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Andreas Juul Bay-Smidt

Publications and source records attributed to Andreas Juul Bay-Smidt.

4 recordsLinked to original sources

A Platform-aware Compilation Framework for Fault-tolerant Quantum Computation

The compilation of an algorithm can vary significantly with the choice of physical hardware platform and error correction model. Yet, current compilation frameworks typically commit to a single architecture-hardware configuration, making it difficult to assess resource estimates across platforms. We present a platform-aware compilation framework that re-compiles a quantum circuit into a hardware-compatible instruction set as well as fault-tolerant operations and provides end-to-end resource estimates in terms of physical-qubit count, time-to-solution, and classical processing time. We benchmark the framework by obtaining end-to-end resource estimates for different compilers, each tailored to the functionalities of specific hardware modalities: connectivity, clock speed, and noise model. As part of this framework, we introduce a transversal active volume (t-AV) compilation architecture designed for the efficient execution of fault-tolerant operations in platforms supporting long-range logical connectivity. We benchmark the framework for Hamiltonian simulation of the 2D Fermi Hubbard model as well as for eigenenergy estimation of a small molecule (trimethylenemethane) as a candidate for early fault-tolerant demonstration of quantum chemistry. For the latter, we show that end-to-end quantum simulations can be achieved with $\sim10^4$ physical qubits and runtimes ranging from $10^2$ ms (photonics, superconducting) to $10^5$ ms (neutral atoms).

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Quantum simulation of nanographenes and Trotter error cancellation

Fault-tolerant quantum computing is a promising tool for simulating molecules and materials, but frequently-considered applications require substantial resources, and the gap between hardware capabilities and requirements remains significant. We propose quantum simulation of nanographene $π$-systems as relevant and scalable problems to span the gap between early and large-scale fault-tolerant quantum computing. We examine the efficiency of Trotterized quantum simulation, present a detailed analysis of worst-case, average-case and energy eigenvalue Trotter errors, and show that these Trotter error estimates vary by orders of magnitude. Trotter eigenvalue errors are obtained from a novel tensor-network-based approach which allows spectral analysis of product formulas for systems beyond brute-force calculation. Notably, we observe a Trotter error cancellation phenomenon whereby the Trotter error for energy differences between low-lying eigenstates is significantly smaller than the Trotter error for absolute energies, resulting in approximately an order of magnitude circuit depth reduction for quantum phase estimation calculation of energy gaps. This is a significant result because for most chemical applications, only energy differences are of practical relevance. We estimate that calculation of energy gaps to chemical accuracy between the ground- and excited-states within the Pariser--Parr--Pople model for large 2D nanographenes (up to 140 spin orbitals) requires circuits with $< 3.2 \times 10^7$ Toffoli gates. This work shows that considering details of chemically-relevant applications and exploiting error cancellation can lead to substantial reductions in resource requirements.

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A Monte Carlo approach to bound Trotter error

Trotter product formulas are a natural and powerful approach to perform quantum simulation. However, the error analysis of product formulas is challenging, and their cost is often overestimated. It is established that Trotter error can be bounded in terms of spectral norms of nested commutators of the Hamiltonian partitions [Childs et al., Phys. Rev. X 11, 011020], but evaluating these expressions is challenging, often achieved by repeated application of the triangle inequality, significantly loosening the bound. Here, we show that the spectral norm of an operator can be upper bounded by the spectral norm of an equivalent sign-problem-free operator, which can be calculated efficiently to large system sizes using projector Monte Carlo simulation. For a range of Hamiltonians and considering second-order formulas, we demonstrate that this Monte Carlo-based bound is often extremely tight, and even exact in some instances. For the uniform electron gas we reduce the cost of performing Trotterization from the literature by an order of magnitude. For the Pariser-Parr-Pople model for linear acene molecules, which has $\mathcal{O}(N^2)$ long-range interaction terms, we show that it suffices to use $\mathcal{O}(N^{0.57})$ Trotter steps and circuit depth $\mathcal{O}(N^{1.57})$ to implement Hamiltonian simulation. We hope that this approach will lead to a better understanding of the potential accuracy of Trotterization in a range of important applications.

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Fault-tolerant quantum simulation of generalized Hubbard models

Quantum simulations of strongly interacting fermionic systems, such as those described by the Hubbard model, are promising candidates for useful early fault-tolerant quantum computing applications. This paper presents Tile Trotterization, a generalization of plaquette Trotterization (PLAQ), which uses a set of tiles to construct Trotter decompositions of arbitrary lattice Hubbard models. The Tile Trotterization scheme also enables the simulation of more complex models, including the extended Hubbard model. We improve previous Hubbard model commutator bounds, further provide tight commutator bounds for periodic extended Hubbard models, and demonstrate the use of tensor network methods for this task. We consider applications of Tile Trotterization to simulate hexagonal lattice Hubbard models and compare the resource requirements of Tile Trotterization for performing quantum phase estimation to a qubitization-based approach, demonstrating that Tile Trotterization scales more efficiently with system size. These advancements significantly broaden the potential applications of early fault-tolerant quantum computers to models of practical interest in materials research and organic chemistry.

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