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14 pages, 7729 KiB

Open AccessArticle

Tunable Non-Markovianity for Bosonic Quantum Memristors

by Jia-Liang Tang, Gabriel Alvarado Barrios, Enrique Solano and Francisco Albarrán-Arriagada

Entropy 2023, 25(5), 756; https://doi.org/10.3390/e25050756 - 06 May 2023

Viewed by 1379

We studied the tunable control of the non-Markovianity of a bosonic mode due to its coupling to a set of auxiliary qubits, both embedded in a thermal reservoir. Specifically, we considered a single cavity mode coupled to auxiliary qubits described by the Tavis–Cummings [...] Read more.

We studied the tunable control of the non-Markovianity of a bosonic mode due to its coupling to a set of auxiliary qubits, both embedded in a thermal reservoir. Specifically, we considered a single cavity mode coupled to auxiliary qubits described by the Tavis–Cummings model. As a figure of merit, we define the dynamical non-Markovianity as the tendency of a system to return to its initial state, instead of evolving monotonically to its steady state. We studied how this dynamical non-Markovianity can be manipulated in terms of the qubit frequency. We found that the control of the auxiliary systems affects the cavity dynamics as an effective time-dependent decay rate. Finally, we show how this tunable time-dependent decay rate can be tuned to engineer bosonic quantum memristors, involving memory effects that are fundamental for developing neuromorphic quantum technologies. Full article

(This article belongs to the Special Issue Quantum Control and Quantum Computing)

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9 pages, 468 KiB

Open AccessArticle

Optimal Shortcuts to Adiabatic Control by Lagrange Mechanics

by Lanlan Ma and Qian Kong

Entropy 2023, 25(5), 719; https://doi.org/10.3390/e25050719 - 26 Apr 2023

Cited by 1 | Viewed by 956

Abstract

We combined an inverse engineering technique based on Lagrange mechanics and optimal control theory to design an optimal trajectory that can transport a cartpole in a fast and stable way. For classical control, we used the relative displacement between the ball and the [...] Read more.

We combined an inverse engineering technique based on Lagrange mechanics and optimal control theory to design an optimal trajectory that can transport a cartpole in a fast and stable way. For classical control, we used the relative displacement between the ball and the trolley as the controller to study the anharmonic effect of the cartpole. Under this constraint, we used the time minimization principle in optimal control theory to find the optimal trajectory, and the solution of time minimization is the bang-bang form, which ensures that the pendulum is in a vertical upward position at the initial and the final moments and oscillates in a small angle range. Full article

(This article belongs to the Special Issue Quantum Control and Quantum Computing)

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13 pages, 2617 KiB

Open AccessArticle

Enhanced Efficiency at Maximum Power in a Fock–Darwin Model Quantum Dot Engine

by Francisco J. Peña, Nathan M. Myers, Daniel Órdenes, Francisco Albarrán-Arriagada and Patricio Vargas

Entropy 2023, 25(3), 518; https://doi.org/10.3390/e25030518 - 17 Mar 2023

Cited by 4 | Viewed by 1470

Abstract

We study the performance of an endoreversible magnetic Otto cycle with a working substance composed of a single quantum dot described using the well-known Fock–Darwin model. We find that tuning the intensity of the parabolic trap (geometrical confinement) impacts the proposed cycle’s performance, [...] Read more.

We study the performance of an endoreversible magnetic Otto cycle with a working substance composed of a single quantum dot described using the well-known Fock–Darwin model. We find that tuning the intensity of the parabolic trap (geometrical confinement) impacts the proposed cycle’s performance, quantified by the power, work, efficiency, and parameter region where the cycle operates as an engine. We demonstrate that a parameter region exists where the efficiency at maximum output power exceeds the Curzon–Ahlborn efficiency, the efficiency at maximum power achieved by a classical working substance. Full article

(This article belongs to the Special Issue Quantum Control and Quantum Computing)

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27 pages, 735 KiB

Open AccessArticle

HybriD-GM: A Framework for Quantum Computing Simulation Targeted to Hybrid Parallel Architectures

by Anderson Avila, Helida Santos, Anderson Cruz, Samuel Xavier-de-Souza, Giancarlo Lucca, Bruno Moura, Adenauer Yamin and Renata Reiser

Entropy 2023, 25(3), 503; https://doi.org/10.3390/e25030503 - 14 Mar 2023

Cited by 1 | Viewed by 1627

Abstract

This paper presents the HybriD-GM model conception, from modeling to consolidation. The D-GM environment is also extended, providing efficient parallel executions for quantum computing simulations, targeted to hybrid architectures considering the CPU and GPU integration. By managing projection operators over quantum structures, and [...] Read more.

