با سلام خدمت کاربران در صورتی که با خطای سیستم پرداخت بانکی مواجه شدید از طریق کارت به کارت (6037997535328901 بانک ملی ناصر خنجری ) مقاله خود را دریافت کنید (تا مشکل رفع گردد).
ردیف | عنوان | نوع |
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91 |
Quantum SVR for Chlorophyll Concentration Estimation in Water With Remote Sensing
-2022 The increasing availability of quantum computers
motivates researching their potential capabilities in enhancing
the performance of data analysis algorithms. Similarly, as in
other research communities, also in remote sensing (RS), it is
not yet defined how its applications can benefit from the usage
of quantum computing (QC). This letter proposes a formulation
of the support vector regression (SVR) algorithm that can be
executed by D-Wave quantum computers. Specifically, the SVR
is mapped to a quadratic unconstrained binary optimization
(QUBO) problem that is solved with quantum annealing (QA).
The algorithm is tested on two different types of computing
environments offered by D-Wave: the advantage system, which
directly embeds the problem into the quantum processing unit
(QPU), and a hybrid solver that employs both classical and
QC resources. For the evaluation, we considered a biophysical
variable estimation problem with RS data. The experimental
results show that the proposed quantum SVR implementation
can achieve comparable or, in some cases, better results than the
classical implementation. This work is one of the first attempts to
provide insight into how QA could be exploited and integrated in
future RS workflows based on machine learning (ML) algorithms.
Index Terms: Quantum annealing (QA) | quantum computing (QC) | quantum machine learning (QML) | remote sensing (RS) | support vector regression (SVR). |
مقاله انگلیسی |
92 |
Qutrit-Inspired Fully Self-Supervised Shallow Quantum Learning Network for Brain Tumor Segmentation
شبکه یادگیری کوانتومی کم عمق کاملاً خود نظارتی الهام گرفته از Qutrit برای تقسیم بندی تومور مغزی-2022 Classical self-supervised networks suffer from convergence problems and reduced segmentation accuracy due
to forceful termination. Qubits or bilevel quantum bits often
describe quantum neural network models. In this article, a novel
self-supervised shallow learning network model exploiting the
sophisticated three-level qutrit-inspired quantum information system, referred to as quantum fully self-supervised neural network
(QFS-Net), is presented for automated segmentation of brain
magnetic resonance (MR) images. The QFS-Net model comprises
a trinity of a layered structure of qutrits interconnected through
parametric Hadamard gates using an eight-connected secondorder neighborhood-based topology. The nonlinear transformation of the qutrit states allows the underlying quantum neural
network model to encode the quantum states, thereby enabling a
faster self-organized counterpropagation of these states between
the layers without supervision. The suggested QFS-Net model
is tailored and extensively validated on the Cancer Imaging
Archive (TCIA) dataset collected from the Nature repository.
The experimental results are also compared with state-of-theart supervised (U-Net and URes-Net architectures) and the selfsupervised QIS-Net model and its classical counterpart. Results
shed promising segmented outcomes in detecting tumors in terms
of dice similarity and accuracy with minimum human intervention and computational resources. The proposed QFS-Net
is also investigated on natural gray-scale images from the
Berkeley segmentation dataset and yields promising outcomes
in segmentation, thereby demonstrating the robustness of the
QFS-Net model.
Index Terms: tum computing | qutrit | U-Net and URes-Net. |
مقاله انگلیسی |
93 |
محلیسازی دقیق سطح خط مبتنی بر تطبیق نقشه با استفاده از دوربین و GPS کمهزینه
سال انتشار: 2022 - تعداد صفحات فایل pdf انگلیسی: 8 - تعداد صفحات فایل doc فارسی: 14 در سیستم های خودران یا وسایل نقلیه خودران(وسایل بدون راننده) (AVs) ، محلی سازی دقیق سطح خط، برای انجام مانورهای پیچیده رانندگی ضروری است. معمولاً روشهای کلاسیک مبتنی بر GNSS از دقت کافی برای محلیسازی در سطح خط و پشتیبانی از مانورهای AV برخوردار نیستند. محلی سازی مبتنی بر LiDAR قابلیت ارائه محلی سازی دقیق را دارد. با این حال، یکی از مسائل مهمی که مانع تبدیل کاربرد گسترده این نوع راه حل می شود، قیمت LiDAR است. بنابراین، در این پژوهش راهحلی کمهزینه برای محلیسازی سطح خط و برای دستیابی به محلیسازی با دقت بالا در سطح خط با استفاده از سیستم مبتنی بر دید و GPS کمهزینه پیشنهاد شد. آزمایشها در دنیای واقعی و زمان واقعی اثبات می کند که روش پیشنهادی در محلیسازی سطح خط دقت مطلوبی داشته و عملکرد بهتری نسبت به راهحلهای مبتنی بر فقط GPS ، ارائه داده است.
