PYSCF is a Python-based general-purpose electronic structure platform that both supports first-principles simulations of molecules and solids, as well as accelerates the development of new methodology and complex computational workflows. The present paper explains the design and philosophy behind PYSCF that enables it to meet these twin objectives. With several case studies, we show how users can easily implement their own methods using PYSCF as a development environment. We then summarize the capabilities of PYSCF for molecular and solid-state simulations. Finally, we describe the growing ecosystem of projects that use PYSCF across the domains of quantum chemistry, materials science, machine learning and quantum information science.

We use the recently developed Heat-bath Configuration Interaction (HCI) algorithm as an efficient active space solver to perform multiconfiguration self-consistent field calculations (HCISCF) with large active spaces. We give a detailed derivation of the theory and show that difficulties associated with non-variationality of the HCI procedure can be overcome by making use of the Lagrangian formulation to calculate the HCI relaxed two-body reduced density matrix. HCISCF is then used to study the electronic structure of butadiene, pentacene, and Fe-porphyrin. One of the most striking results of our work is that the converged active space orbitals obtained from HCISCF are relatively insensitive to the accuracy of the HCI calculation. This allows us to obtain nearly converged CASSCF energies with an estimated error of less than 1 mHa using the orbitals obtained from the HCISCF procedure in which the integral transformation is the dominant cost. For example, an HCISCF calculation on the Fe-porphyrin model complex with an active space of (44e, 44o) took only 412 s per iteration on a single node containing 28 cores, out of which 185 s was spent in the HCI calculation and the remaining 227 s was used mainly for integral transformation. Finally, we also show that active space orbitals can be optimized using HCISCF to substantially speed up the convergence of the HCI energy to the Full CI limit because HCI is not invariant to unitary transformations within the active space.

The thermal atomic layer etching (ALE) of Al 2 O 3 can be achieved using sequential fluorination and ligand-exchange reactions. Although previous investigations have characterized the etch rates and surface chemistry, no reports have identified the volatile etch products. This study explored the volatile etch species during thermal Al 2 O 3 ALE at 300 °C using quadrupole mass spectrometry (QMS). HF was the fluorination reactant; Al(CH 3 ) 3 (trimethylaluminum (TMA)) and AlCl(CH 3 ) 2 (dimethylaluminum chloride, (DMAC)) were the metal precursors for ligand exchange. When TMA was used as the metal precursor after the fluorination of Al 2 O 3 powder, the QMS measurements revealed that the main ion species were consistent with dimers of AlF(CH 3 ) 2 (dimethylaluminum fluoride (DMAF)) with itself (DMAF + DMAF) or with TMA (DMAF + TMA). These ion species were observed after loss of a methyl group as Al 2 F 2 (CH 3 ) 3 + at m/z = 137 and Al 2 F(CH 3 ) 4 + at m/z = 133, respectively. In addition, an ion species consistent with a trimer was also observed as Al 3 F 3 (CH 3 ) 5 + at m/z = 213. Very similar results were observed for TMA exposures on AlF 3 powder. Comparable results were also obtained using DMAC as the metal precursor for ligand exchange. In contrast, SiCl 4 and TiCl 4 are not successful metal precursors because they do not lead to thermal Al 2 O 3 ALE at 300 °C. QMS measurements revealed no Alcontaining etch species after SiCl 4 and TiCl 4 exposures on AlF 3 powder. However, SiF x Cl y + and TiF x Cl y + species were observed which suggested that ligand-exchange reactions can occur without the release of Al-containing etch species. Density functional theory (DFT) and coupled cluster singles, doubles, and perturbative triples (CCSD(T)) calculations were performed to support the preference for dimer products. The theoretical results confirmed the stability of the dimer products and showed that dimers with two Al−F−Al bridging bonds are the most stable and dimers with two Al−CH 3 −Al bridging bonds are the least stable. In addition, the calculations suggested that dimers with terminal CH 3 ligands are most able to desorb from the surface because these dimers need to break weak Al−CH 3 −Al bridging bonds. Transmission electron microscopy (TEM) studies confirmed the thermal Al 2 O 3 ALE of Al 2 O 3 films on W powders. The TEM images revealed that the etch process was uniform and conformal after various numbers of thermal Al 2 O 3 ALE cycles using HF and TMA as the reactants.

We introduce NetKet, a comprehensive open source framework for the study of many-body quantum systems using machine learning techniques. The framework is built around a general and flexible implementation of neural-network quantum states, which are used as a variational ansatz for quantum wavefunctions. NetKet provides algorithms for several key tasks in quantum many-body physics and quantum technology, namely quantum state tomography, supervised learning from wavefunction data, and ground state searches for a wide range of customizable lattice models. Our aim is to provide a common platform for open research and to stimulate the collaborative development of computational methods at the interface of machine learning and many-body physics. I. MOTIVATION AND SIGNIFICANCERecent years have seen a tremendous activity around the development of physics-oriented numerical techniques based on machine learning (ML) tools [1]. In the context of many-body quantum physics, one of the main goals of these approaches is to tackle complex quantum problems using compact representations of many-body states based on artificial neural networks. These representations, dubbed neural-network quantum states (NQS) [2], can be used for several applications. In the supervised learning setting, they can be used, e.g., to learn existing quantum states for which a non-NQS representation is available [3]. In the unsupervised setting, they can be used to reconstruct complex quantum states from experimental measurements, a task known as quantum state tomography [4]. Finally, in the context of purely variational applications, NQS can be used to find approximate ground-and excited-state solutions of the Schrödinger equation [2, 5-9], as well as to describe unitary [2, 10, 11] and dissipative [12-15] many-body dynamics. Despite the increasing methodological and theoretical interest in NQS and their applications, a set of comprehensive, easyto-use tools for research applications is still lacking. This is particularly pressing as the complexity of NQS-related approaches and algorithms is expected to grow rapidly given these first successes, steepening the learning curve.The goal of NetKet is to provide a set of primitives and flexible tools to ease the development of cuttingedge ML applications for quantum many-body physics. NetKet also wants to help bridge the gap between the latest and technically demanding developments in the field and those scholars and students who approach the subject for the first time. Pedagogical tutorials are provided to this aim. Serving as a common platform for future research, the NetKet project is meant to stimulate the open and easy-to-certify development of new methods and to provide a common set of tools to reproduce published results.A central philosophy of the NetKet framework is to provide tools that are as simple as possible to use for the end user. Given the huge popularity of the Python programming language and of the many accompanying tools gravitating around the Python ecosystem, we have built NetKet as a full...

We report the electronic spectrum of the prototypical ruthenium coordination complex Ru(bpy)3 (2+) (bpy = 2, 2'-bipyridine) by messenger tagging with N2 in a cryogenic ion trap and photodissociation spectroscopy of mass selected Ru(bpy)3 (2+) ⋅ N2 ions. We observe individual electronic bands and groups of bands with unprecedented detail, particularly in the usually unresolved metal-to-ligand charge transfer region of the spectrum. By comparing our experimental results with time-dependent density functional theory, both with and without spin-orbit interaction [Heully et al., J. Chem. Phys. 131, 184308 (2009)], we are able to assign the spectrum of the isolated ion.