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Journal of Modern Optics

RISQ - reduced instruction set quantum computers

Klaus Mølmer, Anders Sørensen

Published Nov 20, 2000• 1 citation
Publisher

Abstract

Candidates for quantum computing which offer only restricted control, e.g., due to lack of access to individual qubits, are not useful for general purpose quantum computing.We present concrete proposals for the use of systems with such limitations as RISQreduced instruction set quantum computers and devices -for simulation of quantum dynamics, for multi-particle entanglement and squeezing of collective spin variables.These tasks are useful in their own right, and they also provide experimental probes for the functioning of quantum gates in pre-mature proto-types of quantum computers.

DOI
10.1080/095003400750039519

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Candidates for quantum computing which offer only restricted control, e.g., due to lack of access to individual qubits, are not useful for general purpose quantum computing.We present concrete proposals for the use of systems with such limitations as RISQreduced instruction set quantum computers and devices -for simulation of quantum dynamics, for multi-particle entanglement and squeezing of collective spin variables.These tasks are useful in their own right, and they also provide experimental probes for the functioning of quantum gates in pre-mature proto-types of quantum computers.
Candidates for quantum computing which offer only restricted control, e.g. due to lack of access to individual qubits, are not useful for general purpose quantum computing. We present concrete proposals for the use of systems with such limitations as RISQ-reduced instruction set quantum computers and devices-for simulation of quantum dynamics, for multi-particle entanglement and squeezing of collective spin variables. These tasks are useful in their own right, and they also provide experimental probes for the functioning of quantum gates in premature prototypes of quantum computers.
We present a quantum CISC compiler and show how to assemble complex instruction sets in a scalable way. Enlarging the toolbox of universal gates by optimised complex multi-qubit instruction sets thus paves the way to fight decoherence for realistic settings. Compiling a quantum module into the machine code for steering a concrete quantum hardware device lends itself to be tackled by means of optimal quantum control. To this end, there are two opposite approaches: (i) one may use a decomposition into the restricted instruction set (RISC) of universal one- and two-qubit gates, which in turn have prefabricated translations into the machine code or (ii) one may prefer to generate the entire target module directly by a complex instruction set (CISC) of available controls. Here we advocate direct compilation up to the limit of system size a classical high-performance parallel computer cluster can reasonably handle. For going beyond these limits, i.e. for large systems we propose a combined way, namely (iii) to make recursive use of medium-sized building blocks generated by optimal control in the sense of a quantum CISC compiler. The advantage of the method over standard RISC compilations into one- and two-qubit universal gates is explored on the parallel cluster HLRB-II (with a total LINPACK performance of 63.3 TFlops/s) for the quantum Fourier transform, the indirect SWAP gate as well as for multiply-controlled CNOT gates. Implications for upper limits to time complexities are also derived.
Near-term quantum computing (QC) systems have limited qubit counts, high gate (instruction) error rates, and typically support a minimal instruction set having one type of two-qubit gate (2Q). To reduce program instruction counts and improve application expressivity, vendors have proposed, and shown proof-of-concept demonstrations of richer instruction sets such as XY gates (Rigetti) and fSim gates (Google). These instruction sets comprise of families of 2Q gate types parameterized by continuous qubit rotation angles. That is, it allows a large set of different physical operations to be realized on the qubits, based on the input angles. However, having such a large number of gate types is problematic because each gate type has to be calibrated periodically, across the full system, to obtain high fidelity implementations. This results in substantial recurring calibration overheads even on current systems which use only a few gate types. Our work aims to navigate this tradeoff between application expressivity and calibration overhead, and identify what instructions vendors should implement to get the best expressivity with acceptable calibration time.Studying this tradeoff is challenging because of the diversity in QC application requirements, the need to optimize applications for widely different hardware gate types and noise variations across gate types. Therefore, our work develops NuOp, a flexible compilation pass based on numerical optimization, to efficiently decompose application operations into arbitrary hardware gate types. Using NuOp and four important quantum applications, we study the instruction set proposals of Rigetti and Google, with realistic noise simulations and a calibration model. Our experiments show that implementing 4-8 types of 2Q gates is sufficient to attain nearly the same expressivity as a full continuous gate family, while reducing the calibration overhead by two orders of magnitude. With several vendors proposing rich gate families as means to higher fidelity, our work has potential to provide valuable instruction set design guidance for near-term QC systems.
Quantum computing represents a fundamental shift in computation, promising to solve problems currently intractable for classical computers. However, misconceptions persist; quantum computers are not universally faster, nor do they replace classical systems. Current Noisy Intermediate-Scale Quantum (NISQ) devices face significant challenges, including decoherence, high error rates, and limited scalability. Additionally, leveraging quantum systems requires rethinking traditional computing principles, adopting different programming models, and addressing the complexities of integrating quantum and classical workflows, making their practical use in computer science both demanding and non-trivial. This article provides a system-level perspective on quantum computing for computer scientists, software engineers, and IT professionals, examining its current capabilities, key architectural and software challenges, and potential paths toward quantum advantage in real-world applications within hybrid quantum-classical environments.