Hardware-Software Co-design for Distributed Quantum Computing
- URL: http://arxiv.org/abs/2503.18329v1
- Date: Mon, 24 Mar 2025 04:19:32 GMT
- Title: Hardware-Software Co-design for Distributed Quantum Computing
- Authors: Ji Liu, Allen Zang, Martin Suchara, Tian Zhong, Paul D Hovland,
- Abstract summary: Distributed quantum computing (DQC) offers a pathway for scaling up quantum computing architectures beyond the confines of a single chip.<n> Entanglement is a crucial resource for implementing non-local operations in DQC.<n>We show that our hardware-software co-design improves both the runtime and the output fidelity under a realistic model of DQC.
- Score: 7.928706053656785
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Distributed quantum computing (DQC) offers a pathway for scaling up quantum computing architectures beyond the confines of a single chip. Entanglement is a crucial resource for implementing non-local operations in DQC, and it is required to allow teleportation of quantum states and gates. Remote entanglement generation in practical systems is probabilistic, has longer duration than that of local operations, and is nondeterministic. Therefore, optimizing the performance of probabilistic remote entanglement generation is critically important for the performance of DQC architectures. In this paper we propose and study a new DQC architecture that combines (1) buffering of successfully generated entanglement, (2) asynchronously attempted entanglement generation, and (3) adaptive scheduling of remote gates based on the entanglement generation pattern. We show that our hardware-software co-design improves both the runtime and the output fidelity under a realistic model of DQC.
Related papers
- Flexion: Adaptive In-Situ Encoding for On-Demand QEC in Ion Trap Systems [16.77947483425163]
A key near-term goal is to build a system capable of executing millions of logical operations reliably.
We propose a novel system architecture targeting MQC on trapped-ion quantum computers.
We propose Flexion, a hybrid encoding scheme that uses bare qubits for 1Q gates and QEC-encoded logical qubits for 2Q gates.
arXiv Detail & Related papers (2025-04-22T22:44:47Z) - Building a Software Stack for Quantum-HPC Integration [0.9360388224886863]
We propose a hardware-agnostic software framework that supports both current intermediate-scale quantum devices and future fault-tolerant quantum computers.<n>The architecture includes a quantum gateway interface, standardized APIs for resource management, and robust scheduling mechanisms.<n>Key innovations include: (1) a unified resource management system that efficiently coordinates quantum and classical resources, (2) a flexible quantum programming interface that abstracts hardware-specific details, and (4) a comprehensive tool chain for quantum circuit optimization and execution.
arXiv Detail & Related papers (2025-03-03T18:18:45Z) - SeQUeNCe GUI: An Extensible User Interface for Discrete Event Quantum Network Simulations [55.2480439325792]
SeQUeNCe is an open source simulator of quantum network communication.<n>We implement a graphical user interface which maintains the core principles of SeQUeNCe.
arXiv Detail & Related papers (2025-01-15T19:36:09Z) - Ecosystem-Agnostic Standardization of Quantum Runtime Architecture: Accelerating Utility in Quantum Computing [0.0]
This research covers all layers of Quantum Computing Optimization Middleware (QCOM)
It requires execution on real quantum hardware (QH)
There is a need for a widely adopted runtime platform (RP) driven by the open-source community.
arXiv Detail & Related papers (2024-09-26T16:43:07Z) - Quantum Compiling with Reinforcement Learning on a Superconducting Processor [55.135709564322624]
We develop a reinforcement learning-based quantum compiler for a superconducting processor.
We demonstrate its capability of discovering novel and hardware-amenable circuits with short lengths.
Our study exemplifies the codesign of the software with hardware for efficient quantum compilation.
arXiv Detail & Related papers (2024-06-18T01:49:48Z) - Compiler for Distributed Quantum Computing: a Reinforcement Learning Approach [6.347685922582191]
We introduce a novel compiler that prioritizes reducing the expected execution time by jointly managing the generation and routing of EPR pairs.
We present a real-time, adaptive approach to compiler design, accounting for the nature of entanglement generation and the operational demands of quantum circuits.
Our contributions are twofold: (i) we model the optimal compiler for DQC using a Markov Decision Process (MDP) formulation, establishing the existence of an optimal algorithm, and (ii) we introduce a constrained Reinforcement Learning (RL) method to approximate this optimal compiler.
arXiv Detail & Related papers (2024-04-25T23:03:20Z) - Elastic Entangled Pair and Qubit Resource Management in Quantum Cloud
Computing [73.7522199491117]
Quantum cloud computing (QCC) offers a promising approach to efficiently provide quantum computing resources.
The fluctuations in user demand and quantum circuit requirements are challenging for efficient resource provisioning.
We propose a resource allocation model to provision quantum computing and networking resources.
arXiv Detail & Related papers (2023-07-25T00:38:46Z) - A Design Framework for the Simulation of Distributed Quantum Computing [2.969582361376132]
Growing demand for large-scale quantum computers is pushing research on Distributed Quantum Computing (DQC)
Recent experimental efforts have demonstrated some of the building blocks for such a design.
DQC systems are clusters of quantum processing units connected by means of quantum network infrastructures.
arXiv Detail & Related papers (2023-06-20T13:52:05Z) - Optimal Stochastic Resource Allocation for Distributed Quantum Computing [50.809738453571015]
We propose a resource allocation scheme for distributed quantum computing (DQC) based on programming to minimize the total deployment cost for quantum resources.
The evaluation demonstrates the effectiveness and ability of the proposed scheme to balance the utilization of quantum computers and on-demand quantum computers.
arXiv Detail & Related papers (2022-09-16T02:37:32Z) - QSAN: A Near-term Achievable Quantum Self-Attention Network [73.15524926159702]
Self-Attention Mechanism (SAM) is good at capturing the internal connections of features.
A novel Quantum Self-Attention Network (QSAN) is proposed for image classification tasks on near-term quantum devices.
arXiv Detail & Related papers (2022-07-14T12:22:51Z) - Optimizing Tensor Network Contraction Using Reinforcement Learning [86.05566365115729]
We propose a Reinforcement Learning (RL) approach combined with Graph Neural Networks (GNN) to address the contraction ordering problem.
The problem is extremely challenging due to the huge search space, the heavy-tailed reward distribution, and the challenging credit assignment.
We show how a carefully implemented RL-agent that uses a GNN as the basic policy construct can address these challenges.
arXiv Detail & Related papers (2022-04-18T21:45:13Z) - Quingo: A Programming Framework for Heterogeneous Quantum-Classical
Computing with NISQ Features [0.0]
We propose the Quingo framework to integrate and manage quantum-classical software and hardware to provide the programmability over HQCC applications.
We also propose the Quingo programming language, an external domain-specific language highlighting timer-based timing control and opaque operation definition.
arXiv Detail & Related papers (2020-09-02T06:42:51Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.