arXiv subjects

David Muñoz Ramo

Publications and source records attributed to David Muñoz Ramo.

At least 19 recordsLinked to original sources

arXiv2026

Quantum Error-Corrected Computation of Molecular Energies

We present the first demonstration of an end-to-end pipeline with quantum error correction (QEC) for a quantum computation of the electronic structure of molecular systems. We calculate the ground-state energy of molecular hydrogen, using quantum phase estimation (QPE) on qubits encoded with the $[[7,1,3]]$ color code on Quantinuum H2--2. We obtain improvements in computational fidelity by (1) introducing several partially fault-tolerant (FT) techniques for the Clifford+$R_{Z}$ (arbitrary-angle single-qubit rotation) gate set, and (2) integrating Steane QEC gadgets for real-time error correction. In particular, the latter enhances the QPE circuits' performance despite the complexity of the extra QEC circuitry. The encoded circuits contain up to 1585 (546) fixed and 7202 (1702) conditional physical two-qubit gates (mid-circuit measurements), and $\sim$3900 ($\sim$760) total operations are applied on average. The energy $E$ is experimentally estimated to within $E - E_{\mathrm{FCI}} = 0.001(13)$ hartree, where $E_{\mathrm{FCI}}$ denotes the exact ground state energy within the given basis set. Additionally, we conduct numerical simulations with tunable noise parameters to identify the dominant sources of noise. We find that orienting the QEC protocols towards higher memory noise protection is the most promising avenue to improve our experimental results.

quant-ph↗

arXiv2026

Large-scale NMR simulation on a trapped-ion quantum computer

Simulating nuclear magnetic resonance (NMR) spectra is a promising application of quantum simulation. Using Quantinuum's System Model H2, a trapped-ion quantum computer, we demonstrate an end-to-end, large-scale digital NMR simulation of a classically challenging benchmark molecule, 1,2-di-tert-butyl-diphosphane. We implement a hardware-efficient reduction of the nuclear-spin Hamiltonian, enabling Trotterized real-time evolution of an effective 21-spin model with tailored error suppression to reduce the effects of device noise. The reconstructed liquid-state proton NMR spectrum agrees with classical reference calculations and reproduces key spectroscopic features that previous quantum hardware demonstrations did not capture. Given the widespread use of NMR in chemical analysis and industrial research, these results advance digital quantum simulation of NMR spectra towards practical quantum utility.

quant-ph↗

arXiv2026

A Quantum-HPC Hybrid Workflow for Reaction-Center Electronic Dynamics: Application to a Cytochrome P450-Inspired Iron-Complex Model

We introduce population-transfer dynamics as a practical validation observable for active-space-derived reduced Hamiltonians in multistate reaction-center chemistry. Using a cytochrome P450-inspired Fe-complex model, we construct a reaction-coordinate-dependent effective Hamiltonian from state-averaged complete active-space self-consistent field (SA-CASSCF) calculations, map it to a quantum-circuit representation suitable for current hardware, and propagate dynamics from the reactant-side ground state. The reduced Hamiltonian reproduces the SA-CASSCF reference with an RMS deviation of 0.030 eV and a maximum absolute deviation of 0.143 eV. As a dynamics-based diagnostic, the product-manifold population p_P(t) identifies a pronounced near-degeneracy region around x = 0.3, where state mixing is strongest. Classical exact time evolution yields a product population of 0.488 at x = 0.3 after 10 fs, compared with 7.26 x 10^-2 at x = 0.2 and 5.90 x 10^-3 at x = 0.0. To enable execution on current trapped-ion hardware, we examine the trade-off between dynamical fidelity and circuit resources through coupling pruning and first-order Trotterization. A coupling cutoff of 0.02 eV reduces the non-zero coupling set from 32 to 7 while preserving the dominant transfer pathways, and M = 30 provides the best practical operating point. Finally, we demonstrate the workflow on Quantinuum's trapped-ion quantum computer Reimei. The hardware reproduces the key reaction-coordinate trend identified by the classical model, including the maximum at x = 0.3, where the measured product population is 0.42 on hardware and 0.43 on the matched emulator. This work establishes a dynamics-based framework for assessing active-space-derived reduced Hamiltonians and demonstrates chemically interpretable multistate electronic dynamics on current trapped-ion hardware.

