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A special issue of Entropy (ISSN 1099-4300). This special issue belongs to the section "Quantum Information".

Deadline for manuscript submissions: closed (30 April 2021) | Viewed by 27206

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Dr. Matthew Broome

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Guest Editor

Department of Physics, University of Warwick, Coventry CV4 7AL, UK
Interests: Quantum computation; Quantum optics

Special Issue Information

Dear Colleagues,

During the last decade, we have made steady and sure progress toward post-classical computational capabilities using the latest experimental methods to control, interact and measure large-scale quantum systems. The culmination of all this work has seen the first credible realisation of so-called quantum supremacy using more than 50 superconducting quantum bits to carry out a task deemed intractable for conventional computers.

As such, today we are entering the realm of so-called noisy intermediate-scale quantum (NISQ) technologies, where post-classical advantages can be realised by exploiting the small yet significant amounts of coherence and entanglement in a many-body quantum system. These machines are precursors to the coveted fully scalable and fault-tolerant quantum computer, composed of 50–300 physical qubits and to date are mostly solving sampling related problems. We expect NISQ machines to have a significant impact in areas such as quantum machine learning, artificial intelligence and most importantly the development of scalable and fault-tolerant quantum computers.

This Special Issue will bring together researchers presenting original and recent developments on NISQ technologies. In particular, authors should address challenges, which once overcome, will allow NISQ machines to serve our computational needs beyond proof-of-principle demonstrations of post-classical problems. Both algorithmic and architectural issues should be explored, in particular, the notion of specific algorithms running on compatible—perhaps even bespoke—physical hardware.

Dr. Matthew Broome
Guest Editor

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Published Papers (7 papers)

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Research

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29 pages, 1543 KiB

Open AccessArticle

Variational Quantum Chemistry Programs in JaqalPaq

by Oliver G. Maupin, Andrew D. Baczewski, Peter J. Love and Andrew J. Landahl

Entropy 2021, 23(6), 657; https://doi.org/10.3390/e23060657 - 24 May 2021

Cited by 2 | Viewed by 2596

Abstract

We present example quantum chemistry programs written with JaqalPaq, a python meta-programming language used to code in Jaqal (Just Another Quantum Assembly Language). These JaqalPaq algorithms are intended to be run on the Quantum Scientific Computing Open User Testbed (QSCOUT) platform at Sandia National Laboratories. Our exemplars use the variational quantum eigensolver (VQE) quantum algorithm to compute the ground state energies of the

H_{2}

{HeH}^{+}

, and

LiH

molecules. Since the exemplars focus on how to program in JaqalPaq, the calculations of the second-quantized Hamiltonians are performed with the PySCF python package, and the mappings of the fermions to qubits are obtained from the OpenFermion python package. Using the emulator functionality of JaqalPaq, we emulate how these exemplars would be executed on an error-free QSCOUT platform and compare the emulated computation of the bond-dissociation curves for these molecules with their exact forms within the relevant basis. Full article

(This article belongs to the Special Issue Noisy Intermediate-Scale Quantum Technologies (NISQ))

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10 pages, 941 KiB

Open AccessFeature PaperArticle

Light-Front Field Theory on Current Quantum Computers

by Michael Kreshchuk, Shaoyang Jia, William M. Kirby, Gary Goldstein, James P. Vary and Peter J. Love

Entropy 2021, 23(5), 597; https://doi.org/10.3390/e23050597 - 12 May 2021

Cited by 43 | Viewed by 2807

Abstract

We present a quantum algorithm for simulation of quantum field theory in the light-front formulation and demonstrate how existing quantum devices can be used to study the structure of bound states in relativistic nuclear physics. Specifically, we apply the Variational Quantum Eigensolver algorithm to find the ground state of the light-front Hamiltonian obtained within the Basis Light-Front Quantization (BLFQ) framework. The BLFQ formulation of quantum field theory allows one to readily import techniques developed for digital quantum simulation of quantum chemistry. This provides a method that can be scaled up to simulation of full, relativistic quantum field theories in the quantum advantage regime. As an illustration, we calculate the mass, mass radius, decay constant, electromagnetic form factor, and charge radius of the pion on the IBM Vigo chip. This is the first time that the light-front approach to quantum field theory has been used to enable simulation of a real physical system on a quantum computer. Full article

(This article belongs to the Special Issue Noisy Intermediate-Scale Quantum Technologies (NISQ))

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21 pages, 413 KiB

Open AccessArticle

Quantum Randomness is Chimeric

by Karl Svozil

Entropy 2021, 23(5), 519; https://doi.org/10.3390/e23050519 - 24 Apr 2021

Cited by 3 | Viewed by 2794

Abstract

If quantum mechanics is taken for granted, the randomness derived from it may be vacuous or even delusional, yet sufficient for many practical purposes. “Random” quantum events are intimately related to the emergence of both space-time as well as the identification of physical [...] Read more.

