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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

This paper concerns quantum heuristics able to extend the domain of quantum computing, defining a promising way in the large number of well-known classical algorithms. Quantum approximate heuristics take advantage of alternation between a…

Quantum Physics · Physics 2022-07-22 Eric Bourreau , Gérard Fleury , Philippe Lacomme

We derive a version of the adiabatic theorem that is especially suited for applications in adiabatic quantum computation, where it is reasonable to assume that the adiabatic interpolation between the initial and final Hamiltonians is…

Quantum Physics · Physics 2009-10-21 D. A. Lidar , A. T. Rezakhani , A. Hamma

We present an adiabatic quantum algorithm for the abstract problem of searching marked vertices in a graph, or spatial search. Given a random walk (or Markov chain) $P$ on a graph with a set of unknown marked vertices, one can define a…

Quantum Physics · Physics 2010-09-08 Hari Krovi , Maris Ozols , Jérémie Roland

In adiabatic quantum computing the aim is to track an eigenstate as the Hamiltonian changes. In the usual setup this is achieved using the natural time-dependent Hamiltonian evolution of the system and the main technical tool is the…

Quantum Physics · Physics 2026-05-29 Joseph Cunningham , Jérémie Roland

A computation in adiabatic quantum computing is implemented by traversing a path of nondegenerate eigenstates of a continuous family of Hamiltonians. We introduce a method that traverses a discretized form of the path: At each step we apply…

Quantum Physics · Physics 2009-08-14 S. Boixo , E. Knill , R. D. Somma

We propose a strategy to achieve the Grover search algorithm by adiabatic passage in a very efficient way. An adiabatic process can be characterized by the instantaneous eigenvalues of the pertaining Hamiltonian, some of which form a gap.…

Quantum Physics · Physics 2008-10-23 D. Daems , S. Guérin , N. J. Cerf

Quantum adiabatic optimization seeks to solve combinatorial problems using quantum dynamics, requiring the Hamiltonian of the system to align with the problem of interest. However, these Hamiltonians are often incompatible with the native…

Towards better understanding of how to design efficient adiabatic quantum algorithms, we study how the adiabatic gap depends on the spectra of the initial and final Hamiltonians in a natural family of test-bed examples. We show that perhaps…

Mathematical Physics · Physics 2019-06-07 Yosi Atia , Dorit Aharonov

According to the adiabatic theorem of quantum mechanics, a system initially in the ground state of a Hamiltonian remains in the ground state if one slowly changes the Hamiltonian. This can be used in principle to solve hard problems on…

Quantum Physics · Physics 2025-09-03 Etienne Granet , Henrik Dreyer

In this paper we analyze the performance of the Quantum Adiabatic Evolution algorithm on a variant of Satisfiability problem for an ensemble of random graphs parametrized by the ratio of clauses to variables, $\gamma=M/N$. We introduce a…

Quantum Physics · Physics 2009-11-10 V. N. Smelyanskiy , S. Knysh , R. D. Morris

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

There are few known exponential speedups for quantum algorithms and these tend to fall into even fewer families. One speedup that has mostly resisted generalization is the use of quantum walks to traverse the welded-tree graph, due to…

Quantum Physics · Physics 2026-01-21 Shankar Balasubramanian , Tongyang Li , Aram Harrow

We present an optimized adiabatic quantum schedule for unstructured search building on the original approach of Roland and Cerf [Phys. Rev. A 65, 042308 (2002)]. Our schedule adiabatically varies the Hamiltonian even more rapidly at the…

Quantum Physics · Physics 2025-02-13 Sean A. Adamson , Petros Wallden

In this paper, we demonstrate that it is possible to create an adiabatic quantum computing algorithm that solves the shortest path between any two vertices on an undirected graph with at most 3V qubits, where V is the number of vertices of…

Quantum Physics · Physics 2024-09-18 Venkat Padmasola , Rupak Chatterjee

Gradient descent is a fundamental algorithm in both theory and practice for continuous optimization. Identifying its quantum counterpart would be appealing to both theoretical and practical quantum applications. A conventional approach to…

Quantum Physics · Physics 2023-03-03 Jiaqi Leng , Ethan Hickman , Joseph Li , Xiaodi Wu

Classical optimization problems can be solved by adiabatically preparing the ground state of a quantum Hamiltonian that encodes the problem. The performance of this approach is determined by the smallest gap encountered during the…

At present, several models for quantum computation have been proposed. Adiabatic quantum computation scheme particularly offers this possibility and is based on a slow enough time evolution of the system, where no transitions take place. In…

Quantum Physics · Physics 2012-10-12 P. J. Salas Peralta

Adiabatic passage employs a slowly varying time-dependent Hamiltonian to control the evolution of a quantum system along the Hamiltonian eigenstates. For processes of finite duration, the exact time evolving state may deviate from the…

Quantum Physics · Physics 2021-06-18 Albert Benseny , Klaus Mølmer

Motivated by the quantum adiabatic algorithm (QAA), we consider the scaling of the Hamiltonian gap at quantum first order transitions, generally expected to be exponentially small in the size of the system. However, we show that a quantum…

Quantum Physics · Physics 2012-10-30 C. R. Laumann , R. Moessner , A. Scardicchio , S. L. Sondhi