Automated Quantum Chemistry Code Generation with the p$^\dagger$q Package (2501.08882v2)

Abstract: This article summarizes recent updates to the p$^\dagger$q package, which is a C++ accelerated Python library for generating equations and computer code corresponding to singly-reference many-body quantum chemistry methods such as coupled-cluster (CC) and equation-of-motion (EOM) CC theory. Since 2021, the functionality in \pq has expanded to include boson operators, coupled fermion-boson operators, unitary cluster operators, non-particle-conserving EOM operators, spin tracing, multiple single-particle subspaces, and more. Additional developments allow for the generation of C++ and Python code that minimizes floating-point operations via contraction order optimization, sub-expression elimination, and the fusion of similar terms.

• The paper introduces the p^ package as an automated tool for generating and optimizing quantum chemistry code for coupled-cluster and EOM-CC methods.
• It leverages advanced operator support, including unitary and non-particle-conserving operators, to precisely model complex electron interactions and cavity-QED phenomena.
• The improved code generation algorithms, featuring contraction order optimization and the pq-graph module, significantly reduce computational overhead in large-scale quantum simulations.

Automated Quantum Chemistry Code Generation with the p$^ Package</h2> <p>The paper introduces the p$^ package, an automated tool designed to facilitate the generation of equations and corresponding code for many-body quantum chemistry methods, with a focus on the development and implementation of single-reference electronic structure theories like coupled-cluster (CC) and equation-of-motion (EOM) CC. Since its initial release, the p$$^ package has undergone significant updates, expanding its functionalities and enhancing its utility for quantum chemists.</p> <h3 class='paper-heading' id='key-developments-and-features'>Key Developments and Features</h3> <ol> <li><strong>Extended Operator Support</strong>: The package now supports various operator types relevant to quantum chemistry. These include fermionic operators and more complex constructs involving boson operators, which are pertinent for studies in cavity quantum electrodynamics (QED) and coupled fermion-boson systems. This extension accommodates both conventional electronic structure calculations as well as those incorporating interactions with structured environments such as cavities.</li> <li><strong>Unitary and Non-Particle Conserving Operators</strong>: Unitary cluster operators and non-particle-conserving excitation operators have been incorporated. These operators are essential for methods such as unitary coupled-cluster (UCC) and forms of EOM-CC that investigate processes like electron attachment, ionization potentials, and the more complex double electron attachment or ionization forms.</li> <li><strong>Optimization in Code Generation</strong>: The p$$^ package includes improved algorithms for the optimization of floating-point operations during code generation. Techniques such as contraction order optimization and sub-expression elimination have been implemented to reduce computational costs, thereby making the generated code more efficient.

Spin-Traced and Orbital Space Specifications: Users can define spin-traced equations and specify active space formulations for complex quantum chemistry methods. This enhances the accuracy and computational efficiency of calculations by reducing unnecessary redundancies and focusing on essential interactions.

pq-graph Module: The introduction of the pq-graph module provides advanced graph-theoretical optimization strategies that result in the efficient execution of tensor contractions. This module supports code generation in both Python and C++, leveraging the TiledArray library syntax for C++, which enhances compatibility with high-performance computing environments.

Implications and Future Directions

The advancements in the p$$^ package have significant theoretical and practical implications for quantum chemistry. By automating the generation of complex quantum chemistry methods, the package reduces the potential for human error and accelerates the development and testing of quantum chemical theories. The integration of new operator types and the potential for cavity-QED applications open avenues for investigating new physical phenomena, especially in strongly coupled systems where light-matter interactions are predominant.</p> <p>The improvements in code efficiency through the pq-graph module ensure that the computational resources required are minimized, which is crucial for scaling these calculations on large chemical systems or condensed phase environments. The developments suggest a possible future trajectory in which automated methods could be dynamically adjusted based on real-time feedback from ongoing computations, further optimizing resource allocation and output accuracy.</p> <p>As quantum computing technologies evolve, tools like the p$$^ package are positioned well to adapt and extend their capabilities, potentially interfacing with quantum processors to solve quantum many-body problems beyond the classical computational capabilities. The future of automated quantum chemistry thus seems promising, with tools like p$^ playing a pivotal role in bridging current methodologies with emerging computational paradigms.