Rigetti & Co, LLC

Specialized digital and mixed-signal circuits for controlling and reading out quantum bits (qubits), including generating precise modulated RF signals and integrating with photonic components for quantum operations.

Developing and applying machine learning algorithms that leverage quantum computing principles, such as quantum circuits or autoencoders, for tasks like simulation or data processing.

Devices leveraging superconductivity or quantum phenomena for applications such as quantum computing, high-efficiency power transmission, or sensitive detection, including materials like graphene Josephson junctions and quantum bits.

Specialized hardware, architectural designs, and computational methods to improve the speed, efficiency, and security of artificial intelligence and machine learning model execution, particularly for inference and data processing.

Systems and methods for preparing, organizing, and electrically connecting individual conductors or cable bundles to connector terminals, ensuring reliable contact and strain relief.

Development of memory cells utilizing resistive switching or phase-change materials, including novel material compositions, multi-layered structures, and integration with selector devices like bipolar junction transistors, to achieve non-volatile storage.

Methods and systems for efficiently allocating computing resources, balancing workloads, and managing power states to improve performance, reduce energy consumption, or enhance reliability in computing platforms.

Methods and structures for integrating and enclosing electronic components into compact, multi-functional modules, often involving embedded components, multi-layer substrates, and electromagnetic shielding for performance and miniaturization.

Development of polymer compositions and material structures for electrical insulation and protective sheathing of cables, focusing on properties like flame retardancy, flexibility, and semiconductivity.

Novel hardware designs and processing pipelines tailored for specific computational tasks, such as graphics rendering, neural network operations, or matrix transformations, often involving custom circuits, memory arrays, or data flow mechanisms.