Influence of HW-SW-Co-Design on Quantum Computing Scalability
- URL: http://arxiv.org/abs/2306.04246v1
- Date: Wed, 7 Jun 2023 08:36:33 GMT
- Title: Influence of HW-SW-Co-Design on Quantum Computing Scalability
- Authors: Hila Safi, Karen Wintersperger, Wolfgang Mauerer
- Abstract summary: We investigate how key figures - circuit depth and gate count - required to solve four NP-complete problems vary with tailored hardware properties.
Our results reveal that achieving near-optimal performance and properties does not necessarily require optimal quantum hardware.
- Score: 6.2543855067453675
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: The use of quantum processing units (QPUs) promises speed-ups for solving
computational problems. Yet, current devices are limited by the number of
qubits and suffer from significant imperfections, which prevents achieving
quantum advantage. To step towards practical utility, one approach is to apply
hardware-software co-design methods. This can involve tailoring problem
formulations and algorithms to the quantum execution environment, but also
entails the possibility of adapting physical properties of the QPU to specific
applications. In this work, we follow the latter path, and investigate how key
figures - circuit depth and gate count - required to solve four cornerstone
NP-complete problems vary with tailored hardware properties. Our results reveal
that achieving near-optimal performance and properties does not necessarily
require optimal quantum hardware, but can be satisfied with much simpler
structures that can potentially be realised for many hardware approaches. Using
statistical analysis techniques, we additionally identify an underlying general
model that applies to all subject problems. This suggests that our results may
be universally applicable to other algorithms and problem domains, and tailored
QPUs can find utility outside their initially envisaged problem domains. The
substantial possible improvements nonetheless highlight the importance of QPU
tailoring to progress towards practical deployment and scalability of quantum
software.
Related papers
- QCircuitNet: A Large-Scale Hierarchical Dataset for Quantum Algorithm Design [17.747641494506087]
We introduce QCircuitNet, the first benchmark and test dataset designed to evaluate AI's capability in designing and implementing quantum algorithms.
Unlike using AI for writing traditional codes, this task is fundamentally different and significantly more complicated due to highly flexible design space and intricate manipulation of qubits.
arXiv Detail & Related papers (2024-10-10T14:24:30Z) - PO-QA: A Framework for Portfolio Optimization using Quantum Algorithms [4.2435928520499635]
Portfolio Optimization (PO) is a financial problem aiming to maximize the net gains while minimizing the risks in a given investment portfolio.
We propose a novel scalable framework, denoted PO-QA, to investigate the variation of quantum parameters.
Our results provide effective insights into comprehending PO from the lens of Quantum Machine Learning.
arXiv Detail & Related papers (2024-07-29T10:26:28Z) - Quantum algorithms: A survey of applications and end-to-end complexities [90.05272647148196]
The anticipated applications of quantum computers span across science and industry.
We present a survey of several potential application areas of quantum algorithms.
We outline the challenges and opportunities in each area in an "end-to-end" fashion.
arXiv Detail & Related papers (2023-10-04T17:53:55Z) - Variational Quantum Algorithms for Computational Fluid Dynamics [0.0]
Variational quantum algorithms are particularly promising since they are comparatively noise tolerant.
We show how variational quantum algorithms can be utilized in computational fluid dynamics.
We argue that a quantum advantage over classical computing methods could be achieved by the end of this decade.
arXiv Detail & Related papers (2022-09-11T18:49:22Z) - QPU-System Co-Design for Quantum HPC Accelerators [6.2543855067453675]
We study the influence of different parameters on the runtime of quantum programs on tailored hybrid CPU-QPU-systems.
We provide an intuition to the HPC community on potentials and limitations of co-design approaches.
arXiv Detail & Related papers (2022-08-24T11:33:48Z) - Adiabatic Quantum Computing for Multi Object Tracking [170.8716555363907]
Multi-Object Tracking (MOT) is most often approached in the tracking-by-detection paradigm, where object detections are associated through time.
As these optimization problems are often NP-hard, they can only be solved exactly for small instances on current hardware.
We show that our approach is competitive compared with state-of-the-art optimization-based approaches, even when using of-the-shelf integer programming solvers.
arXiv Detail & Related papers (2022-02-17T18:59:20Z) - Quantum circuit architecture search on a superconducting processor [56.04169357427682]
Variational quantum algorithms (VQAs) have shown strong evidences to gain provable computational advantages for diverse fields such as finance, machine learning, and chemistry.
However, the ansatz exploited in modern VQAs is incapable of balancing the tradeoff between expressivity and trainability.
We demonstrate the first proof-of-principle experiment of applying an efficient automatic ansatz design technique to enhance VQAs on an 8-qubit superconducting quantum processor.
arXiv Detail & Related papers (2022-01-04T01:53:42Z) - 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) - Space-efficient binary optimization for variational computing [68.8204255655161]
We show that it is possible to greatly reduce the number of qubits needed for the Traveling Salesman Problem.
We also propose encoding schemes which smoothly interpolate between the qubit-efficient and the circuit depth-efficient models.
arXiv Detail & Related papers (2020-09-15T18:17:27Z) - 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) - Approximate Approximation on a Quantum Annealer [13.66711311825402]
Many problems of industrial interest are NP-complete, and quickly exhaust resources of computational devices with increasing input sizes.
Quantumnealers (QA) are physical devices that aim at this class of problems by exploiting quantum mechanical properties.
arXiv Detail & Related papers (2020-04-20T13:15:20Z)
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.