Article
Physics, Multidisciplinary
Tadashi Nakajima
Summary: This article investigates the measurement problem in quantum mechanics from two aspects. It identifies the classicality of apparatus postulate as the source of the problem and introduces the concept of microscopic quantum jump to explain the measurement process. By adopting the postulate of the microscopic quantum jump and discarding the classicality of apparatus postulate, a consistent measurement theory has been constructed.
INTERNATIONAL JOURNAL OF THEORETICAL PHYSICS
(2023)
Article
Quantum Science & Technology
Guang Ping He
Summary: This study proposes an MDI-QKD protocol that only requires individual measurements and classical operations, reducing the technical requirements for Bob and Charlie during implementation.
QUANTUM INFORMATION PROCESSING
(2022)
Article
Computer Science, Hardware & Architecture
Hyeokjea Kwon, Joonwoo Bae
Summary: This article presents a scheme to mitigate errors in measurement readout with NISQ devices by dealing with unknown quantum noise, which is implemented in two quantum algorithms and shows an enhancement in the statistics of measurement outcomes for both algorithms using NISQ devices.
IEEE TRANSACTIONS ON COMPUTERS
(2021)
Article
Physics, Multidisciplinary
Stephane Avner
Summary: This study examines the possible existence of a local fundamentally realist interpretation of quantum mechanics by conceiving particles as granular systems composed of numerous extremely sensitive fluctuating subcorpuscles. The model involves numerous subparticles that constitute some tight nucleus and loosely bound envelope, allegedly forming real waves, which could capture the measured values of observables and predict mass from the stability of the substructure. Drawing inspiration from non-linear dynamical systems, subparticles would involve realist hidden variables while high-level observables would generally not be determined.
Article
Quantum Science & Technology
Avinash Chalumuri, Raghavendra Kune, B. S. Manoj
Summary: This study introduces the Quantum Multi-Class Classifier (QMCC), a hybrid model based on both quantum and classical computers for machine learning tasks, utilizing quantum properties such as superposition and entanglement to achieve high classification accuracy. Quantum simulations on benchmark datasets demonstrate that the proposed QMCC model achieved classification accuracy of 92.10% for the Iris dataset, 89.50% for the Banknote Authentication dataset, and 91.73% for the Wireless Indoor Localization dataset.
QUANTUM INFORMATION PROCESSING
(2021)
Article
Quantum Science & Technology
Guillermo Gonzalez-Garcia, Rahul Trivedi, J. Ignacio Cirac
Summary: The study proposes a random circuit model that accounts for single-qubit error propagation, finding that a specific single-qubit error rate is needed to achieve a quantum advantage even with small noise levels. This translates to an error rate lower than 10-6 when using the quantum approximate optimization algorithm for classical optimization problems with two-dimensional circuits.
Article
Physics, Multidisciplinary
Charis Anastopoulos, Bei-Lok Hu
Summary: The paper points out three common problems in using quantum information theory to address gravity-related issues, including the inconsistency between interactions mediated by an information channel and those treated by quantum field theory, the neglect of important quantum features when replacing a quantum field with a classical stochastic field, and the conditions under which semi-classical and stochastic theories can be formulated from their quantum origins.
Article
Optics
Ziyang You, Yanxiang Wang, Zikang Tang, Hou Ian
Summary: The article introduces a method for detecting classical entanglement, determining the value of the Schmidt number through interference patterns of light sources to understand the degree of entanglement. These methods can be applied in the fields of computation and communication, and are of significant importance for understanding the entanglement relationships of optical fields.
JOURNAL OF THE OPTICAL SOCIETY OF AMERICA B-OPTICAL PHYSICS
(2021)
Article
Multidisciplinary Sciences
Xiaodong Yang, Xi Chen, Jun Li, Xinhua Peng, Raymond Laflamme
Summary: This study introduces a quantum metrology scheme that does not require complex offline design and can automatically optimize controls online, improving measurement precision. Successful experimental demonstration was conducted on a nuclear magnetic resonance processor.
SCIENTIFIC REPORTS
(2021)
Article
Physics, Multidisciplinary
Pierpaolo Pravatto, Davide Castaldo, Federico Gallina, Barbara Fresch, Stefano Corni, Giorgio J. Moro
Summary: This paper presents a new quantum algorithm for solving the Fokker-Planck-Smoluchowski eigenvalue problem and demonstrates its effective application in classical systems. By encoding the probability distribution on a quantum computer, the conformational transition rate in a linear chain of rotors with nearest-neighbour interactions was successfully computed, with scalability assessed. Performance analysis on noisy quantum emulators and devices showed good agreement with the classical benchmark.
NEW JOURNAL OF PHYSICS
(2021)
Review
Chemistry, Multidisciplinary
Zhe Liu, Alessandro Sergi, Gabriel Hanna
Summary: Mixed quantum-classical dynamics is an efficient method for simulating the dynamics of quantum subsystems coupled to many-body environments. The recently developed DECIDE method has shown high accuracy and low computational cost, but has mainly been applied using subsystem and adiabatic energy bases. This review provides a step-by-step derivation of the DECIDE approach in a quantum harmonic oscillator position basis for a hydrogen bond model, demonstrating energy conservation and calculating various quantities of interest. Limitations of incomplete basis representation are also discussed.
APPLIED SCIENCES-BASEL
(2022)
Article
Computer Science, Hardware & Architecture
Gui-Lu Long, Dong Pan, Yu-Bo Sheng, Qikun Xue, Jianhua Lu, Lajos Hanzo
Summary: This study proposes a method to build secure quantum networks by combining classical and quantum communication. By using the principles of quantum secure direct communication and quantum-resistant algorithms, this network enables secure end-to-end communication and provides eavesdropping detection and prevention in the quantum Internet. The solution is compatible with existing networks and facilitates a smooth transition to the future quantum Internet.
Article
Thermodynamics
Wei Fu, Haipeng Xie, Hao Zhu, Hefeng Wang, Lizhou Jiang, Chen Chen, Zhaohong Bie
Summary: Incorporating multiple resilient resources into coordinated post-disaster restoration strategy contributes positively to resilience enhancement of power distribution systems. However, considering multiple factors may increase model complexity, resulting in longer solution times and compromised practicality. This paper proposes a hybrid quantum-classical algorithm to address this problem and verifies its effectiveness and computational efficiency.
Article
Quantum Science & Technology
Kouhei Nakaji, Suguru Endo, Yuichiro Matsuzaki, Hideaki Hakoshima
Summary: Simulating large quantum systems is the ultimate goal of quantum computing. Variational quantum simulation (VQS) provides a tool to distribute computation load between classical and quantum computers for near-term devices. However, as the size of the system increases, the execution of VQS becomes more challenging due to the drastic increase in measurements. This work aims to optimize measurements in VQS using recently proposed techniques such as classical shadow and derandomization.
Article
Computer Science, Artificial Intelligence
Samuel Yen-Chi Chen, Chih-Min Huang, Chia-Wei Hsing, Ying-Jer Kao
Summary: The hybrid model combines a quantum-inspired tensor network and a variational quantum circuit for supervised learning tasks, allowing simultaneous training of classical and quantum parts. It outperforms principal component analysis as a feature extractor in binary and ternary classification of MNIST and Fashion-MNIST datasets. The architecture is highly adaptable, with the classical-quantum boundary adjustable based on quantum resource availability.
MACHINE LEARNING-SCIENCE AND TECHNOLOGY
(2021)
