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Improved Strategies for Fermionic Simulation with Global Interactions

Kaldenbach, Thierry, Gabriel Breuil

Published Apr 4, 2025• 0 citations
OpenAlex

Abstract

We present efficient quantum circuits for fermionic excitation operators tailored for ion trap quantum computers exhibiting the Mölmer-Sörensen (MS) gate. Such operators commonly arise in the study of static and dynamic properties in electronic structure problems using Unitary Coupled Cluster theory or Trotterized time evolution. We detail how the global MS interaction naturally suits the non-local structure of fermionic excitation operators under the Jordan-Wigner mapping and simultaneously provides optimal parallelism in their circuit decompositions. Compared to previous schemes on ion traps, our approach reduces the number of MS gates by factors of 2-, and 4, for single-, and double excitations, respectively. This improvement promises significant speedups and error reductions.

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Improved strategies for fermionic quantum simulation with global interactions

Thierry N. Kaldenbach, Erik Schultheis, Niklas Stewen +1 more

Abstract We present efficient quantum circuits for fermionic excitation operators tailored for ion trap quantum computers exhibiting the Mølmer-Sørensen (MS) gate. Such operators commonly arise in the study of static and dynamic properties in electronic structure problems using Unitary Coupled Cluster theory or Trotterized time evolution. We detail how the global MS interaction naturally suits the non-local structure of fermionic excitation operators under the Jordan-Wigner mapping and simultaneously provides optimal parallelism in their circuit decompositions. Compared to previous schemes on ion traps, our approach reduces the number of MS gates by factors of 2-, and 4, for single-, and double excitations, respectively. These improvements promise significant speedups and error reductions, which we demonstrate by characterizing our circuits under a realistic pulse-level noise model of a linear ion trap quantum processor.

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Efficient Simulation of Sparse, Non-Local Fermion Models

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Efficient simulation of interacting fermionic systems is a key application of near-term quantum computers, but is hindered by the overhead required to encode fermionic operators on qubit hardware. Here, we consider models with $N$ fermionic modes in which each participates in at most a constant number $d$ of interactions and study the circuit depth required to implement the Trotterized time evolution on qubit hardware with all-to-all connectivity. We introduce an encoding that augments each physical fermionic mode with a small number of auxiliary fermions, enabling the removal of Jordan--Wigner strings. Although the preparation of the auxiliary fermion state incurs an initial overhead, this state remains invariant under time evolution. As a result, long-time evolution can be implemented with asymptotically optimal circuit depth, reducing a previously multiplicative $O(\log N)$ overhead to an additive overhead. Our results thus establish that the simulation of sparse fermionic models on qubit hardware matches the performance achievable on ideal fermionic hardware up to constant factors and $O(dN)$ ancillary qubits.

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Optimisation and synthesis of quantum circuits with global gates

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Abstract Compiling quantum circuits to account for hardware restrictions is an essential part of the quantum computing stack. Circuit compilation allows us to adapt algorithm descriptions into a sequence of operations supported by real quantum hardware, and has the potential to significantly improve their performance when optimisation techniques are added to the process. One such optimisation technique is reducing the number of quantum gates that are needed to execute a circuit. For instance, methods for reducing the number of non-Clifford gates or CNOT gates from a circuit are an extensive research area that has gathered significant interest over the years. For certain hardware platforms such as trapped-ion quantum computers, we can leverage some of their special properties to further reduce the cost of executing a quantum circuit in them. In this work we use global interactions, such as the Global Mølmer–Sørensen (MS) gate present in trapped-ion hardware, to optimise and synthesise quantum circuits. We design and implement an algorithm that is able to compile an arbitrary quantum circuit into another circuit that uses global gates as the entangling operation, while optimising the number of global interactions needed. The algorithm is based on the ZX -calculus and uses a specialised circuit extraction routine that groups entangling gates into Global MS gates. We benchmark the algorithm in a variety of circuits, and show how it improves their performance under state-of-the-art hardware considerations in comparison to a naive algorithm and the Qiskit optimiser.

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As quantum computing scales up, circuits relying on sequential two-qubit gates face severe challenges from excessive depth and decoherence. In trapped-ion systems, global entangling gates offer a highly parallel alternative but are hindered by complex numerical optimization. We propose an efficient numerical framework for piecewise-constant amplitude-modulated global gates. Based on the Mølmer-Sørensen protocol, we utilize null-space projection for linear constraints of spin-motion coupling and tangent-space gradient descent to minimize laser power, while achieving high-order robustness against frequency drifts. At the application level, we identify a structural correspondence between hardware-native global interactions and Pauli strings in Hamiltonian simulation and propose an efficient compilation scheme. By reducing common physical models to fundamental X X interactions and formulating interaction graph partitioning as a Set Cover problem, we leverage global gates to significantly optimize the compilation process. Explicit pulse-level benchmarks further show that, for the tested weighted interaction graphs, the reduction in entangling-gate count can translate into a substantial reduction in total entangling duration. These results demonstrate that integrating hardware-native operations with tailored compilation strategies can substantially reduce circuit overhead, providing a practical roadmap for the codesign of near-term quantum simulators.