کلیدواژه: رانندگی خودران | محلی سازی سطح خط | تشخیص خط | GNSS| GPS| تطبیق نقشه |
مقاله ترجمه شده |
94 |
Reordering and Partitioning of Distributed Quantum Circuits
مرتب سازی مجدد و پارتیشن بندی مدارهای کوانتومی توزیع شده-2022 A new approach to reduce the teleportation cost and execution time in Distributed Quantum
Circuits (DQCs) was proposed in the present paper. DQCs, a well-known solution, have been applied to
solve the problem of maintaining a large number of qubits next to each other. In the distributed quantum
system, the qubits are transferred to another subsystem by a quantum protocol like teleportation. Hence,
a novel method was proposed to optimize the number of teleportation and to reduce the execution time for
generating DQC. To this end, first, the quantum circuit was reordered according to the qubits placement to
improve the computational execution time, and then the quantum circuit was modeled as a graph. Finally,
we combined the genetic algorithm (GA) and the modified tabu search algorithm (MTS) to partition the
graph model in order to obtain a distributed quantum circuit aimed at reducing the number of teleportation
costs. A significant reduction in teleportation cost (TC) and execution time (ET) was obtained in benchmark
circuits. In particular, we performed a more accurate optimization than the previous approaches, and the
proposed approach yielded the best results for several benchmark circuits.
INDEX TERMS: Quantum computing | distributed quantum circuit | optimization | genetic algorithm | teleportation. |
مقاله انگلیسی |
95 |
Resource Management for Edge Intelligence (EI)-Assisted IoV Using Quantum-Inspired Reinforcement Learning
مدیریت منابع برای IoV به کمک هوش لبه (EI) با استفاده از یادگیری تقویتی الهام گرفته از پردازش کوانتومی-2022 Recent developments in the Internet of Vehicles
(IoV) enable interconnected vehicles to support ubiquitous
services. Various emerging service applications are promising to
increase the Quality of Experience (QoE) of users. On-board
computation tasks generated by these applications have heavily
overloaded the resource-constrained vehicles, forcing it to offload
on-board tasks to other edge intelligence (EI)-assisted servers.
However, excessive task offloading can lead to severe competition
for communication and computation resources among vehicles,
thereby increasing the processing latency, energy consumption,
and system cost. To address these problems, we investigate
the transmission-awareness and computing-sense uplink resource
management problem and formulate it as a time-varying Markov
decision process. Considering the total delay, energy consumption, and cost, quantum-inspired reinforcement learning (QRL)
is proposed to develop an intelligence-oriented edge offloading
strategy. Specifically, the vehicle can flexibly choose the network
access mode and offloading strategy through two different radio
interfaces to offload tasks to multiaccess edge computing (MEC)
servers through WiFi and cloud servers through 5G. The objective of this joint optimization is to maintain a self-adaptive
balance between these two aspects. Simulation results show that
the proposed algorithm can significantly reduce the transmission
latency and computation delay.
Index Terms: Cloud computing | edge intelligence (EI) | Internet of Vehicles (IoV) | multiaccess edge computing (MEC) | quantum-inspired reinforcement learning (QRL) |
مقاله انگلیسی |
96 |
Retargetable Optimizing Compilers for Quantum Accelerators via a Multilevel Intermediate Representation
کامپایلرهای بهینه سازی مجدد قابل هدف گیری برای شتاب دهنده های کوانتومی از طریق یک نمایش میانی چند سطحی-2022 We present a multilevel quantum–classical intermediate representation (IR) that
enables an optimizing, retargetable compiler for available quantum languages.
Our work builds upon the multilevel intermediate representation (MLIR)
framework and leverages its unique progressive lowering capabilities to map
quantum languages to the low-level virtual machine (LLVM) machine-level IR.
We provide both quantum and classical optimizations via the MLIR pattern
rewriting subsystem and standard LLVM optimization passes, and demonstrate
the programmability, compilation, and execution of our approach via standard
benchmarks and test cases. In comparison to other standalone language and
compiler efforts available today, our work results in compile times that are
1,000 faster than standard Pythonic approaches, and 5–10 faster than
comparative standalone quantum language compilers. Our compiler provides
quantum resource optimizations via standard programming patterns that result
in a 10 reduction in entangling operations, a common source of program
noise. We see this work as a vehicle for rapid quantum compiler prototyping.
|
مقاله انگلیسی |
97 |
Secure Social Internet of Things Based on Post-Quantum Blockchain
اینترنت اجتماعی ایمن اشیا بر اساس بلاک چین پس کوانتومی-2022 With the advancement of the application of Internet
of Things (IoTs), the IoT technology is combining with the social
network, forming a new network with private object information
as the media and social entertainment as the purpose. Social
Internet of things (SIoTs) is a new application of IoT technology
in social network. The current SIoT systems are centralized and
the user’s security and privacy is not properly protected. In
order to address the challenges in SIoTs, we propose a privacy
protection system for the users. First, we propose a post-quantum
ring signature. Second, we propose a blockchain system based on
the ring signature. Compared with the traditional SIoTs, our
system is based on post-quantum techniques, which is secure
against both traditional computers and quantum computers. The
results of the blockchain system show that it is very suitable for
SIoTs.