quant-ph↗

arXiv2026

Split-Evolution Quantum Phase Estimation for Particle-Conserving Hamiltonians

We present a hardware demonstration and resource analysis of split-evolution quantum phase estimation (SE-QPE) on a Quantinuum System Model H2 quantum computer. SE-QPE is a modification to canonical QPE for particle-conserving Hamiltonians in which controlled time evolution is replaced by CSWAP-based interference between a target register and a reference register. For factorizations of time evolution with a shared eigenbasis, SE-QPE preserves the phase-register outcome distribution of canonical QPE and, unlike with compute--uncompute substitutions, it remains compatible with non-exact eigenstates. The substitution removes controlled-simulation overhead and enables parallel evolution on two registers, reducing the depth of each phase-kickback block. Resource analysis for Trotterized double-factorized chemistry Hamiltonians shows that the substitution becomes increasingly favorable at higher phase powers and combining QPE and SE-QPE implementations can be a useful option. Over a range of FeMoco active spaces, SE-QPE reduces time evolution resources, with asymptotic reductions of about 33% in CX count, 25% in $T$ count, and an asymptotic depth ratio of $3/N$ for CX layers. On Quantinuum H2-2, a four-qubit model ethylene demonstration with explicit inverse QFT and repeated phase-kickback steps up to 8 phase bits yields distinct energies and shows the auxiliary registers provide useful error detection filters.

quant-ph↗

arXiv2026

Quantum State Preparation Of Multiconfigurational States For Quantum Chemistry

The ability to prepare states for quantum chemistry is a promising feature of quantum computers, and efficient techniques for chemical state preparation is an active area of research. In this paper, we implement and investigate two methods of quantum circuit preparation for multiconfigurational states for quantum chemical applications. It has previously been shown that controlled Givens rotations are universal for quantum chemistry. To prepare a selected linear combination of Slater determinants (represented as occupation number configurations) using Givens rotations, the gates that rotate between the reference and excited determinants need to be controlled on qubits outside the excitation (external controls), in general. We implement a method to automatically find the external controls required for utilizing Givens rotations to prepare multiconfigurational states on a quantum circuit. We compare this approach to an alternative technique that exploits the sparsity of the chemical state vector and find that the latter can outperform the method of externally controlled Givens rotations; highly reduced circuits can be obtained by taking advantage of the sparse nature (where the number of basis states is significantly less than 2$^{n_q}$ for $n_q$ qubits) of chemical wavefunctions. We demonstrate the benefits of these techniques in a range of applications, including the ground states of a strongly correlated molecule, matrix elements of the Q-SCEOM algorithm for excited states, as well as correlated initial states for a quantum subspace method based on quantum computed moments and quantum phase estimation.

quant-ph↗

arXiv2026

Quantum-HPC hybrid computation of biomolecular excited-state energies

We develop a workflow within the ONIOM framework and demonstrate it on the hybrid computing system consisting of the supercomputer Fugaku and the Quantinuum Reimei trapped-ion quantum computer. This hybrid platform extends the layered approach for biomolecular chemical reactions to accurately treat the active site, such as a protein, and the large and often weakly correlated molecular environment. Our result marks a significant milestone in enabling scalable and accurate simulation of complex biomolecular reactions

