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Analysis of Video Quality Datasets via Design of Minimalistic Video Quality Models

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arXiv 2023年

作者： Sun, Wei Wen, Wen Min, Xiongkuo Lan, Long Zhai, Guangtao Ma, Kede The Institute of Image Communication and Information Processing Shanghai Jiao Tong University Shanghai200240 China The Department of Computer Science City University of Hong Kong Kowloon Hong Kong The Institute for Quantum Information State Key Laboratory of High Performance Computing College of Computer Science and Technology National University of Defense Technology Changsha410073 China The Institute of Image Communication and Information Processing The MoE Key Lab of Artificial Intelligence AI Institute Shanghai Jiao Tong University Shanghai200240 China The Department of Computer Science The Shenzhen Research Institute City University of Hong Kong Kowloon Hong Kong

Blind video quality assessment (BVQA) plays an indispensable role in monitoring and improving the end-users’ viewing experience in various real-world video-enabled media applications. As an experimental field, the improvements of BVQA models have been measured primarily on a few human-rated VQA datasets. Thus, it is crucial to gain a better understanding of existing VQA datasets in order to properly evaluate the current progress in BVQA. Towards this goal, we conduct a first-of-its-kind computational analysis of VQA datasets via designing minimalistic BVQA models. By minimalistic, we restrict our family of BVQA models to build only upon basic blocks: a video preprocessor (for aggressive spatiotemporal downsampling), a spatial quality analyzer, an optional temporal quality analyzer, and a quality regressor, all with the simplest possible instantiations. By comparing the quality prediction performance of different model variants on eight VQA datasets with realistic distortions, we find that nearly all datasets suffer from the easy dataset problem of varying severity, some of which even admit blind image quality assessment (BIQA) solutions. We additionally justify our claims by comparing our model generalization capabilities on these VQA datasets, and by ablating a dizzying set of BVQA design choices related to the basic building blocks. Our results cast doubt on the current progress in BVQA, and meanwhile shed light on good practices of constructing next-generation VQA datasets and models. Code is available at https://***/sunwei925/***. Copyright © 2023, The Authors. All rights reserved.

关键词： Deep neural networks

Resilience of quantum Key Distribution Source Against Laser-Damage Attack by a Variety of Lasers

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Resilience of Quantum Key Distribution Source Against Laser-...

Conference on Lasers and Electro-Optics Europe (CLEO EUROPE)

作者： Daria Ruzhitskaya Irina Zhluktova Anastasiya Ponosova Daniil Trefilov Poompong Chaiwongkhot Anqi Huang Vladimir Kamynin Vadim Makarov Russian Quantum Center Skolkovo Moscow Russia NTI Center for Quantum Communications National University of Science and Technology MISiS Moscow Russia Prokhorov General Physics Institute of Russian Academy of Sciences Moscow Russia MIREA - Russian Technological University Moscow Russia Vigo Quantum Communication Center University of Vigo Vigo Spain Department of Physics Faculty of Science Mahidol University Bangkok Thailand State Key Laboratory of High Performance Computing Institute for Quantum Information College of Computer Science and Technology National University of Defense Technology Changsha China Shanghai Branch National Laboratory for Physical Sciences at Microscale CAS Center for Excellence in Quantum Information University of Science and Technology of China Shanghai People's Republic of China

ISBN: (纸本)9798350345995

quantum key distribution (QKD) systems provide quantum-safe key exchange. Therefore, complete security analysis of implementations of QKD protocols is in the focus of interest of a worldwide information-security community. For today, a number of QKD loopholes are closed by countermeasures, which are also considered in emerging QKD security evaluation and certification [1]–[3]. However, new threats to practical QKD implementations are still found, such as the laser-damage attack, which is a powerful hacking strategy. In investigations, CW laser radiation is most often used, but in contrast to it, the interaction of pulsed laser radiation with optical materials may lead to a wide range of effects, like nonlinear effects, dielectric breakdown, etc.

