scholarly journals Iterative qubit-excitation based variational quantum eigensolver

2021 ◽  
Author(s):  
Yordan Yordanov ◽  
Vasileios Armaos ◽  
Crispin Barnes ◽  
David Arvidsson-Shukur
Keyword(s):  
Numerical Simulations ◽  
Small Molecules ◽  
Time Complexity ◽  
Molecular Simulations ◽  
Quantum Circuits ◽  
Quantum Computers ◽  
Successful Implementation ◽  
Intermediate Scale ◽  
Promising Application ◽  
Physical Features

Abstract Molecular simulations with the variational quantum eigensolver (VQE) are a promising application for emerging noisy intermediate-scale quantum computers. Constructing accurate molecular ansatze that are easy to optimize and implemented by shallow quantum circuits is crucial for the successful implementation of such simulations. Ansatze are, generally, constructed as series of fermionic-excitation evolutions. Instead, we demonstrate the usefulness of constructing ansatze with ``qubit-excitation evolutions', which, contrary to fermionic excitation evolutions, obey ``qubit commutation relations'. We show that qubit excitation evolutions, despite the lack of some of the physical features of fermionic excitation evolutions, accurately construct ansatze, while requiring asymptotically fewer gates. Utilizing qubit excitation evolutions, we introduce the iterative qubit excitation based VQE (IQEB-VQE) algorithm. The IQEB-VQE performs molecular simulations using a problem-tailored ansatz, grown iteratively by appending evolutions of single and double qubit excitation operators. By performing numerical simulations for small molecules, we benchmark the IQEB-VQE, and compare it against other competitive VQE algorithms. In terms of circuit efficiency and time complexity, we find that the IQEB-VQE systematically outperforms the previously most circuit-efficient, practically scalable VQE algorithms.

scholarly journals Qubit-excitation-based adaptive variational quantum eigensolver

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Yordan S. Yordanov ◽  
V. Armaos ◽  
Crispin H. W. Barnes ◽  
David R. M. Arvidsson-Shukur
Keyword(s):  
Numerical Simulations ◽  
Small Molecules ◽  
Molecular Simulations ◽  
Quantum Circuits ◽  
Quantum Computers ◽  
Successful Implementation ◽  
Intermediate Scale ◽  
Commutation Relations ◽  
Promising Application ◽  
Physical Features

AbstractMolecular simulations with the variational quantum eigensolver (VQE) are a promising application for emerging noisy intermediate-scale quantum computers. Constructing accurate molecular ansätze that are easy to optimize and implemented by shallow quantum circuits is crucial for the successful implementation of such simulations. Ansätze are, generally, constructed as series of fermionic-excitation evolutions. Instead, we demonstrate the usefulness of constructing ansätze with "qubit-excitation evolutions”, which, contrary to fermionic excitation evolutions, obey "qubit commutation relations”. We show that qubit excitation evolutions, despite the lack of some of the physical features of fermionic excitation evolutions, accurately construct ansätze, while requiring asymptotically fewer gates. Utilizing qubit excitation evolutions, we introduce the qubit-excitation-based adaptive (QEB-ADAPT)-VQE protocol. The QEB-ADAPT-VQE is a modification of the ADAPT-VQE that performs molecular simulations using a problem-tailored ansatz, grown iteratively by appending evolutions of qubit excitation operators. By performing classical numerical simulations for small molecules, we benchmark the QEB-ADAPT-VQE, and compare it against the original fermionic-ADAPT-VQE and the qubit-ADAPT-VQE. In terms of circuit efficiency and convergence speed, we demonstrate that the QEB-ADAPT-VQE outperforms the qubit-ADAPT-VQE, which to our knowledge was the previous most circuit-efficient scalable VQE protocol for molecular simulations.

scholarly journals Decoherence dynamics estimation for superconducting gate-model quantum computers

2020 ◽  
Vol 19 (10) ◽  
Author(s):  
Laszlo Gyongyosi
Keyword(s):  
Gaussian Noise ◽  
Quantum Computer ◽  
Computer Architectures ◽  
Quantum Circuits ◽  
Optimal Placement ◽  
Quantum Computers ◽  
Intermediate Scale ◽  
Layout Generation ◽  
Quantum Technology ◽  
Physical Layout

Abstract Superconducting gate-model quantum computer architectures provide an implementable model for practical quantum computations in the NISQ (noisy intermediate scale quantum) technology era. Due to hardware restrictions and decoherence, generating the physical layout of the quantum circuits of a gate-model quantum computer is a challenge. Here, we define a method for layout generation with a decoherence dynamics estimation in superconducting gate-model quantum computers. We propose an algorithm for the optimal placement of the quantum computational blocks of gate-model quantum circuits. We study the effects of capacitance interference on the distribution of the Gaussian noise in the Josephson energy.