This paper presents the HybriD-GM model conception, from modeling to consolidation. The D-GM environment is also extended, providing efficient parallel executions for quantum computing simulations, targeted to hybrid architectures considering the CPU and GPU integration. By managing projection operators over quantum structures, and exploring coalescing memory access patterns, the HybriD-GM model enables granularity control, optimizing hardware resources in distributed computations organized as tree data structures. In the HybriD-GM evaluation, simulations of Shor’s and Grover’s algorithms achieve significant performance improvements in comparison to the previous D-GM version, and also with other related works, for example, LIQUi|⟩ and ProjectQ simulators. Full article

(This article belongs to the Special Issue Quantum Control and Quantum Computing)

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15 pages, 878 KiB

Open AccessFeature PaperArticle

Characterization of a Driven Two-Level Quantum System by Supervised Learning

by Raphaël Couturier, Etienne Dionis, Stéphane Guérin, Christophe Guyeux and Dominique Sugny

Entropy 2023, 25(3), 446; https://doi.org/10.3390/e25030446 - 03 Mar 2023

Cited by 1 | Viewed by 1231

Abstract

We investigate the extent to which a two-level quantum system subjected to an external time-dependent drive can be characterized by supervised learning. We apply this approach to the case of bang-bang control and the estimation of the offset and the final distance to [...] Read more.

We investigate the extent to which a two-level quantum system subjected to an external time-dependent drive can be characterized by supervised learning. We apply this approach to the case of bang-bang control and the estimation of the offset and the final distance to a given target state. For any control protocol, the goal is to find the mapping between the offset and the distance. This mapping is interpolated using a neural network. The estimate is global in the sense that no a priori knowledge is required on the relation to be determined. Different neural network algorithms are tested on a series of data sets. We show that the mapping can be reproduced with very high precision in the direct case when the offset is known, while obstacles appear in the indirect case starting from the distance to the target. We point out the limits of the estimation procedure with respect to the properties of the mapping to be interpolated. We discuss the physical relevance of the different results. Full article

(This article belongs to the Special Issue Quantum Control and Quantum Computing)

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17 pages, 759 KiB

Open AccessArticle

Quantum Machine Learning for Distributed Quantum Protocols with Local Operations and Noisy Classical Communications

by Hari Hara Suthan Chittoor and Osvaldo Simeone

Entropy 2023, 25(2), 352; https://doi.org/10.3390/e25020352 - 14 Feb 2023

Viewed by 1434

Abstract

Distributed quantum information processing protocols such as quantum entanglement distillation and quantum state discrimination rely on local operations and classical communications (LOCC). Existing LOCC-based protocols typically assume the availability of ideal, noiseless, communication channels. In this paper, we study the case in which [...] Read more.

Distributed quantum information processing protocols such as quantum entanglement distillation and quantum state discrimination rely on local operations and classical communications (LOCC). Existing LOCC-based protocols typically assume the availability of ideal, noiseless, communication channels. In this paper, we study the case in which classical communication takes place over noisy channels, and we propose to address the design of LOCC protocols in this setting via the use of quantum machine learning tools. We specifically focus on the important tasks of quantum entanglement distillation and quantum state discrimination, and implement local processing through parameterized quantum circuits (PQCs) that are optimized to maximize the average fidelity and average success probability in the respective tasks, while accounting for communication errors. The introduced approach, Noise Aware-LOCCNet (NA-LOCCNet), is shown to have significant advantages over existing protocols designed for noiseless communications. Full article

(This article belongs to the Special Issue Quantum Control and Quantum Computing)

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12 pages, 574 KiB

Open AccessEditor’s ChoiceArticle

Toward Prediction of Financial Crashes with a D-Wave Quantum Annealer

by Yongcheng Ding, Javier Gonzalez-Conde, Lucas Lamata, José D. Martín-Guerrero, Enrique Lizaso, Samuel Mugel, Xi Chen, Román Orús, Enrique Solano and Mikel Sanz

Entropy 2023, 25(2), 323; https://doi.org/10.3390/e25020323 - 10 Feb 2023

Cited by 22 | Viewed by 3056

Abstract

The prediction of financial crashes in a complex financial network is known to be an NP-hard problem, which means that no known algorithm can efficiently find optimal solutions. We experimentally explore a novel approach to this problem by using a D-Wave quantum annealer, [...] Read more.

The prediction of financial crashes in a complex financial network is known to be an NP-hard problem, which means that no known algorithm can efficiently find optimal solutions. We experimentally explore a novel approach to this problem by using a D-Wave quantum annealer, benchmarking its performance for attaining a financial equilibrium. To be specific, the equilibrium condition of a nonlinear financial model is embedded into a higher-order unconstrained binary optimization (HUBO) problem, which is then transformed into a spin-

1 / 2

Hamiltonian with at most, two-qubit interactions. The problem is thus equivalent to finding the ground state of an interacting spin Hamiltonian, which can be approximated with a quantum annealer. The size of the simulation is mainly constrained by the necessity of a large number of physical qubits representing a logical qubit with the correct connectivity. Our experiment paves the way for the codification of this quantitative macroeconomics problem in quantum annealers. Full article

(This article belongs to the Special Issue Quantum Control and Quantum Computing)

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26 pages, 3817 KiB

Open AccessArticle

Quantum Control by Few-Cycles Pulses: The Two-Level Problem

by François Peyraut, Frédéric Holweck and Stéphane Guérin

Entropy 2023, 25(2), 212; https://doi.org/10.3390/e25020212 - 22 Jan 2023

Cited by 1 | Viewed by 1440

Abstract

We investigate the problem of population transfer in a two-states system driven by an external electromagnetic field featuring a few cycles, until the extreme limit of two or one cycle. Taking the physical constraint of zero-area total field into account, we determine strategies [...] Read more.

