Quantum Langevin equation

Oliveira, Mário J. de

doi:10.1088/1742-5468/ab6de2

Cited by 5 publications

(4 citation statements)

References 24 publications

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“…Therefore, the introduction of stochastic differentials [32] converts (15) into a Langevin equation [33][34][35][36]…”

Section: Equations Of Motion With Thermal Noisementioning

confidence: 99%

“…A mathematically rigorous derivation of Langevin molecular dynamics, for the case of a composite quantum system that is weakly coupled to a heat bath of many fast particles, has been recently developed by Hoel and Szepessy [54]. Thus, we maintain the view that the system of equations ( 27) and ( 28) represents a quantum Langevin model [34][35][36] of protein α-helix immersed in water-based solvent at physiological temperature.…”

Section: Three-spine Model With Lateral Couplingmentioning

confidence: 99%

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Thermal stability of solitons in protein $α$-helices

Georgiev,

Glazebrook

2022

Preprint

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Protein α-helices provide an ordered biological environment that is conducive to soliton-assisted energy transport. The nonlinear interaction between amide I excitons and phonon deformations induced in the hydrogen-bonded lattice of peptide groups leads to self-trapping of the amide I energy, thereby creating a localized quasiparticle (soliton) that persists at zero temperature. The presence of thermal noise, however, could destabilize the protein soliton and dissipate its energy within a finite lifetime. In this work, we have computationally solved the system of stochastic differential equations that govern the quantum dynamics of protein solitons at physiological temperature, T = 310 K, for either a single isolated α-helix spine of hydrogen bonded peptide groups or the full protein α-helix comprised of three parallel α-helix spines. The simulated stochastic dynamics revealed that although the thermal noise is detrimental for the single isolated α-helix spine, the cooperative action of three amide I exciton quanta in the full protein α-helix ensures soliton lifetime of over 30 ps, during which the amide I energy could be transported along the entire extent of an 18-nm-long α-helix. Thus, macromolecular protein complexes, which are built up of protein α-helices could harness soliton-assisted energy transport at physiological temperature. Because the hydrolysis of a single adenosine triphosphate molecule is able to initiate three amide I exciton quanta, it is feasible that multiquantal protein solitons subserve a variety of specialized physiological functions in living systems.

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“…Therefore, the introduction of stochastic differentials [32] converts (15) into a Langevin equation [33][34][35][36]…”

Section: Equations Of Motion With Thermal Noisementioning

confidence: 99%

Section: Three-spine Model With Lateral Couplingmentioning

confidence: 99%

Thermal stability of solitons in protein $α$-helices

Georgiev,

Glazebrook

2022

Preprint

View full text Add to dashboard Cite

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“…Noise, loss, and other dissipative processes as well as out-of-equilibrium processes will have to be considered, albeit at the cost of significant added complexity and intractability. The sensor’s dynamics may then be described via a master equation [ 28 , 29 ]. Once a measurement has occurred, the measurement data can be processed using the QPU.…”

Section: Introductionmentioning

confidence: 99%

The Concept of a Quantum Edge Simulator: Edge Computing and Sensing in the Quantum Era

Passian

Buchs

Seck

et al. 2022

Sensors

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Sensors, enabling observations across vast spatial, spectral, and temporal scales, are major data generators for information technology (IT). Processing, storing, and communicating this ever-growing amount of data pose challenges for the current IT infrastructure. Edge computing—an emerging paradigm to overcome the shortcomings of cloud-based computing—could address these challenges. Furthermore, emerging technologies such as quantum computing, quantum sensing, and quantum communications have the potential to fill the performance gaps left by their classical counterparts. Here, we present the concept of an edge quantum computing (EQC) simulator—a platform for designing the next generation of edge computing applications. An EQC simulator is envisioned to integrate elements from both quantum technologies and edge computing to allow studies of quantum edge applications. The presented concept is motivated by the increasing demand for more sensitive and precise sensors that can operate faster at lower power consumption, generating both larger and denser datasets. These demands may be fulfilled with edge quantum sensor networks. Envisioning the EQC era, we present our view on how such a scenario may be amenable to quantification and design. Given the cost and complexity of quantum systems, constructing physical prototypes to explore design and optimization spaces is not sustainable, necessitating EQC infrastructure and component simulators to aid in co-design. We discuss what such a simulator may entail and possible use cases that invoke quantum computing at the edge integrated with new sensor infrastructures.

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“…These models have the appealing feature that the many-body dynamics for arbitrary spatial dimension d can be reduced to the solution of a single integro-differential equation, from which all observables of physical interest can be determined. We shall describe the non-equilibrium dynamics of these models by a quantum Langevin equation, which is known to guarantee physically desirable properties for a relaxation process, including the validity of the quantum fluctuation-dissipation theorem [40][41][42][43][44][45][46]53]. Since the emerging equations are linear and we focus on observables which are at most quadratic in the fluctuating fields, this scheme is self-consistent and more advanced field-theoretical treatments, that are usually needed in order to describe interacting models [9,12], are not required.…”

Section: Introductionmentioning

confidence: 99%

Non-equilibrium dynamics of the open quantum O(n)-model with non-Markovian noise: exact results

Wald¹,

Henkel²,

Gambassi³

2021

J. Stat. Mech.

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The collective and purely relaxational dynamics of quantum manybody systems after a quench at temperature T = 0, from a disordered state to various phases is studied through the exact solution of the quantum Langevin equation of the spherical and the O(n)-model in the limit n → ∞. The stationary state of the quantum dynamics is shown to be a non-equilibrium state. The quantum spherical and the quantum O(n)-model for n → ∞ are in the same dynamical universality class. The long-time behaviour of single-time and twotime correlation and response functions is analysed and the universal exponents which characterise quantum coarsening and quantum ageing are derived. The importance of the non-Markovian long-time memory of the quantum noise is elucidated by comparing it with an effective Markovian noise having the same scaling behaviour and with the case of non-equilibrium classical dynamics.

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Quantum Langevin equation

Cited by 5 publications

References 24 publications

Thermal stability of solitons in protein $α$-helices

Thermal stability of solitons in protein $α$-helices

The Concept of a Quantum Edge Simulator: Edge Computing and Sensing in the Quantum Era

Non-equilibrium dynamics of the open quantum O(n)-model with non-Markovian noise: exact results

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