Quantum methods that leave the simulator
A large body of theory exists across quantum algorithms, sensing, and information. Much of its value depends on
whether it can be engineered for problems at real scale. That gap between theory and deployability is where I work.
I use space systems as the near-term application domain. Limited onboard resources, harsh operating
environments, and the need for precise sensing and autonomous operation in deep space make them a demanding testbed
for finding where near-term quantum methods deliver practical value. My long-term vision, which I call
Quantronautics, is to design space systems from quantum principles rather than adding quantum components
to classical designs.
Quantum Optimization for Real-World Systems
I build quantum and hybrid quantum-classical solvers (Simulated Quantum Annealing, QAOA, VQE) by translating
real combinatorial and continuous problems into quantum-compatible formulations.
At NASA JPL I developed a hybrid Simulated Quantum Annealing solver in Julia, based on a
Suzuki-Trotter path-integral formulation, for Deep Space Network scheduling. The DSN coordinates
tracking and communication for more than 40 deep-space missions and is often oversubscribed. The solver produced
schedules with more satisfied requests, faster than MILP, machine-learning, and prior approaches. A journal article
is in preparation.
Also: QAOA/VQE for satellite routing in debris collection and on-orbit servicing.
Renormalization Group Methods for NISQ Tractability
Real problems often exceed the qubit count and connectivity of today's hardware. I use
Renormalization Group theory from statistical physics to find which degrees of freedom matter for a
target observable and integrate out the rest. The result is a compact, NISQ-compatible model that keeps classical
solution quality.
The coarse-graining also reveals structure on its own, such as coordination timescales and network vulnerabilities,
independent of the quantum solver used afterwards.
Applied to cislunar space situational awareness, constellation design, and coverage optimization.
Quantum Walk Algorithms for Graph Inference
Quantum walks spread amplitude along a graph's own topology. Paths aligned with the structure interfere
constructively and irrelevant paths cancel, so arrival probabilities encode both local and global structure.
This led to QSearchNet, which combines topology-aware quantum walks with Grover's amplitude
amplification for link prediction and network-evolution forecasting. I later extended it with adaptive quantum
teleportation for sparse networks, capturing long-range correlations while preserving local structure.
Multi-Node Quantum-Classical Sensing Networks
In QuaSense I study how Rydberg-state quantum sensors can work alongside existing classical space
infrastructure, through three architectures: locally enhanced arrays, distributed entangled sensing, and
capability-based data fusion.
The goal is an actionable framework for designing, tasking, and tuning a mixed network of quantum and classical
nodes toward a single shared mission objective, for Earth observation and space situational awareness.