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Control of topological edge modes is desirable for encoding quantum information resiliently against external noise. Their implementation on quantum hardware, however, remains a long-standing problem due to current limitations of circuit depth and noise, which grows with the number of time steps. By utilizing recently developed constant-depth quantum circuits in which the circuit depth is independent of time, we demonstrate successful long-time dynamics simulation of bulk and surface modes in topological insulators on noisy intermediate-scale quantum (NISQ) processors, which exhibits robust signatures of localized topological modes. We further identify a class of one-dimensional topological Hamiltonians that can be readily simulated with NISQ hardware. Our results provide a pathway towards stable long-time implementation of topological quantum spin systems on present day quantum processors.

Electronic Energy Transfer (EET) between chromophores is fundamental in many natural light-harvesting complexes, serving as a critical step for solar energy funneling in photosynthetic plants and bacteria. The complicated role of the environment in mediating this process in natural architectures has been addressed by recent scanning tunneling microscope (STM) experiments involving EET between two molecules supported on a solid substrate. These measurements demonstrated that EET in such conditions has peculiar features, such as a steep dependence on the donor-acceptor distance, reminiscent of a short-range mechanism more than of a Forster-like process. By using state of the art hybrid ab initio electromagnetic modeling, here we provide a comprehensive theoretical analysis of tip-enhanced EET. In particular, we show that this process can be understood as a complex interplay of electromagnetic-based molecular plasmonic processes, whose result may effectively mimic short range effects. Therefore, the established identification of an exponential decay with Dexter-like effects does not hold for tip-enhanced EET, and accurate electromagnetic modeling is needed to identify the EET mechanism.

Interest in building dedicated Quantum Information Science and Engineering (QISE) education programs has greatly expanded in recent years. These programs are inherently convergent, complex, often resource intensive and likely require collaboration with a broad variety of stakeholders. In order to address this combination of challenges, we have captured ideas from many members in the community. This manuscript not only addresses policy makers and funding agencies (both public and private and from the regional to the international level) but also contains needs identified by industry leaders and discusses the difficulties inherent in creating an inclusive QISE curriculum. We report on the status of eighteen post-secondary education programs in QISE and provide guidance for building new programs. Lastly, we encourage the development of a comprehensive strategic plan for quantum education and workforce development as a means to make the most of the ongoing substantial investments being made in QISE., Comment: 18 pages, 2 figures, 1 table

Quantum annealers have grown in complexity to the point that quantum computations involving few thousands of qubits are now possible. In this paper, \textcolor{black}{with the intentions to show the feasibility of quantum annealing to tackle problems of physical relevance, we used a simple model, compatible with the capability of current quantum annealers, to study} the relative stability of graphene vacancy defects. By mapping the crucial interactions that dominate carbon-vacancy interchange onto a quadratic unconstrained binary optimization problem, our approach exploits \textcolor{black}{the ground state as well the excited states found by} the quantum annealer to extract all the possible arrangements of multiple defects on the graphene sheet together with their relative formation energies. This approach reproduces known results and provides a stepping stone towards applications of quantum annealing to problems of physical-chemical interest.

The recent availability of quantum annealers has fueled a new area of information technology where such devices are applied to address practically motivated and computationally difficult problems with hardware that exploits quantum mechanical phenomena. D-Wave annealers are promising platforms to solve these problems in the form of quadratic unconstrained binary optimization. Here we provide a formulation of the Chinese postman problem that can be used as a tool for probing the local connectivity of graphs and networks. We treat the problem classically with a tabu algorithm and using a D-Wave device. We systematically analyze computational parameters associated with the specific hardware. Our results clarify how the interplay between the embedding due to limited connectivity of the Chimera graph, the definition of logical qubits, and the role of spin-reversal controls the probability of reaching the expected solution.

Genome editing allows scientists to change an organism's DNA. One promising genome editing protocol, already validated in living organisms, is based on clustered regularly interspaced short palindromic repeats (CRISPR)/Cas protein-nucleic acid complexes. When the CRISPR/Cas approach was first demonstrated in 2012, its advantages with respect to previously available techniques, such as zinc-finger nucleases (ZFNs) and transcription activator-like effector nucleases (TALENs), immediately got attention and the method has seen a surge of experimental and computational investigations since then. However, the molecular mechanisms involved in target DNA recognition and cleavage are still not completely resolved and need further attention. The large size and complex nature of CRISPR/Cas9 complexes has been a challenge for computational studies, but some seed results exist and are illuminating on the cleavage activity. In this short review, we present recent progress in studying CRISPR/Cas9 systems by molecular dynamics simulations with coarse-grained and atomistic descriptions, including enhanced sampling., Comment: 24 pages, 10 figures, few figures are from previously published work for which appropriate permissions have been taken

