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Simulated annealing is a popular method for approaching the solution of a global optimization problem. Existing results on its performance apply to discrete combinatorial optimization where the optimization variables can assume only a…

Machine Learning · Statistics 2007-09-20 A. Lecchini-Visintini , J. Lygeros , J. Maciejowski

In quantum physics, multiparticle systems are described by quantum states acting on tensor products of Hilbert spaces. This product structure leads to the distinction between product states and entangled states; moreover, one can quantify…

Quantum Physics · Physics 2026-03-06 Lisa T. Weinbrenner , Albert Rico , Kenneth Goodenough , Xiao-Dong Yu , Otfried Gühne

Quantum annealing is a computational paradigm in which optimisation problems are mapped onto the energy landscape of an interacting quantum system and explored through its dynamical evolution. By continuously transforming a simple initial…

Quantum Physics · Physics 2026-05-11 Steven Abel , Andrei Constantin , Luca A. Nutricati

Compared with time independent Hamiltonians, the dynamics of generic quantum Hamiltonians $H(t)$ are complicated by the presence of time ordering in the evolution operator. In the context of digital quantum simulation, this difficulty…

Quantum Physics · Physics 2024-04-08 Jacob Watkins , Nathan Wiebe , Alessandro Roggero , Dean Lee

The possibility of using similarity transformations to alter dynamical entanglement growth in matrix-product-state simulations of quantum systems is explored. By appropriately choosing the similarity transformation, the entanglement growth…

Quantum Physics · Physics 2023-07-14 Hanggai Nuomin , Feng-feng Song , Peng Zhang , David N. Beratan

The work that we present in this thesis tries to be at the crossover of quantum information science, quantum many-body physics, and quantum field theory. We use tools from these three fields to analyze problems that arise in the…

Quantum Physics · Physics 2009-09-29 Roman Orus

Magnetic properties of the transverse-field Ising model on curved (hyperbolic) lattices are studied by a tensor product variational formulation that we have generalized for this purpose. First, we identify the quantum phase transition for…

Statistical Mechanics · Physics 2023-06-27 Andrej Gendiar

Hamiltonian simulation is a promising application for quantum computers to achieve a quantum advantage. We present classical algorithms based on tensor network methods to optimize quantum circuits for this task. We show that, compared to…

Quantum Physics · Physics 2023-06-05 Conor Mc Keever , Michael Lubasch

Entanglement sharing among sites of one-particle states is considered using the measure of concurrence. These are the simplest in an hierarchy of number-specific states of many qubits and corresponds to ``one-magnon'' states of spins. We…

Quantum Physics · Physics 2009-11-07 Arul Lakshminarayan , V. Subrahmanyam

The concept of space-evolution (or space-time duality) has emerged as a promising approach for studying quantum dynamics. The basic idea involves exchanging the roles of space and time, evolving the system using a space transfer matrix…

Quantum Physics · Physics 2023-11-03 Alessandro Foligno , Tianci Zhou , Bruno Bertini

We propose a novel family of entanglement measures for time-separated subsystems. Our definitions are applicable to any quantum system, continuous or discrete. To illustrate their utility, we derive upper and lower bounds on time-separated…

Quantum Physics · Physics 2025-12-16 Alexey Milekhin , Zofia Adamska , John Preskill

The optimal use of quantum and classical computational techniques together is important to address problems that cannot be easily solved by quantum computations alone. This is the case of the ground state problem for quantum many-body…

Quantum Physics · Physics 2022-05-03 Patrick Huembeli , Giuseppe Carleo , Antonio Mezzacapo

The accurate first-principles description of strongly-correlated materials is an important and challenging problem in condensed matter physics. Ab initio downfolding has emerged as a way of deriving compressed many-body Hamiltonians that…

Quantum Physics · Physics 2025-04-17 Antonios M. Alvertis , Abid Khan , Norm M. Tubman

Achieving chemical accuracy for strongly correlated molecules is a defining milestone for first-generation, fault-tolerant quantum computers, yet the factorial growth of three, four, and six-index tensor contractions in coupled-cluster…

Geometric numerical integration has recently been exploited to design symplectic accelerated optimization algorithms by simulating the Lagrangian and Hamiltonian systems from the variational framework introduced in Wibisono et al. In this…

Optimization and Control · Mathematics 2023-05-19 Valentin Duruisseaux , Melvin Leok

We present efficient quantum algorithms for simulating time-dependent Hamiltonian evolution of general input states using an oracular model of a quantum computer. Our algorithms use either constant or adaptively chosen time steps and are…

Quantum Physics · Physics 2011-11-03 Nathan Wiebe , Dominic W. Berry , Peter Hoyer , Barry C. Sanders

Recently developed quantum algorithms suggest that quantum computers can solve certain problems and perform certain tasks more efficiently than conventional computers. Among other reasons, this is due to the possibility of creating…

Quantum Physics · Physics 2007-05-23 Rolando D. Somma

Characterizing the entanglement of matrix degrees of freedom is essential for understanding the holographic emergence of spacetime. The Quantum Hall Matrix Model is a gauged $U(N)$ matrix quantum mechanics with two matrices whose ground…

High Energy Physics - Theory · Physics 2022-06-08 Alexander Frenkel , Sean A. Hartnoll

Recently, quantum entanglement has been presented as a cohomological obstruction to reconstructing a global quantum state from locally compatible information, where sheafification provides a functor that is forgetful with regards to…

Quantum Physics · Physics 2026-01-21 Kazuki Ikeda , Steven Rayan

Combinatorial optimization problems are ubiquitous in industrial applications. However, finding optimal or close-to-optimal solutions can often be extremely hard. Because some of these problems can be mapped to the ground-state search of…

Quantum Physics · Physics 2025-09-04 Junpeng Hou , Amin Barzegar , Helmut G. Katzgraber
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