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In this paper we present an invariant perturbation theory to adiabatic process according to the concepts of adiabatic orbits, adiabatic evolution orbit and U(1)-invariant adiabatic orbit. The probabilities of keeping the adiabatic orbit in…

Quantum Physics · Physics 2007-06-06 Jian-Lan Chen , Mei-sheng Zhao , Jian-da Wu , Yong-de Zhang

This paper presents an accelerated composite gradient (ACG) variant, referred to as the AC-ACG method, for solving nonconvex smooth composite minimization problems. As opposed to well-known ACG variants that are either based on a known…

Optimization and Control · Mathematics 2020-10-30 Jiaming Liang , Renato D. C. Monteiro

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

Adiabatic quantum computing is a framework for quantum computing that is superficially very different to the standard circuit model. However, it can be shown that the two models are computationally equivalent. The key to the proof is a…

Quantum Physics · Physics 2020-04-08 Shane Dooley , Graham Kells , Hosho Katsura , Tony C. Dorlas

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

Exploiting the similarity between adiabatic quantum algorithms and quantum phase transitions, we argue that second-order transitions -- typically associated with broken or restored symmetries -- should be advantageous in comparison to…

Quantum Physics · Physics 2010-01-07 Gernot Schaller , Ralf Schützhold

Gaussian process (GP) regression is a powerful probabilistic modeling technique with built-in uncertainty quantification. When one has access to multiple correlated simulations (tasks), it is common to fit a multitask GP (MTGP) surrogate…

Computation · Statistics 2026-03-18 Aleksei G. Sorokin , Pieterjan Robbe , Fred J. Hickernell

We study quantum dynamics of Grover's adiabatic search algorithm with the equivalent two-level system. Its adiabatic and non-adiabatic evolutions are visualized as trajectories of Bloch vectors on a Bloch sphere. We find the change in the…

Quantum Physics · Physics 2020-05-28 Sangchul Oh , Sabre Kais

It has previously been established that adiabatic quantum computation, operating based on a continuous Zeno effect due to dynamical phases between eigenstates, is able to realise an optimal Grover-like quantum speedup. In other words, is…

Quantum Physics · Physics 2024-11-20 Jesse Berwald , Nick Chancellor , Raouf Dridi

This article proposes a self-consistent methodology for determining the mechanical adiabatic work of Brownian particles trapped in optical tweezers. Rather than varying the trap frequency, the proposed protocol involves displacing the trap…

Statistical Mechanics · Physics 2026-05-07 Pedro J. Colmenares

Quantum computation by the adiabatic theorem requires a slowly varying Hamiltonian with respect to the spectral gap. We show that the Landau-Zener-St\"uckelberg oscillation phenomenon, that naturally occurs in quantum two level systems…

Quantum Physics · Physics 2019-10-23 Yosi Atia , Yonathan Oren , Nadav Katz

We investigated some variational methods to compute a wavefunction based on antisymmetric product of geminals (APG). The Waring decomposition on the APG wavefunction leads a finite sum of antisymmetrized geminal power (AGP) wavefunctions,…

Chemical Physics · Physics 2024-10-10 Airi Kawasaki , Naoki Nakatani

Topological quantum computing promises error-resistant quantum computation without active error correction. However, there is a worry that during the process of executing quantum gates by braiding anyons around each other, extra anyonic…

Quantum Physics · Physics 2015-08-05 Chris Cesare , Andrew J. Landahl , Dave Bacon , Steven T. Flammia , Alice Neels

Adiabatic Quantum Computing (AQC) is an attractive paradigm for solving hard integer polynomial optimization problems. Available hardware restricts the Hamiltonians to be of a structure that allows only pairwise interactions. This requires…

Quantum Physics · Physics 2018-10-04 Raouf Dridi , Hedayat Alghassi , Sridhar Tayur

Perturbed Hamming weight problems serve as examples of optimization instances for which the adiabatic algorithm provably out performs classical simulated annealing. In this work we study the efficiency of the adiabatic algorithm for solving…

Quantum Physics · Physics 2015-11-24 Linghang Kong , Elizabeth Crosson

Adiabatic quantum computing (AQC) started as an approach to solving optimization problems, and has evolved into an important universal alternative to the standard circuit model of quantum computing, with deep connections to both classical…

Quantum Physics · Physics 2018-02-05 Tameem Albash , Daniel A. Lidar

The quantum geometric potential is a gauge invariant carrying novel geometric features between any two energy levels or bands in quantum systems. In generic time-dependent systems it gives a vital physical modification for the instantaneous…

Quantum Physics · Physics 2018-01-03 Jianda Wu

The quantum adiabatic theorem, a cornerstone of quantum mechanics, asserts that a gapped quantum system remains in its instantaneous eigenstate during sufficiently slow evolution, provided no resonances occur. Here we challenge this…

Quantum Physics · Physics 2025-06-04 Oubo You , Zhaoqi Jiang , Jinhui Shi , Qing Dai , Chunying Guan , Shuang Zhang

Critical points of a function subject to a constraint can be either detected by restricting the function to the constraint or by looking for critical points of the Lagrange multiplier functional. Although the critical points of the two…

Differential Geometry · Mathematics 2022-10-25 Urs Frauenfelder , Joa Weber

In this paper we present a novel analysis of variance Gaussian process (ANOVA-GP) emulator for models governed by partial differential equations (PDEs) with high-dimensional random inputs. Gaussian process (GP) is a widely used surrogate…

Computational Engineering, Finance, and Science · Computer Science 2020-05-14 Chen Chen , Qifeng Liao