quant-ph↗

arXiv2025

Shorter width truncated Taylor series for Hamiltonian dynamics simulations

As established in the seminal work by Berry et al.[1], expanding the time evolution operator using truncated Taylor series (up to some order $K$) makes a good candidate for simulating Hamiltonian dynamics. Here, we adapt the method but present an alternative quantum circuit that maintains an equivalent asymptotic elementary gate cost but has an exponentially reduced number of ancilla qubits. This is realized by utilizing mid-circuit measurements (with early abort-and-restart of circuit execution), and transforming a series of multi-controlled$(H^k)$ to a series of singly-controlled$(H^{k'})$, where $H$ is a linear combination of unitaries and $k, k'$ are integers. The proposed circuit utilizes a total of $\lceil \log(K) \rceil + \lceil \log(L) \rceil +n$ qubits, where $L$ is the number of terms in the Hamiltonian and $n$ is the system qubit size. Our shorter width circuit with mid-measurements protocol is implemented and evaluated using the programming language Guppy[2,3].

quant-ph↗

arXiv2025

Measuring Correlation and Entanglement between Molecular Orbitals on a Trapped-Ion Quantum Computer

Quantifying correlation and entanglement between molecular orbitals can elucidate the role of quantum effects in strongly correlated reaction processes. However, accurately storing the wavefunction for a classical computation of those quantities can be prohibitive. Here we use the Quantinuum H1-1 trapped-ion quantum computer to calculate von Neumann entropies which quantify the orbital correlation and entanglement in a strongly correlated molecular system relevant to lithium-ion batteries (vinylene carbonate interacting with an O$_2$ molecule). As shown in previous works, fermionic superselection rules decrease correlations and reduce measurement overheads for constructing orbital reduced density matrices. Taking into account superselection rules we further reduce the number of measurements by finding commuting sets of Pauli operators. Using low overhead noise reduction techniques we calculate von Neumann entropies in excellent agreement with noiseless benchmarks, indicating that correlations and entanglement between molecular orbitals can be accurately estimated from a quantum computation. Our results show that the one-orbital entanglement vanishes unless opposite-spin open shell configurations are present in the wavefunction.

quant-ph↗

arXiv2025

High-precision Quantum Phase Estimation on a Trapped-ion Quantum Computer

Emergent quantum computing technologies are widely expected to provide novel approaches in the simulation of quantum chemistry. Despite rapid improvements in the scale and fidelity of quantum computers, high resource requirements make the execution of quantum chemistry experiments challenging. Typical experiments are limited in the number of qubits used, incur a substantial shot cost, or require complex architecture-specific optimization and error mitigation techniques. In this paper, we propose a conceptually simple benchmarking approach involving the use of multi-ancilla quantum phase estimation. Our approach is restricted to very small chemical systems, and does not scale favorably beyond molecular systems that can be described with $2$ qubits; however, this restriction allows us to generate circuits that scale quadratically in gate count with the number of qubits in the readout register. This enables the execution of quantum chemistry circuits that act on many qubits, while producing meaningful results with limited shot counts. We use this technique (with $200$ shots per experiment) to calculate the ground state energy of molecular hydrogen to $50$ bits of precision ($8.9 \times 10^{-16}$ hartree) on a $56$-qubit trapped-ion quantum computer, negating Trotter error. Including Trotter error, we obtain between $32$ and $36$ bits of precision ($1.5 * 10^{-10}$ and $6.0 * 10^{-11}$ hartree respectively), vastly exceeding chemical accuracy ($1.6 * 10^{-3}$ hartree) against Full Configuration Interaction. We consider application of the approach to deeper circuits, and discuss potential as a benchmark task for near-term quantum devices.

quant-ph↗

arXiv2025

Simulation of Atomic Layer Deposition with a Quantum Computer

In this work, we present the study of an atomic layer deposition (ALD) of zirconium by means of a quantum computation on an emulator representing the features of an architecture based on qubits implemented on carbon nanotubes. ALD process control is key in several technological applications such as spintronics, catalysis and renewable energy storage. We first derive a large ab-initio model of the precursor molecule approaching the infinite hydroxylated silicon (100) surface. In particular, we optimize geometry in three configurations: reactants, transition state and products. Subsequently, we derive an effective small cluster model for each state. Atomic valence active space (AVAS) transformation is then performed on these small clusters, leading to an effective qubit Hamiltonian, which is solved using the Variational Quantum Eigensolver (VQE) algorithm. We study the convergence of the reaction activation barrier with respect to the active space size and benchmark quantum calculations on a noiseless emulator and on an emulator representing a carbon nanotube qubit architecture, including an appropriate noise model and post-selection error mitigation. These calculations reveal an excellent agreement between the two emulation modes. Our VQE calculations provide the multi-configurational corrections to the single determinant DFT and HF states and pave the way for the routine quantum calculations of ALD reactions.

