Methods and Apparatus to Allocate Physical Qubits to Support Distributed Quantum Error Correction (QEC) Codes

Background:

Quantum Processing Units (QPUs) are specialized components of Quantum Computing systems which leverage the principles of quantum mechanics to perform complex calculations. Current quantum processing units are called Noisy-Intermediate Scale Quantum (NISQ) computers (systems) because (1) the qubits are fragile and error-prone, and (2) a monolithic Quantum Processing Unit (QPU) hosts only limited number of qubits, thereby reducing its computational power. These quantum processing units, however, are limited in their capabilities by several factors, including qubit count, qubit quality, and susceptibility to noise. As such Quantum Error Correction codes (QECCs) have been developed to protect quantum information from errors caused by these factors.   

Technology Overview:

This University at Buffalo technology features a Distributed Quantum Computing System, and a unique set of methods designed to create a fault-tolerant Distributed Quantum Computing system (FT-DQC). These methods, when integrated into a DQC operating system or resource management layer, provide a backbone for allocating data and ancilla qubits.  

Advantages:

• Through the distributed implementation of QEC codes, the proposed methods enable the realization of a fault-tolerant Virtual Quantum Computer (VQC) or Quantum DataCenter (QDC) that supports a significantly larger number of logical qubits, thereby achieving utility-scale quantum computing power. Mechanical flexibility of these devices will enable a broad range of new applications. 
• The suite of methods in this invention offers a comprehensive set of solutions that can maximize load balance among the QPUs (in terms of both overall qubits and role-specific qubits) to eliminate performance bottlenecks and facilitate modular system design and deployment, minimize QEC-related overheads such as the number of required EPR pairs, remote CNOT/CZ gates, and tele-data operations. 
• The system can leverage heterogeneous qubit modalities to substantially improve both computational throughput and operational fidelity. This architectural flexibility also effectively increases the system’s Quantum Volume (QV), reflecting its enhanced hardware capability to execute deeper and wider circuits with higher fidelity.

Applications:

• Material Science 
• Financial Modeling 
• Climate Science 
• Artificial Intelligence

Intellectual Property Summary:

United States Provisional Patent Application 63/952,381 filed December 31st, 2025.  

Stage of Development:

• Prototypes fabricated and validated within the laboratory setting.
• TRL 4

Licensing Status:

Available for licensing or collaboration.