Index Terms—Social Internet of Things (SIoTs) | Internet of Things (IoTs) | Blockchain | Post-Quantum Signature. |
مقاله انگلیسی |
98 |
Shuttle-Exploiting Attacks and Their Defenses in Trapped-Ion Quantum Computers
حملات بهره برداری شاتل و دفاع آنها در کامپیوترهای کوانتومی یونی به دام افتاده-2022 Trapped-ion (TI) quantum bits are a front-runner technology for quantum computing.
TI systems with multiple interconnected traps can overcome the hardware connectivity issue inherent in
superconducting qubits and can solve practical problems at scale. With a sufficient number of qubits on the
horizon, the multi-programming model for Quantum Computers (QC) has been proposed where multiple
users share the same QC for their computing. Multi-programming is enticing for quantum cloud providers
as it can maximize device utilization, throughput, and profit for clouds. Users can also benefit from the
short wait queue. However, shared access to quantum computers can create new security issues. This paper
presents one such vulnerability in shared TI systems that require shuttle operations for communication among
traps. Repeated shuttle operations increase quantum bit energy and degrade the reliability of computations
(fidelity). We show adversarial program design approaches requiring numerous shuttles. We propose a random and systematic methodology for adversary program generation. Our analysis shows shuttle-exploiting
attacks can substantially degrade the fidelities of victim programs by ≈2× to ≈63×. Finally, we present
several countermeasures such as adopting a hybrid initial mapping policy, padding victim programs with
dummy qubits, and capping maximum shuttles.
INDEX TERMS: Trapped-ion | qubit | quantum computing | shuttle | security | fidelity. |
مقاله انگلیسی |
99 |
Simultaneous Estimation of Parameters and the State of an Optical Parametric Oscillator System
تخمین همزمان پارامترها و وضعیت یک سیستم نوسان ساز پارامتری نوری-2022 In this article, we consider the filtering problem of an optical parametric oscillator (OPO).
The OPO pump power may fluctuate due to environmental disturbances, resulting in uncertainty in the
system modeling. Thus, both the state and the unknown parameter may need to be estimated simultaneously.
We formulate this problem using a state-space representation of the OPO dynamics. Under the assumption
of Gaussianity and proper constraints, the dual Kalman filter method and the joint extended Kalman filter
method are employed to simultaneously estimate the system state and the pump power. Numerical examples
demonstrate the effectiveness of the proposed algorithms. keywords: Optical parametric oscillator (OPO) | OPO system | parameter estimation | quantum state estimation | simultaneous estimation. |
مقاله انگلیسی |
100 |
Simultaneous Execution of Quantum Circuits on Current and Near-Future NISQ Systems
اجرای همزمان مدارهای کوانتومی در سیستمهای NISQ فعلی و آینده نزدیک-2022 In the noisy intermediate-scale quantum (NISQ) era, the idea of quantum multiprogramming,
running multiple quantum circuits (QCs) simultaneously on the same hardware, helps to improve the
throughput of quantum computation. However, the crosstalk, unwanted interference between qubits on NISQ
processors, may cause performance degradation when using multiprogramming. To address this challenge,
we introduce palloq (parallel allocation of QCs), a novel compilation protocol. Palloq improves the performance of quantum multiprogramming on NISQ processors, while paying attention to 1) the combination
of QCs chosen for parallel execution and 2) the assignment of program qubit variables to physical qubits,
to reduce unwanted interference among the active set of QCs. We also propose a software-based crosstalk
detection protocol using a new combination of randomized benchmarking methods. Our method successfully
characterizes the suitability of hardware for multiprogramming with relatively low detection costs. We found
a tradeoff between the success rate and execution time of the multiprogramming. Our results will be of value
when device throughput becomes a significant bottleneck. Until service providers have enough quantum
processors available to more than meet demand, this approach will be attractive to the service providers and
users who want to optimize job management and throughput of the processor.
INDEX TERMS: Compiler | crosstalk | multiprogramming | noisy intermediate-scale quantum (NISQ) | quantum computing. |
مقاله انگلیسی |