scholarly journals State transfer with separable optical beams and variational quantum algorithms with classical light

2021 ◽  
Author(s):  
SOORYANSH ASTHANA ◽  
V. Ravishankar
Keyword(s):  
Quantum Algorithms ◽  
State Transfer ◽  
Optical Beams

The Influence of Optical Beams on Semiconductor Devices During Failure Analysis

2002 ◽  
Author(s):  
Charles Zhang ◽  
Matt Thayer ◽  
Lowell Herlinger ◽  
Greg Dabney ◽  
Manuel Gonzalez
Keyword(s):  
Failure Analysis ◽  
Semiconductor Devices ◽  
Laser Wavelength ◽  
Fault Isolation ◽  
Analysis Techniques ◽  
Cmos Transistor ◽  
Optical Beams

Abstract A number of backside analysis techniques rely on the successful use of optical beams in performing backside fault isolation. In this paper, the authors have investigated the influence of the 1340 nm and 1064 nm laser wavelength on advanced CMOS transistor performance.

The Essence of Quantum Computing

2018 ◽  
Author(s):  
Rajendra K. Bera
Keyword(s):  
Hilbert Space ◽  
Quantum Computing ◽  
Quantum Physics ◽  
Quantum Algorithms ◽  
Quantum Computers ◽  
Turing Machines ◽  
Classical Physics ◽  
Core Set ◽  
The World ◽  
Subordinate Role

It now appears that quantum computers are poised to enter the world of computing and establish its dominance, especially, in the cloud. Turing machines (classical computers) tied to the laws of classical physics will not vanish from our lives but begin to play a subordinate role to quantum computers tied to the enigmatic laws of quantum physics that deal with such non-intuitive phenomena as superposition, entanglement, collapse of the wave function, and teleportation, all occurring in Hilbert space. The aim of this 3-part paper is to introduce the readers to a core set of quantum algorithms based on the postulates of quantum mechanics, and reveal the amazing power of quantum computing.

scholarly journals Quantum Algorithms for Mixed Binary Optimization applied to Transaction Settlement

2021 ◽  
pp. 1-1
Author(s):  
Lee Braine ◽  
Daniel Egger ◽  
Jennifer Glick ◽  
Stefan Woerner
Keyword(s):  
Quantum Algorithms ◽  
Binary Optimization

Learning adiabatic quantum algorithms over optimization problems

2021 ◽  
Vol 3 (1) ◽  
Author(s):  
Davide Pastorello ◽  
Enrico Blanzieri ◽  
Valter Cavecchia
Keyword(s):  
Optimization Problems ◽  
Quantum Algorithms

scholarly journals Smooth input preparation for quantum and quantum-inspired machine learning

2021 ◽  
Vol 3 (1) ◽  
Author(s):  
Zhikuan Zhao ◽  
Jack K. Fitzsimons ◽  
Patrick Rebentrost ◽  
Vedran Dunjko ◽  
Joseph F. Fitzsimons
Keyword(s):  
Machine Learning ◽  
Quantum Algorithms ◽  
Machine Learning Algorithms ◽  
Low Rank ◽  
Smoothed Analysis ◽  
Machine Learning Applications ◽  
Data Points ◽  
Input Model ◽  
The Cost ◽  
Input Perturbation

AbstractMachine learning has recently emerged as a fruitful area for finding potential quantum computational advantage. Many of the quantum-enhanced machine learning algorithms critically hinge upon the ability to efficiently produce states proportional to high-dimensional data points stored in a quantum accessible memory. Even given query access to exponentially many entries stored in a database, the construction of which is considered a one-off overhead, it has been argued that the cost of preparing such amplitude-encoded states may offset any exponential quantum advantage. Here we prove using smoothed analysis that if the data analysis algorithm is robust against small entry-wise input perturbation, state preparation can always be achieved with constant queries. This criterion is typically satisfied in realistic machine learning applications, where input data is subjective to moderate noise. Our results are equally applicable to the recent seminal progress in quantum-inspired algorithms, where specially constructed databases suffice for polylogarithmic classical algorithm in low-rank cases. The consequence of our finding is that for the purpose of practical machine learning, polylogarithmic processing time is possible under a general and flexible input model with quantum algorithms or quantum-inspired classical algorithms in the low-rank cases.

scholarly journals Practical Security of RSA Against NTC-Architecture Quantum Computing Attacks

2021 ◽  
Author(s):  
Kai Li ◽  
Qing-yu Cai
Keyword(s):  
Quantum Computing ◽  
Ion Trap ◽  
Quantum Algorithms ◽  
Coherence Time ◽  
Quantum Computers ◽  
Quantum Time ◽  
Speed Up ◽  
Key Length ◽  
Concurrent Architecture ◽  
Qubit Gate

AbstractQuantum algorithms can greatly speed up computation in solving some classical problems, while the computational power of quantum computers should also be restricted by laws of physics. Due to quantum time-energy uncertainty relation, there is a lower limit of the evolution time for a given quantum operation, and therefore the time complexity must be considered when the number of serial quantum operations is particularly large. When the key length is about at the level of KB (encryption and decryption can be completed in a few minutes by using standard programs), it will take at least 50-100 years for NTC (Neighbor-only, Two-qubit gate, Concurrent) architecture ion-trap quantum computers to execute Shor’s algorithm. For NTC architecture superconducting quantum computers with a code distance 27 for error-correcting, when the key length increased to 16 KB, the cracking time will also increase to 100 years that far exceeds the coherence time. This shows the robustness of the updated RSA against practical quantum computing attacks.

Reliability analysis and state transfer scheduling optimization of degrading load-sharing system equipped with warm standby components

2021 ◽  
pp. 1748006X2110017
Author(s):  
Sheng-Jia Ruan ◽  
Yan-Hui Lin
Keyword(s):  
Reliability Analysis ◽  
System Reliability ◽  
High Reliability ◽  
Quadrature Rule ◽  
Load Sharing ◽  
Measurement Information ◽  
Model Parameters ◽  
Scheduling Optimization ◽  
State Transfer ◽  
Warm Standby

Standby redundancy can meet system safety requirements in industries with high reliability standards. To evaluate reliability of standby systems, failure dependency among components has to be considered especially when systems have load-sharing characteristics. In this paper, a reliability analysis and state transfer scheduling optimization framework is proposed for the load-sharing 1-out-of- N: G system equipped with M warm standby components and subject to continuous degradation process. First, the system reliability function considering multiple dependent components is derived in a recursive way. Then, a Monte Carlo method is developed and the closed Newton-Cotes quadrature rule is invoked for the system reliability quantification. Besides, likelihood functions are constructed based on the measurement information to estimate the model parameters of both active and standby components, whose degradation paths are modeled by the step-wise drifted Wiener processes. Finally, the system state transfer scheduling is optimized by the genetic algorithm to maximize the system reliability at mission time. The proposed methodology and its effectiveness are illustrated through a case study referring to a simplified aircraft hydraulic system.

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