Variational Quantum Optimization of Nonlocality in Noisy Quantum Networks

The noise and complexity inherent to quantum communication networks leads to technical challenges in designing quantum network protocols using classical methods. We address this issue with a hybrid variational quantum optimization (VQO) framework that simulates quantum networks on quantum hardware and optimizes the simulation using differential programming. We maximize nonlocality in noisy quantum networks to […]

Hardness of Braided Quantum Circuit Optimization in the Surface Code

Large-scale quantum information processing requires the use of quantum error-correcting codes to mitigate the effects of noise in quantum devices. Topological error-correcting codes, such as surface codes, are promising candidates, as they can be implemented using only local interactions in a 2-D array of physical qubits. Procedures, such as defect braiding and lattice surgery, can […]

Efficient Construction of a Control Modular Adder on a Carry-Lookahead Adder Using Relative-Phase Toffoli Gates

Control modular addition is a core arithmetic function, and we must consider the computational cost for actual quantum computers to realize efficient implementation. To achieve a low computational cost in a control modular adder, we focus on minimizingKQ (where K is the number of logical qubits required by the algorithm, and Q is the elementary […]

Layer VQE: A Variational Approach for Combinatorial Optimization on Noisy Quantum Computers

Combinatorial optimization on near-term quantum devices is a promising path to demonstrating quantum advantage. However, the capabilities of these devices are constrained by high noise or error rates. In this article, inspired by the variational quantum eigensolver (VQE), we propose an iterative layer VQE (L-VQE) approach. We present a large-scale numerical study, simulating circuits with […]

On the Realistic Worst-Case Analysis of Quantum Arithmetic Circuits

We provide evidence that commonly held intuitions when designing quantum circuits can be misleading. In particular, we show that 1) reducing the T-count can increase the total depth; 2) it may be beneficial to trade controlled NOTs for measurements in noisy intermediate-scale quantum (NISQ) circuits; 2) measurement-based uncomputation of relative phase Toffoli ancillae can make […]

A Distributed Learning Scheme for Variational Quantum Algorithms

Variational quantum algorithms (VQAs) are prime contenders to gain computational advantages over classical algorithms using near-term quantum machines. As such, many endeavors have been made to accelerate the optimization of modern VQAs in past years. To further improve the capability of VQAs, here, we propose a quantum distributed optimization scheme (dubbed as QUDIO), whose back […]

Quantum Volume in Practice: What Users Can Expect From NISQ Devices

Quantum volume (QV) has become the de-facto standard benchmark to quantify the capability of noisy intermediate-scale quantum (NISQ) devices. While QV values are often reported by NISQ providers for their systems, we perform our own series of QV calculations on 24 NISQ devices currently offered by IBM Q, IonQ, Rigetti, Oxford Quantum Circuits, and Quantinuum […]

Deep Space Network Scheduling Using Quantum Annealing

The National Aeronautics and Space Administration’s (NASA) Deep Space Network (DSN) is responsible for communication and navigation for several NASA and international missions. The DSN comprises three complexes located in Goldstone (California, USA), Cambera (Australia), and Madrid (Spain). This distribution in longitude guarantees a full sky coverage. Each complex has one 70-m and several 34-m […]

The Optimization and Application of 3-Bit Hermitian Gates and Multiple Control Toffoli Gates

The well-known 3-bit Hermitian gate (a Toffoli gate) has been implemented using Clifford+T circuits. Compared with the Peres gate, its implementation circuit requires more controlled- not (cnot) gates. However, the Peres gate is not Hermitian. This article reports four 3-bit Hermitian gates named LI gates, whose realized circuits have the same T-count, T-depth, and cnot […]

Model-Predictive Quantum Control via Hamiltonian Learning

This article proposes an end-to-end framework for the learning-enabled control of closed quantum systems. The proposed learning technique is the first of its kind to utilize a hierarchical design, which layers probing control, quantum state tomography, quantum process tomography, and Hamiltonian learning to identify both the internal and control Hamiltonians. Within this context, a novel […]