We investigate the problem of population transfer in a two-states system driven by an external electromagnetic field featuring a few cycles, until the extreme limit of two or one cycle. Taking the physical constraint of zero-area total field into account, we determine strategies leading to ultrahigh-fidelity population transfer despite the failure of the rotating wave approximation. We specifically implement adiabatic passage based on adiabatic Floquet theory for a number of cycles as low as 2.5 cycles, finding and making the dynamics follow an adiabatic trajectory connecting the initial and targeted states. Nonadiabatic strategies with shaped or chirped pulses, extending the

π

-pulse regime to two- or single-cycle pulses, are also derived. Full article

(This article belongs to the Special Issue Quantum Control and Quantum Computing)

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11 pages, 339 KiB

Open AccessArticle

Digital Quantum Simulation and Circuit Learning for the Generation of Coherent States

by Ruilin Liu, Sebastián V. Romero, Izaskun Oregi, Eneko Osaba, Esther Villar-Rodriguez and Yue Ban

Entropy 2022, 24(11), 1529; https://doi.org/10.3390/e24111529 - 25 Oct 2022

Cited by 3 | Viewed by 1508

Abstract

Coherent states, known as displaced vacuum states, play an important role in quantum information processing, quantum machine learning, and quantum optics. In this article, two ways to digitally prepare coherent states in quantum circuits are introduced. First, we construct the displacement operator by [...] Read more.

Coherent states, known as displaced vacuum states, play an important role in quantum information processing, quantum machine learning, and quantum optics. In this article, two ways to digitally prepare coherent states in quantum circuits are introduced. First, we construct the displacement operator by decomposing it into Pauli matrices via ladder operators, i.e., creation and annihilation operators. The high fidelity of the digitally generated coherent states is verified compared with the Poissonian distribution in Fock space. Secondly, by using Variational Quantum Algorithms, we choose different ansatzes to generate coherent states. The quantum resources—such as numbers of quantum gates, layers and iterations—are analyzed for quantum circuit learning. The simulation results show that quantum circuit learning can provide high fidelity on learning coherent states by choosing appropriate ansatzes. Full article

(This article belongs to the Special Issue Quantum Control and Quantum Computing)

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9 pages, 734 KiB

Open AccessArticle

Cryptanalysis of a Semi-Quantum Bi-Signature Scheme Based on W States

by Chun-Wei Yang, Jason Lin, Chia-Wei Tsai and Ching-Lin Cheng

Entropy 2022, 24(10), 1408; https://doi.org/10.3390/e24101408 - 01 Oct 2022

Cited by 5 | Viewed by 1430

Abstract

Recently, Zhao et al. proposed a semi-quantum bi-signature (SQBS) scheme based on W states with two quantum signers and just one classical verifier. In this study, we highlight three security issues with Zhao et al.’s SQBS scheme. In Zhao et al.’s SQBS protocol, [...] Read more.

Recently, Zhao et al. proposed a semi-quantum bi-signature (SQBS) scheme based on W states with two quantum signers and just one classical verifier. In this study, we highlight three security issues with Zhao et al.’s SQBS scheme. In Zhao et al.’s SQBS protocol, an insider attacker can perform an impersonation attack in the verification phase and an impersonation attack in the signature phase to capture the private key. In addition, an eavesdropper can perform a man-in-the-middle attack to obtain all of the signer’s secret information. All of the above three attacks can pass the eavesdropping check. Without considering these security issues, the SQBS protocol could fail to ensure the signer’s secret information. Full article

(This article belongs to the Special Issue Quantum Control and Quantum Computing)

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7 pages, 640 KiB

Open AccessPerspective

Towards Quantum Control with Advanced Quantum Computing: A Perspective

by Yongcheng Ding, Yue Ban and Xi Chen

Entropy 2022, 24(12), 1743; https://doi.org/10.3390/e24121743 - 29 Nov 2022

Cited by 3 | Viewed by 1830

Abstract

We propose the combination of digital quantum simulation and variational quantum algorithms as an alternative approach to numerical methods for solving quantum control problems. As a hybrid quantum–classical framework, it provides an efficient simulation of quantum dynamics compared to classical algorithms, exploiting the [...] Read more.

We propose the combination of digital quantum simulation and variational quantum algorithms as an alternative approach to numerical methods for solving quantum control problems. As a hybrid quantum–classical framework, it provides an efficient simulation of quantum dynamics compared to classical algorithms, exploiting the previous achievements in digital quantum simulation. We analyze the trainability and the performance of such algorithms based on our preliminary works. We show that specific quantum control problems, e.g., finding the switching time for bang-bang control or the digital quantum annealing schedule, can already be studied in the noisy intermediate-scale quantum era. We foresee that these algorithms will contribute even more to quantum control of high precision if the hardware for experimental implementation is developed to the next level. Full article

(This article belongs to the Special Issue Quantum Control and Quantum Computing)

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