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2024 Frontiers in Optics, FiO 2024

作者： Endo, Mamoru Takahashi, Kazuma Nomura, Takefumi Sonoyama, Tatsuki Miki, Shigehito Yabuno, Masahiro Terai, Hirotaka Kashiwazaki, Takahiro Inoue, Asuka Umeki, Takeshi Nehra, Rajveer Takase, Kan Asavanant, Warit Furusawa, Akira Department of Applied Physics School of Engineering The University of Tokyo 7-3-1 Hongo Bunkyo Tokyo113-8656 Japan Optical Quantum Computing Research Team RIKEN Center for Quantum Computing 2-1 Hirosawa Saitama Wako351-0198 Japan Advanced ICT Research Institute National Institute of Information and Communications Technology Japan Department of Electrical and Computer Engineering University of Massachusetts Amherst AmherstMA01003 United States Department of Physics University of Massachusetts Amherst AmherstMA01003 United States College of Information and Computer Science University of Massachusetts Amherst AmherstMA01003 United States

Superconducting-nanostrip photon detectors with optical sampling method now function as true photon-number resolving detectors in real-time without multiplexing. We applied this technique for quantum state generation ... 详细信息

关键词： quantum computers

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Stock Market Prediction Using Machine Learning Based Techniques

Stock Market Prediction Using Machine Learning Based Techniq...

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2024 IEEE International Conference on Intelligent Signal Processing and Effective Communication Technologies, INSPECT 2024

作者： Dubey, Aditya Sharma, Ramnaresh Bisen, Dhananjay Venu, Nookala Jaiswal, Varshali Raghuwanshi, Bhagat Singh Shakywar, Khemchand Madhav Institute of Technology & Science Centre for Internet of Things Gwalior India Madhav Institute of Technology & Science Centre for AI Gwalior India ABV Indian Institute of Information Technology and Management Data Science and Quantum Computing Gwalior India School of Engineering Avantika University MP Ujjain India

ISBN: (纸本)9798350379525

Many methods have been used to forecast stock market trends in the big data age, including real numbers, fuzzy time series data, fuzzy sets design, and conventional time series data. The control of semantic value data is made possible by the use of fuzzy time series data in stock market prediction, which makes accurate value predictions possible. These techniques are mostly used to forecast dynamic, non-linear datasets in a variety of industries, such as stock markets and cryptocurrencies. In order to predict stock prices, artificial intelligence (AI) methods such as neural networks (NN) have become increasingly important. Many methods have been developed to validate parametric and non-parametric theories for predicting trends and gains in the stock market using the feed-forward (FF) NN technique. A variety of soft computing techniques have been investigated in order to provide ways for decision-making based on profit and loss criteria without relying on artificial intelligence. This paper's main goal is to perform a comprehensive examination of the different prediction techniques used to estimate price and return in the stock market. The study includes a comparative review of several approaches as well as a variety of stock market forecasting strategies. © 2024 IEEE.

关键词： Marketplaces

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Scalable circuit depth reduction in feedback-based quantum optimization with a quadratic approximation

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Physical Review Research 2025年第1期7卷 013035-013035页

作者： Don Arai Ken N. Okada Yuichiro Nakano Kosuke Mitarai Keisuke Fujii Graduate School of Engineering Science Osaka University 1-3 Machikaneyama Toyonaka Osaka 560-8531 Japan Center for Quantum Information and Quantum Biology Osaka University 1-2 Machikaneyama Toyonaka 560-0043 Japan RIKEN Center for Quantum Computing (RQC) Hirosawa 2-1 Wako Saitama 351-0198 Japan