关键词： Fiber optic components High power lasers Nonlinear effects Optical materials quantum key distribution quantum key distribution networks

Optimizing Low-Energy Carbon IIoT Systems with quantum Algorithms: Performance Evaluation and Noise Robustness

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arXiv 2025年

作者： Dave, Kshitij Innan, Nouhaila Behera, Bikash K. Mumtaz, Shahid Al-Kuwari, Saif Farouk, Ahmed Institute of Advanced Research Gandhinagar India Quantum Physics and Magnetism Team LPMC Faculty of Sciences Ben M’sick Hassan II University of Casablanca Morocco NYUAD Research Institute NYUAD Abu Dhabi United Arab Emirates Pvt. Ltd. WB Mohanpur741246 India Nottingham Trent University Engineering Department United Kingdom Qatar Center for Quantum Computing College of Science and Engineering Hamad Bin Khalifa University Doha Qatar Department of Computer Science Faculty of Computers and Artificial Intelligence Hurghada University Hurghada Egypt

Low-energy carbon Internet of Things (IoT) systems are essential for sustainable development, as they reduce carbon emissions while ensuring efficient device performance. Although classical algorithms manage energy efficiency and data processing within these systems, they often face scalability and real-time processing limitations. quantum algorithms offer a solution to these challenges by delivering faster computations and improved optimization, thereby enhancing both the performance and sustainability of low-energy carbon IoT systems. Therefore, we introduced three quantum algorithms: quantum neural networks utilizing Pennylane (QNN-P), Qiskit (QNN-Q), and hybrid quantum neural networks (QNN-H). These algorithms are applied to two low-energy carbon IoT datasets—room occupancy detection (RODD) and GPS tracker (GPSD). For the RODD dataset, QNN-P achieved the highest accuracy at 0.95, followed by QNN-H at 0.91 and QNN-Q at 0.80. Similarly, for the GPSD dataset, QNN-P attained an accuracy of 0.94, QNN-H 0.87, and QNN-Q 0.74. Furthermore, the robustness of these models is verified against six noise models. The proposed quantum algorithms demonstrate superior computational efficiency and scalability in noisy environments, making them highly suitable for future low-energy carbon IoT systems. These advancements pave the way for more sustainable and efficient IoT infrastructures, significantly minimizing energy consumption while maintaining optimal device performance. © 2025, CC BY.

关键词： Low emission

quantum memory assisted entangled state verification with local measurements

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arXiv 2023年

作者： Chen, Siyuan Xie, Wei Xu, Ping Wang, Kun Hefei National Research Center for Physical Sciences Microscale School of Physical Sciences University of Science and Technology of China Hefei230026 China College of Physics Jilin University Changchun130012 China School of Computer Science and Technology University of Science and Technology of China Hefei230027 China Institute for Quantum Information State Key Laboratory of High Performance Computing College of Computer Science and Technology National University of Defense Technology Changsha410073 China

We consider the quantum memory assisted quantum state verification task, where an adversary prepare independent multipartite entangled states and send to the local verifiers, who then store several copies in the quantum memory and measure them collectively to make decision. We establish an exact analytic formula for optimizing two-copy state verification, where the verifiers store two copies, and give a globally optimal two-copy strategy for multi-qubit graph states involving only Bell measurements. When the verifiers can store arbitrarily many copies, we present a dimension expansion technique that designs efficient verification strategies for this case, showcasing its application to efficiently verifying GHZ-like states. These strategies become increasingly advantageous with growing memory resources, ultimately approaching the theoretical limit of efficiency. Our findings demonstrate that quantum memories enhance state verification efficiency, sheding light on error-resistant strategies and practical applications of large-scale quantum memory-assisted verification. © 2023, CC BY.

关键词： quantum entanglement

Minimizing quantum Rényi Divergences via Mirror Descent with Polyak Step Size

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Minimizing Quantum Rényi Divergences via Mirror Descent wit...

