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How Resonant Computing Works
Instead of simulating optimization digitally, the Resonant Phase Computer implements it physically. Oscillators represent variables, couplers represent constraints, and the system's natural dynamics converge on optimal or near-optimal solutions.
Core Technology Components
Analog Compute Core
- • Arrays of oscillators capture binary variables as phase states
- • Couplers enforce relationships between variables
- • DACs inject control signals to guide annealing schedules
- • ADCs read out the final states, yielding the computed solution
Digital Control Layer
- • FPGA manages timing, synchronization, and data flow
- • MCU handles calibration, health monitoring, and housekeeping
- • PCIe interface provides high-bandwidth connection to the host
Calibration Engine
- • Self-calibration using LUTs (lookup tables)
- • Compensates for drift, temperature variation, and analog non-idealities
- • Guarantees repeatability across runs and across boards
Developer SDK
- • Python and C++ APIs for direct integration
- • CUDA-like workflow: load a problem, run an anneal, fetch solutions
- • OpenQASM/QUBO import planned for compatibility with quantum workflows
Think GPU — But for Optimization
Plug it into your server, call the API, and physics does the rest. No quantum refrigeration, no error correction overhead — just robust, manufacturable hardware that scales.
Ready to Experience the Future?
Join the pilot program and be among the first to harness physics-based computing for your optimization challenges.