Efficient arbitrary simultaneously entangling gates on a trapped-ion quantum computer

Grzesiak, Nikodem; Blümel, R.; Wright, Kenneth; Beck, Kristin M.; Pisenti, Neal C.; Li, Ming; Chaplin, V.; Amini, Jason M.; Debnath, Shantanu; Chen, Jwo-Sy; Nam, Yoonsu

doi:10.1038/s41467-020-16790-9

Cited by 88 publications

(77 citation statements)

References 35 publications

(81 reference statements)

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“…Harking back to the power and impact of parallel operations in conventional computing, we look forward to the revolution that EASE gates are to bring in quantum computing. Experimental demonstrations have already been successful [2], and the exciting challenges of finding more use cases of EASE gates continue. In this paper, we took a first step towards this goal, leveraging in particular the random access over any pairs of qubits.…”

Section: Discussionmentioning

confidence: 99%

“…is a Pauli operator, defined over a vector that points to the equator of a Bloch sphere with azimuthal angle φ j , acting on qubit j and free parameters θ jk are the entanglement coupling between qubits j and k. Shown in [2] was that, even though the number of θ jk parameters increases quadratically in the number of qubits n, the complexity of the control signal design scales at most linearly in the number of qubits n, bounded from above by 3n − 1. Note a single two-qubit gate requires similar complexity, i.e., 2n + 1 [6].…”

Section: Ease Gatesmentioning

confidence: 99%

“…As detailed in Sec. 2 (see also [2]), an EASE gate can entangle arbitrarily selected pairs of qubits in one step. When the entanglement couplings for all pairs are identical, the EASE gate becomes the so-called global Mølmer-Sørensen (GMS) gate, investigated in [3][4][5] to demonstrate more efficient compilation of quantum programs when compared to a serial approach.…”

Section: Introductionmentioning

confidence: 99%

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Efficient quantum programming using EASE gates on a trapped-ion quantum computer

Grzesiak

Maksymov

Niroula

et al. 2022

Quantum

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Parallel operations in conventional computing have proven to be an essential tool for efficient and practical computation, and the story is not different for quantum computing. Indeed, there exists a large body of works that study advantages of parallel implementations of quantum gates for efficient quantum circuit implementations. Here, we focus on the recently invented efficient, arbitrary, simultaneously entangling (EASE) gates, available on a trapped-ion quantum computer. Leveraging its flexibility in selecting arbitrary pairs of qubits to be coupled with any degrees of entanglement, all in parallel, we show an n-qubit Clifford circuit can be implemented using 6log(n) EASE gates, an n-qubit multiply-controlled NOT gate can be implemented using 3n/2 EASE gates, and an n-qubit permutation can be implemented using six EASE gates. We discuss their implications to near-term quantum chemistry simulations and the state of the art pattern matching algorithm. Given Clifford + multiply-controlled NOT gates form a universal gate set for quantum computing, our results imply efficient quantum computation by EASE gates, in general.

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Section: Discussionmentioning

confidence: 99%

Section: Ease Gatesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Efficient quantum programming using EASE gates on a trapped-ion quantum computer

Grzesiak

Maksymov

Niroula

et al. 2022

Quantum

Self Cite

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“…In the meantime, quantum computers are introduced to the general public by several technology companies such as IBM [ 6 ], Google [ 7 ], IonQ [ 8 ] and D-Wave [ 9 ]. Theoretically, quantum computing can provide exponential speedup to certain classes of hard problems that are intractable on classical computers [ 10 , 11 ].…”

Section: Introductionmentioning

confidence: 99%

Federated Quantum Machine Learning

Chen

Yoo

2021

Entropy

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Distributed training across several quantum computers could significantly improve the training time and if we could share the learned model, not the data, it could potentially improve the data privacy as the training would happen where the data is located. One of the potential schemes to achieve this property is the federated learning (FL), which consists of several clients or local nodes learning on their own data and a central node to aggregate the models collected from those local nodes. However, to the best of our knowledge, no work has been done in quantum machine learning (QML) in federation setting yet. In this work, we present the federated training on hybrid quantum-classical machine learning models although our framework could be generalized to pure quantum machine learning model. Specifically, we consider the quantum neural network (QNN) coupled with classical pre-trained convolutional model. Our distributed federated learning scheme demonstrated almost the same level of trained model accuracies and yet significantly faster distributed training. It demonstrates a promising future research direction for scaling and privacy aspects.

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“…Likewise, a quantum version of MIMD is highly desirable to design new protocols that are able to implement multiple entangling gates in parallel and enhance the operation rate within the coherence time of the hardware. Quantum gate parallelism which is essential for fault-tolerant error correction [1,58] has so far been realized in iontraps [29,35], superconducting circuits [57] and optical lattices [42,46]. Nonetheless, the development of parallel operation of two-qubit gates between selected pair of qubits in the context of spin-based computation has remained a critical open question.…”

Section: Introductionmentioning

confidence: 99%

Parallel entangling gate operations and two-way quantum communication in spin chains

Yousefjani

Bayat

2021

Quantum

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The power of a quantum circuit is determined through the number of two-qubit entangling gates that can be performed within the coherence time of the system. In the absence of parallel quantum gate operations, this would make the quantum simulators limited to shallow circuits. Here, we propose a protocol to parallelize the implementation of two-qubit entangling gates between multiple users which are spatially separated, and use a commonly shared spin chain data-bus. Our protocol works through inducing effective interaction between each pair of qubits without disturbing the others, therefore, it increases the rate of gate operations without creating crosstalk. This is achieved by tuning the Hamiltonian parameters appropriately, described in the form of two different strategies. The tuning of the parameters makes different bilocalized eigenstates responsible for the realization of the entangling gates between different pairs of distant qubits. Remarkably, the performance of our protocol is robust against increasing the length of the data-bus and the number of users. Moreover, we show that this protocol can tolerate various types of disorders and is applicable in the context of superconductor-based systems. The proposed protocol can serve for realizing two-way quantum communication.

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Efficient arbitrary simultaneously entangling gates on a trapped-ion quantum computer

Cited by 88 publications

References 35 publications

Efficient quantum programming using EASE gates on a trapped-ion quantum computer

Efficient quantum programming using EASE gates on a trapped-ion quantum computer

Federated Quantum Machine Learning

Parallel entangling gate operations and two-way quantum communication in spin chains

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