quant-ph↗

arXiv2025

Hamiltonian dynamics simulation using linear combination of unitaries on an ion trap quantum computer

The linear combination of unitaries (LCU) method has proven to scale better than existing product formulas in simulating long time Hamiltonian dynamics. However, given the number of multi-control gate operations in the standard prepare-select-unprepare architecture of LCU, it is still resource-intensive to implement on the current quantum computers. In this work, we demonstrate LCU implementations on an ion trap quantum computer for calculating squared overlaps $|\langle ψ(t=0)|ψ(t>0)\rangle|^2$ of time-evolved states. This is achieved by an optimized LCU method, based on pre-selecting relevant unitaries, coupled with a compilation strategy which makes use of quantum multiplexor gates, leading to a significant reduction in the depth and number of two-qubit gates in circuits. For $L$ Pauli strings in a Taylor series expanded $n$-qubit-mapped time evolution operator, we find a two-qubit gate count of $2^{\lceil log_2(L)\rceil}(2n+1)-n-2$. We test this approach by simulating a Rabi-Hubbard Hamiltonian.

quant-ph↗

arXiv2024

Shallow Quantum Scalar Products with Phase Information

The measurement of scalar products between two vectors is a common task in scientific computing and, by extension, in quantum computing. In this work, we introduce two alternative quantum circuits for computing scalar products with phase information, combining the structure of the swap test, the vacuum test, and the Hadamard test. These novel frameworks, called the zero-control and one-control tests, present different trade-offs between circuit depth and qubit count for accessing the scalar product between two quantum states. We demonstrate that our approach significantly reduces the gate count for large numbers of qubits and decreases the scaling of quantum requirements compared to the Hadamard test.

quant-ph↗

arXiv2024

Quantum Computed Green's Functions using a Cumulant Expansion of the Lanczos Method

In this paper, we present a quantum computational method to calculate the many-body Green's function matrix in a spin orbital basis. We apply our approach to finite-sized fermionic Hubbard models and related impurity models within Dynamical Mean Field Theory, and demonstrate the calculation of Green's functions on Quantinuum's H1-1 trapped-ion quantum computer. Our approach involves a cumulant expansion of the Lanczos method, using Hamiltonian moments as measurable expectation values. This bypasses the need for a large overhead in the number of measurements due to repeated applications of the variational quantum eigensolver (VQE), and instead measures the expectation value of the moments with one set of measurement circuits. From the measured moments, the tridiagonalised Hamiltonian matrix can be computed, which in turn yields the Green's function via continued fractions. While we use a variational algorithm to prepare the ground state in this work, we note that the modularity of our implementation allows for other (non-variational) approaches to be used for the ground state.

cond-mat.str-el↗

arXiv2024

Platinum-based Catalysts for Oxygen Reduction Reaction simulated with a Quantum Computer

Hydrogen has emerged as a promising energy source, holding the key to achieve low-carbon and sustainable mobility. However, its applications are still limited by modest conversion efficiency in the electrocatalytic oxygen reduction reaction (ORR) within fuel cells. Consequently, the development of novel catalysts and a profound understanding of the underlying reactions have become of paramount importance. The complex nature of the ORR potential energy landscape and the presence of strong electronic correlations present challenges to atomistic modelling using classical computers. This scenario opens new avenues for the implementation of novel quantum computing workflows to address these molecular systems. Here, we present a pioneering study that combines classical and quantum computational approaches to investigate the ORR on pure platinum and platinum/cobalt surfaces. Our research demonstrates, for the first time, the feasibility of implementing this workflow on the H1-series trapped-ion quantum computer and identify the challenges of the quantum chemistry modelling of this reaction. The results highlight the involvement of strongly correlated species in the cobalt-containing catalyst, suggesting their potential as ideal candidates for showcasing quantum advantage in future applications.

