QuantumCircuitOpt: An Open-source Framework for Provably Optimal Quantum
Circuit Design
- URL: http://arxiv.org/abs/2111.11674v1
- Date: Tue, 23 Nov 2021 06:45:40 GMT
- Title: QuantumCircuitOpt: An Open-source Framework for Provably Optimal Quantum
Circuit Design
- Authors: Harsha Nagarajan, Owen Lockwood, Carleton Coffrin
- Abstract summary: We propose QuantumCircuitOpt, a novel open-source framework which implements mathematical optimization formulations and algorithms for decomposing arbitrary unitary gates into a sequence of hardware-native gates.
We show that QCOpt can find up to 57% reduction in the number of necessary gates on circuits with up to four qubits, and in run times less than a few minutes on commodity computing hardware.
We also show how the QCOpt package can be adapted to various built-in types of native gate sets, based on different hardware platforms like those produced by IBM, Rigetti and Google.
- Score: 0.0
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: In recent years, the quantum computing community has seen an explosion of
novel methods to implement non-trivial quantum computations on near-term
hardware. An important direction of research has been to decompose an arbitrary
entangled state, represented as a unitary, into a quantum circuit, that is, a
sequence of gates supported by a quantum processor. It has been well known that
circuits with longer decompositions and more entangling multi-qubit gates are
error-prone for the current noisy, intermediate-scale quantum devices. To this
end, there has been a significant interest to develop heuristic-based methods
to discover compact circuits. We contribute to this effort by proposing
QuantumCircuitOpt (QCOpt), a novel open-source framework which implements
mathematical optimization formulations and algorithms for decomposing arbitrary
unitary gates into a sequence of hardware-native gates. A core innovation of
QCOpt is that it provides optimality guarantees on the quantum circuits that it
produces. In particular, we show that QCOpt can find up to 57% reduction in the
number of necessary gates on circuits with up to four qubits, and in run times
less than a few minutes on commodity computing hardware. We also validate the
efficacy of QCOpt as a tool for quantum circuit design in comparison with a
naive brute-force enumeration algorithm. We also show how the QCOpt package can
be adapted to various built-in types of native gate sets, based on different
hardware platforms like those produced by IBM, Rigetti and Google. We hope this
package will facilitate further algorithmic exploration for quantum processor
designers, as well as quantum physicists.
Related papers
- Implementing multi-controlled X gates using the quantum Fourier transform [0.0]
We show how a quantum arithmetic-based approach can be efficiently used to implement many complex quantum gates.
We show how the depth of the circuit can be significantly reduced using only a few ancilla qubits.
arXiv Detail & Related papers (2024-07-25T13:22:00Z) - 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) - 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) - Revisiting the Mapping of Quantum Circuits: Entering the Multi-Core Era [2.465579331213113]
We introduce the Hungarian Qubit Assignment (HQA) algorithm, a multi-core mapping algorithm designed to optimize qubit assignments to cores with the aim of reducing inter-core communications.
Our evaluation of HQA against state-of-the-art circuit mapping algorithms for modular architectures reveals a $4.9times$ and $1.6times$ improvement in terms of execution time and non-local communications.
arXiv Detail & Related papers (2024-03-25T21:31:39Z) - Distributed quantum architecture search [0.0]
Variational quantum algorithms, inspired by neural networks, have become a novel approach in quantum computing.
Quantum architecture search tackles this by adjusting circuit structures along with gate parameters to automatically discover high-performance circuit structures.
We propose an end-to-end distributed quantum architecture search framework, where we aim to automatically design distributed quantum circuit structures for interconnected quantum processing units with specific qubit connectivity.
arXiv Detail & Related papers (2024-03-10T13:28:56Z) - QuantumSEA: In-Time Sparse Exploration for Noise Adaptive Quantum
Circuits [82.50620782471485]
QuantumSEA is an in-time sparse exploration for noise-adaptive quantum circuits.
It aims to achieve two key objectives: (1) implicit circuits capacity during training and (2) noise robustness.
Our method establishes state-of-the-art results with only half the number of quantum gates and 2x time saving of circuit executions.
arXiv Detail & Related papers (2024-01-10T22:33:00Z) - Iterative Qubits Management for Quantum Index Searching in a Hybrid
System [56.39703478198019]
IQuCS aims at index searching and counting in a quantum-classical hybrid system.
We implement IQuCS with Qiskit and conduct intensive experiments.
Results demonstrate that it reduces qubits consumption by up to 66.2%.
arXiv Detail & Related papers (2022-09-22T21:54:28Z) - Quantum Circuit Compiler for a Shuttling-Based Trapped-Ion Quantum
Computer [26.47874938214435]
We present a compiler capable of transforming and optimizing a quantum circuit targeting a shuttling-based trapped-ion quantum processor.
The results show that the gate counts can be reduced by factors up to 5.1 compared to standard Pytket and up to 2.2 compared to standard Qiskit compilation.
arXiv Detail & Related papers (2022-07-05T11:21:09Z) - Synthesis of Quantum Circuits with an Island Genetic Algorithm [44.99833362998488]
Given a unitary matrix that performs certain operation, obtaining the equivalent quantum circuit is a non-trivial task.
Three problems are explored: the coin for the quantum walker, the Toffoli gate and the Fredkin gate.
The algorithm proposed proved to be efficient in decomposition of quantum circuits, and as a generic approach, it is limited only by the available computational power.
arXiv Detail & Related papers (2021-06-06T13:15:25Z) - QUANTIFY: A framework for resource analysis and design verification of
quantum circuits [69.43216268165402]
QUANTIFY is an open-source framework for the quantitative analysis of quantum circuits.
It is based on Google Cirq and is developed with Clifford+T circuits in mind.
For benchmarking purposes QUANTIFY includes quantum memory and quantum arithmetic circuits.
arXiv Detail & Related papers (2020-07-21T15:36:25Z)
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.