IEEE International Symposium on Information theory

作者： Jun-Kai You Hao-Chung Cheng Yen-Huan Li Department of Computer Science and Information Engineering National Taiwan University Department of Mathematics National Taiwan University Department of Electrical Engineering and Graduate Institute of Communication Engineering National Taiwan University Hon Hai (Foxconn) Quantum Computing Research Center Center for Quantum Science and Engineering National Taiwan University

ISBN: (数字)9781665421591

ISBN: (纸本)9781665421607

quantum information quantities play a substantial role in characterizing operational quantities in various quantum information-theoretic problems. We consider the numerical computation of four quantum information quantities: Petz-Augustin information, sandwiched Augustin information, conditional sandwiched Rényi entropy, and sandwiched Rényi information. To compute these quantities requires minimizing some order-α quantum Rényi divergences over the set of quantum states. Whereas the optimization problems are obviously convex, they violate standard bounded gradient/Hessian conditions in the literature, so existing convex optimization methods and their convergence guarantees do not directly apply. In this paper, we propose a new class of convex optimization methods called mirror descent with the Polyak step size. We prove their convergence under a weak condition, showing that they provably converge for minimizing quantum Rényi divergences. Numerical experiment results show that entropic mirror descent with the Polyak step size converges fast in minimizing quantum Rényi divergences.

关键词： quantum computing quantum state Convex functions Entropy Mirrors Standards Optimization

On stability of k-local quantum phases of matter

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arXiv 2024年

作者： Lavasani, Ali Gullans, Michael J. Albert, Victor V. Barkeshli, Maissam Joint Quantum Institute NIST University of Maryland College ParkMD20742 United States Condensed Matter Theory Center University of Maryland College ParkMD20742 United States Kavli Institute for Theoretical Physics University of California Santa BarbaraCA93106 United States Joint Center for Quantum Information and Computer Science NIST University of Maryland College ParkMD20742 United States Department of Physics University of Maryland College ParkMD20742 United States

The current theoretical framework for topological phases of matter is based on the thermodynamic limit of a system with geometrically local interactions. A natural question is to what extent the notion of a phase of matter remains well-defined if we relax the constraint of geometric locality, and replace it with a weaker graph-theoretic notion of k-locality. As a step towards answering this question, we analyze the stability of the energy gap to perturbations for Hamiltonians corresponding to general quantum low-density parity-check codes, extending work of Bravyi and Hastings [Commun. Math. Phys. 307, 609 (2011)]. A corollary of our main result is that if there exist constants Ε1,Ε2 > 0 such that the size Γ(r) of balls of radius r on the interaction graph satisfy Γ(r) = O(exp(r1−Ε1)) and the local ground states of balls of radius r ≤ ρ∗ = O(log(n)1+Ε2) are locally indistinguishable, then the energy gap of the associated Hamiltonian is stable against local perturbations. This gives an almost exponential improvement over the D-dimensional Euclidean case, which requires Γ(r) = O(rD) and ρ∗ = O(nα) for some α. The approach we follow falls just short of proving stability of finite-rate qLDPC codes, which have Ε1 = 0;we discuss some strategies to extend the result to these cases. We discuss implications for the third law of thermodynamics, as k-local Hamiltonians can have extensive zero-temperature entropy. © 2024, CC BY.

关键词： Hamiltonians

Approaching multifractal complexity in decentralized cryptocurrency trading

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arXiv 2024年

作者： Wątorek, Marcin Królczyk, Marcin Kwapień, Jaroslaw Stanisz, Tomasz Drozdz, Stanislaw Faculty of Computer Science and Telecommunications Cracow University of Technology Kraków31-155 Poland Complex Systems Theory Department Institute of Nuclear Physics Polish Academy of Sciences Kraków31-342 Poland Adapt Centre School of Computing Dublin City University DublinD09 Y074 Ireland

Multifractality is a concept that helps compactly grasping the most essential features of the financial dynamics. In its fully developed form, this concept applies to essentially all mature financial markets and even to more liquid cryptocurrencies traded on the centralized exchanges. A new element that adds complexity to cryptocurrency markets is the possibility of decentralized trading. Based on the extracted tick-by-tick transaction data from the Universal Router contract of the Uniswap decentralized exchange, from June 6, 2023, to June 30, 2024, the present study using Multifractal Detrended Fluctuation Analysis (MFDFA) shows that even though liquidity on these new exchanges is still much lower compared to centralized exchanges convincing traces of multifractality are already emerging on this new trading as well. The resulting multifractal spectra are however strongly left-side asymmetric which indicates that this multifractality comes primarily from large fluctuations and small ones are more of the uncorrelated noise type. What is particularly interesting here is the fact that multifractality is more developed for time series representing transaction volumes than rates of return. On the level of these larger events a trace of multifractal cross-correlations between the two characteristics is also observed. Copyright © 2024, The Authors. All rights reserved.

