Classically Optimal Variational Quantum Algorithms

Hybrid quantum-classical algorithms, such as variational quantum algorithms (VQAs), are suitable for implementation on noisy intermediate-scale quantum computers. In this article, we expand an implicit step of VQAs: the classical precomputation subroutine, which can nontrivially use classical algorithms to simplify, transform, or specify problem instance-specific variational quantum circuits. In VQA, there is a tradeoff between […]

Quantum Circuit Architecture Optimization for Variational Quantum Eigensolver via Monto Carlo Tree Search

The advent of noisy intermediate-scale quantum (NISQ) devices provide crucial promise for the development of quantum algorithms. Variational quantum algorithms have emerged as one of the best hopes to utilize NISQ devices. Among these is the famous variational quantum eigensolver (VQE), where one trains a parameterized and fixed quantum circuit (or an ansatz) to accomplish […]

Efficient Optimization of Cutoffs in Quantum Repeater Chains

Quantum communication enables the implementation of tasks that are unachievable with classical resources. However, losses on the communication channel preclude the direct long-distance transmission of quantum information in many relevant scenarios. In principle, quantum repeaters allow one to overcome losses. However, realistic hardware parameters make long-distance quantum communication a challenge in practice. For instance, in […]

Performance of Domain-Wall Encoding for Quantum Annealing

In this article, we experimentally test the performance of the recently proposed domain-wall encoding of discrete variables Chancellor, 2019, on Ising model flux qubit quantum annealers. We compare this encoding with the traditional one-hot methods and find that they outperform the one-hot encoding for three different problems at different sizes of both the problem and […]

Quantum Approximate Optimization With Parallelizable Gates

The quantum approximate optimization algorithm (QAOA) has been introduced as a heuristic digital quantum computing scheme to find approximate solutions of combinatorial optimization problems. We present a scheme to parallelize this approach for arbitrary all-to-all connected problem graphs in a layout of quantum bits (qubits) with nearest-neighbor interactions. The protocol consists of single qubit operations […]

Multiblock ADMM Heuristics for Mixed-Binary Optimization on Classical and Quantum Computers

Solving combinatorial optimization problems on current noisy quantum devices is currently being advocated for (and restricted to) binary polynomial optimization with equality constraints via quantum heuristic approaches. This is achieved using, for example, the variational quantum eigensolver (VQE) and the quantum approximate optimization algorithm (QAOA). In this article, we present a decomposition-based approach to extend […]

Entanglement Distribution in a Quantum Network: A Multicommodity Flow-Based Approach

We consider the problem of optimizing the achievable EPR-pair distribution rate between multiple source-destination pairs in a quantum Internet, where the repeaters may perform a probabilistic Bell-state measurement and we may impose a minimum end-to-end fidelity as a requirement. We construct an efficient linear programming (LP) formulation that computes the maximum total achievable entanglement distribution […]

Logical Clifford Synthesis for Stabilizer Codes

Quantum error-correcting codes are used to protect qubits involved in quantum computation. This process requires logical operators to be translated into physical operators acting on physical quantum states. In this article, we propose a mathematical framework for synthesizing physical circuits that implement logical Clifford operators for stabilizer codes. Circuit synthesis is enabled by representing the […]

Solving the Network Shortest Path Problem on a Quantum Annealer

This article addresses the formulation for implementing a single source, single-destination shortest path algorithm on a quantum annealing computer. Three distinct approaches are presented. In all the three cases, the shortest path problem is formulated as a quadratic unconstrained binary optimization problem amenable to quantum annealing. The first implementation builds on existing quantum annealing solutions […]