Combinatorial optimization problems are one of the areas where near-term noisy quantum computers may have practical advantage against classical computers. Recently, a feedback-based quantum optimization algorithm has been proposed by Magann et al., Phys. Rev. Lett. 129, 250502 (2022). The method explicitly determines quantum circuit parameters by feeding back measurement results thus avoids classical parameter optimization that is known to cause significant trouble in quantum approximate optimization algorithm, the well-studied near-term algorithm. Meanwhile, a significant drawback of the feedback-based quantum optimization is that it requires deep circuits, rendering the method unsuitable to noisy quantum devices. In this study we propose a feedback law for parameter determination by introducing the second-order approximation with respect to time interval, a hyperparameter in the feedback-based quantum optimization. This allows one to take larger time interval, leading to acceleration of convergence to solutions. In numerical simulations on the maximum cut problem we demonstrate that our proposal significantly reduces circuit depth, with its linear scaling with the problem size smaller by more than an order of magnitude. We expect that the feedback law proposed in this work may pave the way for feedback-based quantum optimization with near-term noisy quantum computers.

关键词： quantum computers

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Efficient CNN-based disaster events classification using UAV-aided images for emergency response application

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Neural computing and Applications 2024年第18期36卷 10599-10612页

作者： Bashir, Munzir Hubiba Ahmad, Musheer Rizvi, Danish Raza El-Latif, Ahmed A. Abd Department of Computer Engineering Jamia Millia Islamia New Delhi110025 India EIAS Data Science Lab College of Computer and Information Sciences Prince Sultan University Riyadh11586 Saudi Arabia Center of Excellence in Quantum and Intelligent Computing Prince Sultan University Riyadh11586 Saudi Arabia Department of Mathematics and Computer Science Faculty of Science Menoufia University Shebin El-Kom32511 Egypt

Natural disasters can be unpredictable and catastrophic. Even after the event, the repercussions are prolonged due to the incompetence of disaster management strategies. To mitigate the effects of a natural hazard, disaster management teams have to rapidly come forth with innovative plans of action. To contain the damage that a disaster causes, the response time, and preparedness of a disaster management team is crucial. Having a forewarning about the nature of the disaster can prove to be beneficial for the management team. Remote/unreachable areas such as deep parts of the forests, far-flung rural areas, oceans and other hard to reach locations are at a higher risk of receiving poorer aid and response due to the lack of communication and connectivity with the rest of the world. Our paper provides a solution for this particular problem by suggesting UAV/Drones for surveillance and monitoring in these inaccessible, disaster struck areas. The drones not only monitor the situation but constantly click pictures and send them to a base station, where the images are used to collect insights about the type of disaster that has to be dealt with. The paper proposes a deep learning model based on feature concatenation for classification of disasters which can be deployed at the base station, and can receive data in the form of images from a UAV/drone hovering over the affected place. The proposed model is efficient and able to achieve a higher accuracy as compared to the leading CNN models and closely related recent works as well. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.

关键词： Human resource management

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Self-correcting GKP qubit and gates in a driven-dissipative circuit

arXiv

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arXiv 2024年

作者： Nathan, Frederik O’Brien, Liam Noh, Kyungjoo Matheny, Matthew H. Grimsmo, Arne L. Jiang, Liang Refael, Gil Center for Quantum Devices and NNF Quantum Computing Programme Niels Bohr Institute University of Copenhagen Copenhagen2100 Denmark Department of Physics Institute for Quantum Information and Matter California Institute of Technology PasadenaCA91125 United States AWS Center for Quantum Computing PasadenaCA91125 United States Pritzker School of Molecular Engineering The University of Chicago ChicagoIL60637 United States

We propose a circuit architecture for a dissipatively error-corrected GKP qubit. The device consists of a high-impedance LC circuit coupled to a Josephson junction and a resistor via a controllable switch. When the switch is activated via a particular family of stepwise protocols, the resistor absorbs all noise-induced entropy, resulting in dissipative error correction of both phase and amplitude errors. This leads to an exponential increase of qubit lifetime, reaching beyond 10ms in simulations with near-feasible parameters. We show that the lifetime remains exponentially long in the presence of extrinsic noise and device/control imperfections (e.g., due to parasitics and finite control bandwidth) under specific thresholds. In this regime, lifetime is likely only limited by phase slips and quasiparticle tunneling. We show that the qubit can be read out and initialized via measurement of the supercurrent in the Josephson junction. We finally show that the qubit supports native self-correcting single-qubit Clifford gates, where dissipative error-correction of control noise leads to exponential suppression of gate infidelity. Copyright © 2024, The Authors. All rights reserved.

