Developments in ultrafast-spectroscopy techniques have revealed notably long-lived quantum coherence between electronic states in Fenna–Matthews–Olson complex bacteriochlorophylls, a group of molecules setting a nanoscale structure responsible of the coherent energy transfer in the photosynthetic process of green sulfur bacteria. Despite the experimental advances, such a task should normally be complemented with physical computer simulations to understand its complexity. Several methods have been explored to model this quantum phenomenon, mainly using the quantum open systems theory as a first approach. The traditional methods used in this approach do not take into account the memory effects of the surroundings, which is commonly approximated as a phonon bath on thermal equilibrium. To surpass such an approximation, this article applies the Hierarchical Equations of Motion method, a non-markovian approach also used to analyze the dynamic of such a complex, for the modeling of the system evolution. We perform a parametric analysis about some physical features in the quantum regime involved during the quantum excitation process in order to get a comprehension about its non-trivial dependence on operation parameters. Thus, the analysis is conducted in terms of some relevant physical parameters in the system to track the complex global behavior in aspects as coherence, entanglement, decoherence times, transference times, and efficiency of the main process of energy capturing. As a complementary analysis from the derived outcomes, we compare those features for two different species as a suggestive possible roadmap to track genetic differences in the photosynthetic performance of the complex through its biological nature.

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Proteins’ structure is a challenge in bioinformatics. We revisit the Hidrophobic-Polar (HP) model for Quantum Adiabatic Computation (AQC) formalizing its modeling, together an analysis about its unfeasibility in classical simulation versus quantum processing.

Determining the tertiary complexity of proteins using ab-initio algorithms is a hard problem. Adiabatic Quantum Computing allows to construct simple Ising-like Hamiltonians in order to elucidate the aminoacid interactions minimizing the conformation energy of the protein. Exploring the energy distribution of the Hamiltonian allows to compare the efficiency of different models there proposed. This article compare the efficiency of two algorithms through the conformation energy of a protein stating a benchmark through the energy distributions of the conformation states.

Fenna-Matthews-Olson (FMO) bacteriochlorophylls (BChls) are molecules responsible of the high efficiency energy transfer in the photosynthetic process of green sulfur bacteria, controversially associated to quantum phenomena of long lived coherence. This phenomenon is modelled using Quantum Open Systems (QOS) without included memory effects of the surrounding approximated as a phonon bath on thermal equilibrium. This work applies the Hierarchical Equations of Motion method (HEOM), a non-Markovian approach, in the modelling of the system evolution of the FMO complex to perform predictions about the coherence time scales together with global and semi-local entanglement during the quantum excitation.