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We study the efficiency of a simple quantum dot heat engine at maximum power. In contrast to the quasi-statically operated Carnot engine whose efficiency reaches the theoretical maximum, recent research on more realistic engines operated in…

Statistical Mechanics · Physics 2018-12-05 Sang Hoon Lee , Jaegon Um , Hyunggyu Park

The optimized effective potential method is formulated as a convex minimization problem. This formulation does not require assumptions about $v$-representability nor functional differentiability. The formulation provides a natural framework…

Chemical Physics · Physics 2022-02-01 Erik I. Tellgren , Andre Laestadius , Markus Penz

Quantum embedding is an appealing route to fragment a large interacting quantum system into several smaller auxiliary `cluster' problems to exploit the locality of the correlated physics. In this work we critically review approaches to…

Strongly Correlated Electrons · Physics 2023-07-19 Max Nusspickel , Basil Ibrahim , George H. Booth

In quantum field theory it is generally known that the energy density may be negative at a given point in spacetime. A number of papers have shown that there is a restriction on this energy density which is called a quantum inequality (QI).…

Quantum Physics · Physics 2009-01-20 Dan Solomon

The power flow equations are non-linear multivariate equations that describe the relationship between power injections and bus voltages of electric power networks. Given a network topology, we are interested in finding network parameters…

Machine Learning · Computer Science 2026-03-09 Alperen Ergur , Julia Lindberg , Vinny Miller

Wavefunction correlations and density matrices for few or many particles are derived from the properties of semiclassical energy Green functions. Universal features of fixed energy (microcanonical) random wavefunction correlation functions…

Quantum Physics · Physics 2009-11-13 Eric J. Heller , Brian R. Landry

We consider the hypothesis that quantum mechanics is an approximation to another, cosmological theory, accurate only for the description of subsystems of the universe. Quantum theory is then to be derived from the cosmological theory by…

Quantum Physics · Physics 2007-05-23 Lee Smolin

Deep energy-based models are powerful, but pose challenges for learning and inference (Belanger and McCallum, 2016). Tu and Gimpel (2018) developed an efficient framework for energy-based models by training "inference networks" to…

Computation and Language · Computer Science 2020-10-13 Lifu Tu , Richard Yuanzhe Pang , Kevin Gimpel

Quantum variational algorithms have been one of major applications of quantum computing with current quantum devices. There are recent attempts to establish the foundation for these algorithms. A possible approach is to characterize the…

Quantum Physics · Physics 2023-12-06 Trong Duong

The kinetic energy (KE) kernel, which is defined as the second order functional derivative of the KE functional with respect to density, is the key ingredient to the construction of KE models for orbital free density functional theory…

Materials Science · Physics 2025-05-15 Zhandos A. Moldabekov , Xuecheng Shao , Michele Pavanello , Jan Vorberger , Tobias Dornheim

Our work combines aspects of three promising paradigms in machine learning, namely, attention mechanism, energy-based models, and associative memory. Attention is the power-house driving modern deep learning successes, but it lacks clear…

The self-energy functional theory (SFT) is generalized to describe the real-time dynamics of correlated lattice-fermion models far from thermal equilibrium. This is achieved by means of a reformulation of the original equilibrium theory in…

Strongly Correlated Electrons · Physics 2013-10-21 Felix Hofmann , Martin Eckstein , Enrico Arrigoni , Michael Potthoff

In this work we prove that the possibility of superactivation of quantum channel capacities is determined by the mathematical properties of the quantum relative entropy function. Before our work this fundamental and purely mathematical…

Quantum Physics · Physics 2012-06-26 Laszlo Gyongyosi , Sandor Imre

Variational quantum algorithms provide a direct, physics-based approach to protein structure prediction, but their accuracy is limited by the coarse resolution of the energy landscapes generated on current noisy devices. We propose a hybrid…

Emerging Technologies · Computer Science 2025-10-09 Yuqi Zhang , Yuxin Yang , Feixiong Chen , Cheng-Chang Lu , Nima Saeidi , Samuel L. Volchenboum , Junhan Zhao , Siwei Chen , Weiwen Jiang , Qiang Guan

Standard derivations of ``time-independent perturbation theory'' of quantum mechanics cannot be applied to the general case where potentials are energy dependent or where the inverse free Green function is a non-linear function of energy.…

High Energy Physics - Theory · Physics 2007-05-23 A. N. Kvinikhidze , B. Blankleider

We consider energy-constrained infinite-dimensional quantum channels from a given system (satisfying a certain condition) to any other systems. We show that dealing with basic capacities of these channels we may assume (accepting…

Quantum Physics · Physics 2021-09-28 M. E. Shirokov

Optimal Power Flow (OPF) is a core optimization problem in power system operation and planning, aiming to minimize generation costs while satisfying physical constraints such as power flow equations, generator limits, and voltage limits.…

Machine Learning · Computer Science 2025-12-02 Xuezhi Liu

The quest to develop a general framework for thermodynamics, suitable for the regime of strong coupling and correlations between subsystems of an autonomous quantum "universe," has entailed diverging definitions for basic quantities,…

Quantum Physics · Physics 2025-09-30 Luis Rodrigo Neves , Frederico Brito

The resource theory of quantum thermodynamics has emerged as a powerful tool for exploring the out-of-equilibrium dynamics of microscopic and highly correlated systems. Recently, it has been employed in photoisomerization, a mechanism…

Quantum Physics · Physics 2024-12-19 Mattheus Burkhard , Onur Pusuluk , Tristan Farrow

Time-dependent quantum mechanics provides an intuitive picture of particle propagation in external fields. Semiclassical methods link the classical trajectories of particles with their quantum mechanical propagation. Many analytical results…

Mesoscale and Nanoscale Physics · Physics 2008-03-07 Tobias Kramer , Eric J. Heller , Robert E. Parrott