Daniel Mejı́a-Rodrı́guez, Edoardo Aprà, Jochen Autschbach, Nicholas P. Bauman, Eric J. Bylaska, Niranjan Govind, Jeff R. Hammond, Karol Kowalski, Alexander A. Kunitsa, Ajay Panyala, Bo Peng, John J. Rehr, Huajing Song, Sergei Tretiak, Marat Valiev, Fernando D. Vila
This paper summarizes developments in the NWChem computational chemistry suite since the last major release (NWChem 7.0.0). Specifically, we focus on functionality, along with input blocks, that is accessible in the current stable release (NWChem 7.2.0) and in the "master" development branch, interfaces to quantum computing simulators, interfaces to external libraries, the NWChem github repository, and containerization of NWChem executable images. Some ongoing developments that will be available in the near future are also discussed.
This paper summarizes developments in the NWChem computational chemistry suite since the last major release (NWChem 7.0.0). Specifically, we focus on functionality, along with input blocks, that is accessible in the current stable release (NWChem 7.2.0) and in the "master" development branch, interfaces to quantum computing simulators, interfaces to external libraries, the NWChem github repository, and containerization of NWChem executable images. Some ongoing developments that will be available in the near future are also discussed.
Fault-tolerant quantum computation promises to solve outstanding problems in quantum chemistry within the next decade. Realizing this promise requires scalable tools that allow users to translate descriptions of electronic structure problems to optimized quantum gate sequences executed on physical hardware, without requiring specialized quantum computing knowledge. To this end, we present a quantum chemistry library, under the open-source MIT license, that implements and enables straightforward use of state-of-art quantum simulation algorithms. The library is implemented in Q#, a language designed to express quantum algorithms at scale, and interfaces with NWChem, a leading electronic structure package. We define a standardized schema for this interface, Broombridge, that describes second-quantized Hamiltonians, along with metadata required for effective quantum simulation, such as trial wavefunction ansatzes. This schema is generated for arbitrary molecules by NWChem, conveniently accessible, for instance, through Docker containers and a recently developed web interface EMSL Arrows. We illustrate use of the library with various examples, including ground- and excited-state calculations for LiH, H10, and C20 with an active-space simplification, and automatically obtain resource estimates for classically intractable examples.
ABSTRACT Version 6.0 of the ORCA quantum chemistry program suite was released in July 2024. ORCA 6.0 is a major turning point in the history of the program since it represents a near complete rewrite of the code base that leads to: (1) major performance improvements, (2) a clean and highly efficient code base that greatly facilitates future development, (3) a large amount of new functionality, and (4) new interface capabilities that facilitate inter‐operability with other quantum chemistry program packages. The article describes the most salient features of the program.
The transformative impact of modern computational paradigms and technologies, such as high-performance computing (HPC), quantum computing, and cloud computing, has opened up profound new opportunities for scientific simulations. Scalable computational chemistry is one beneficiary of this technological progress. The main focus of this paper is on the performance of various quantum chemical formulations, ranging from low-order methods to high-accuracy approaches, implemented in different computational chemistry packages and libraries, such as NWChem, NWChemEx, Scalable Predictive Methods for Excitations and Correlated Phenomena, ExaChem, and Fermi-Löwdin orbital self-interaction correction on Azure Quantum Elements, Microsoft's cloud services platform for scientific discovery. We pay particular attention to the intricate workflows for performing complex chemistry simulations, associated data curation, and mechanisms for accuracy assessment, which is demonstrated with the Arrows automated workflow for high throughput simulations. Finally, we provide a perspective on the role of cloud computing in supporting the mission of leadership computational facilities.
In the contemporary era of scientific and technical innovations, we are witnessing remarkable progress in the realm of quantum computing. Today’s phase is referred to as the second quantum revolution, characterized by ongoing research and progress in the hardware, software, and applications of quantum computers. While the theoretical foundations of quantum computing have been in place for decades, the practical tools and technologies that have emerged in recent years have catapulted this field from theory into reality. This paper provides a brief overview of the fundamental principles of quantum computing and explores the various technologies that support them. From quantum programming languages and simulators to quantum hardware platforms and software development kits, these tools have paved the way for groundbreaking research, experimentation, and the exploration of quantum’s boundless potential. Furthermore, it addresses the current developments, existing challenges, ongoing improvements, and future prospects in this dynamic field.
As the year-to-year gains in speeds of classical computers continue to taper off, computational chemists are increasingly examining quantum computing as a possible route to achieve greater computational performance. Quantum computers, built upon the properties of superposition, interference, and entanglement of quantum bits, offer, in principle, the possibility to outperform classical computers for solving many important classes of problems. In the field of chemistry, quantum algorithm development offers promising propositions for solving classically intractable problems in areas such as electronic structure, chemical quantum dynamics, spectroscopy, and cheminformatics. However, physical implementations of quantum computers are still in their infancy and have yet to outperform classical computers for useful computations. Still, quantum software development for chemistry is a highly active area of research. In this perspective, we summarize recent progress in the areas of quantum computing algorithms, hardware, and software, and we describe the challenges that remain for useful implementations of quantum computing for chemical applications.
Abstract The systematic evaluation of the performance of Quantum Computers allows users to identify the best platform to execute a certain class of workload, and it can also guide the future developments of hardware companies. The NEASQC Benchmark Suite (TNBS) is a methodology designed in the context of the NEASQC (NExt ApplicationS of Quantum Computing) European project to perform such evaluation across several benchmark cases identified as common in one or several domains of application of Quantum Computing. TNBS follows several design principles identified as relevant after a thorough evaluation of the existing benchmarking methodologies: (1) benchmarks are defined at high-level not being linked to any algorithmic approach or implementation, (2) benchmarks are scalable (in qubits) and their output is classically verifiable, (3) performance metrics may be defined per case to fit the nature of the outputs of each case, and (4) the benchmark report also keeps record of all the relevant components of the execution stack. Finally, in the future, the reports may be submitted to a centralized repository, which is equipped with a web interface allowing a systematic and objective comparison of different platforms across the different cases. The first release of TNBS is composed of 4 benchmark cases and provides a reference implementation in myQLM. Documentation and code are available at https://github.com/NEASQC/WP3_Benchmark .