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Existing quantum algorithms for quantum chemistry work well near the equilibrium geometry of molecules, but the results can become unstable when the chemical bonds are broken at large atomic distances. For any adiabatic approach, this…

Chemical Physics · Physics 2023-05-09 Hongye Yu , Deyu Lu , Qin Wu , Tzu-Chieh Wei

The difficulty in producing precisely timed and controlled quantum gates is a significant source of error in many physical implementations of quantum computers. Here we introduce a simple universal primitive, adiabatic gate teleportation,…

Quantum Physics · Physics 2010-04-29 Dave Bacon , Steven T. Flammia

Time-dependent density functional theory continues to draw a large number of users in a wide range of fields exploring myriad applications involving electronic spectra and dynamics. Although in principle exact, the predictivity of the…

Chemical Physics · Physics 2023-08-14 Lionel Lacombe , Neepa T. Maitra

Matrix product states provide a natural entanglement basis to represent a quantum register and operate quantum gates on it. This scheme can be materialized to simulate a quantum adiabatic algorithm solving hard instances of a NP-Complete…

Quantum Physics · Physics 2009-11-11 M. C. Banuls , R. Orus , J. I. Latorre , A. Perez , P. Ruiz-Femenia

We apply adiabatic theorems developed for quantum mechanics to stochastic annealing processes described by the classical master equation with a time-dependent generator. When the instantaneous stationary state is unique and the minimum…

Statistical Mechanics · Physics 2024-03-21 Kazutaka Takahashi

Adiabatic quantum computation has recently attracted attention in the physics and computer science communities, but its computational power was unknown. We describe an efficient adiabatic simulation of any given quantum algorithm, which…

Quantum Physics · Physics 2007-11-22 Dorit Aharonov , Wim van Dam , Julia Kempe , Zeph Landau , Seth Lloyd , Oded Regev

Quantum annealing is a promising algorithm for solving combinatorial optimization problems. It searches for the ground state of the Ising model, which corresponds to the optimal solution of a given combinatorial optimization problem. The…

Statistical Mechanics · Physics 2026-02-25 Tomohiro Hattori , Shu Tanaka

Current approaches in approximate inference for Bayesian neural networks minimise the Kullback-Leibler divergence to approximate the true posterior over the weights. However, this approximation is without knowledge of the final application,…

Machine Learning · Statistics 2018-05-11 Adam D. Cobb , Stephen J. Roberts , Yarin Gal

In this paper we consider the problem of obtaining sharp bounds for the performance of temporal difference (TD) methods with linear function approximation for policy evaluation in discounted Markov decision processes. We show that a simple…

Machine Learning · Statistics 2024-06-18 Sergey Samsonov , Daniil Tiapkin , Alexey Naumov , Eric Moulines

The analytical expression for shortcuts to adiabaticity for any switching time and any thermally isolated system performing a finite-time and weakly driven process is presented. It is based on the analytical solution of the optimal…

Quantum Physics · Physics 2025-09-26 Pierre Nazé

The application of adiabatic protocols in quantum technologies is severely limited by environmental sources of noise and decoherence. Shortcuts to adiabaticity by counterdiabatic driving constitute a powerful alternative that speed up…

Quantum Physics · Physics 2019-07-12 Shuoming An , Dingshun Lv , Adolfo del Campo , Kihwan Kim

We present two quantum algorithms based on evolution randomization, a simple variant of adiabatic quantum computing, to prepare a quantum state $\vert x \rangle$ that is proportional to the solution of the system of linear equations $A…

Quantum Physics · Physics 2019-02-20 Yigit Subasi , Rolando D. Somma , Davide Orsucci

We aim to give more insights on adiabatic evolution concerning the occurrence of anti-crossings and their link to the spectral minimum gap $\Delta_{min}$. We study in detail adiabatic quantum computation applied to a specific combinatorial…

Quantum Physics · Physics 2022-04-13 Arthur Braida , Simon Martiel

We consider quantum dynamics for which the strict adiabatic approximation fails but which do not escape too far from the adiabatic limit. To treat these systems we introduce a generalisation of the time dependent wave operator theory which…

Quantum Physics · Physics 2015-06-16 David Viennot

Quantum adiabatic algorithm is of vital importance in quantum computation field. It offers us an alternative approach to manipulate the system instead of quantum gate model. Recently, an interesting work arXiv:1805.10549 indicated that we…

Quantum Physics · Physics 2019-01-23 Jingwei Wen , Xiangyu Kong , Shijie Wei , Bixue Wang , Tao Xin , Guilu Long

The quantum adiabatic unstructured search algorithm is one of only a handful of quantum adiabatic optimization algorithms to exhibit provable speedups over their classical counterparts. With no fault tolerance theorems to guarantee the…

Quantum Physics · Physics 2019-11-14 Mikhail Slutskii , Tameem Albash , Lev Barash , Itay Hen

One of the difficulties in adiabatic quantum computation is the limit on the computation time. Here we propose two schemes to speed-up the adiabatic evolution. To apply this controlled adiabatic evolution to adiabatic quantum computation,…

Quantum Physics · Physics 2015-05-14 W. Wang , S. C. Hou , X. X. Yi

We investigate bounds on speed, non-adiabatic entropy production and trade-off relation between them for classical stochastic processes with time-independent transition rates. Our results show that the time required to evolve from an…

Statistical Mechanics · Physics 2023-11-10 Jie Gu

This work develops Monte Carlo Euler adaptive time stepping methods for the weak approximation problem of jump diffusion driven stochastic differential equations. The main result is the derivation of a new expansion for the omputational…

Numerical Analysis · Mathematics 2007-05-23 E. Mordecki , A. Szepessy , R. Tempone , G. E. Zouraris

Adiabatic quantum optimization offers a new method for solving hard optimization problems. In this paper we calculate median adiabatic times (in seconds) determined by the minimum gap during the adiabatic quantum optimization for an NP-hard…

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