SCALABLE MULTI-CHIP QUANTUM ARCHITECTURES ENABLED BY CRYOGENIC WIRELESS / QUANTUM -COHERENT NETWORK-IN PACKAGE

Introduction

Todays tremendous interdisciplinary effort towards building a quantum computer promises to tackle problems beyond reach of any classical computer. Although intermediate-scale quantum computers have been recently demonstrated to exceed the capability of the most powerful supercomputers, it is widely recognized that addressing any real-world problem will require upscaling quantum computers to thousands or even millions of qubits.

Project Focus

This proposal focuses on the grand challenge of scalability in quantum computers, from a full-stack architectural standpoint, and enabled by communication networks operating within the quantum computing package at cryogenic temperatures.

Project Goals

The QUADRATURE project hence aims to pioneer a new generation of scalable quantum computing architectures featuring distributed quantum cores (Qcores) interconnected via quantum-coherent qubit state transfer links and orchestrated via an integrated wireless interconnect. This novel architecture supports reconfigurability to serve massive flows of heterogeneous quantum algorithmic demands.

Main Objectives

The main objectives are:

1. To experimentally prove the first micro-integrated all-RF qubit-state transfer link within a cryogenic tunable superconducting cavity waveguide in the microwave and THz frequency region for quantum-coherent frequency-multiplex and routing.
2. To achieve experimentally the transfer of classical data through wireless in-package links by integrated cryo-antennas and transceivers.
3. To build protocols for a quantum-coherent integrated network enabling the exchange of qubits through the coordination of the quantum-coherent data plane and the wireless control plane.
4. To develop appropriate scalable architectural methods such as mapping, scheduling, and coordination approaches across multiple Qcores.
5. To demonstrate the scalability of the approach via multi-scale design space optimization and for a set of quantum algorithm benchmarks, with at least 10x improvement in overall performance.