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Fermionic Gaussian circuits can be simulated efficiently on a classical computer, but become universal when supplemented with non-Gaussian operations. Similar to stabilizer circuits augmented with non-stabilizer resources, these non-Gaussian circuits can be simulated classically using rank- or extent-based methods. These methods decompose non-Gaussian states or operations into Gaussian ones, with runtimes that scale polynomially with measures of non-Gaussianity such as the rank and the extent -- quantities that typically grow exponentially with the number of non-Gaussian resources. Current fermionic rank- and extent-based simulators have mostly been limited to Gaussian circuits with magic-state injection. Extending them to mixed states and non-unitary channels has been hindered by the lack of known extent-optimized decompositions for physically relevant gates and noisy channels. In this work, we address this gap. First, we derive analytic decompositions for key non-Gaussian gates and channels, including decompositions for arbitrary two-qubit fermionic gates which are provably optimal for diagonal gates or those acting on Jordan-Wigner-adjacent qubit pairs. Second, we show that stochastic Pauli noise can reduce the effective extent of non-Gaussian rotation gates, but that fermionic magic is substantially more robust to such noise than stabilizer magic. Finally, we demonstrate how these decompositions can accelerate classical sampling from the output distribution of a quantum circuit. This involves a generalization of existing sparsification methods, previously limited to convex-unitary channels, to circuits involving intermediate measurements and feed-forward. Our decompositions also yield speedups for emulating noisy Pauli rotations with quasiprobability simulators in the large-angle/arbitrary-strength-noise and small-angle/low-noise parameter regimes.

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Quantum circuit synthesis for fermionic excitations in coupled cluster theory

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This work provides a step-by-step quantum computing derivation of the unitary coupled cluster singles and doubles ansatz. We show how the structure of the ansatz emerges from fermionic algebra under unitary constraints. By explicitly connecting second quantization, Jordan-Wigner mapping, and quantum circuit synthesis, we clarify conceptual gaps between quantum physics and quantum computing implementations, particularly regarding operator locality, commutation structure, and hardware realization. We exemplify the procedure on the singles and doubles coupled cluster ansatz for the hydrogen molecule.

