arXiv subjects

Etienne Granet

Publications and source records attributed to Etienne Granet.

At least 19 recordsLinked to original sources

arXiv2026

Backpropagating Pauli Propagation

We develop a backpropagation algorithm for evaluating parameter gradients in quantum circuits using Pauli propagation simulation. The method has computational complexity comparable to that of standard sparse Pauli simulation techniques, while producing gradients whose accuracy is of the same order as the corresponding observable expectation values. By exploiting the reversibility of quantum circuits, the algorithm reduces the memory cost by a factor of $\mathcal{O}(n_\text{param})$ compared with conventional reverse-mode automatic differentiation, where $n_\text{param}$ denotes the number of parameters in the circuit. Compared with finite difference methods, the algorithm is $\mathcal{O}(n_\text{param})$ more efficient in function evaluations. These features enable efficient and accurate classical optimization of quantum circuits for applications such as state preparation and time-evolution compression, while also allowing operator-complexity measures such as the operator stabilizer Rényi entropy to be monitored and regularized during optimization. We demonstrate the method by optimizing low-energy state-preparation circuits for transverse-field Ising models in one, two, and three dimensions and for the three-dimensional Heisenberg model, and by compressing two-dimensional time-evolution circuits.

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arXiv2026

Dynamical structure factor with a pumping approach on a trapped-ion quantum computer

Dynamical structure factors (DSF) measured with neutron-scattering experiments provide key insights into the structure of materials. Their computation requires both the preparation of an equilibrium state and the implementation of Hamiltonian dynamics. We demonstrate the feasibility of computing DSF on the Quantinuum Reimei trapped-ion quantum computer, comparing the DSF of 1D Heisenberg model on $20$ sites, and that of the copper sulfate crystal. To that end, we introduce a pumping approach for computing the DSF $S(q,ω)$ on quantum computers that enables targeting specific arbitrary values of frequencies $ω$. This method time-evolves the initial state using a time-dependent Hamiltonian perturbed by a source term oscillating at the target frequency $ω$. When targeting only a few frequency values, this approach provides a significant reduction in shot overhead compared to previous methods.

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arXiv2026

Spectral functions on a quantum computer through system-environment interaction

Spectral functions measured with angle-resolved photoemission spectroscopy (ARPES) provide key insight to elucidate the band structure of materials. Comparison with theory requires computing dynamical one-point functions in some equilibrium state, which can be classically challenging. Their measurement on quantum computers poses multiple problems and comes with a large sampling overhead when standard techniques are used. We introduce an efficient way of measuring spectral functions on a quantum computer by directly modeling the interaction of the system with the environment involved in ARPES experiments. We develop quantum circuits whose local expectation values are proportional to the spectral function $A(k,ω)$ for all momentum $k$ and a specific chosen frequency $ω$. Although coming with a qubit and two-qubit gate overhead, our approach requires $O(N)$ times less sampling than previous approaches, translating into a factor $O(N)$ faster in runtime, and is particularly adapted to ion-trap quantum computers. The algorithm requires to implement a fermionic Fourier transform (FFT). We write out an efficient gate decomposition for generic radix-$n$ FFT and benchmark it on hardware for radix-$3$ on $27$ qubits. We finally demonstrate our algorithm on a Quantinuum System Model H2 ion-trap system, computing the spectral function on a one-dimensional system of $27$ sites, using $54$ qubits.

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arXiv2026

Digital quantum magnetism on a trapped-ion quantum computer

Digital quantum matter -- realized when discrete quantum gates approximate continuous time evolution -- is susceptible to heating into chaotic, structureless states. If digitization errors are adequately suppressed, a long-lived transient regime of approximately energy-conserving dynamics can be observed on gate-based quantum computers. Conservation of energy, in turn, enables the exploration of a wide variety of complex behaviors observed in equilibrium systems, ranging from the nontrivial microscopic origins of thermalization itself to the stabilization of effective models hosting exotic emergent properties. Here, we use Quantinuum's system model H2 quantum computer to simulate digitized dynamics of the quantum Ising model, suppressing digitization errors well enough to observe thermalization on timescales that severely challenge classical simulation methods. Relaxation of an inhomogeneous state reveals an emergent hydrodynamics due to approximate energy conservation, and we compute the associated diffusion constant. By reprogramming our simulations to take place on a triangular lattice with periodic boundary conditions, we observe thermalization consistent with emergent gauge and topological constraints resulting from lattice frustration. Our results were enabled by continued advances in two-qubit gate quality (native partial entangler fidelities of $99.94(1)\%$), and establish digital quantum computers as powerful tools for studying (effectively) continuous-time dynamics.

