Introduction to UniversalQCompiler

Iten, Raban; Reardon-Smith, Oliver; Emanuel, Malvetti,; Luca, Mondada,; Pauvert, Gabrielle; Redmond, Ethan; Kohli, Ravjot Singh; Colbeck, Roger

doi:10.48550/arxiv.1904.01072

Cited by 21 publications

(42 citation statements)

References 27 publications

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“…In order to improve the classical computation time, we do not consider all possible qubit splittings, but randomly sample 100 splittings and choose the one with the largest number of non-zero elements in one column. We use the dense state preparation scheme from [5], implemented in [10], which achieves near optimal C-not counts for arbitrary dense states. The results are presented in Figure 4.…”

Section: Numerical Results For Sparse State Preparationmentioning

confidence: 99%

“…Computing the vector takes O(2 n ) and applying the reflection takes O(2 m+n ). Producing the circuit takes O(2 3n/2 ) according to Appendix B.4 of [10]. Thus the classical complexity is O(2 m+n (2 m + 2 n/2 )).…”

Section: A Dense Isometriesmentioning

confidence: 99%

“…decomposition and the Cosine-sine decomposition both require O(2 3n ) [10]. A high performance implementation for a decomposition of dense unitaries based on Householder reflections is presented in [14].…”

Section: A Dense Isometriesmentioning

confidence: 99%

“…Near optimal methods for decomposing arbitrary isometries exist, and again they achieve C-not counts approximately twice as large as the best known lower bounds. The implementation of quantum channels has been considered in [9] and these have been implemented along with POVMs and instruments in [10].…”

Section: Introductionmentioning

confidence: 99%

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Quantum Circuits for Sparse Isometries

Emanuel

Iten

Colbeck

2021

Quantum

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We consider the task of breaking down a quantum computation given as an isometry into C-NOTs and single-qubit gates, while keeping the number of C-NOT gates small. Although several decompositions are known for general isometries, here we focus on a method based on Householder reflections that adapts well in the case of sparse isometries. We show how to use this method to decompose an arbitrary isometry before illustrating that the method can lead to significant improvements in the case of sparse isometries. We also discuss the classical complexity of this method and illustrate its effectiveness in the case of sparse state preparation by applying it to randomly chosen sparse states.

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Section: Numerical Results For Sparse State Preparationmentioning

confidence: 99%

Section: A Dense Isometriesmentioning

confidence: 99%

Section: A Dense Isometriesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Quantum Circuits for Sparse Isometries

Emanuel

Iten

Colbeck

2021

Quantum

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“…However, to actually run on real hardware, these programs must be compiled down to an assembly language. OpenQASM [18,19] is the most widely used assembly [20], and it is backed by wide academic study such as LLVM integration [21], conversion tools [22], benchmarks [23], and formal verification [20].…”

Section: B Native Gatesmentioning

confidence: 99%

Faster and More Reliable Quantum SWAPs via Native Gates

Gokhale¹,

Tomesh²,

Suchara³

et al. 2021

Preprint

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Due to the sparse connectivity of superconducting quantum computers, qubit communication via SWAP gates accounts for the vast majority of overhead in quantum programs. We introduce a method for improving the speed and reliability of SWAPs at the level of the superconducting hardware's native gateset. Our method relies on four techniques: 1) SWAP Orientation, 2) Cross-Gate Pulse Cancellation, 3) Commutation through Cross-Resonance, and 4) Cross-Resonance Polarity. Importantly, our Optimized SWAP is bootstrapped from the pre-calibrated gates, and therefore incurs zero calibration overhead. We experimentally evaluate our optimizations with Qiskit Pulse on IBM hardware. Our Optimized SWAP is 11% faster and 13% more reliable than the Standard SWAP. We also experimentally validate our optimizations on application-level benchmarks. Due to (a) the multiplicatively compounding gains from improved SWAPs and (b) the frequency of SWAPs, we observe typical improvements in success probability of 10-40%. The Optimized SWAP is available through the SuperstaQ platform.

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Exploring ab initio machine synthesis of quantum circuits

2023

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Gate-level quantum circuits are often derived manually from higher level algorithms. While this suffices for small implementations and demonstrations, ultimately automatic circuit design will be required to realise complex algorithms using hardware-specific operations and connectivity. Therefore, ab initio creation of circuits within a machine, either a classical computer or a hybrid quantum-classical device, is of key importance. We explore a range of established and novel techniques for the synthesis of new circuit structures, the optimisation of parameterised circuits, and the efficient removal of low-value gates via the quantum geometric tensor. Using these techniques we tackle the tasks of automatic encoding of unitary processes and translation (recompilation) of a circuit from one form to another. Using emulated quantum computers with various noise-free gate sets we provide simple examples involving up to 10 qubits, corresponding to 20 qubits in the augmented space we use. Further applications of specific relevance to chemistry modelling are considered in a sister paper, 'Exploiting subspace constraints and ab initio variational methods for quantum chemistry'.

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Introduction to UniversalQCompiler

Cited by 21 publications

References 27 publications

Quantum Circuits for Sparse Isometries

Quantum Circuits for Sparse Isometries

Faster and More Reliable Quantum SWAPs via Native Gates

Exploring ab initio machine synthesis of quantum circuits

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