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Related papers: Quantum Factorization of 143 on a Dipolar-Coupling…

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Shor's algorithm for integer factorization offers an exponential speedup over classical methods but remains impractical on Noisy Intermediate Scale Quantum (NISQ) hardware due to the need for many coherent qubits and very deep circuits.…

Quantum Physics · Physics 2025-12-09 Alok Shukla , Prakash Vedula

Motivated by the need to uncover some underlying mathematical structure of optimal quantum computation, we carry out a systematic analysis of a wide variety of quantum algorithms from the majorization theory point of view. We conclude that…

Quantum Physics · Physics 2009-11-07 Roman Orus , Jose I. Latorre , Miguel A. Martin-Delgado

We factorize a 48-bit integer using 10 trapped-ion qubits on a Quantinuum's quantum computer. This result outperforms the recent achievement by B. Yan et al., arXiv:2212.12372 (2022), increasing the success probability by a factor of 6 with…

Quantum Physics · Physics 2023-01-27 Narendra N. Hegade , Enrique Solano

Quantum computing and modern tensor-based computing have a strong connection, which is especially demonstrated by simulating quantum computations with tensor networks. The other direction is less studied: quantum computing is not often…

Quantum Physics · Physics 2025-09-03 Valter Uotila

We report a quantum-classical hybrid scheme for factorization of bi-prime numbers (which are odd and square-free) using IBM's quantum processors. The hybrid scheme proposed here involves both classical optimization techniques and adiabatic…

Quantum Physics · Physics 2022-06-07 Ashwin Saxena , Abhishek Shukla , Anirban Pathak

Adiabatic quantum computation for performing quantum computations such as Shor's algorithm is protected against thermal errors by an energy gap of size $O(1/n)$, where $n$ is the length of the computation to be performed.

Quantum Physics · Physics 2008-05-20 Seth Lloyd

We give an overview of a quantum adiabatic algorithm for Hilbert's tenth problem, including some discussions on its fundamental aspects and the emphasis on the probabilistic correctness of its findings. For the purpose of illustration, the…

Quantum Physics · Physics 2007-05-23 Tien D. Kieu

Adiabatic quantum computing (AQC) is a promising approach for discrete and often NP-hard optimization problems. Current AQCs allow to implement problems of research interest, which has sparked the development of quantum representations for…

Machine Learning · Computer Science 2024-05-02 Jan-Nico Zaech , Martin Danelljan , Tolga Birdal , Luc Van Gool

We consider a classical and superadiabatic version of an iterative quantum adiabatic algorithm to solve combinatorial optimization problems. This algorithm is deterministic because it is based on purely classical dynamics, that is, it does…

Statistical Mechanics · Physics 2020-05-08 Takuya Hatomura

The goal of this paper is to introduce building blocks for adiabatic quantum algorithms. Adiabatic quantum computing uses the principle of quantum annealing, which implies that a carefully controlled energy solution is optimal and…

Quantum Physics · Physics 2014-08-27 Richard H. Warren

Adiabatic quantum computing is implemented on specialized hardware using the heuristics of the quantum annealing algorithm. This setup requires the addressed problems to be formatted as discrete quadratic functions without constraints and…

Computer Science and Game Theory · Computer Science 2024-01-23 Olga Okrut , Keith Cannon , Kareem H. El-Safty , Nada Elsokkary , Faisal Shah Khan

In previous implementations of adiabatic quantum algorithms using spin systems, the average Hamiltonian method with Trotter's formula was conventionally adopted to generate an effective instantaneous Hamiltonian that simulates an adiabatic…

The adiabatic quantum algorithm has drawn intense interest as a potential approach to accelerating optimization tasks using quantum computation. The algorithm is most naturally realised in systems which support Hamiltonian evolution, rather…

Quantum Physics · Physics 2019-10-02 Liming Zhao , Carlos A. Perez-Delgado , Simon C. Benjamin , Joseph F. Fitzsimons

We present fast and highly parallelized versions of Shor's algorithm. With a sizable quantum computer it would then be possible to factor numbers with millions of digits. The main algorithm presented here uses FFT-based fast integer…

Quantum Physics · Physics 2007-05-23 Christof Zalka

Quantum annealing is guaranteed to find the ground state of optimization problems in the adiabatic limit. Recent work [Phys. Rev. X 6, 031010 (2016)] has found that for some barrier tunneling problems, quantum annealing can be run much…

Quantum Physics · Physics 2017-04-05 Lucas T. Brady , Wim van Dam

Quantum algorithm design plays a crucial role in exploiting the computational advantage of quantum devices. Here we develop a deep-reinforcement-learning based approach for quantum adiabatic algorithm design. Our approach is generically…

Quantum Physics · Physics 2020-05-20 Jian Lin , Zhong Yuan Lai , Xiaopeng Li

Adiabatic quantum computers can solve difficult optimization problems (e.g., the quadratic unconstrained binary optimization problem), and they seem well suited to train machine learning models. In this paper, we describe an adiabatic…

In the circuit model of quantum computing, amplitude amplification techniques can be used to find solutions to NP-hard problems defined on $n$-bits in time $\text{poly}(n) 2^{n/2}$. In this work, we investigate whether such general…

The quantum adiabatic algorithm is a Hamiltonian based quantum algorithm designed to find the minimum of a classical cost function whose domain has size N. We show that poor choices for the Hamiltonian can guarantee that the algorithm will…

Quantum Physics · Physics 2008-06-30 Edward Farhi , Jeffrey Goldstone , Sam Gutmann , Daniel Nagaj

We present a comprehensive review of past research into adiabatic quantum computation and then propose a scalable architecture for an adiabatic quantum computer that can treat NP-hard problems without requiring local coherent operations.…

Quantum Physics · Physics 2007-05-23 William M. Kaminsky , Seth Lloyd