Transcription factors regulate gene expression, but how these proteins recognize and specifically bind to their DNA targets is still debated. Machine learning models are effective means to reveal interaction mechanisms. Here we studied the ability of a quantum machine learning approach to predict binding specificity. Using simplified datasets of a small number of DNA sequences derived from actual binding affinity experiments, we trained a commercially available quantum annealer to classify and rank transcription factor binding. The results were compared to state-of-the-art classical approaches for the same simplified datasets, including simulated annealing, simulated quantum annealing, multiple linear regression, LASSO, and extreme gradient boosting. Despite technological limitations, we find a slight advantage in classification performance and nearly equal ranking performance using the quantum annealer for these fairly small training data sets. Thus, we propose that quantum annealing might be an effective method to implement machine learning for certain computational biology problems.

We report a theoretical scheme that enables the calculation of maximally localized Wannier functions in the formalism of projector-augmented-waves (PAW) which also includes the ultrasoft-pseudopotential (USPP) approach. We give a description of the basic underlying formalism and explicitly write all the required matrix elements from the common ingredients of the PAW/USPP theory. We report an implementation of the method in a form suitable to accept the input electronic structure from USPP plane-wave DFT simulations. We apply the method to the calculation of Wannier functions, dipole moments and spontaneous polarizations in a range of test cases. Comparison with norm-conserving pseudopotentials is reported as a benchmark., Comment: 10 pages, 3 figures

Charge migration along DNA molecules has attracted scientific interest for over half a century. Reports on possible high rates of charge transfer between donor and acceptor through the DNA, obtained in the last decade from solution chemistry experiments on large numbers of molecules, triggered a series of direct electrical transport measurements through DNA single molecules, bundles and networks. These measurements are reviewed and presented here. From these experiments we conclude that electrical transport is feasible in short DNA molecules, in bundles and networks, but blocked in long single molecules that are attached to surfaces. The experimental background is complemented by an account of the theoretical/computational schemes that are applied to study the electronic and transport properties of DNA-based nanowires. Examples of selected applications are given, to show the capabilities and limits of current theoretical approaches to accurately describe the wires, interpret the transport measurements, and predict suitable strategies to enhance the conductivity of DNA nanostructures., Comment: A single pdf file of 52 pages, containing the text and 23 figures. Review about direct measurements of DNA conductivity and related theoretical studies. For higher-resolution figures contact the authors or retrieve the original publications cited in the captions

We present a first-principle study of the electronic and conduction properties of a few classes of nanowires constituted of guanine (G) molecules, self-assembled in different geometries. We first analyze the effect of the vertical $\pi$-$\pi$ interaction in model G-stack columns. Then, we exploit the results obtained from those models to interpret the features of realistic stacked and hydrogen-bonded structures, namely the guanine quadruple helices and the planar ribbons. With respect to natural DNA, the different structures as well as the inclusion of metal cations, drastically affect the bonding pattern among the bases, introducing novel features in the electronic properties of the systems. These supramolecular G-aggregates, alternative to DNA, are expected to show intersting properties for molecular elec tronics applications., Comment: 30 pages (preprint format), 8 figures. To appear in Solid State Communications - Special Issue on "New advances on collective phenomena in one-dimensional systems"

We report a first-principle study of the electronic and conduction properties of a quadruple-helix guanine wire (G4-wire), a DNA-derivative, with inner potassium ions. The analysis of the electronic structure highlights the presence of energy manifolds that are equivalent to the bands of (semi)conducting materials, and reveals the formation of extended electron channels available for charge transport along the wire. The specific metal-nucleobase interactions affect the electronic properties at the Fermi level, leading the wire to behave as an intrinsically p-doped system., Comment: To be published in Journal of Physical Chemistry B, 8 pages (double column), 4 figures

Recently, great attention has been paid to the possibility of implementing hybrid electronic devices exploiting the self-assembling properties of single molecules. Impressive progress has been done in this field by using organic molecules and macromolecules. However, the use of biomolecules is of great interest because of their larger size (few nanometers) and of their intrinsic functional properties. Here, we show that electron-transfer proteins, such as the blue copper protein azurin (Az), can be used to fabricate biomolecular electronic devices exploiting their intrinsic redox properties, self assembly capability and surface charge distribution. The device implementation follows a bottom-up approach in which the self assembled protein layer interconnects nanoscale electrodes fabricated by electron beam lithography, and leads to efficient rectifying behavior at room temperature., Comment: 13 pages including two figures. Accepted for publication in Advanced Materials