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arXiv:quant-ph/0004014 · Journal of Modern Optics

RISQ-reduced instruction set quantum computers

Klaus Mølmer, Anders S⊘rensen

Published Nov 1, 2000• 8 citations
arXivHTMLPDF

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 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.

DOI
10.1080/09500340008232178

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Proceedings - International Symposium on Computer Architecture/Proceedings•May 31, 2022•39 citations
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.
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.
Trapped ions, trapped atoms, and NMR spin systems are all fine ways of building small “toy” quantum computers, each with its own advantages and disadvantages. There are also many other techniques which have been suggested, although these three so far remain in the lead for general-purpose quantum computing. However, the most powerful general-purpose quantum computers constructed to date have only about a dozen qubits, and this is not nearly large enough to make quantum computers useful rather than merely interesting. (Larger systems have been used to demonstrate particular quantum information processing techniques, but these cannot as yet be used to implement arbitrary quantum algorithms.) Although it is not completely clear how complex a general-purpose quantum computer needs to be, it is clear that such a device will involve thousands or even millions of qubits, rather than the dozens involved today. It is, therefore, important to consider whether there is any hope of scaling up these technologies to useful sizes, and we will consider each of the three approaches in turn, before turning briefly to alternative technologies which have not been discussed so far. Trapped ions Trapped ions initially look very promising as a candidate for scaling up, as it is possible to trap thousands of ions while keeping a reasonable distance between them. Early experiments relied on particular tricks which only work with systems of two ions, but this is not true of more recent work, and there is no reason in principle why these large strings of ions could not be controlled.
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.
Simulating quantum systems is one of the most important potential applications of quantum computers. The high-level circuit defining the simulation needs to be compiled into one that complies with hardware limitations such as qubit architecture (connectivity) and instruction (gate) set. General-purpose quantum compilers work at the gate level and have little knowledge of the mathematical properties of quantum applications, missing further optimization opportunities. Existing application-specific compilers only apply advanced optimizations in the scheduling procedure and are restricted to the CNOT or CZ gate set. In this work, we develop a compiler, named 2QAN, to optimize quantum circuits for 2-local qubit Hamiltonian simulation problems, a framework which includes the important quantum approximate optimization algorithm (QAOA). In particular, we exploit the flexibility of permuting different operators in the Hamiltonian (no matter whether they commute) and propose permutation-aware techniques for qubit routing, gate optimization and scheduling to minimize compilation overhead. 2QAN can target different architectures and different instruction sets. Compilation results on four applications (up to 50 qubits) and three quantum computers (namely, Google Sycamore, IBMQ Montreal and Rigetti Aspen) show that 2QAN outperforms state-of-the-art general-purpose compilers and application-specific compilers. Specifically, 2QAN can reduce the number of inserted SWAP gates by 11.5X, reduce overhead in hardware gate count by 68.5X, and reduce overhead in circuit depth by 21X. Experimental results on the Montreal device demonstrate that benchmarks compiled by 2QAN achieve the highest fidelity.