(This article belongs to the Special Issue Noisy Intermediate-Scale Quantum Technologies (NISQ))

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14 pages, 1344 KiB

Open AccessEditor’s ChoiceArticle

Federated Quantum Machine Learning

by Samuel Yen-Chi Chen and Shinjae Yoo

Entropy 2021, 23(4), 460; https://doi.org/10.3390/e23040460 - 13 Apr 2021

Cited by 44 | Viewed by 7944

Abstract

Distributed training across several quantum computers could significantly improve the training time and if we could share the learned model, not the data, it could potentially improve the data privacy as the training would happen where the data is located. One of the potential schemes to achieve this property is the federated learning (FL), which consists of several clients or local nodes learning on their own data and a central node to aggregate the models collected from those local nodes. However, to the best of our knowledge, no work has been done in quantum machine learning (QML) in federation setting yet. In this work, we present the federated training on hybrid quantum-classical machine learning models although our framework could be generalized to pure quantum machine learning model. Specifically, we consider the quantum neural network (QNN) coupled with classical pre-trained convolutional model. Our distributed federated learning scheme demonstrated almost the same level of trained model accuracies and yet significantly faster distributed training. It demonstrates a promising future research direction for scaling and privacy aspects. Full article

(This article belongs to the Special Issue Noisy Intermediate-Scale Quantum Technologies (NISQ))

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20 pages, 8795 KiB

Open AccessEditor’s ChoiceArticle

Dynamic Topology Reconfiguration of Boltzmann Machines on Quantum Annealers

by Jeremy Liu, Ke-Thia Yao and Federico Spedalieri

Entropy 2020, 22(11), 1202; https://doi.org/10.3390/e22111202 - 24 Oct 2020

Cited by 5 | Viewed by 2484

Abstract

Boltzmann machines have useful roles in deep learning applications, such as generative data modeling, initializing weights for other types of networks, or extracting efficient representations from high-dimensional data. Most Boltzmann machines use restricted topologies that exclude looping connectivity, as such connectivity creates complex distributions that are difficult to sample. We have used an open-system quantum annealer to sample from complex distributions and implement Boltzmann machines with looping connectivity. Further, we have created policies mapping Boltzmann machine variables to the quantum bits of an annealer. These policies, based on correlation and entropy metrics, dynamically reconfigure the topology of Boltzmann machines during training and improve performance. Full article

(This article belongs to the Special Issue Noisy Intermediate-Scale Quantum Technologies (NISQ))

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12 pages, 966 KiB

Open AccessEditor’s ChoiceArticle

Hybrid Quantum-Classical Neural Network for Calculating Ground State Energies of Molecules

by Rongxin Xia and Sabre Kais

Entropy 2020, 22(8), 828; https://doi.org/10.3390/e22080828 - 29 Jul 2020

Cited by 17 | Viewed by 5647

Abstract

We present a hybrid quantum-classical neural network that can be trained to perform electronic structure calculation and generate potential energy curves of simple molecules. The method is based on the combination of parameterized quantum circuits and measurements. With unsupervised training, the neural network can generate electronic potential energy curves based on training at certain bond lengths. To demonstrate the power of the proposed new method, we present the results of using the quantum-classical hybrid neural network to calculate ground state potential energy curves of simple molecules such as H

_{2}

, LiH, and BeH

_{2}

. The results are very accurate and the approach could potentially be used to generate complex molecular potential energy surfaces. Full article

(This article belongs to the Special Issue Noisy Intermediate-Scale Quantum Technologies (NISQ))

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Review

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7 pages, 483 KiB

Open AccessEditor’s ChoiceReview

Advances in Atomtronics

by Ron A. Pepino

Entropy 2021, 23(5), 534; https://doi.org/10.3390/e23050534 - 27 Apr 2021

Cited by 5 | Viewed by 1895

Abstract

Atomtronics is a relatively new subfield of atomic physics that aims to realize the device behavior of electronic components in ultracold atom-optical systems. The fact that these systems are coherent makes them particularly interesting since, in addition to current, one can impart quantum states onto the current carriers themselves or perhaps perform quantum computational operations on them. After reviewing the fundamental ideas of this subfield, we report on the theoretical and experimental progress made towards developing externally-driven and closed loop devices. The functionality and potential applications for these atom analogs to electronic and spintronic systems is also discussed. Full article

(This article belongs to the Special Issue Noisy Intermediate-Scale Quantum Technologies (NISQ))

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