scholarly journals Fisher Information in Noisy Intermediate-Scale Quantum Applications

Quantum ◽  
2021 ◽  
Vol 5 ◽  
pp. 539
Author(s):  
Johannes Jakob Meyer
Keyword(s):  
Fisher Information ◽  
Quantum Algorithms ◽  
Quantum Fisher Information ◽  
Quantum Systems ◽  
Quantum Circuits ◽  
Quantum Computers ◽  
Quantum Devices ◽  
Intermediate Scale ◽  
Quantum Sensing ◽  
Near Term

The recent advent of noisy intermediate-scale quantum devices, especially near-term quantum computers, has sparked extensive research efforts concerned with their possible applications. At the forefront of the considered approaches are variational methods that use parametrized quantum circuits. The classical and quantum Fisher information are firmly rooted in the field of quantum sensing and have proven to be versatile tools to study such parametrized quantum systems. Their utility in the study of other applications of noisy intermediate-scale quantum devices, however, has only been discovered recently. Hoping to stimulate more such applications, this article aims to further popularize classical and quantum Fisher information as useful tools for near-term applications beyond quantum sensing. We start with a tutorial that builds an intuitive understanding of classical and quantum Fisher information and outlines how both quantities can be calculated on near-term devices. We also elucidate their relationship and how they are influenced by noise processes. Next, we give an overview of the core results of the quantum sensing literature and proceed to a comprehensive review of recent applications in variational quantum algorithms and quantum machine learning.

scholarly journals VQE method: a short survey and recent developments

2022 ◽  
Vol 6 (1) ◽  
Author(s):  
Dmitry A. Fedorov ◽  
Bo Peng ◽  
Niranjan Govind ◽  
Yuri Alexeev
Keyword(s):  
Small Molecules ◽  
Optimization Problem ◽  
Quantum Algorithms ◽  
Quantum Circuits ◽  
Quantum Computers ◽  
Phase Estimation ◽  
Two Factors ◽  
Recent Developments ◽  
Near Future ◽  
Classical Optimization

AbstractThe variational quantum eigensolver (VQE) is a method that uses a hybrid quantum-classical computational approach to find eigenvalues of a Hamiltonian. VQE has been proposed as an alternative to fully quantum algorithms such as quantum phase estimation (QPE) because fully quantum algorithms require quantum hardware that will not be accessible in the near future. VQE has been successfully applied to solve the electronic Schrödinger equation for a variety of small molecules. However, the scalability of this method is limited by two factors: the complexity of the quantum circuits and the complexity of the classical optimization problem. Both of these factors are affected by the choice of the variational ansatz used to represent the trial wave function. Hence, the construction of an efficient ansatz is an active area of research. Put another way, modern quantum computers are not capable of executing deep quantum circuits produced by using currently available ansatzes for problems that map onto more than several qubits. In this review, we present recent developments in the field of designing efficient ansatzes that fall into two categories—chemistry–inspired and hardware–efficient—that produce quantum circuits that are easier to run on modern hardware. We discuss the shortfalls of ansatzes originally formulated for VQE simulations, how they are addressed in more sophisticated methods, and the potential ways for further improvements.

scholarly journals Expressibility of the alternating layered ansatz for quantum computation

Quantum ◽  
2021 ◽  
Vol 5 ◽  
pp. 434
Author(s):  
Kouhei Nakaji ◽  
Naoki Yamamoto
Keyword(s):  
Quantum Computing ◽  
Quantum Computation ◽  
Critical Issue ◽  
Quantum Circuits ◽  
Quantum Computers ◽  
Intermediate Scale ◽  
State Generation ◽  
Proper Definition ◽  
Definition Of ◽  
Designing Method

The hybrid quantum-classical algorithm is actively examined as a technique applicable even to intermediate-scale quantum computers. To execute this algorithm, the hardware efficient ansatz is often used, thanks to its implementability and expressibility; however, this ansatz has a critical issue in its trainability in the sense that it generically suffers from the so-called gradient vanishing problem. This issue can be resolved by limiting the circuit to the class of shallow alternating layered ansatz. However, even though the high trainability of this ansatz is proved, it is still unclear whether it has rich expressibility in state generation. In this paper, with a proper definition of the expressibility found in the literature, we show that the shallow alternating layered ansatz has almost the same level of expressibility as that of hardware efficient ansatz. Hence the expressibility and the trainability can coexist, giving a new designing method for quantum circuits in the intermediate-scale quantum computing era.

scholarly journals An Optimal Footprint Based Coverage Planning for Hydro Blasting Robots

