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Luksan,

doi:10.1016/s0025-5610(97)00108-1

Cited by 7 publications

(3 citation statements)

References 0 publications

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“…depends on the ordering of generators in Eq. (12). We sort all possible generators [whose number is equal to the number of terms in the sum in the right-hand side of Eq.…”

Section: S14 Qcc Operator Rankingmentioning

confidence: 99%

“…No additional constraints a Implemented and posted online as a LGPL Fortran library by Ladislav Luksan. 12 The L-BFGS method itself is originated from Refs. 13 and 14.…”

Section: S15 Variational Quantum Eigensolver (Vqe)-style Energy Optim...mentioning

confidence: 99%

“…Quantum computers, which operate using quantum states of matter, have recently attracted major research interest as potential new tools for high-accuracy quantum chemistry simulations. [10][11][12][13] The largest quantum chemistry simulation to date on a quantum computer was limited to a Hartree-Fock simulation of H 12 and diazene using 12 logical qubits, 14 problems that are otherwise straightforward to simulate on a classical computer. It is not yet possible to perform a quantum chemistry simulation that is difficult (or impossible) to solve on a classical computer, using current noisy intermediate-scale quantum (NISQ) computers.…”

Section: Introductionmentioning

confidence: 99%

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Estimating Phosphorescent Emission Energies in Ir(III) Complexes using Large-Scale Quantum Computing Simulations

Genin,

Ryabinkin,

Paisley

et al. 2021

Preprint

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Quantum chemistry simulations that accurately predict the properties of materials are among the most highly anticipated applications of quantum computing. It is widely believed that simulations running on quantum computers will allow for higher accuracy, but there has not yet been a convincing demonstration that quantum methods are competitive with existing classical methods at scale. Here we apply the iterative qubit coupled cluster (iQCC) method on classical hardware to the calculation of the T 1 → S 0 transition energies in nine phosphorescent iridium complexes, to determine if quantum simulations have any advantage over traditional computing methods. Phosphorescent iridium complexes are integral to the widespread commercialization of organic lightemitting diode (OLED) technology, yet accurate computational prediction of their emission energies remains a challenge. Our simulations would require a gate-based quantum computer with a minimum of 72 fully-connected and error-corrected logical

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“…depends on the ordering of generators in Eq. (12). We sort all possible generators [whose number is equal to the number of terms in the sum in the right-hand side of Eq.…”

Section: S14 Qcc Operator Rankingmentioning

confidence: 99%

“…No additional constraints a Implemented and posted online as a LGPL Fortran library by Ladislav Luksan. 12 The L-BFGS method itself is originated from Refs. 13 and 14.…”

Section: S15 Variational Quantum Eigensolver (Vqe)-style Energy Optim...mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Estimating Phosphorescent Emission Energies in Ir(III) Complexes using Large-Scale Quantum Computing Simulations

Genin,

Ryabinkin,

Paisley

et al. 2021

Preprint

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Comparison of formulations and solution methods for image restoration problems

Kärkkäinen¹,

Majava²,

Mäkelä³

2001

Inverse Problems

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The purpose of this paper is twofold: First aim is to seek for a proper formulation for recovering both sharp edges and smooth surfaces from a given, noisy, image. The formulations proposed here can be di erentiable, but as our numerical experiments show, so close to a nonsmooth problem that ordinary optimization methods for smooth problems, like the conjugate gradient method, have di culties in convergence. Hence, another aim of this paper is to compare di erent numerical methods for solving the image restoration problems. Two methods of nonsmooth optimization are applied: a (rst order) proximal bundle method and a (second order) bundle-Newton method. Moreover, a generalization of the active-set methods that have earlier shown high e ciency for nonsmooth image restoration problems is proposed and analysed. Comparison of the methods as well as comparison of formulations are made through numerical experiments.

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A Robust Gradient Sampling Algorithm for Nonsmooth, Nonconvex Optimization

2005

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Let f be a continuous function on R n , and suppose f is continuously differentiable on an open dense subset. Such functions arise in many applications, and very often minimizers are points at which f is not differentiable. Of particular interest is the case where f is not convex, and perhaps not even locally Lipschitz, but whose gradient is easily computed where it is defined. We present a practical, robust algorithm to locally minimize such functions, based on gradient sampling. No subgradient information is required by the algorithm.When f is locally Lipschitz and has bounded level sets, and the sampling radius ǫ is fixed, we show that, with probability one, the algorithm generates a sequence with a cluster point that is Clarke ǫ-stationary. Furthermore, we show that if f has a unique Clarke stationary pointx, then the set of all cluster points generated by the algorithm converges tox as ǫ is reduced to zero.

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Untitled

Cited by 7 publications

References 0 publications

Estimating Phosphorescent Emission Energies in Ir(III) Complexes using Large-Scale Quantum Computing Simulations

Estimating Phosphorescent Emission Energies in Ir(III) Complexes using Large-Scale Quantum Computing Simulations

Comparison of formulations and solution methods for image restoration problems

A Robust Gradient Sampling Algorithm for Nonsmooth, Nonconvex Optimization

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