Adam A. Holmes
I am a Research Engineer & Computational Physicist (Ph.D. Theoretical Physics, Cornell) focused on AI for Science and Neurosymbolic Systems.
My work centers on designing high-performance stochastic optimization algorithms (Rust/C++) that navigate vast search spaces efficiently—whether for finding the ground state of a molecule or the optimal move in a game. I specialize in building hybrid architectures that combine the reasoning of deterministic search with the intuition of neural networks.
AI Systems & Agentic Research
My expertise in designing algorithms for interacting quantum systems provides a unique perspective for modeling other complex systems. The following projects explore the application of these principles to challenges in Artificial Intelligence and Robotics.
| Project | Description | Tech Stack |
|---|---|---|
| ♟️ Neurosymbolic Chess | A neurosymbolic chess engine (Rust) that integrates MCTS with a state-dependent alpha-beta portfolio to solve the “cold start” inefficiency of pure RL. | Rust • MCTS • PyTorch |
| ⚛️ Arrow (SHCI) | High-Performance Quantum Chemistry Engine. The reference C++/MPI implementation of Semistochastic Heat-Bath CI. I currently lead maintenance and architectural extensions. | C++ • MPI • HPC |
| 🗺️ Multi-Agent Pathfinding | A navigation stack combining Conflict-Based Search (CBS) for global optimality with ORCA for local avoidance. | CBS • ORCA |
| 🛡️ Adversarial Defense | A decentralized strategy for slower defenders to intercept a faster, intelligent intruder using Apollonian Circle geometry and game-theoretic control. | Game Theory • Computational Geometry |
| 🧭 Multi-Robot Exploration | A communication-aware algorithm for a team of robots to autonomously map an unknown environment using an “Iterative Boundary Trace & Coordinated Sweep” strategy. | SLAM • Frontier-Based Exploration |
Foundational Research & Impact: High-Accuracy Quantum Chemistry
My Ph.D. research introduced a new family of quantum chemistry methods—Heat-Bath Configuration Interaction (HCI) (Holmes, et al., JCTC 2016) and its successor, Semistochastic HCI (SHCI) (Sharma, Holmes, et al., JCTC 2017)—that significantly advanced the state-of-the-art in high-accuracy electronic structure calculations. The core innovation was a paradigm shift in algorithm design, replacing inefficient “generate-and-test” approaches with a highly efficient strategy that deterministically identifies the most significant components of the quantum wavefunction.
These new methods enabled calculations on a scale previously considered intractable, allowing us to produce the first near-exact potential energy surfaces for fourteen low-lying electronic states of the carbon dimer (Holmes, et al., JCP 2017), a key benchmark system for multireference quantum chemistry, and the ground state binding curve of the chromium dimer (Li, Yao, Holmes, et al., Phys. Rev. Res. 2020), a grand-challenge problem that had remained outstanding for decades, effectively “closing a chapter in quantum chemistry.” Today, SHCI is recognized as a leading benchmark method and has been implemented in or interfaced with major quantum chemistry packages.
Contact
I’m always open to discussing new research ideas, projects, or opportunities. The best way to reach me is via email or on LinkedIn.