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Springer eBooks

Synthesis of Entangled Atomic States and Quantum Computation

Thomas Pellizzari, S. A. Gardiner, J. I. Cirac, P. Zoller

Published Jan 1, 1996• 0 citations
Publisher
DOI
10.1007/978-1-4757-9742-8_6

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Because of the largest number of qubits available, and the massive parallel execution of entangling two-qubit gates, atom arrays is a promising platform for quantum computing. The qubits are selectively loaded into arrays of optical traps, some of which can be moved during the computation itself. By adjusting the locations of the traps and shining a specific global laser, different pairs of qubits, even those initially far away, can be entangled at different stages of the quantum program execution. In comparison, previous QC architectures only generate entanglement on a fixed set of quantum register pairs. Thus, reconfigurable atom arrays (RAA) present a new challenge for QC compilation, especially the qubit mapping/layout synthesis stage which decides the qubit placement and gate scheduling. In this paper, we consider an RAA QC architecture that contains multiple arrays, supports 2D array movements, represents cutting-edge experimental platforms, and is much more general than previous works. We start by systematically examining the fundamental constraints on RAA imposed by physics. Built upon this understanding, we discretize the state space of the architecture, and we formulate layout synthesis for such an architecture to a satisfactory modulo theories problem. Finally, we demonstrate our work by compiling the quantum approximate optimization algorithm (QAOA), one of the promising near-term quantum computing applications. Our layout synthesizer reduces the number of required native two-qubit gates in 22-qubit QAOA by 5.72x (geomean) compared to leading experiments on a superconducting architecture. Combined with a better coherence time, there is an order-of-magnitude increase in circuit fidelity.
The synthesis of materials into quantum entangled materials is a complicated challenge to an accurate and computational prediction of those materials. In this proposed work, it develops an AI-guided framework based on the combination between machine learning (ML) and reinforcement learning (RL), and quantum simulations to push the designing and validating of quantum materials at a much faster pace. In the first, graph neural networks (GNNs) are used to extract the atomic level quantum features, and in the second, generative models (VAE/GAN) are utilized to discover some novel entangled structures. In addition, fabrication with the synthesis parameters as parameters in the reinforcement learning results in an improvement of the experiment synthesis and a decrease of experiment failures as well as significant improvement of reproducibility. It demonstrates that the proposed hybrid ML-quantum simulation is validated on entanglement fidelity in real-world quantum computing platforms using IBM Qiskit and Google Cirq. As the proposed method is way beyond traditional ones, it has higher quantum coherence time, synthesis efficiency as well as higher prediction accuracy. In addition to enabling scaling-up of cryptography, quantum computing, and next generation nanomaterials, it is a cost and scalable framework for creating next generation quantum technologies applications as it is. And the model is further researched for the generalization in regards to real-time experimental feedback and for the expansion of the framework to a more general quantum materials program. The results show that AI approaches can truly accelerate the quantum material innovation even when syntheses are not at all possible.
Quantum computation established itself as a promising emerging technology and, hence, attracted considerable attention in the domain of computer-aided-design (CAD). However, quantum mechanical phenomena such as superposition, phase shifts, or entanglement lead to a logic model which poses serious challenges to the development of a proper design flow for quantum circuits. Consequently, researchers addressed synthesis of quantum circuits not as a single design step, but considered sub-tasks such as synthesis of Boolean components or synthesis of restricted subsets of quantum functionality. Generating a particularly desired quantum state is another of these sub-tasks. However, logic synthesis of quantum circuits accomplishing that has hardly been considered yet. In this work, we propose a generic method which automatically synthesizes a quantum circuit generating any desired quantum state from an initially given basis state. The proposed method allows for both, a theoretical determination of upper bounds as well as an experimental evaluation of the number of quantum gates needed for this important design step.