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Related papers: Adiabatic Quantum Search in Open Systems

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Adiabatic quantum control protocols have been of wide interest to quantum computation due to their robustness and insensitivity to their actual duration of execution. As an extension of previous quantum learning algorithms, this work…

Quantum Physics · Physics 2023-03-03 Nannan Ma , Wenhao Chu , Jiangbin Gong

Two recent preprints [B. Altshuler, H. Krovi, and J. Roland, "Quantum adiabatic optimization fails for random instances of NP-complete problems", arXiv:0908.2782 and "Anderson localization casts clouds over adiabatic quantum optimization",…

Quantum Physics · Physics 2010-05-18 S. Knysh , V. Smelyanskiy

Adiabatic quantum computation, based on the adiabatic theorem, is a promising alternative to conventional quantum computation. The validity of an adiabatic algorithm depends on the existence of a nonzero energy gap between the ground and…

Quantum Physics · Physics 2014-10-20 Da-Jian Zhang , Xiao-Dong Yu , D. M. Tong

Suppressing undesired nonunitary effects is a major challenge in quantum computation and quantum control. In this work, by considering the adiabatic dynamics in presence of a surrounding environment, we theoretically and experimentally…

We generalize the standard quantum adiabatic approximation to the case of open quantum systems. We define the adiabatic limit of an open quantum system as the regime in which its dynamical superoperator can be decomposed in terms of…

Quantum Physics · Physics 2007-05-23 M. S. Sarandy , D. A. Lidar

We propose a quantum algorithm for solving combinatorial search problems that uses only a sequence of measurements. The algorithm is similar in spirit to quantum computation by adiabatic evolution, in that the goal is to remain in the…

A numerical method is proposed for simulation of composite open quantum systems. It is based on Lindblad master equations and adiabatic elimination. Each subsystem is assumed to converge exponentially towards a stationary subspace, slightly…

Quantum Physics · Physics 2023-11-10 François-Marie Le Régent , Pierre Rouchon

We propose a new adiabatic algorithm for the unsorted database search problem. This algorithm saves two thirds of qubits than Grover's algorithm in realizations. Meanwhile, we analyze the time complexity of the algorithm by both…

Quantum Physics · Physics 2008-11-06 Nanyang Xu , Xinhua Peng , Mingjun Shi , Jiangfeng Du

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

Adiabatic quantum computation provides an alternative approach to quantum computation using a time-dependent Hamiltonian. The time evolution of entanglement during the adiabatic quantum search algorithm is studied, and its relevance as a…

Quantum Physics · Physics 2009-11-11 Daria Ahrensmeier

We show that by a suitable choice of time-dependent Hamiltonian, the search for a marked item in an unstructured database can be achieved in unit time, using Adiabatic Quantum Computation. This is a considerable improvement over the…

Quantum Physics · Physics 2007-05-23 Daria Ahrensmeier , Saurya Das , Randy Kobes , Gabor Kunstatter , Haitham Zaraket

It is believed that the presence of anticrossings with exponentially small gaps between the lowest two energy levels of the system Hamiltonian, can render adiabatic quantum optimization inefficient. Here, we present a simple adiabatic…

Quantum Physics · Physics 2013-05-30 Neil G. Dickson , Mohammad H. Amin

Real life quantum computers are inevitably affected by intrinsic noise resulting in dissipative non-unitary dynamics realized by these devices. We consider an open system quantum annealing algorithm optimized for a realistic analog quantum…

Quantum Physics · Physics 2016-06-08 Kostyantyn Kechedzhi , Vadim N. Smelyanskiy

A common trick for designing faster quantum adiabatic algorithms is to apply the adiabaticity condition locally at every instant. However it is often difficult to determine the instantaneous gap between the lowest two eigenvalues, which is…

Quantum Physics · Physics 2007-05-23 M. V. Panduranga Rao

In this paper we present a quantum algorithm that uses noise as a resource. The goal of our quantum algorithm is the calculation of operator averages of an open quantum system evolving in time. Selected low-noise system qubits and noisy…

We describe a many-body quantum system which can be made to quantum compute by the adiabatic application of a large applied field to the system. Prior to the application of the field quantum information is localized on one boundary of the…

Quantum Physics · Physics 2013-06-19 Dave Bacon , Steven T. Flammia , Gregory M. Crosswhite

We examine the use of adiabatic quantum algorithms to solve structured, or nested, search problems. We construct suitable time dependent Hamiltonians and derive the computation times for a general class of nested searches involving n…

Quantum Physics · Physics 2007-05-23 Daria Ahrensmeier , Saurya Das , Randy Kobes , Gabor Kunstatter , Haitham Zaraket

Preparation of low-energy quantum many-body states has a wide range of applications in quantum information processing and condensed matter physics. Quantum cooling algorithms offer a promising alternative to other methods based, for…

Quantum Physics · Physics 2025-08-22 Daniel Molpeceres , Sirui Lu , J. Ignacio Cirac , Barbara Kraus

We propose an implementation of the quantum search algorithm of a marked item in an unsorted list of N items by adiabatic passage in a cavity-laser-atom system. We use an ensemble of N identical three-level atoms trapped in a single-mode…

Quantum Physics · Physics 2007-10-30 D. Daems , S. Guérin

Quantum computing for machine learning attracts increasing attention and recent technological developments suggest that especially adiabatic quantum computing may soon be of practical interest. In this paper, we therefore consider this…

Machine Learning · Statistics 2017-06-20 Christian Bauckhage , Eduardo Brito , Kostadin Cvejoski , Cesar Ojeda , Rafet Sifa , Stefan Wrobel