Distributing quantum circuits faster using pre-shared connections
Distributing Quantum Circuits Using Pre-Distributed Entanglement Pairs over Quantum Networks
Emerging Technologies
Summary
Running quantum computations across multiple quantum devices can be slow because these devices need special linked qubit pairs called entanglement pairs, which take time to create. The authors look at how providing some of these entanglement pairs ahead of time helps make the overall computation faster. They develop a method to decide which pairs to prepare in advance and how to assign qubits to devices to speed up execution. Their approach also plans how to create any extra pairs needed during the process to minimize waiting times.
What this means in practice
- •For quantum hardware engineers: Optimize placement and pre-distribution of entanglement pairs in quantum networks to reduce computation delays.
- •For quantum cloud service providers: Enhance scheduling of distributed quantum workloads by preloading entanglement resources to improve overall service throughput.$Commercial implications: Enables faster multi-node quantum computations that cloud providers can offer as a premium service.
Authors
Yukun Yang, Ranjani G. Sundaram, Himanshu Gupta
Abstract
Distributing quantum circuits across a network of quantum devices is a recent approach to improve the scalability of quantum computation. Entangled pairs of qubits distributed across network nodes are used as a communication resource for executing inter-node (remote) gates. However, establishing these entanglement pairs incurs significant latency, and doing so during the circuit's execution may lead to the decoherence of logical qubits. Instead, it may be beneficial to distribute certain entanglement pairs before the circuit is executed. Thus, we consider the problem of distributing a quantum circuit across a quantum network containing some pre-distributed entanglement pairs and seek to minimize the execution time of the circuit. We address this problem in three steps. First, given the quantum network and (optionally) a probability distribution over training circuits, we determine a set of pre-distributed entanglement pairs under a specified budget. Second, we compute a qubit-to-memory allocation that minimizes the expected execution time given these pre-distributed resources. Finally, we identify any additional entanglement pairs required during execution, generate them concurrently, and execute the circuit gates. We evaluate our methods on a broad range of benchmark circuits.