Publications

Abstract not provided.

Quantum simulations promise to be one of the primary applications of quantum computers, should one be constructed. This article briefly summarizes the history of quantum simulation in light of the recent result of Wang and co-workers, demonstrating calculation of the ground and excited states for a HeH+ molecule, and concludes with a discussion of why this and other recent progress in the field suggest that quantum simulations of quantum chemistry have a bright future. (Figure Presented).

In this paper, we present a strategy for producing multiqubit gates that promise high fidelity with minimal tuning requirements. Our strategy combines gap protection from the adiabatic theorem with dynamical decoupling in a complementary manner. Energy-level transition errors are protected by adiabaticity and remaining phase errors are mitigated via dynamical decoupling. This is a powerful way to divide and conquer the various error channels. In order to accomplish this without violating a no-go theorem regarding black-box dynamically corrected gates [Phys. Rev. A 80, 032314 (2009)], we require a robust operating point (sweet spot) in control space where the qubits interact with little sensitivity to noise. There are also energy gap requirements for effective adiabaticity. We apply our strategy to an architecture in Si with P donors where we assume we can shuttle electrons between different donors. Electron spins act as mobile ancillary qubits and P nuclear spins act as long-lived data qubits. Furthermore, this system can have a very robust operating point where the electron spin is bound to a donor in the quadratic Stark shift regime. High fidelity single qubit gates may be performed using well-established global magnetic resonance pulse sequences. Single electron-spin preparation and measurement has also been demonstrated. Thus, putting this all together, we present a robust universal gate set for quantum computation.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

This report details the findings of the DOE ASCR Workshop on Quantum Computing for Science that was organized to assess the viability of quantum computing technologies to meet the computational requirements of the DOE’s science and energy mission, and to identify the potential impact of quantum technologies. The workshop was held on February 17-18, 2015, in Bethesda, MD, to solicit input from members of the quantum computing community. The workshop considered models of quantum computation and programming environments, physical science applications relevant to DOE's science mission as well as quantum simulation, and applied mathematics topics including potential quantum algorithms for linear algebra, graph theory, and machine learning. This report summarizes these perspectives into an outlook on the opportunities for quantum computing to impact problems relevant to the DOE’s mission as well as the additional research required to bring quantum computing to the point where it can have such impact.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

We have been using RedSky to investigate the physics of donor atoms in silicon for use as qubits for quantum computing. Quantum computing promises to dramatically change the performance of certain algorithms; this work is part of a quantum computing project led by Malcolm Carroll. We have investigated the magnitude of energy barriers for transferring electrons between donor centers and to elecrostaticallydefined quantum dots at the silicon oxide interface. Understanding these barriers helps us design structures that we think will be robust to noise and decoherence effects, and will help us understand experimental results as we build preliminary structures. There are only a few other research groups in the world conducting research along these lines. The work has been an important element of understanding the design principles that constrain computing devices at low temperature. We will continue this work in the future, in particular to analyze experimental results we anticipate coming from CINT collaborators.

Abstract not provided.

Abstract not provided.

We report Pauli blockade in a multielectron silicon metal–oxide–semiconductor double quantum dot with an integrated charge sensor. The current is rectified up to a blockade energy of 0.18 ± 0.03 meV. The blockade energy is analogous to singlet–triplet splitting in a two electron double quantum dot. Built-in imbalances of tunnel rates in the MOS DQD obfuscate some edges of the bias triangles. A method to extract the bias triangles is described, and a numeric rate-equation simulation is used to understand the effect of tunneling imbalances and finite temperature on charge stability (honeycomb) diagram, in particular the identification of missing and shifting edges. A bound on relaxation time of the triplet-like state is also obtained from this measurement.

We present the Quantum Computer Aided Design (QCAD) simulator that targets modeling quantum devices, particularly silicon double quantum dots (DQDs) developed for quantum qubits. The simulator has three di erentiating features: (i) its core contains nonlinear Poisson, e ective mass Schrodinger, and Con guration Interaction solvers that have massively parallel capability for high simulation throughput, and can be run individually or combined self-consistently for 1D/2D/3D quantum devices; (ii) the core solvers show superior convergence even at near-zero-Kelvin temperatures, which is critical for modeling quantum computing devices; (iii) it couples with an optimization engine Dakota that enables optimization of gate voltages in DQDs for multiple desired targets. The Poisson solver includes Maxwell- Boltzmann and Fermi-Dirac statistics, supports Dirichlet, Neumann, interface charge, and Robin boundary conditions, and includes the e ect of dopant incomplete ionization. The solver has shown robust nonlinear convergence even in the milli-Kelvin temperature range, and has been extensively used to quickly obtain the semiclassical electrostatic potential in DQD devices. The self-consistent Schrodinger-Poisson solver has achieved robust and monotonic convergence behavior for 1D/2D/3D quantum devices at very low temperatures by using a predictor-correct iteration scheme. The QCAD simulator enables the calculation of dot-to-gate capacitances, and comparison with experiment and between solvers. It is observed that computed capacitances are in the right ballpark when compared to experiment, and quantum con nement increases capacitance when the number of electrons is xed in a quantum dot. In addition, the coupling of QCAD with Dakota allows to rapidly identify which device layouts are more likely leading to few-electron quantum dots. Very efficient QCAD simulations on a large number of fabricated and proposed Si DQDs have made it possible to provide fast feedback for design comparison and optimization.