An Automatic Approach for Combinational Problems on a Hybrid Quantum Architecture

Quantum computing has shown great potential and advantages in solving integer factorization and disordered database search. However, it is not easy to solve specific problems with quantum computing device efficiently and widely, because a lot of professional background knowledge is required. In order to solve this problem, we propose an optimization problem’s automatic hybird quantum framework (OpAQ) for solving user-specified problems on a hybrid computing architecture including both quantum and classical computing resources. Such a solver can allow nonprofessionals who are not familiar with quantum physics and quantum computing to use quantum computing device to solve some classically difficult problems easily. Combinatorial optimization problem is one of the most important problems in both academic and industry. In this paper, we mainly focus on these problems and solve them with OpAQ, which is based on quantum approximation optimization algorithm (QAOA). We evaluate the performance of our approach in solving Graph Coloring, Max-cut, Traveling Salesman and Knapsack Problem. The experimental results show that quantum solver can achieve almost the same optimal solutions with the classical.

Qubit Allocation

The availability of the first prototypes of quantum computers, in 2016, with free access through the cloud, brought much enthusiasm to the research community. Yet, programming said computers is difficult. One core challenge is the so called qubit allocation problem. This problem consists in mapping the virtual qubits that make up a logical quantum program onto the physical qubits that exist in the target quantum architecture. To deal with this challenge, we have proposed one of the first algorithms to solve qubit allocation. This algorithm, together with its ensuing formulations, is today available in the Enfield compilera concrete product of this work. Our first paper in this field, titled Qubit Allocation, has inspired much research, and our latest qubit allocation design, called Bounded Mapping Tree, stands out today as one of the most effective qubit allocators in the world.

Graphene Quantum Dots for Quantum GPU architectures.

This paper is on a quantum architecture using the Display Computing paradigm, for a Quantum GPU design. It builds on my previous work on quantum reconfigurable computing. The design builds on a generalized 10 qubit architecture that can be reconfigured to provide display stream and input stream transformation using quantum computing.

Adiabatic Hamming Code Generator-Checker using 4-Dot-2-Electron Quantum Dot Cellular Automata

Technological advancements have witnessed rapid regression of Moore’s Law within the past few years. With rising demand for higher clocking speeds, CMOS has already started exhibiting threshold limitations. Reversible Logic has emerged as a suitable alternative with near zero heat dissipation attribute. Quantum Dot Cellular Automata (QCA) has adopted the concept of reversibility and emerged as a primitive tool for quantum architecture deigns with clocking near Terra-Hertz range. A plethora of quantum architectures based on QCA cells have been proposed till date. With rise of research on digital designs based on QCA, multiple literary proposals exist which realize digital designs incorporating QCA cells. This communication proposes a Hamming Code Generator-Checker architecture design using 4-dot-2-electron QCA cells. We employ an existing QCA based XOR gate literary proposal for designing the proposed architecture. Peer comparison with literary counterparts has proven our design to fare better with a gain of 60.6% in area.

Quantum Physics Takes Free Will into Account

In this dialogue, the physicist Ignacio Cirac, director of the Theoretical Division of the Max Planck Institute for Quantum Optics, outlines why quantum physics has brought about a much greater change than that caused by Einstein’s theory of relativity, how quantum physics takes free will into account and how it combines with philosophy. He describes why quantum theory defines “everything else,” yet is unable to define itself. Explaining how, together with Peter Zoller, he developed and presented the first theoretical description of a quantum computing architecture based on trapped ions, and, how this quantum architecture will be viable and capable of performing calculations we cannot perform at present. Their quantum computer calculates in qubits, which would require at least 100,000 qubits to function, rising to 1,000,000 if error correction is implemented. It will be able to perform calculations previously unachievable and create encrypted messages impossible to decipher. Building a functional quantum computer still requires a huge technological change, which has yet to come about. Lastly, Cirac explains the differences between European and American visions of science and why mathematicians are even more conservative than physicists.

Performance and error analysis of Knill's postselection scheme in a two-dimensional architecture

Knill demonstrated a fault-tolerant quantum computation scheme based on concatenated error-detecting codes and postselection with a simulated error threshold of $3\%$ over the depolarizing channel. We show how to use Knill's postselection scheme in a practical two-dimensional quantum architecture that we designed with the goal to optimize the error correction properties, while satisfying important architectural constraints. In our 2D architecture, one logical qubit is embedded in a tile consisting of $5\times 5$ physical qubits. The movement of these qubits is modeled as noisy SWAP gates and the only physical operations that are allowed are local one- and two-qubit gates. We evaluate the practical properties of our design, such as its error threshold, and compare it to the concatenated Bacon-Shor code and the concatenated Steane code. Assuming that all gates have the same error rates, we obtain a threshold of $3.06\times 10^{-4}$ in a local adversarial stochastic noise model, which is the highest known error threshold for concatenated codes in 2D. We also present a Monte Carlo simulation of the 2D architecture with depolarizing noise and we calculate a pseudo-threshold of about $0.1\%$. With memory error rates one-tenth of the worst gate error rates, the threshold for the adversarial noise model, and the pseudo-threshold over depolarizing noise, are $4.06\times 10^{-4}$ and $0.2\%$, respectively. In a hypothetical technology where memory error rates are negligible, these thresholds can be further increased by shrinking the tiles into a $4\times 4$ layout.

A 2D nearest-neighbor quantum architecture for factoring in polylogarithmic depth

We present a 2D nearest-neighbor quantum architecture for Shor's algorithm to factor an $n$-bit number in $O(\log^3n)$ depth. Our implementation uses parallel phase estimation, constant-depth fanout and teleportation, and constant-depth carry-save modular addition. We derive upper bounds on the circuit resources of our architecture under a new 2D model which allows a classical controller and parallel, communicating modules. We provide a comparison to all previous nearest-neighbor factoring implementations. Our circuit results in an exponential improvement in nearest-neighbor circuit depth at the cost of a polynomial increase in circuit size and width.