关键词： Resistors

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Practical quantum Advantage on Partially Fault-Tolerant quantum Computer

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Physical Review X 2025年第2期15卷 021057-021057页

作者： Riki Toshio Yutaro Akahoshi Jun Fujisaki Hirotaka Oshima Shintaro Sato Keisuke Fujii Quantum Laboratory Fujitsu Research Fujitsu Limited 4-1-1 Kawasaki Kanagawa 211-8588 Japan Fujitsu Quantum Computing Joint Research Division Center for Quantum Information and Quantum Biology Osaka University 1-2 Machikaneyama Toyonaka Osaka 565-8531 Japan Graduate School of Engineering Science Osaka University 1-3 Machikaneyama Toyonaka Osaka 560-8531 Japan Center for Quantum Information and Quantum Biology Osaka University 560-0043 Japan RIKEN Center for Quantum Computing (RQC) Wako Saitama 351-0198 Japan

Achieving quantum speedups in practical tasks remains challenging for current noisy intermediate-scale quantum (NISQ) devices. These devices always encounter significant obstacles such as inevitable physical errors and the limited scalability of current near-term algorithms. Meanwhile, assuming a typical architecture for fault-tolerant quantum computing (FTQC), realistic applications inevitably require a vast number of qubits, typically exceeding 106, which seems far beyond near-term realization. In this work, to bridge the gap between the NISQ and FTQC eras, we propose an alternative approach to achieve practical quantum advantages on early-FTQC devices. Our framework is based on partially fault-tolerant logical operations to minimize spatial overhead and avoids the costly distillation techniques typically required for executing non-Clifford gates. To this end, we develop a space-time efficient state preparation protocol to generate an ancillary non-Clifford state consumed for implementing an analog rotation gate with an arbitrary small angle θ and a remarkably low worst-case error rate below O(|θ|pph), where pph is the physical error rate. Furthermore, we propose several error suppression schemes tailored to our preparation protocol, which are essential to minimize the overhead for mitigating errors. Based on this framework, we present several promising applications that leverage the potential of our framework, including the Trotter simulation and quantum phase estimation (QPE). Notably, we demonstrate that our framework allows us to perform the QPE for an (8×8)-site Hubbard model with fewer than 6.8×104 qubits and an execution time of 10.6 days (or 14 min with full parallelization) under pph=10−4, which is significantly faster than recent classical estimation with tensor network techniques (density matrix renormalization group and projected entangled pair states).

关键词： Qubits

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A Benchmark of Cryo-CMOS 40-nm Embedded SRAM/DRAMs for quantum computing

A Benchmark of Cryo-CMOS 40-nm Embedded SRAM/DRAMs for Quant...

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European Conference on Solid-State Circuits (ESSCIRC)

作者： Rob A. Damsteegt Ramon W.J. Overwater Masoud Babaie Fabio Sebastiano Department of Quantum & Computing Engineering & QuTech TU Delft The Netherlands Department of Microelectronics & QuTech TU Delft The Netherlands

The cryogenic electronic interface for quantum pro-cessors requires cryo-CMOS embedded memories that cover a wide range of specifications. The temperature dependence of device parameters, such as the threshold voltage, the gate/subthreshold leakage, and the variability, severely alters the memories’ performance between room temperature (RT) and cryogenic temperatures (4.2K). To assess the best memory design for a given application, this paper benchmarks three custom DRAMs and a custom SRAM in 40-nm CMOS at 4.2 K and RT, e.g., identifying that, while the SRAM is more power efficient for moderate-to-high speeds at RT, the 2T DRAM performs better than SRAM and 3T DRAMs at 4.2 K.

