A quantum-classical cloud platform optimized for variational hybrid
algorithms
- URL: http://arxiv.org/abs/2001.04449v3
- Date: Sun, 31 May 2020 01:59:15 GMT
- Title: A quantum-classical cloud platform optimized for variational hybrid
algorithms
- Authors: Peter J. Karalekas, Nikolas A. Tezak, Eric C. Peterson, Colm A. Ryan,
Marcus P. da Silva, and Robert S. Smith
- Abstract summary: This work enumerates the architectural requirements of a quantum-classical cloud platform.
We present a framework for benchmarking its runtime performance.
We show that integrating these two features into the Rigetti Quantum Cloud Services (QCS) platform results in considerable improvements to the latencies that govern algorithm runtime.
- Score: 0.0
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: In order to support near-term applications of quantum computing, a new
compute paradigm has emerged--the quantum-classical cloud--in which quantum
computers (QPUs) work in tandem with classical computers (CPUs) via a shared
cloud infrastructure. In this work, we enumerate the architectural requirements
of a quantum-classical cloud platform, and present a framework for benchmarking
its runtime performance. In addition, we walk through two platform-level
enhancements, parametric compilation and active qubit reset, that specifically
optimize a quantum-classical architecture to support variational hybrid
algorithms (VHAs), the most promising applications of near-term quantum
hardware. Finally, we show that integrating these two features into the Rigetti
Quantum Cloud Services (QCS) platform results in considerable improvements to
the latencies that govern algorithm runtime.
Related papers
- Parallel Quantum Computing Simulations via Quantum Accelerator Platform Virtualization [44.99833362998488]
We present a model for parallelizing simulation of quantum circuit executions.
The model can take advantage of its backend-agnostic features, enabling parallel quantum circuit execution over any target backend.
arXiv Detail & Related papers (2024-06-05T17:16:07Z) - Multi-GPU-Enabled Hybrid Quantum-Classical Workflow in Quantum-HPC Middleware: Applications in Quantum Simulations [1.9922905420195367]
This study introduces an innovative distribution-aware Quantum-Classical-Quantum architecture.
It integrates cutting-edge quantum software framework works with high-performance classical computing resources.
It addresses challenges in quantum simulation for materials and condensed matter physics.
arXiv Detail & Related papers (2024-03-09T07:38:45Z) - Quantum Subroutine for Variance Estimation: Algorithmic Design and Applications [80.04533958880862]
Quantum computing sets the foundation for new ways of designing algorithms.
New challenges arise concerning which field quantum speedup can be achieved.
Looking for the design of quantum subroutines that are more efficient than their classical counterpart poses solid pillars to new powerful quantum algorithms.
arXiv Detail & Related papers (2024-02-26T09:32:07Z) - A Quantum-Classical Collaborative Training Architecture Based on Quantum
State Fidelity [50.387179833629254]
We introduce a collaborative classical-quantum architecture called co-TenQu.
Co-TenQu enhances a classical deep neural network by up to 41.72% in a fair setting.
It outperforms other quantum-based methods by up to 1.9 times and achieves similar accuracy while utilizing 70.59% fewer qubits.
arXiv Detail & Related papers (2024-02-23T14:09:41Z) - Hungarian Qubit Assignment for Optimized Mapping of Quantum Circuits on
Multi-Core Architectures [1.1288814203214292]
Quantum computers are expected to adopt a modular approach, featuring clusters of tightly connected quantum bits with sparser connections between these clusters.
Efficiently distributing qubits across multiple processing cores is critical for improving quantum computing systems' performance and scalability.
We propose the Hungarian Qubit Assignment (HQA) algorithm, which leverages the Hungarian algorithm to improve qubit-to-core assignment.
arXiv Detail & Related papers (2023-09-21T15:48:45Z) - Quantum Annealing for Single Image Super-Resolution [86.69338893753886]
We propose a quantum computing-based algorithm to solve the single image super-resolution (SISR) problem.
The proposed AQC-based algorithm is demonstrated to achieve improved speed-up over a classical analog while maintaining comparable SISR accuracy.
arXiv Detail & Related papers (2023-04-18T11:57:15Z) - A Framework for Demonstrating Practical Quantum Advantage: Racing
Quantum against Classical Generative Models [62.997667081978825]
We build over a proposed framework for evaluating the generalization performance of generative models.
We establish the first comparative race towards practical quantum advantage (PQA) between classical and quantum generative models.
Our results suggest that QCBMs are more efficient in the data-limited regime than the other state-of-the-art classical generative models.
arXiv Detail & Related papers (2023-03-27T22:48:28Z) - Practical application-specific advantage through hybrid quantum
computing [0.0]
We present a hybrid quantum cloud based on a memory-centric and heterogeneous multiprocessing architecture.
We show the advantage of hybrid algorithms compared to standard classical algorithms in both the computational speed and quality of the solution.
arXiv Detail & Related papers (2022-05-10T12:58:41Z) - Quantum circuit architecture search for variational quantum algorithms [88.71725630554758]
We propose a resource and runtime efficient scheme termed quantum architecture search (QAS)
QAS automatically seeks a near-optimal ansatz to balance benefits and side-effects brought by adding more noisy quantum gates.
We implement QAS on both the numerical simulator and real quantum hardware, via the IBM cloud, to accomplish data classification and quantum chemistry tasks.
arXiv Detail & Related papers (2020-10-20T12:06:27Z) - Electronic structure with direct diagonalization on a D-Wave quantum
annealer [62.997667081978825]
This work implements the general Quantum Annealer Eigensolver (QAE) algorithm to solve the molecular electronic Hamiltonian eigenvalue-eigenvector problem on a D-Wave 2000Q quantum annealer.
We demonstrate the use of D-Wave hardware for obtaining ground and electronically excited states across a variety of small molecular systems.
arXiv Detail & Related papers (2020-09-02T22:46:47Z) - Intel Quantum Simulator: A cloud-ready high-performance simulator of
quantum circuits [0.0]
We introduce the latest release of Intel Quantum Simulator (IQS), formerly known as qHiPSTER.
The high-performance computing capability of the software allows users to leverage the available hardware resources.
IQS allows to subdivide the computational resources to simulate a pool of related circuits in parallel.
arXiv Detail & Related papers (2020-01-28T19:00:25Z)
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.