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Adiabatic quantum computation starts from embedding a computational problem into a Hamiltonian whose ground state encodes the solution to the problem. This problem Hamiltonian, $H_{\rm p}$, is normally chosen to be diagonal in the…

Quantum Physics · Physics 2020-03-05 Oleg Lychkovskiy

The simulation of adiabatic evolution has deep connections with Adiabatic Quantum Computation, the Quantum Approximate Optimization Algorithm and adiabatic state preparation. Here we address the error analysis problem in quantum simulation…

Quantum Physics · Physics 2022-02-09 Changhao Yi

Combinatorial optimization problems that arise in science and industry typically have constraints. Yet the presence of constraints makes them challenging to tackle using both classical and quantum optimization algorithms. We propose a new…

We propose a method to implement cavity QED and quantum information processing in high-Q cavities with a single trapped but non-localized atom. The system is beyond the Lamb-Dick limit due to the atomic thermal motion. Our method is based…

Quantum Physics · Physics 2009-11-07 L. -M. Duan , A. Kuzmich , H. J. Kimble

We point out that, when an optimization problem has more than one solution, the quantum adiabatic algorithms (QAA) encounter topological obstructions leading to adiabatic spectral flows where spectral branches unavoidably traverse the…

Quantum Physics · Physics 2026-03-24 Prathamesh S. Joshi , Emil Prodan

In many quantum technologies adiabatic processes are used for coherent quantum state operations, offering inherent robustness to errors in the control parameters. The main limitation is the long operation time resulting from the requirement…

Quantum Physics · Physics 2019-04-12 A. Vepsäläinen , S. Danilin , G. S. Paraoanu

Quantum alternating operator ansatz (QAOA) has a strong connection to the adiabatic algorithm, which it can approximate with sufficient depth. However, it is unclear to what extent the lessons from the adiabatic regime apply to QAOA as…

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

A typical goal of a quantum simulation is to find the energy levels and eigenstates of a given Hamiltonian. This can be realized by adiabatically varying the system control parameters to steer an initial eigenstate into the eigenstate of…

Quantum Physics · Physics 2021-01-04 Gian Salis , Nikolaj Moll , Marco Roth , Marc Ganzhorn , Stefan Filipp

Adiabatic quantum computing is a general framework for preparing eigenstates of Hamiltonians on quantum devices. However, its digital implementation requires an efficient Hamiltonian simulation subroutine, which may introduce extra…

Quantum Physics · Physics 2025-09-03 Dong An , Pedro C. S. Costa , Dominic W. Berry

Adiabatic transport provides a powerful way to manipulate quantum states. By preparing a system in a readily initialised state and then slowly changing its Hamiltonian, one may achieve quantum states that would otherwise be inaccessible.…

Quantum Physics · Physics 2015-02-13 P. J. D. Crowley , T. Duric , W. Vinci , P. A. Warburton , A. G. Green

Digitizing an adiabatic evolution is a strategy able to combine the good performance of gate-based quantum processors with the advantages of adiabatic algorithms, providing then a hybrid model for efficient quantum information processing.…

Quantum Physics · Physics 2025-02-27 Alan C. Santos

In Amin and Choi \cite{AC09}, we show that an adiabatic quantum algorithm for the NP-hard maximum independent set (MIS) problem on a set of special family of graphs in which there are exponentially many local maxima would have the…

Quantum Physics · Physics 2011-08-04 Vicky Choi

We develop a scheme of fast forward of adiabatic spin dynamics of quantum entangled states. We settle the quasi-adiabatic dynamics by adding the regularization terms to the original Hamiltonian and then accelerate it with use of a large…

Quantum Physics · Physics 2018-05-25 Iwan Setiawan , Bobby Eka Gunara , Shumpei Masuda , Katsuhiro Nakamura

In this paper we show that the performance of the quantum adiabatic algorithm is determined by phase transitions in underlying problem in the presence of transverse magnetic field $\Gamma$. We show that the quantum version of random…

Disordered Systems and Neural Networks · Physics 2007-05-23 S. Knysh , V. N. Smelyanskiy

The adiabatic approximation exhibits wide applicability in quantum mechanics, providing a simple approach for nontransitional dynamics in quantum systems governed by slowly varying time-dependent Hamiltonians. However, the standard…

Quantum Physics · Physics 2020-11-12 Alan C. Santos , Marcelo S. Sarandy

Recently, several approaches to solving linear systems on a quantum computer have been formulated in terms of the quantum adiabatic theorem for a continuously varying Hamiltonian. Such approaches enabled near-linear scaling in the condition…

Quantum Physics · Physics 2021-11-17 Pedro C. S. Costa , Dong An , Yuval R. Sanders , Yuan Su , Ryan Babbush , Dominic W. Berry

We review a scheme for the systematic design of quantum control protocols based on shortcuts to adiabaticity in few-level quantum systems. The adiabatic dynamics is accelerated by introducing high-frequency modulations in the control…

Quantum Physics · Physics 2024-02-08 Francesco Petiziol , Florian Mintert , Sandro Wimberger

Quantum adiabatic processes -that keep constant the populations in the instantaneous eigenbasis of a time-dependent Hamiltonian- are very useful to prepare and manipulate states, but take typically a long time. This is often problematic…

Analog quantum algorithms are formulated in terms of Hamiltonians rather than unitary gates and include quantum adiabatic computing, quantum annealing, and the quantum approximate optimization algorithm (QAOA). These algorithms are…