quant-pharXiv:2601.07890•Jan 13, 2026•0 citations
We present efficient quantum circuits for fermionic excitation operators tailored for ion trap quantum computers exhibiting the Mölmer-Sörensen (MS) gate. Such operators commonly arise in the study of static and dynamic properties in electronic structure problems using Unitary Coupled Cluster theory or Trotterized time evolution. We detail how the global MS interaction naturally suits the non-local structure of fermionic excitation operators under the Jordan-Wigner mapping and simultaneously provides optimal parallelism in their circuit decompositions. Compared to previous schemes on ion traps, our approach reduces the number of MS gates by factors of 2-, and 4, for single-, and double excitations, respectively. This improvement promises significant speedups and error reductions.
Abstract We present efficient quantum circuits for fermionic excitation operators tailored for ion trap quantum computers exhibiting the Mølmer-Sørensen (MS) gate. Such operators commonly arise in the study of static and dynamic properties in electronic structure problems using Unitary Coupled Cluster theory or Trotterized time evolution. We detail how the global MS interaction naturally suits the non-local structure of fermionic excitation operators under the Jordan-Wigner mapping and simultaneously provides optimal parallelism in their circuit decompositions. Compared to previous schemes on ion traps, our approach reduces the number of MS gates by factors of 2-, and 4, for single-, and double excitations, respectively. These improvements promise significant speedups and error reductions, which we demonstrate by characterizing our circuits under a realistic pulse-level noise model of a linear ion trap quantum processor.
Efficient simulation of interacting fermionic systems is a key application of near-term quantum computers, but is hindered by the overhead required to encode fermionic operators on qubit hardware. Here, we consider models with NNN fermionic modes in which each participates in at most a constant number ddd of interactions and study the circuit depth required to implement the Trotterized time evolution on qubit hardware with all-to-all connectivity. We introduce an encoding that augments each physical fermionic mode with a small number of auxiliary fermions, enabling the removal of Jordan--Wigner strings. Although the preparation of the auxiliary fermion state incurs an initial overhead, this state remains invariant under time evolution. As a result, long-time evolution can be implemented with asymptotically optimal circuit depth, reducing a previously multiplicative O(log⁡N)O(\log N)O(logN) overhead to an additive overhead. Our results thus establish that the simulation of sparse fermionic models on qubit hardware matches the performance achievable on ideal fermionic hardware up to constant factors and O(dN)O(dN)O(dN) ancillary qubits.
Abstract Compiling quantum circuits to account for hardware restrictions is an essential part of the quantum computing stack. Circuit compilation allows us to adapt algorithm descriptions into a sequence of operations supported by real quantum hardware, and has the potential to significantly improve their performance when optimisation techniques are added to the process. One such optimisation technique is reducing the number of quantum gates that are needed to execute a circuit. For instance, methods for reducing the number of non-Clifford gates or CNOT gates from a circuit are an extensive research area that has gathered significant interest over the years. For certain hardware platforms such as trapped-ion quantum computers, we can leverage some of their special properties to further reduce the cost of executing a quantum circuit in them. In this work we use global interactions, such as the Global Mølmer–Sørensen (MS) gate present in trapped-ion hardware, to optimise and synthesise quantum circuits. We design and implement an algorithm that is able to compile an arbitrary quantum circuit into another circuit that uses global gates as the entangling operation, while optimising the number of global interactions needed. The algorithm is based on the ZX -calculus and uses a specialised circuit extraction routine that groups entangling gates into Global MS gates. We benchmark the algorithm in a variety of circuits, and show how it improves their performance under state-of-the-art hardware considerations in comparison to a naive algorithm and the Qiskit optimiser.
As quantum computing scales up, circuits relying on sequential two-qubit gates face severe challenges from excessive depth and decoherence. In trapped-ion systems, global entangling gates offer a highly parallel alternative but are hindered by complex numerical optimization. We propose an efficient numerical framework for piecewise-constant amplitude-modulated global gates. Based on the Mølmer-Sørensen protocol, we utilize null-space projection for linear constraints of spin-motion coupling and tangent-space gradient descent to minimize laser power, while achieving high-order robustness against frequency drifts. At the application level, we identify a structural correspondence between hardware-native global interactions and Pauli strings in Hamiltonian simulation and propose an efficient compilation scheme. By reducing common physical models to fundamental X X interactions and formulating interaction graph partitioning as a Set Cover problem, we leverage global gates to significantly optimize the compilation process. Explicit pulse-level benchmarks further show that, for the tested weighted interaction graphs, the reduction in entangling-gate count can translate into a substantial reduction in total entangling duration. These results demonstrate that integrating hardware-native operations with tailored compilation strategies can substantially reduce circuit overhead, providing a practical roadmap for the codesign of near-term quantum simulators.
Fermionic Gaussian circuits can be simulated efficiently on a classical computer, but become universal when supplemented with non-Gaussian operations. Similar to stabilizer circuits augmented with non-stabilizer resources, these non-Gaussian circuits can be simulated classically using rank- or extent-based methods. These methods decompose non-Gaussian states or operations into Gaussian ones, with runtimes that scale polynomially with measures of non-Gaussianity such as the rank and the extent -- quantities that typically grow exponentially with the number of non-Gaussian resources. Current fermionic rank- and extent-based simulators have mostly been limited to Gaussian circuits with magic-state injection. Extending them to mixed states and non-unitary channels has been hindered by the lack of known extent-optimized decompositions for physically relevant gates and noisy channels. In this work, we address this gap. First, we derive analytic decompositions for key non-Gaussian gates and channels, including decompositions for arbitrary two-qubit fermionic gates which are provably optimal for diagonal gates or those acting on Jordan-Wigner-adjacent qubit pairs. Second, we show that stochastic Pauli noise can reduce the effective extent of non-Gaussian rotation gates, but that fermionic magic is substantially more robust to such noise than stabilizer magic. Finally, we demonstrate how these decompositions can accelerate classical sampling from the output distribution of a quantum circuit. This involves a generalization of existing sparsification methods, previously limited to convex-unitary channels, to circuits involving intermediate measurements and feed-forward. Our decompositions also yield speedups for emulating noisy Pauli rotations with quasiprobability simulators in the large-angle/arbitrary-strength-noise and small-angle/low-noise parameter regimes.
This work provides a step-by-step quantum computing derivation of the unitary coupled cluster singles and doubles ansatz. We show how the structure of the ansatz emerges from fermionic algebra under unitary constraints. By explicitly connecting second quantization, Jordan-Wigner mapping, and quantum circuit synthesis, we clarify conceptual gaps between quantum physics and quantum computing implementations, particularly regarding operator locality, commutation structure, and hardware realization. We exemplify the procedure on the singles and doubles coupled cluster ansatz for the hydrogen molecule.