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The operation of near-term quantum technologies requires the development of feasible, implementable, and robust strategies of controlling complex many body systems. To this end, a variety of techniques, so-called "shortcuts to adiabaticty",…

Quantum Physics · Physics 2022-10-21 Artur Soriani , Eduardo Miranda , Sebastian Deffner , Marcus V. S. Bonança

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

A discretized version of the adiabatic theorem is described with the help of a rule relating a Hermitian operator to its expectation value and variance. The simple initial operator X with known ground state is transformed in a series of N…

Quantum Physics · Physics 2018-02-20 Bernhard K. Meister

Agentic artificial intelligence (AI) -- multi-agent systems that combine large language models with external tools and autonomous planning -- are rapidly transitioning from research laboratories into high-stakes domains. Our earlier "Basic"…

Artificial Intelligence · Computer Science 2025-09-16 Manish Shukla

The Cahn-Hilliard equation is one of the most common models to describe phase separation processes in mixtures of two materials. For a better description of short-range interactions between the material and the boundary, various dynamic…

Numerical Analysis · Mathematics 2023-01-23 Stefan Metzger

This paper considers the problem of minimizing the sum of a smooth function and the Schatten-$p$ norm of the matrix. Our contribution involves proposing accelerated iteratively reweighted nuclear norm methods designed for solving the…

Optimization and Control · Mathematics 2024-06-27 Hao Wang , Ye Wang , Xiangyu Yang

We present a simple and easy to implement method for the numerical solution of a rather general class of Hamilton-Jacobi-Bellman (HJB) equations. In many cases, the considered problems have only a viscosity solution, to which, fortunately,…

Computational Finance · Quantitative Finance 2011-02-17 Jan Hendrik Witte , Christoph Reisinger

Adiabatic techniques are known to allow for engineering quantum states with high fidelity. This requirement is currently of large interest, as applications in quantum information require the preparation and manipulation of quantum states…

Recent advances in both theoretical and computational methods have enabled large-scale, precision calculations of the properties of atomic nuclei. With the growing complexity of modern nuclear theory, however, also comes the need for novel…

Nuclear Theory · Physics 2024-11-26 R. Y. Cheng , K. Godbey , Y. B. Niu , Y. G. Ma , W. B. He , S. M. Wang

A computation in adiabatic quantum computing is implemented by traversing a path of nondegenerate eigenstates of a continuous family of Hamiltonians. We introduce a method that traverses a discretized form of the path: At each step we apply…

Quantum Physics · Physics 2009-08-14 S. Boixo , E. Knill , R. D. Somma

A shortcut-to-adiabaticity is compared with a numerically optimized protocol for implementing a high-fidelity quantum gate on Rydberg atoms. The counterdiabatic method offers an analytical framework for accelerating high-fidelity gates by…

Quantum Physics · Physics 2025-11-13 Luis S. Yagüe Bosch , Sandro Wimberger

Shortcuts to adiabaticity is a general method for speeding up adiabatic quantum protocols, and has many potential applications in quantum information processing. Unfortunately, analytically constructing shortcuts to adiabaticity for systems…

Quantum Physics · Physics 2021-07-13 F. Setiawan , Peter Groszkowski , Hugo Ribeiro , Aashish A. Clerk

An artificial intelligence-augmented Streamline Upwind/Petrov-Galerkin finite element scheme (AiStab-FEM) is proposed for solving singularly perturbed partial differential equations. In particular, an artificial neural network framework is…

Analysis of PDEs · Mathematics 2022-11-28 Sangeeta Yadav , Sashikumaar Ganesan

We present straightforward proofs of estimates used in the adiabatic approximation. The gap dependence is analyzed explicitly. We apply the result to interpolating Hamiltonians of interest in quantum computing.

Quantum Physics · Physics 2007-11-08 Sabine Jansen , Mary-Beth Ruskai , Ruedi Seiler

Alexandrov proved that any simplicial complex homeomorphic to a sphere with strictly non-negative Gaussian curvature at each vertex can be isometrically embedded uniquely in $\mathbb{R}^3$ as a convex polyhedron. Due to the nonconstructive…

General Relativity and Quantum Cosmology · Physics 2017-10-30 Shannon Ray , Warner A. Miller , Paul M. Alsing , Shing-Tung Yau

We present numerical calculations, and simulations performed on a Rydberg atom quantum simulator, of the adiabatic evolution of many-body quantum systems around a quantum phase transition. We demonstrate that the end-to-end transfer error,…

Quantum Physics · Physics 2025-12-22 Emil T. M. Pedersen , Freek Witteveen , Klaus Mølmer , Matthias Christandl

An algorithm capable of finding a likely global optimum (minimum) and a set of sub-optimal points for arbitrary generic functions of several variables is presented. The algorithm is designed to deal even with functions of complex behavior,…

Optimization and Control · Mathematics 2017-08-23 Glauco Masotti

A general time-dependent quantum system can be driven fast from its initial ground state to its final ground state without generating transitions by adding a steering term to the Hamiltonian. We show how this technique can be modified to…

Quantum Physics · Physics 2018-12-11 A. Barış Özgüler , Robert Joynt , Maxim G. Vavilov

We consider non-adiabatic transitions in multiple dimensions, which occur when the Born-Oppenheimer approximation breaks down. We present a general, multi-dimensional algorithm which can be used to accurately and efficiently compute the…

Chemical Physics · Physics 2018-04-16 V. Betz , B. D. Goddard , T. Hurst

This paper proposes a stochastic variant of a classic algorithm---the cubic-regularized Newton method [Nesterov and Polyak 2006]. The proposed algorithm efficiently escapes saddle points and finds approximate local minima for general…

Machine Learning · Computer Science 2017-12-07 Nilesh Tripuraneni , Mitchell Stern , Chi Jin , Jeffrey Regier , Michael I. Jordan
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