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Optimal Second-Order Rates for quantum Information Decoupling

Optimal Second-Order Rates for Quantum Information Decouplin...

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2023 IEEE International Symposium on Information Theory, ISIT 2023

作者： Shen, Yu-Chen Gao, Li Cheng, Hao-Chung National Taiwan University Department of Electrical Engineering Graduate Institute of Communication Engineering Taipei10617 Taiwan Department of Mathematics National Taiwan University Taipei10617 Taiwan Center for Quantum Science and Engineering National Taiwan University Taipei10617 Taiwan Department of Mathematics University of Houston HoustonTX77204 United States Quantum Computing Research Center New Taipei City236 Taiwan Physics Division National Center for Theoretical Sciences Taipei10617 Taiwan

ISBN: (纸本)9781665475549

In this paper, we consider the standard quantum information decoupling, in which Alice aims to decouple her system from the environment by discarding some of her systems. To achieve an ?-decoupling with trace distance as the error criterion, we establish a one-shot characterization for the largest size of the remainder system in terms of the conditional (1 - ?)-hypothesis-testing entropy. When the underlying system is independent and identically prepared, our result leads to the matched second-order rate as well as the moderate deviation rate. © 2023 IEEE.

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AN INEXACT FEASIBLE INTERIOR POINT METHOD FOR LINEAR OPTIMIZATION WITH HIGH ADAPTABILITY TO quantum COMPUTERS

arXiv

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arXiv 2023年

作者： Mohammadisiahroudi, Mohammadhossein Fakhimi, Ramin Wu, Zeguan Terlaky, Tamás Quantum Computing and Optimization Lab Industrial and System Engineering Department Lehigh University BethlehemPA United States

The use of quantum computing to accelerate complex optimization problems is a burgeoning research field. This paper applies quantum Linear System Algorithms (QLSAs) to Newton systems within Interior Point Methods (IPMs) to take advantage of quantum speedup in solving Linear Optimization (LO) problems. Due to their inexact nature, QLSAs can be applied only to inexact variants of IPMs. Existing IPMs with inexact Newton directions are infeasible methods due to the inexact nature of their computations. This paper proposes an Inexact-Feasible IPM (IF-IPM) for LO problems, using a novel linear system to generate inexact but feasible steps. We show that this method has O(√nL) iteration complexity, analogous to the best exact IPMs, where n is the number of variables and L is the binary length of the input data. Moreover, we examine how QLSAs can efficiently solve the proposed system in an iterative refinement (IR) scheme to find the exact solution without excessive calls to QLSAs. We show that the proposed IR-IF-IPM can also be helpful to mitigate the impact of the condition number when a classical iterative method, such as a Conjugate Gradient method or a quantum solver is used at iterations of IPMs. After applying the proposed IF-IPM to the self-dual embedding formulation, we investigate the proposed IF-IPM’s efficiency using the QISKIT simulator of *** Codes 90C51, 90C05, 68Q12, 81P68 © 2023, CC BY.

关键词： Linear systems

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Asymptotically Optimal Synthesis of Reversible Circuits

arXiv

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arXiv 2023年

作者： Wu, Xian Li, Lvzhou Institute of Quantum Computing and Software School of Computer and Engineering Sun Yat-sen University Guangzhou510006 China

Reversible circuits have been studied extensively and intensively, and have plenty of applications in various areas, such as digital signal processing, cryptography, and especially quantum computing. In 2003, the lower bound Ω(2nn/log n) for the synthesis of n-wire reversible circuits was proved. Whether this lower bound has a matching upper bound was listed as one of the future challenging open problems in the survey (M. Saeedi and I. L Markov, ACM computing Surveys, 45(2):1–34, 2013). In this paper we propose an algorithm to implement an arbitrary n-wire reversible circuit with no more than O(2nn/log n) elementary gates, and thus close the open problem. © 2023, CC BY.

关键词： quantum computers

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