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Molecular Docking (MD) is an important step of the drug discovery process which aims at calculating the preferred position and shape of one molecule to a second when they are bound to each other. During such analysis, 3D representations of molecules are manipulated according to their degree of freedoms: rigid roto-translation and fragment rotations along the rotatable bonds. In our work, we focused on one specific phase of the molecular docking procedure i.e. Molecular Unfolding (MU), which is used to remove the initial bias of a molecule by expanding it to an unfolded shape. The objective of the MU problem is to find the configuration that maximizes the molecular area, or equivalently, that maximizes the internal distances between atoms inside the molecule. We propose a quantum annealing approach to MU by formulating it as a High-order Unconstrained Binary Optimization (HUBO) which was possible to solve on the latest D-Wave annealing hardware (2000Q and Advantage). Results and performances obtained with quantum annealers are compared with state of art classical solvers.
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We examine the emergence of objectivity via quantum Darwinism through the use of a collision model, i.e. where the dynamics is modeled through sequences of unitary interactions between the system and the individual constituents of the environment, termed ancillas. By exploiting versatility of this framework, we show that one can transition from a Darwinistic to an encoding environment by simply tuning their interaction. Furthermore we establish that in order for a setting to exhibit quantum Darwinism we require a mutual decoherence to occur between the system and environmental ancillas, thus showing that system decoherence alone is not sufficient. Finally, we demonstrate that the observation of quantum Darwinism is sensitive to a non-uniform system-environment interaction.
Understanding system-bath correlations in open quantum systems is essential for various quantum information and technology applications. Derivations of most master equations (MEs) for the dynamics of open systems require approximations that mask dependence of the system dynamics on correlations, since the MEs focus on reduced system dynamics. Here we demonstrate that the most common MEs indeed contain hidden information about explicit system-environment correlation. We unfold these correlations by recasting the MEs into a universal form in which the system-bath correlation operator appears. The equations include the Lindblad, Redfield, second-order time-convolutionless, second-order Nakajima-Zwanzig, and second-order universal Lindblad-like cases. We further illustrate our results in an example, which implies that the second-order universal Lindblad-like equation captures correlation more accurately than other standard techniques.
We propose a model for motor proteins based on a hierarchical Hamiltonian that we have previously introduced to describe protein folding. The proposed motor model has high efficiency and is consistent with a linear load-velocity response. The main improvement with respect to previous models is that this description suggests a connection between folding and function of allosteric proteins.
We present Quantum Unfolding, a Fortran90 program for unfolding first-principles electronic energy bands. It unfolds energy bands accurately by handling the Fourier components of Bloch wavefunctions, which are reconstructed from Wannier functions from Wannier90. Due to the wide application of Wannier90 package and the possibility of focusing only on the most important energy bands, the present code works very conveniently.
Molecular vibrations underpin important phenomena such as spectral properties, energy transfer, and molecular bonding. However, obtaining a detailed understanding of the vibrational structure of even small molecules is computationally expensive. While several algorithms exist for efficiently solving the electronic structure problem on a quantum computer, there has been comparatively little attention devoted to solving the vibrational structure problem with quantum hardware. In this work, we discuss the use of quantum algorithms for investigating both the static and dynamic vibrational properties of molecules. We introduce a physically motivated unitary vibrational coupled cluster ansatz, which also makes our method accessible to noisy, near-term quantum hardware. We numerically test our proposals for the water and sulfur dioxide molecules.
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