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arXiv2026

Adiabatic preparation of thermal states and entropy-noise relation on noisy quantum computers

We consider the problem of preparing thermal equilibrium states at finite temperature on quantum computers. Assuming thermalization, we show that states that are locally at thermal equilibrium can be prepared by evolving adiabatically an initial thermal Gibbs state of a simple Hamiltonian with an interpolating time-dependent Hamiltonian, identically to adiabatic ground state preparation. We argue that the entropy density of local density matrices is conserved during the adiabatic evolution in the thermodynamic limit, so that both the entropy and energy of the final state can be computed, and thus the final temperature too. We show that in the presence of hardware noise, the entropy created by the noisy evolution can be precisely benchmarked with mirror circuits. We give numerical evidence that the resulting thermal state preparation protocol is noise-resilient for depolarizing noise, in the sense that the energy-temperature curve measured on a noisy quantum computer is remarkably insensitive to the amplitude of depolarizing noise in the state preparation. We finally propose a protocol to estimate the lack of adiabaticity in a given actual Trotter implementation of the dynamics. We test our protocol on Quantinuum's H1-1 ion-trap device. We measure that a circuit with $640$ two-qubit gates implemented on hardware generates an entropy per site of $0.166 \pm 0.0045$, giving a benchmark metric for this state preparation. We report the preparation of a thermal state with temperature $2.56 \pm 0.26$ of the Ising model in size $5\times 4$.

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arXiv2026

Effect of slowly decaying long-range interactions on topological qubits

We study the robustness of topological ground state degeneracy to long-range interactions in quantum many-body systems. We focus on slowly decaying two-body interactions that scale like a power-law $1/r^α$ where $α$ is smaller than the spatial dimension; such interactions are beyond the reach of known stability theorems which only apply to short-range or rapidly decaying long-range perturbations. Our main result is a computation of the ground state splitting of several toy models, which are variants of the 1D Ising model $H = -\sum_i σ^z_i σ^z_{i+1} + λ\sum_{ij} |i-j|^{-α} σ^x_i σ^x_j$ with $λ> 0$ and $α< 1$. In one variant, the power-law interactions are replaced by all-to-all interactions, $\fracλ{4 L^α}\sum_{ij} σ^x_i σ^x_j$, where $L$ is the system size, while the other variant has true power-law interactions but is built out of quantum rotors rather than Ising spins. These models are also closely connected to the Kitaev p-wave wire model with power-law density-density interactions. In these examples, we find that the splitting $δ$ scales like a stretched exponential $δ\sim \exp(-C L^{\frac{1+α}{2}})$. Our computations are based on path integral techniques similar to the instanton method introduced by Coleman. We also study another toy model with long-range interactions that can be analyzed without path integral techniques and that shows similar behavior.

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arXiv2026

Superconducting pairing correlations on a trapped-ion quantum computer

The Fermi-Hubbard model is the starting point for the simulation of many strongly correlated materials, including high-temperature superconductors, whose modelling is a key motivation for the construction of quantum simulation and computing devices. However, the detection of superconducting pairing correlations has so far remained out of reach, both because of their off-diagonal character - which makes them inaccessible to local density measurements - and because of the difficulty of preparing superconducting states. Here, we report measurement of significant pairing correlations in three different regimes of Fermi-Hubbard models simulated on Quantinuum's Helios trapped-ion quantum computer. Specifically, we measure non-equilibrium pairing induced by an electromagnetic field in the half-filled square lattice model, d-wave pairing in an approximate ground state of the checkerboard Hubbard model at $1/6$-doping, and s-wave pairing in a bilayer model relevant to nickelate superconductors. These results show that a quantum computer can reliably create and probe physically relevant states with superconducting pairing correlations, opening a path to the exploration of superconductivity with quantum computers.

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arXiv2025

Ground State Energy via Adiabatic Evolution and Phase Measurement for a Molecular Hamiltonian on an Ion-Trap Quantum Computer

Estimating molecular ground-state energies is a central application of quantum computing, requiring both the preparation of accurate quantum states and efficient energy readout. Understanding the effect of hardware noise on these experiments is crucial to distinguish errors that have low impact, errors that can be mitigated, and errors that must be reduced at the hardware level. We ran a state preparation and energy measurement protocol on an ion-trap quantum computer, without any non-scalable off-loading of computational tasks to classical computers, and show that leakage errors are the main obstacle to chemical accuracy. More specifically, we apply adiabatic state preparation to prepare the ground state of a six-qubit encoding of the H3+ molecule and extract its energy using a noise-resilient variant of iterative quantum phase estimation. Our results improve upon the classical Hartree-Fock energy. Analyzing the effect of hardware noise on the result, we find that while coherent and incoherent noise have little influence, the hardware results are mainly impacted by leakage errors. Absent leakage errors, noisy numerical simulations show that with our experimental settings we would have achieved close to chemical accuracy, even shot noise included. These insights highlight the importance of targeting leakage suppression in future algorithm and hardware development.

