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We investigate the efficiency of Quantum Adiabatic Optimization when overcoming potential barriers to get from a local to a global minimum. Specifically we look at n qubit systems with symmetric cost functions f:{0, 1}^n->R where the ground…

Quantum Physics · Physics 2016-09-12 Lucas T. Brady , Wim van Dam

Non-equilibrium phase transitions exist in damped-driven open quantum systems, when the continuous tuning of an external parameter leads to a transition between two robust steady states. In second-order transitions this change is abrupt at…

Quantum Physics · Physics 2017-02-02 J. M. Fink , A. Dombi , A. Vukics , A. Wallraff , P. Domokos

Quantum annealing is a continuous-time heuristic quantum algorithm for solving or approximately solving classical optimization problems. The algorithm uses a schedule to interpolate between a driver Hamiltonian with an easy-to-prepare…

Quantum fluctuations driven by non-stoquastic Hamiltonians have been conjectured to be an important and perhaps essential missing ingredient for achieving a quantum advantage with adiabatic optimization. We introduce a transformation that…

Quantum Physics · Physics 2020-09-30 Elizabeth Crosson , Tameem Albash , Itay Hen , A. P. Young

Big Data is characterized by Volume, Velocity, Veracity and Complexity. The interaction between this huge data is complex with an associated free will having dynamic and non linear nature. We reduced big data based on its characteristics,…

Other Computer Science · Computer Science 2018-05-30 Sahil Imtiyaz

In one-dimension, quantum fluctuations prevent the appearance of long-range order in a supersolid, and only quasi long-range order can survive. We derive this quantum critical behavior and study its influence on the superfluid response and…

Quantum Gases · Physics 2023-08-11 Chris Bühler , Tobias Ilg , Hans Peter Büchler

Domain wall networks are two-dimensional topological defects generally predicted in many beyond standard model physics. In this Letter, we propose to solve the domain wall problem with the first-order phase transition. We numerically study…

High Energy Physics - Phenomenology · Physics 2023-04-12 Yang Li , Ligong Bian , Yongtao Jia

We develop several algorithms for performing quantum phase estimation based on basic measurements and classical post-processing. We present a pedagogical review of quantum phase estimation and simulate the algorithm to numerically determine…

Quantum Physics · Physics 2013-07-30 Krysta M. Svore , Matthew B. Hastings , Michael Freedman

We explore the relationship between two figures of merit for an adiabatic quantum computation process: the success probability $P$ and the minimum gap $\Delta_{min}$ between the ground and first excited states, investigating to what extent…

Quantum Physics · Physics 2015-05-28 M. Cullimore , M. J. Everitt , M. A. Ormerod , J. H. Samson , R. D. Wilson , A. M. Zagoskin

We present an algorithm to analyze numerically the bounce solution of first-order phase transitions. Our approach is well suited to treat phase transitions with several fields. The algorithm consists of two parts. In the first part the…

High Energy Physics - Phenomenology · Physics 2009-11-11 Thomas Konstandin , Stephan J. Huber

Gate-based quantum computers can in principle simulate the adiabatic dynamics of a large class of Hamiltonians. Here we consider the cyclic adiabatic evolution of a parameter in the Hamiltonian. We propose a quantum algorithm to estimate…

Quantum Physics · Physics 2020-02-19 Bruno Murta , G. Catarina , J. Fernandez-Rossier

We study temporal behavior of a quantum system under a slow external perturbation, which drives the system across a second order quantum phase transition. It is shown that despite the conventional adiabaticity conditions are always violated…

Statistical Mechanics · Physics 2007-05-23 Anatoli Polkovnikov

Grover's algorithm is one of the most important quantum algorithms, which performs the task of searching an unsorted database without a priori probability. Recently the adiabatic evolution has been used to design and reproduce quantum…

Quantum Physics · Physics 2007-05-23 Zhaohui Wei , Mingsheng Ying

The adiabatic theorem has been recently used to design quantum algorithms of a new kind, where the quantum computer evolves slowly enough so that it remains near its instantaneous ground state which tends to the solution [Farhi et al.,…

Quantum Physics · Physics 2009-11-07 Jeremie Roland , Nicolas J. Cerf

Preparing the ground state of a Hamiltonian is a problem of great significance in physics with deep implications in the field of combinatorial optimization. The adiabatic algorithm is known to return the ground state for sufficiently long…

Quantum Physics · Physics 2023-08-02 Benjamin F. Schiffer , Jordi Tura , J. Ignacio Cirac

A novel class of hybrid quantum-classical algorithms based on the variational approach have recently emerged from separate proposals addressing, for example, quantum chemistry and combinatorial problems. These algorithms provide an…

Quantum Physics · Physics 2017-01-09 Gian Giacomo Guerreschi , Mikhail Smelyanskiy

We predict the existence of novel first-order phase transitions in a general class of multi-qubit-cavity systems. Apart from atomic systems, the associated super-radiant phase transition should be observable in a variety of solid-state…

Quantum Physics · Physics 2007-05-23 Chiu Fan Lee , Neil F. Johnson

Models for quantum computation with circuit connections subject to the quantum superposition principle have been recently proposed. There, a control quantum system can coherently determine the order in which a target quantum system…

We study the quantum phase transition of the one-dimensional phase model in the presence of dissipative frustration, provided by an interaction of the system with the environment through two non-commuting operators. Such a model can be…

Statistical Mechanics · Physics 2018-04-25 Dominik Maile , Sabine Andergassen , Wolfgang Belzig , Gianluca Rastelli

Gradient-based (a.k.a. `first order') optimization algorithms are routinely used to solve large scale non-convex problems. Yet, it is generally hard to predict their effectiveness. In order to gain insight into this question, we revisit the…

Probability · Mathematics 2024-12-10 Andrea Montanari , Eliran Subag