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We consider a composite open quantum system consisting of a fast subsystem coupled to a slow one. Using the time-scale separation, we develop an adiabatic elimination technique to derive at any order the reduced model describing the slow…

Quantum Physics · Physics 2017-07-11 Remi Azouit , Francesca Chittaro , Alain Sarlette , Pierre Rouchon

Adiabatic elimination is a perturbative model reduction technique based on timescale separation and often used to simplify the description of composite quantum systems. We here analyze a quantum experiment where the perturbative expansion…

Quantum Physics · Physics 2020-01-09 Alain Sarlette , Pierre Rouchon , Antoine Essig , Quentin Ficheux , Benjamin Huard

In this paper we continue our work on adiabatic time of time-inhomogeneous Markov chains first introduced in Kovchegov (2010) and Bradford and Kovchegov (2011). Our study is an analog to the well-known Quantum Adiabatic (QA) theorem which…

Probability · Mathematics 2015-03-20 Kyle Bradford , Yevgeniy Kovchegov , Thinh Nguyen

For multi-level time-dependent quantum systems one can construct superadiabatic representations in which the coupling between separated levels is exponentially small in the adiabatic limit. Based on results from [BeTe1] for special…

Mathematical Physics · Physics 2009-11-10 Volker Betz , Stefan Teufel

We present a study of the phase diagram of a random optimization problem in presence of quantum fluctuations. Our main result is the characterization of the nature of the phase transition, which we find to be a first-order quantum phase…

Disordered Systems and Neural Networks · Physics 2010-05-24 T. Jorg , F. Krzakala , G. Semerjian , F. Zamponi

Quantum protocols often require the generation of specific quantum states. We describe a quantum algorithm for generating any prescribed quantum state. For an important subclass of states, including pure symmetric states, this algorithm is…

Quantum Physics · Physics 2007-05-23 Phillip Kaye , Michele Mosca

We give a careful proof that a parallelized version of adiabatic quantum computation can efficiently simulate universal gate model quantum computation. The proof specifies an explicit parameter-dependent Hamiltonian $H({\lambda})$ that is…

Quantum Physics · Physics 2019-02-20 Ari Mizel

Many schemes to realize quantum state transfer in spin chains are not robust to random fluctuations in the spin-spin coupling strength. In efforts to achieve robust quantum state transfer, an adiabatic quantum population transfer scheme is…

Quantum Physics · Physics 2009-11-13 Vinitha Balachandran , Jiangbin Gong

We study the complexity of two closely related learning problems, one quantum and one classical. In the quantum setting, we consider agnostic tomography for the natural class of product mixed states. Given $N$ copies of an $n$-qubit state…

Quantum Physics · Physics 2026-04-30 Alvan Arulandu , Ilias Diakonikolas , Daniel Kane , Jerry Li

We show how to apply the quantum adiabatic algorithm directly to the quantum computation of molecular properties. We describe a procedure to map electronic structure Hamiltonians to 2-local qubit Hamiltonians with a small set of physically…

Quantum Physics · Physics 2015-02-20 Ryan Babbush , Peter J. Love , Alán Aspuru-Guzik

We develop an approach to machine learning and anomaly detection via quantum adiabatic evolution. In the training phase we identify an optimal set of weak classifiers, to form a single strong classifier. In the testing phase we…

Quantum Physics · Physics 2012-12-14 Kristen L. Pudenz , Daniel A. Lidar

A novel quantum pattern recognition scheme is presented, which combines the idea of a classic Hopfield neural network with adiabatic quantum computation. Both the input and the memorized patterns are represented by means of the problem…

Quantum Physics · Physics 2009-04-20 Rodion Neigovzen , Jorge L. Neves , Rudolf Sollacher , Steffen J. Glaser

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

Adiabatic elimination is a standard tool in quantum optics, which produces an effective Hamiltonian for a relevant subspace of states, incorporating effects of its coupling to states with much higher unperturbed energy. It shares with…

Quantum Physics · Physics 2015-09-30 Mikel Sanz , Enrique Solano , Íñigo L. Egusquiza

Polynomially-large ground-state energy gaps are rare in many-body quantum systems, but useful for adiabatic quantum computing. We show analytically that the gap is generically polynomially-large for quadratic fermionic Hamiltonians. We then…

Quantum Physics · Physics 2013-05-29 Michael J. O'Hara , Dianne P. O'Leary

A theoretical scheme is presented for the adiabatic generation of N-quNit singlet states with $N\geqslant3$, which may be more feasible than previous ones in a cavity. In this proposal, the system may be robust both parameter fluctuations…

Quantum Physics · Physics 2016-07-28 Li-Xiang Ye , Xiu Lin , Rong-Can Yang , Hong-Yu Liu

Exploring the ground state properties of many-body quantum systems conventionally involves adiabatic processes, alongside exact diagonalization, in the context of quantum annealing or adiabatic quantum computation. Shortcuts to adiabaticity…

Adiabatic time evolution of quantum systems is a widely used tool with applications ranging from state preparation through simplifications of computations and topological transformations to optimization and quantum computing. Adiabatic time…

Quantum Physics · Physics 2024-06-27 Hadi Yarloo , Hua-Chen Zhang , Anne E. B. Nielsen

The creation complexity of a quantum state is the minimum number of elementary gates required to create it from a basic initial state. The creation complexity of quantum states is closely related to the complexity of quantum circuits, which…

Quantum Physics · Physics 2022-02-11 Zixuan Hu , Sabre Kais

Adiabatic quantum computers can solve difficult optimization problems (e.g., the quadratic unconstrained binary optimization problem), and they seem well suited to train machine learning models. In this paper, we describe an adiabatic…

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