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Arianne Meijer-van de Griend

Publications and source records attributed to Arianne Meijer-van de Griend.

12 recordsLinked to original sources

Architecture-aware Unitary Synthesis

We present a novel architecture-aware transpilation method for exact general unitary gate synthesis on superconducting quantum hardware. Our approach is tightly integrated with the optimized block-ZXZ decomposition, exploiting its recursive structure to make hardware-aware decisions at each level of the recursion rather than treating transpilation as an independent post-processing step. The method introduces three key techniques: a greedy qubit mapping strategy that minimizes pairwise distances between physical qubits, an adaptive Gray code selection combined with qubit swapping that optimizes the construction of uniformly controlled Rz gates for the target topology, and a heuristic for reducing CNOT gates by exploiting the structure of long-range CNOT ladders. We benchmark our method against TKet, Qiskit, and Pennylane on the 20-qubit IQM Garnet (square lattice) and the 156-qubit IBM Marrakesh (heavy-hex) architectures with qubit counts ranging from 3 to 11. Our method achieves CNOT count reductions of up to 36 percent on the IQM Garnet and up to 34 percent on the IBM Marrakesh compared to the best competing transpiler, while simultaneously achieving transpilation speedups of up to 553x. Furthermore, our method is the only one capable of transpiling circuits beyond 10 qubits within a 30-minute time limit across both architectures.

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Shortest Path in Pauli Forest -- An Algorithm for Decomposing Pauli Exponentials to Quantum Circuits

Decomposing Pauli exponentials efficiently to quantum circuits has been the subject of intense research in recent years. Pauli exponentials are an essential component of many different quantum algorithms. Due to the error-prone nature of current and near term quantum devices, it is crucial that quantum circuits are as compact as possible. Several different types of algorithms have been developed to decompose Pauli exponentials into as short circuits as possible. We propose a novel algorithm for architecture-aware synthesis of Pauli exponentials that also determines the initial qubit placement on the device. We call this the Shortest Path in Pauli Forest algorithm. The results show an improved CNOT count and runtime for both random Pauli exponentials and molecular ansätze.

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Qubit Routing for (Almost) Free

In this paper, we give a mathematical proof that bounds the number of CNOT gates required to synthesize an $n$ qubit phase polynomial with $g$ terms to be at least $O(\frac{gn}{\max (\log g, 1)})$ and at most $O(gn)$. However, when targeting restricted hardware, not all CNOTs are allowed. If we were to use SWAP-based methods to route the qubits on the architecture such that the earlier synthesized gates are natively allowed, we increase the number of CNOTs by a routing overhead factor of $O(\log n) \leq α\leq O(n \log^2 n)$. However, if we only synthesize allowed gates, we do not need to route any qubits. Moreover, in that case the routing overhead factor is $1 \leq α\leq 4 \simeq O(1)$. Additionally, since phase polynomials and Hadamard gates together form a universal gate set, we get qubit routing for almost free.

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Optimizing State Preparation for Variational Quantum Regression on NISQ Hardware

The execution of quantum algorithms on modern hardware is often constrained by noise and qubit decoherence, limiting the circuit depth and the number of gates that can be executed. Circuit optimization techniques help mitigate these limitations, enhancing algorithm feasibility. In this work, we implement, optimize, and execute a variational quantum regression algorithm using a novel state preparation method. By leveraging ZX-calculus-based optimization techniques, such as Pauli pushing, phase folding, and Hadamard pushing, we achieve a more efficient circuit design. Our results demonstrate that these optimizations enable the successful execution of the quantum regression algorithm on current hardware. Furthermore, the techniques presented are broadly applicable to other quantum circuits requiring arbitrary real-valued state preparation, advancing the practical implementation of quantum algorithms.

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Architecture-Aware Synthesis of Stabilizer Circuits from Clifford Tableaus

Since quantum computing is currently in the NISQ-Era, compilation strategies to reduce the number of gates executed on specific hardware are required. In this work, we utilize the concept of synthesis of a data structure called Clifford tableaus, focusing on applying CNOTs within the respective connectivity graph of the quantum device. We hence contribute to the field of compilation or, more precisely, synthesis by reducing the number of CNOTs in the synthesized quantum circuit. Upon convergence, our method shows to outperform other state-of-the-art synthesis techniques, when executed with respect to a specific hardware. Upon executing the resulting circuits on real hardware, our synthesized circuits tend to increase the final fidelity and reduce the overall execution times.

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Technology and Performance Benchmarks of IQM's 20-Qubit Quantum Computer

Quantum computing has tremendous potential to overcome some of the fundamental limitations present in classical information processing. Yet, today's technological limitations in the quality and scaling prevent exploiting its full potential. Quantum computing based on superconducting quantum processing units (QPUs) is among the most promising approaches towards practical quantum advantage. In this article the basic technological approach of IQM Quantum Computers is described covering both the QPU and the rest of the full-stack quantum computer. In particular, the focus is on a 20-qubit quantum computer featuring the Garnet QPU and its architecture, which we will scale up to 150 qubits. We also present QPU and system-level benchmarks, including a median 2-qubit gate fidelity of 99.5% and genuinely entangling all 20 qubits in a Greenberger-Horne-Zeilinger (GHZ) state.

