Quantum Algorithms for Integer Factorization

2015 ◽  
pp. 59-119
Author(s):  
Song Y. Yan
Keyword(s):  
Quantum Algorithms ◽  
Integer Factorization

scholarly journals Quantum Simulation Logic, Oracles, and the Quantum Advantage

Entropy ◽  
2019 ◽  
Vol 21 (8) ◽  
pp. 800 ◽  
Author(s):  
Niklas Johansson ◽  
Jan-Åke Larsson
Keyword(s):  
Quantum Computer ◽  
Quantum Algorithms ◽  
Success Probability ◽  
Quantum Simulation ◽  
Query Complexity ◽  
Integer Factorization ◽  
Simulation Framework ◽  
Shor's Algorithm ◽  
Quantum Query ◽  
Do So

Query complexity is a common tool for comparing quantum and classical computation, and it has produced many examples of how quantum algorithms differ from classical ones. Here we investigate in detail the role that oracles play for the advantage of quantum algorithms. We do so by using a simulation framework, Quantum Simulation Logic (QSL), to construct oracles and algorithms that solve some problems with the same success probability and number of queries as the quantum algorithms. The framework can be simulated using only classical resources at a constant overhead as compared to the quantum resources used in quantum computation. Our results clarify the assumptions made and the conditions needed when using quantum oracles. Using the same assumptions on oracles within the simulation framework we show that for some specific algorithms, such as the Deutsch-Jozsa and Simon’s algorithms, there simply is no advantage in terms of query complexity. This does not detract from the fact that quantum query complexity provides examples of how a quantum computer can be expected to behave, which in turn has proved useful for finding new quantum algorithms outside of the oracle paradigm, where the most prominent example is Shor’s algorithm for integer factorization.

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.

Research on a New Public Key Cryptosystem as Secure as Integer Factorization

2011 ◽  
Vol 30 (6) ◽  
pp. 1450-1452 ◽  
Author(s):  
Zheng-tao Jiang ◽  
Jing-liang Zhang ◽  
Yu-min Wang
Keyword(s):  
Public Key ◽  
Public Key Cryptosystem ◽  
Integer Factorization ◽  
New Public

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

Reduction of the integer factorization complexity upper bound to the complexity of the Diffie–Hellman problem

2021 ◽  
Vol 31 (1) ◽  
pp. 1-4
Author(s):  
Mikhail A. Cherepnev
Keyword(s):  
Upper Bound ◽  
Polynomial Algorithm ◽  
Integer Factorization ◽  
Factorization Problem ◽  
Diffie Hellman ◽  
Integer Factorization Problem

Abstract We construct a probabilistic polynomial algorithm that solves the integer factorization problem using an oracle solving the Diffie–Hellman problem.

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.

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