关键词： Decentralized finance

Teleportation of quantum coherence

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arXiv 2023年

作者： Sohail Pati, Arun K. Aradhya, Vijeth Chakrabarty, Indranil Patro, Subhasree Quantum Information and Computation Group Harish-Chandra Research Institute A CI of Homi Bhabha National Institute Chhatnag Road Jhunsi Prayagraj211019 India Centre for Quantum Science and Technology International Institute of Information Technology-Hyderabad Gachibowli Hyderabad India Center for Security Theory and Algorithmic Research International Institute of Information Technology-Hyderabad Gachibowli Hyderabad India Department of Computer Science National University of Singapore 117417 Singapore Utrecht University Utrecht3584 CS Netherlands QuSoft Centrum Wiskunde & Informatica Amsterdam1098 XG Netherlands

We investigate whether it is possible to teleport the coherence of an unknown quantum state from Alice to Bob by communicating a lesser number of classical bits in comparison to what is required for teleporting an unknown quantum state. We find that we cannot achieve perfect teleportation of coherence with one bit of classical communication for an arbitrary qubit. However, we find that if the qubit is partially known, i.e., chosen from the equatorial and polar circles of the Bloch sphere, then teleportation of coherence is possible with the transfer of one cbit of information when we have maximally entangled states as a shared resource. In the case of the resource being a non-maximally entangled state, we can teleport the coherence with a certain probability of success. In a general teleportation protocol for coherence, we derive a compact formula for the final state at Bob’s lab in terms of the composition of the completely positive maps corresponding to the shared resource state and joint POVM performed by Alice on her qubit and the unknown state. Using this formula, we show that teleportation of the coherence of a partially known state with real matrix elements is possible perfectly with the help of a maximally entangled state as a resource. Furthermore, we explore the teleportation of coherence with the Werner states and show that even when the Werner states become separable, the amount of teleported coherence is non-zero, implying the possibility of teleportation of coherence without entanglement. Copyright © 2023, The Authors. All rights reserved.

关键词： Qubits

Deep-Neural-Network Discrimination of Multiplexed Superconducting-Qubit States

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Physical Review Applied 2022年第1期17卷 014024-014024页

作者： Benjamin Lienhard Antti Vepsäläinen Luke C.G. Govia Cole R. Hoffer Jack Y. Qiu Diego Ristè Matthew Ware David Kim Roni Winik Alexander Melville Bethany Niedzielski Jonilyn Yoder Guilhem J. Ribeill Thomas A. Ohki Hari K. Krovi Terry P. Orlando Simon Gustavsson William D. Oliver Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology Cambridge Massachusetts 02139 USA Research Laboratory of Electronics Massachusetts Institute of Technology Cambridge Massachusetts 02139 USA Quantum Engineering and Computing Group Raytheon BBN Technologies Cambridge Massachusetts 02138 USA MIT Lincoln Laboratory Lexington Massachusetts 02421 USA

Demonstrating a quantum computational advantage will require high-fidelity control and readout of multiqubit systems. As system size increases, multiplexed qubit readout becomes a practical necessity to limit the growth of resource overhead. Many contemporary qubit-state discriminators presume single-qubit operating conditions or require considerable computational effort, limiting their potential extensibility. Here, we present multiqubit readout using neural networks as state discriminators. We compare our approach to contemporary methods employed on a quantum device with five superconducting qubits and frequency-multiplexed readout. We find that fully connected feedforward neural networks increase the qubit-state-assignment fidelity for our system. Relative to contemporary discriminators, the assignment error rate is reduced by up to 25% due to the compensation of system-dependent nonidealities such as readout crosstalk, which is reduced by up to one order of magnitude. Our work demonstrates a potentially extensible building block for high-fidelity readout relevant to both near-term devices and future fault-tolerant systems.

关键词： Machine learning Measurement-based quantum computing Optoelectronics quantum control quantum information with solid state qubits Superconducting qubits Artificial neural networks Microwave techniques