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arXiv2025

Simulating sparse SYK model with a randomized algorithm on a trapped-ion quantum computer

The Sachdev-Ye-Kitaev (SYK) model describes a strongly correlated quantum system that shows a strong signature of quantum chaos. Due to its chaotic nature, the simulation of real-time dynamics becomes quickly intractable by means of classical numerics, and thus, quantum simulation is deemed to be an attractive alternative. Nevertheless, quantum simulations of the SYK model on noisy quantum processors are severely limited by the complexity of its Hamiltonian. In this work, we simulate the real-time dynamics of a sparsified version of the SYK model with 24 Majorana fermions on a trapped-ion quantum processor. We adopt a randomized quantum algorithm, TETRIS, and develop an error mitigation technique tailored to the algorithm. Leveraging the hardware's high-fidelity quantum operations and all-to-all connectivity of the qubits, we successfully calculate the Loschmidt amplitude for sufficiently long times so that its decay is observed. Based on the experimental and further numerical results, we assess the future possibility of larger-scale simulations of the SYK model by estimating the required quantum resources. Moreover, we present a scalable mirror-circuit benchmark based on the randomized SYK Hamiltonian and the TETRIS algorithm, which we argue provides a better estimate of the decay of fidelity for local observables than standard mirror-circuits.

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arXiv2025

BenchQC -- Scalable and modular benchmarking of industrial quantum computing applications

We present BenchQC, a research project funded by the state of Bavaria, which promotes an application-centric perspective for benchmarking real-world quantum applications. Diverse use cases from industry consortium members are the starting point of a benchmarking workflow, that builds on the open-source platform QUARK, encompassing the full quantum software stack from the hardware provider interface to the application layer. By identifying and evaluating key metrics across the entire pipeline, we aim to uncover meaningful trends, provide systematic guidance on quantum utility, and distinguish promising research directions from less viable approaches. Ultimately, this initiative contributes to the broader effort of establishing reliable benchmarking standards that drive the transition from experimental demonstrations to practical quantum advantage.

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arXiv2025

AppQSim: Application-oriented benchmarks for Hamiltonian simulation on a quantum computer

We introduce AppQSim, a benchmarking suite for quantum computers focused on applications of Hamiltonian simulation. We consider five different settings for which we define a precise task and score: condensed matter and material simulation (dynamic and static properties), nuclear magnetic resonance simulation, chemistry ground state preparation, and classical optimization. These five different benchmark tasks display different resource requirements and scalability properties. We introduce a metric to evaluate the quality of the output of a tested quantum hardware, called distinguishability cost, defined as the minimal number of gates that a perfect quantum computer would have to run to certify that the output of the benchmarked hardware is incorrect.

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arXiv2024

Analog simulation of noisy quantum circuits

It is well-known that simulating quantum circuits with low but non-zero hardware noise is more difficult than without noise. It requires either to perform density matrix simulations (coming with a space overhead) or to sample over "quantum trajectories" where Kraus operators are inserted randomly (coming with a runtime overhead). We propose a simulation technique based on a representation of hardware noise in terms of trajectories generated by operators that remain close to identity at low noise. This representation significantly reduces the variance over the quantum trajectories, speeding up noisy simulations by factors around $10$ to $100$. As a by-product, we provide a formula to factorize multiple-Pauli channels into a concatenation of single Pauli channels.

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arXiv2024

Experimental Demonstration of Break-Even for the Compact Fermionic Encoding

The utility of solving the Fermi-Hubbard model has been estimated in the billions of dollars. Digital quantum computers can in principle address this task, but have so far been limited to quasi one-dimensional models. This is because of exponential overheads caused by the interplay of noise and the non-locality of the mapping between fermions and qubits. Here, we show experimentally that a recently developed local encoding can overcome this problem. We develop a new compilation scheme, called "corner hopping", that reduces the cost of simulating fermionic hopping by 42% which allows us to conduct the largest digital quantum simulations of a fermionic model to date, using a trapped ion quantum computer to prepare adiabatically the ground state of a 6 x 6 spinless Fermi-Hubbard model encoded in 48 physical qubits. We also develop two new error mitigation schemes for systems with conserved quantities, one based on local postselection and one on extrapolation of local observables. Our results suggest that Fermi-Hubbard models beyond classical simulability can be addressed by digital quantum computers without large increases in gate fidelity.