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1194
Author(s):  
Thejus Pathmakumar ◽  
Madan Mohan Rayguru ◽  
Sriharsha Ghanta ◽  
Manivannan Kalimuthu ◽  
Mohan Rajesh Elara
Keyword(s):  
Genetic Algorithm ◽  
Mobile Robots ◽  
Numerical Simulations ◽  
Labour Force ◽  
Successful Implementation ◽  
Multi Objective Optimization ◽  
Metallic Surfaces ◽  
Industrial Sites ◽  
Experimental Trials ◽  
Time And Energy

The hydro blasting of metallic surfaces is an essential maintenance task in various industrial sites. Its requirement of a considerable labour force and time, calls for automating the hydro blasting jobs through mobile robots. A hydro blasting robot should be able to cover the required area for a successful implementation. If a conventional robot footprint is chosen, the blasting may become inefficient, even though the concerned area is completely covered. In this work, the blasting arm’s sweeping angle is chosen as the robot’s footprint for hydro blasting task, and a multi-objective optimization-based framework is proposed to compute the optimal sweeping arc. The genetic algorithm (GA) methodology is exploited to compute the optimal footprint, which minimizes the blasting time and energy simultaneously. Multiple numerical simulations are performed to show the effectiveness of the proposed approach. Moreover, the strategy is successfully implemented on our hydro blasting robot named Hornbill, and the efficacy of the proposed approach is validated through experimental trials.

scholarly journals Benchmarking Quantum Computers and the Impact of Quantum Noise

2021 ◽  
Vol 54 (7) ◽  
pp. 1-35
Author(s):  
Salonik Resch ◽  
Ulya R. Karpuzcu
Keyword(s):  
Numerical Simulations ◽  
Computer Architecture ◽  
Quantum Noise ◽  
Computing System ◽  
Quantum Computers ◽  
Complicating Factors ◽  
The Impact

Benchmarking is how the performance of a computing system is determined. Surprisingly, even for classical computers this is not a straightforward process. One must choose the appropriate benchmark and metrics to extract meaningful results. Different benchmarks test the system in different ways, and each individual metric may or may not be of interest. Choosing the appropriate approach is tricky. The situation is even more open ended for quantum computers, where there is a wider range of hardware, fewer established guidelines, and additional complicating factors. Notably, quantum noise significantly impacts performance and is difficult to model accurately. Here, we discuss benchmarking of quantum computers from a computer architecture perspective and provide numerical simulations highlighting challenges that suggest caution.

scholarly journals Comparison of quantum-walk implementations on noisy intermediate-scale quantum computers

2021 ◽  
Vol 103 (2) ◽  
Author(s):  
Konstantinos Georgopoulos ◽  
Clive Emary ◽  
Paolo Zuliani
Keyword(s):  
Quantum Walk ◽  
Quantum Computers ◽  
Intermediate Scale

Towards Compact Modeling of Noisy Quantum Computers: A Molecular-Spin-Qubit Case of Study

2022 ◽  
Vol 18 (1) ◽  
pp. 1-26
Author(s):  
Mario Simoni ◽  
Giovanni Amedeo Cirillo ◽  
Giovanna Turvani ◽  
Mariagrazia Graziano ◽  
Maurizio Zamboni
Keyword(s):  
Physical Simulation ◽  
Quantum Circuits ◽  
Compact Modeling ◽  
Quantum Computers ◽  
Expected Performance ◽  
Classical Simulation ◽  
Spin Qubit ◽  
Compact Models ◽  
Standard Formalism ◽  
Definition Of

Classical simulation of Noisy Intermediate Scale Quantum computers is a crucial task for testing the expected performance of real hardware. The standard approach, based on solving Schrödinger and Lindblad equations, is demanding when scaling the number of qubits in terms of both execution time and memory. In this article, attempts in defining compact models for the simulation of quantum hardware are proposed, ensuring results close to those obtained with standard formalism. Molecular Nuclear Magnetic Resonance quantum hardware is the target technology, where three non-ideality phenomena—common to other quantum technologies—are taken into account: decoherence, off-resonance qubit evolution, and undesired qubit-qubit residual interaction. A model for each non-ideality phenomenon is embedded into a MATLAB simulation infrastructure of noisy quantum computers. The accuracy of the models is tested on a benchmark of quantum circuits, in the expected operating ranges of quantum hardware. The corresponding outcomes are compared with those obtained via numeric integration of the Schrödinger equation and the Qiskit’s QASMSimulator. The achieved results give evidence that this work is a step forward towards the definition of compact models able to provide fast results close to those obtained with the traditional physical simulation strategies, thus paving the way for their integration into a classical simulator of quantum computers.

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