed in reasonable time on small quantum computers. Our results demonstrate that quantum computers will be able to tackle important problems in chemistry without requiring exorbitant resources.quantum computing | quantum algorithms | reaction mechanisms C hemical reaction mechanisms are networks of molecular structures representing short-or long-lived intermediates connected by transition structures. The relative energies of all stable structures determine the relative thermodynamical stability. Differences of the energies of local minima and connecting transition structures determine the rates of interconversion, i.e., the chemical kinetics of the process. As they enter exponential expressions, very accurate energy differences are required for the reliable evaluation of the rate constants. At its core, the detailed understanding and prediction of complex reaction mechanisms then requires highly accurate electronic structure methods. However, the electron correlation problem remains, despite decades of progress (1), one of the most vexing problems in quantum chemistry. Although approximate approaches, such as density functional theory (DFT) (2), are very popular, their accuracy is often too low for quantitative predictions (see, e.g., refs. 3 and 4); this holds particularly true for molecules with many energetically close-lying orbitals. For such problems on classical computers, much less than a hundred strongly correlated electrons are already out of reach for systematically improvable ab initio methods that could achieve the required accuracy.The apparent intractability of accurate simulations for such quantum systems led Richard Feynmann to propose quantum computers. The promise of exponential speedups for quantum simulation on quantum computers was first investigated by Lloyd (5) and Zalka (6) and was directly applied to quantum chemistry by Lidar, Aspuru-Guzik, and others (7-11). Quantum chemistry simulation has remained an active area within quantum algorithm development, with ever more sophisticated methods being used to reduce the costs of quantum chemistry simulation (12)(13)(14)(15)(16)(17)(18)(19)(20).The promise of exponential speedups for the electronic structure problem has led many to suspect that quantum computers will one day revolu...