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arXiv2024

Dilution of error in digital Hamiltonian simulation

We provide analytic, numerical and experimental evidence that the amount of noise in digital quantum simulation of local observables can be independent of system size in a number of situations. We provide a microscopic explanation of this dilution of errors based on the "relevant string length" of operators, which is the length of Pauli strings in the operator at time $s$ that belong to the exponentially small subspace of strings that can give a non-zero expectation value at time $t$. We show that this explanation can predict when dilution of errors occurs and when it does not. We propose an error mitigation method whose efficiency relies on this mechanism. Our findings imply that digital quantum simulation with noisy devices is in appropriate cases scalable in the sense that gate errors do not need to be reduced linearly to simulate larger systems.

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arXiv2024

Practicality of quantum adiabatic algorithm for chemistry applications

Despite its simplicity and strong theoretical guarantees, adiabatic state preparation has received considerably less interest than variational approaches for the preparation of low-energy electronic structure states. Two major reasons for this are the large number of gates required for Trotterising time-dependent electronic structure Hamiltonians, as well as discretisation errors heating the state. We show that a recently proposed randomized algorithm, which implements exact adiabatic evolution without heating and with far fewer gates than Trotterisation, can overcome this problem. We develop three methods for measuring the energy of the prepared state in an efficient and noise-resilient manner, yielding chemically accurate results on a 4-qubit molecule in the presence of realistic gate noise, without the need for error mitigation. These findings suggest that adiabatic approaches to state preparation could play a key role in quantum chemistry simulations both in the era of noisy as well as error-corrected quantum computers.

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arXiv2024

Benchmarking a heuristic Floquet adiabatic algorithm for the Max-Cut problem

According to the adiabatic theorem of quantum mechanics, a system initially in the ground state of a Hamiltonian remains in the ground state if one slowly changes the Hamiltonian. This can be used in principle to solve hard problems on quantum computers. Generically, however, implementation of this Hamiltonian dynamics on digital quantum computers requires scaling Trotter step size with system size and simulation time, which incurs a large gate count. In this work, we argue that for classical optimization problems, the adiabatic evolution can be performed with a fixed, finite Trotter step. This "Floquet adiabatic evolution" reduces by several orders of magnitude the gate count compared to the usual, continuous-time adiabatic evolution. We give numerical evidence using matrix-product-state simulations that it can optimally solve the Max-Cut problem on $3$-regular graphs in a large number of instances, with surprisingly low runtime, even with bond dimensions as low as $D=2$. Extrapolating our numerical results, we estimate the resources needed for a quantum computer to compete with classical exact or approximate solvers for this specific problem.

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arXiv2024

A noise-limiting quantum algorithm using mid-circuit measurements for dynamical correlations at infinite temperature

It is generally considered that the signal output by a quantum circuit is attenuated exponentially fast in the number of gates. This letter explores how algorithms using mid-circuit measurements and classical conditioning as computational tools (and not as error mitigation or correction subroutines) can be naturally resilient to complete decoherence, and maintain quantum states with useful properties even for infinitely deep noisy circuits. Specifically, we introduce a quantum channel built out of mid-circuit measurements and feed-forward, that can be used to compute dynamical correlations at infinite temperature and canonical ensemble expectation values for any Hamiltonian. The unusual property of this algorithm is that in the presence of a depolarizing channel it still displays a meaningful, non-zero signal in the large depth limit. We showcase the noise resilience of this quantum channel on Quantinuum's H1-1 ion-trap quantum computer.

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arXiv2023

Continuous Hamiltonian dynamics on digital quantum computers without discretization error

We introduce an algorithm to compute Hamiltonian dynamics on digital quantum computers that requires only a finite circuit depth to reach an arbitrary precision, i.e. achieves zero discretization error with finite depth. This finite number of gates comes at the cost of an attenuation of the measured expectation value by a known amplitude, requiring more shots per circuit. The gate count for simulation up to time $t$ is $O(t^2μ^2)$ with $μ$ the $1$-norm of the Hamiltonian, without dependence on the precision desired on the result, providing a significant improvement over previous algorithms. The only dependence in the norm makes it particularly adapted to non-sparse Hamiltonians. The algorithm generalizes to time-dependent Hamiltonians, appearing for example in adiabatic state preparation. These properties make it particularly suitable for present-day relatively noisy hardware that supports only circuits with moderate depth.

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