The exact solution of the Schrödinger equation for atoms, molecules and extended systems continues to be a "Holy Grail" problem for the field of atomic and molecular physics since inception. Recently, breakthroughs have been made in the development of hardwareefficient quantum optimizers and coherent Ising machines capable of simulating hundreds of interacting spins through an Ising-type Hamiltonian. One of the most vital questions associated with these new devices is: "Can these machines be used to perform electronic structure calculations?" In this study, we discuss the general standard procedure used by these devices and show that there is an exact mapping between the electronic structure Hamiltonian and the Ising Hamiltonian. The simulation results of the transformed Ising Hamiltonian for H2, He2, HeH + , and LiH molecules match the exact numerical calculations. This demonstrates that one can map the molecular Hamiltonian to an Ising-type Hamiltonian which could easily be implemented on currently available quantum hardware.The determination of solutions to the Schrödinger equation is fundamentally difficult as the dimensionality of the corresponding Hilbert space increases exponentially with the number of particles in the system, requiring a commensurate increase in computational resources. Modern quantum chemistry -faced with difficulties associated with solving the Schrödinger equation to chemical accuracy (∼1 kcal/mole) -has largely become an endeavor to find approximate methods. A few products of this effort from the past few decades include methods such as: ab initio, Density Functional, Density Matrix, Algebraic, Quantum Monte Carlo and Dimensional Scaling [1,2,3,4]. However, all methods hitherto devised face the insurmountable challenge of escalating computational resource requirements as the calculation is extended either to higher accuracy or to larger systems. Computational complexity in electronic structure calculations [5,6,7] suggests that these restrictions are an inherent difficulty associated with simulating quantum systems.Electronic structure algorithms developed for quantum computers provide a new promising route to advance the field of electronic structure calculations for large systems [8,9]. Recently, there has been an attempt at using an adiabatic quantum computing model -as is implemented on the D-Wave machine -to perform electronic structure calculations [10]. The fundamental concept behind the adiabatic quantum computing (AQC) method is to define a problem Hamiltonian, H P , engineered to have its ground state encode the solution of a corresponding computational problem. The system is initialized in the ground state of a beginning Hamiltonian, H B , which is easily solved classically. The system is then allowed to evolve adiabatically as: The largest scale implementation of AQC to date is by D-Wave Systems [11,12]. In the case of the DWave device, the physical process undertaken which acts as an adiabatic evolution is more broadly called quantum annealing (QA). The quantum processor...

Motor proteins such as myosin, kinesin, and dynein are essential to eukaryotic life and power countless processes including muscle contraction, wound closure, cargo transport, and cell division. The design of synthetic nanomachines that can reproduce the functions of these motors is a longstanding goal in the field of nanotechnology. DNA walkers, which are programmed to “walk” along defined tracks via the burnt bridge Brownian ratchet mechanism, are among the most promising synthetic mimics of these motor proteins. While these DNA-based motors can perform useful tasks such as cargo transport, they have not been shown to be capable of cooperating to generate large collective forces for tasks akin to muscle contraction. In this work, we demonstrate that highly polyvalent DNA motors (HPDMs), which can be viewed as cooperative teams of thousands of DNA walkers attached to a microsphere, can generate and sustain substantial forces in the 100+ pN regime. Specifically, we show that HPDMs can generate forces that can unzip and shear DNA duplexes (∼12 and ∼50 pN, respectively) and rupture biotin–streptavidin bonds (∼100–150 pN). To help explain these results, we present a variant of the burnt-bridge Brownian ratchet mechanism that we term autochemophoresis, wherein many individual force generating units generate a self-propagating chemomechanical gradient that produces large collective forces. In addition, we demonstrate the potential of this work to impact future engineering applications by harnessing HPDM autochemophoresis to deposit “molecular ink” via mechanical bond rupture. This work expands the capabilities of synthetic DNA motors to mimic the force-generating functions of biological motors. Our work also builds upon previous observations of autochemophoresis in bacterial transport processes, indicating that autochemophoresis may be a fundamental mechanism of pN-scale force generation in living systems.

We compare recently proposed methods to compute the electronic state energies of the water molecule on a quantum computer. The methods include the phase estimation algorithm based on Trotter decomposition, the phase estimation algorithm based on the direct implementation of the Hamiltonian, direct measurement based on the implementation of the Hamiltonian and a specific variational quantum eigensolver, Pairwise VQE. After deriving the Hamiltonian using STO-3G basis, we first explain how each method works and then compare the simulation results in terms of gate complexity and the number of measurements for the ground state of the water molecule with different O-H bond lengths. Moreover, we present the analytical analyses of the error and the gate-complexity for each method. While the required number of qubits for each method is almost the same, the number of gates and the error vary a lot. In conclusion, among methods based on the phase estimation algorithm, the second order direct method provides the most efficient circuit implementations in terms of the gate complexity. With large scale quantum computation, the second order direct method seems to be better for large molecule systems. Moreover, Pairewise VQE serves the most practical method for near-term applications on the current available quantum computers. Finally the possibility of extending the calculation to excited states and resonances is discussed.

In this paper a storage method and a context-aware circuit simulation idea are presented for the sum of block diagonal matrices. Using the design technique for a generalized circuit for the Hamiltonian dynamics through the truncated series, we generalize the idea to (0-1) matrices and discuss the generalization for the real matrices. The presented circuit requires O(n) number of quantum gates and yields the correct output with the success probability depending on the number of elements: for matrices with poly(n), the success probability is 1/poly(n). Since the operations on the circuit are controlled by the data itself, the circuit can be considered as a context aware computing gadget. In addition, it can be used in variational quantum eigensolver and in the simulation of molecular Hamiltonians.

The complex-scaling method can be used to calculate molecular resonances within the Born–Oppenheimer approximation, assuming that the electronic coordinates are dilated independently of the nuclear coordinates. With this method, one will calculate the complex energy of a non-Hermitian Hamiltonian, whose real part is associated with the resonance position and imaginary part is the inverse of the lifetime. In this study, we propose techniques to simulate resonances on a quantum computer. First, we transformed the scaled molecular Hamiltonian to second quantization and then used the Jordan–Wigner transformation to transform the scaled Hamiltonian to the qubit space. To obtain the complex eigenvalues, we introduce the direct measurement method, which is applied to obtain the resonances of a simple one-dimensional model potential that exhibits pre-dissociating resonances analogous to those found in diatomic molecules. Finally, we applied the method to simulate the resonances of the H2− molecule. The numerical results from the IBM Qiskit simulators and IBM quantum computers verify our techniques.