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Redefining Lexicographical Ordering: Optimizing Pauli String Decompositions for Quantum Compiling

In quantum computing, the efficient optimization of Pauli string decompositions is a crucial aspect for the compilation of quantum circuits for many applications, such as chemistry simulations and quantum machine learning. In this paper, we propose a novel algorithm for the synthesis of trotterized time-evolution operators that results in circuits with significantly fewer gates than previous solutions. Our synthesis procedure takes the qubit connectivity of a target quantum computer into account. As a result, the generated quantum circuit does not require routing, and no additional CNOT gates are needed to run the resulting circuit on a target device. We compare our algorithm against Paulihedral and TKET, and show a significant improvement for randomized circuits and different molecular ansatzes. We also investigate the Trotter error introduced by our ordering of the terms in the Hamiltonian versus default ordering and the ordering from the baseline methods and conclude that our method on average does not increase the Trotter error.

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Exposing the hidden layers and interplay in the quantum software stack

Current and near-future quantum computers face resource limitations due to noise and low qubit counts. Despite this, effective quantum advantage can still be achieved due to the exponential nature of bit-to-qubit conversion. However, optimizing the software architecture of these systems is essential to utilize available resources efficiently. Unfortunately, the focus on user-friendly quantum computers has obscured critical steps in the software stack, leading to ripple effects into the stack's upper layer induced by limitations in current qubit implementations. This paper unveils the hidden interplay among layers of the quantum software stack.

cs.SE↗

Dynamic Qubit Routing with CNOT Circuit Synthesis for Quantum Compilation

Many quantum computers have constraints regarding which two-qubit operations are locally allowed. To run a quantum circuit under those constraints, qubits need to be mapped to different quantum registers, and multi-qubit gates need to be routed accordingly. Recent developments have shown that compiling strategies based on the Steiner tree provide a competitive tool to route CNOTs. However, these algorithms require the qubit map to be decided before routing. Moreover, the qubit map is fixed throughout the computation, i.e. the logical qubit will not be moved to a different physical qubit register. This is inefficient with respect to the CNOT count of the resulting circuit. In this paper, we propose the algorithm PermRowCol for routing CNOTs in a quantum circuit. It dynamically remaps logical qubits during the computation, and thus results in fewer output CNOTs than the algorithms Steiner-Gauss and RowCol. Here we focus on circuits over CNOT only, but this method could be generalized to a routing and mapping strategy on Clifford+T circuits by slicing the quantum circuit into subcircuits composed of CNOTs and single-qubit gates. Additionally, PermRowCol can be used in place of Steiner-Gauss in the synthesis of phase polynomials as well as the extraction of quantum circuits from ZX diagrams.

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Architecture-Aware Synthesis of Phase Polynomials for NISQ Devices

We propose a new algorithm to synthesise quantum circuits for phase polynomials, which takes into account the qubit connectivity of the quantum computer. We focus on the architectures of currently available NISQ devices. Our algorithm generates circuits with a smaller CNOT depth than the algorithms currently used in Staq and tket, while improving the runtime with respect the former.

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Quantum Linear Algorithm for Edit Distance Using the Word QRAM Model

Many problems that can be solved in quadratic time have bit-parallel speed-ups with factor $w$, where $w$ is the computer word size. For example, edit distance of two strings of length $n$ can be solved in $O(n^2/w)$ time. In a reasonable classical model of computation, one can assume $w=Θ(\log n)$. There are conditional lower bounds for such problems stating that speed-ups with factor $n^ε$ for any $ε>0$ would lead to breakthroughs in complexity theory. However, these conditional lower bounds do not cover quantum models of computing. Indeed, Boroujeni et al. (J. ACM, 2021) showed that edit distance can be approximated within a factor $3$ in sub-quadratic time $O(n^{1.81})$ using quantum computing. They also showed that, in their chosen model of quantum computing, the approximation factor cannot be improved using sub-quadractic time. To break through the aforementioned classical conditional lower bounds and this latest quantum lower bound, we enrich the model of computation with a quantum random access memory (QRAM), obtaining what we call the word QRAM model. Under this model, we show how to convert the bit-parallelism of quadratic time solvable problems into quantum algorithms that attain speed-ups with factor $n$. The technique we use is simple and general enough to apply to many bit-parallel algorithms that use Boolean logics and bit-shifts. To apply it to edit distance, we first show that the famous $O(n^2/w)$ time bit-parallel algorithm of Myers (J. ACM, 1999) can be adjusted to work without arithmetic + operations. As a direct consequence of applying our technique to this variant, we obtain linear time edit distance algorithm under the word QRAM model for constant alphabet. We give further results on a restricted variant of the word QRAM model to give more insights to the limits of the model.

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CNOT circuit extraction for topologically-constrained quantum memories

Many physical implementations of quantum computers impose stringent memory constraints in which 2-qubit operations can only be performed between qubits which are nearest neighbours in a lattice or graph structure. Hence, before a computation can be run on such a device, it must be mapped onto the physical architecture. That is, logical qubits must be assigned physical locations in the quantum memory, and the circuit must be replaced by an equivalent one containing only operations between nearest neighbours. In this paper, we give a new technique for quantum circuit mapping (a.k.a. routing), based on Gaussian elimination constrained to certain optimal spanning trees called Steiner trees. We give a reference implementation of the technique for CNOT circuits and show that it significantly out-performs general-purpose routines on CNOT circuits. We then comment on how the technique can be extended straightforwardly to the synthesis of CNOT+Rz circuits and as a modification to a recently-proposed circuit simplification/extraction procedure for generic circuits based on the ZX-calculus.

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