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A controlled quantum system possesses a search landscape defined by the target physical objective as a function of the controls. This paper focuses on the landscape for the transition probability Pif between the states of a finite level…

Chemical Physics · Physics 2015-05-27 Vincent Beltrani , Jason Dominy , Tak-San Ho , Herschel Rabitz

Free energy landscapes encode the kinetics, intermediates, and transition states that govern molecular processes and are thus a key target of single biomolecule research. Typical approaches to deriving optimal, error-minimizing,…

Biological Physics · Physics 2025-11-25 Oliver Cheng , Zosia Adamska , Michael P. Brenner , Megan C. Engel

Harnessing the local topography of the loss landscape is a central challenge in advanced optimization tasks. By accounting for the effect of potential parameter changes, we can alter the model more efficiently. Contrary to standard…

Machine Learning · Computer Science 2024-11-27 Jed A. Duersch , Tommie A. Catanach , Alexander Safonov , Jeremy Wendt

The ability to control quantum systems using shaped fields as well as to infer the states of such controlled systems from measurement data are key tasks in the design and operation of quantum devices. Here we associate the success of…

Quantum Physics · Physics 2020-10-14 Christian Arenz , Herschel Rabitz

Optimal control of molecular dynamics is commonly expressed from a quantum mechanical perspective. However, in most contexts the preponderance of molecular dynamics studies utilize classical mechanical models. This paper treats laser-driven…

Chemical Physics · Physics 2015-03-19 Carlee Joe-Wong , Tak-San Ho , Ruixing Long , Herschel Rabitz , Rebing Wu

This review investigates the landscapes of prevalent hybrid quantum-classical optimization algorithms in many rapidly developing quantum technologies, where the objective function is either computed by a natural quantum system or a quantum…

Quantum Physics · Physics 2022-04-12 Xiaozhen Ge , Re-Bing Wu , Herschel Rabitz

The control landscape for various canonical quantum control problems is considered. For the class of pure-state transfer problems, analysis of the fidelity as a functional over the unitary group reveals no suboptimal attractive critical…

Quantum Physics · Physics 2014-03-04 Pierre de Fouquieres , Sophie G. Schirmer

We describe algorithms, and experimental strategies, for the Pareto optimal control problem of simultaneously driving an arbitrary number of quantum observable expectation values to their respective extrema. Conventional quantum optimal…

Quantum Physics · Physics 2009-11-13 Raj Chakrabarti , Rebing Wu , Herschel Rabitz

The ability to control quantum systems is necessary for many applications of quantum technologies ranging from gate generation in quantum computation to NMR and laser control of chemical reactions. In many practical situations, the…

Quantum Physics · Physics 2024-03-21 Alexander Pechen

We show that the second order traps in the control landscape for a three-level $\Lambda$-system found in our previous work {\it Phys. Rev. Lett.} {\bf 106}, 120402 (2011) are not local maxima: there exist directions in the space of controls…

Quantum Physics · Physics 2015-08-19 Alexander Pechen , David J. Tannor

We present a gradient-based optimal-control technique for open quantum systems that utilizes quantum trajectories to simulate the quantum dynamics during optimization. Using trajectories allows for optimizing open systems with less…

Quantum Physics · Physics 2019-06-03 Mohamed Abdelhafez , David I. Schuster , Jens Koch

In quantum optimal control theory the success of an optimization algorithm is highly influenced by how the figure of merit to be optimized behaves as a function of the control field, i.e. by the control landscape. Constraints on the control…

Quantum Physics · Physics 2016-04-07 Niklas Rach , Matthias M. Müller , Tommaso Calarco , Simone Montangero

Parameter control and dynamic algorithm configuration study how to dynamically choose suitable configurations of a parametrized algorithm during the optimization process. Despite being an intensively researched topic in evolutionary…

Neural and Evolutionary Computing · Computer Science 2025-07-14 Gianluca Covini , Denis Antipov , Carola Doerr

A proof that almost all quantum systems have trap free (that is, free from local optima) landscapes is presented for a large and physically general class of quantum system. This result offers an explanation for why gradient methods succeed…

Quantum Physics · Physics 2016-11-14 Benjamin Russell , Herschel Rabitz , Rebing Wu

Many quantum control problems are formulated as a search for an optimal field that maximizes a physical objective. This search is performed over a landscape defined as the objective as a function of the control field. A recent Letter [A. N.…

Quantum Physics · Physics 2012-05-09 Herschel Rabitz , Tak-San Ho , Ruixing Long , Rebing Wu , Constantin Brif

Probabilistic control design is founded on the principle that a rational agent attempts to match modelled with an arbitrary desired closed-loop system trajectory density. The framework was originally proposed as a tractable alternative to…

Machine Learning · Computer Science 2023-11-16 Tom Lefebvre

Optimization is ubiquitous in quantum information science and technology, however, the corresponding optimization landscape can encounter false traps, i.e., local but not global optima, likely to prevent used optimizers from finding optimal…

Quantum Physics · Physics 2026-03-06 Xiaozhen Ge , Shuming Cheng , Guofeng Zhang , Re-Bing Wu

Understanding the quantum control landscape (QCL) is important for designing effective quantum control strategies. In this study, we analyze the QCL for a single two-level quantum system (qubit) using various control strategies. We employ…

Quantum Physics · Physics 2025-05-06 Haftu W. Fentaw , Steve Campbell , Simon Caton

Kraus maps (completely positive trace preserving maps) arise classically in quantum information, as they describe the evolution of noncommutative probability measures. We introduce tropical analogues of Kraus maps, obtained by replacing the…

Optimization and Control · Mathematics 2019-12-30 Stéphane Gaubert , Nikolas Stott

High-dimensional design spaces underpin a wide range of physics-based modeling and computational design tasks in science and engineering. These problems are commonly formulated as constrained black-box searches over rugged objective…

Machine Learning · Computer Science 2026-01-13 Suvo Banik , Troy D. Loeffler , Henry Chan , Sukriti Manna , Orcun Yildiz , Tom Peterka , Subramanian Sankaranarayanan