quant-ph↗

arXiv2024

Quantum Computing Simulation of a Mixed Spin-Boson Hamiltonian and Its Performance for a Cavity Quantum Electrodynamics Problem

In this paper, we aim to broaden the spectrum of possible applications of quantum computers and use their capabilities to investigate effects in cavity quantum electrodynamics ("cavity QED"). Interesting application examples are material properties, multiphoton effects such as superradiance, systems with strong field-matter coupling, and others. For QED applications, experimental studies are challenging, and classical simulations are often expensive. Therefore, exploring the capabilities of quantum computers is of interest. Below we present a methodology for simulating a phase transition in a pair of coupled cavities that permit photon hopping. We map the spin and boson systems to separate parts of the register and use first-order Trotterization to time-propagate the wavefunction. The order parameter, which is the observable for the phase transition, is calculated by measuring the number operator and its square. We introduce a boson-to-qubit mapping to facilitate a multi-photon, multi-atom case study. Our mapping scheme is based on the inverse Holstein-Primakoff transformation. In the multi-photon regime, boson operators are expressed via higher-spin operators which are subsequently mapped on a circuit using Pauli operators. We use a Newton series expansion to enable rigorous treatment of the square root operator. We reproduce the results of classical simulations of a phase transition with a noiseless 6-qubit simulation. We find that the simulation can be performed with a modest amount of quantum resources. Finally, we perform simulations on noisy emulators and find that mitigation techniques are essential to distinguish signal from noise.

quant-ph↗

arXiv2024

Variational Phase Estimation with Variational Fast Forwarding

Subspace diagonalisation methods have appeared recently as promising means to access the ground state and some excited states of molecular Hamiltonians by classically diagonalising small matrices, whose elements can be efficiently obtained by a quantum computer. The recently proposed Variational Quantum Phase Estimation (VQPE) algorithm uses a basis of real time-evolved states, for which the energy eigenvalues can be obtained directly from the unitary matrix U = exp(-iHt), which can be computed with cost linear in the number of states used. In this paper, we report a circuit-based implementation of VQPE for arbitrary molecular systems and assess its performance and costs for the H2, H3+ and H6 molecules. We also propose using Variational Fast Forwarding (VFF) to decrease to quantum depth of time-evolution circuits for use in VQPE. We show that the approximation provides a good basis for Hamiltonian diagonalisation even when its fidelity to the true time evolved states is low. In the high fidelity case, we show that the approximate unitary U can be diagonalised instead, preserving the linear cost of exact VQPE.

quant-ph↗

arXiv2023

Non-unitary Trotter circuits for imaginary time evolution

We propose an imaginary time equivalent of the well-established Pauli gadget primitive for Trotter-decomposed real time evolution, using mid-circuit measurements on a single ancilla qubit. Imaginary time evolution (ITE) is widely used for obtaining the ground state of a system on classical hardware, computing thermal averages, and as a component of quantum algorithms that perform non-unitary evolution. Near-term implementations on quantum hardware rely on heuristics, compromising their accuracy. As a result, there is growing interest in the development of more natively quantum algorithms. Since it is not possible to implement a non-unitary gate deterministically, we resort to the implementation of probabilistic imaginary time evolution (PITE) algorithms, which rely on a unitary quantum circuit to simulate a block encoding of the ITE operator - that is, they rely on successful ancillary measurements to evolve the system non-unitarily. Compared with previous PITE proposals, the suggested block encoding in this paper results in shorter circuits and is simpler to implement, requiring only a slight modification of the Pauli gadget primitive. This scheme was tested on the transverse Ising model and the fermionic Hubbard model and is demonstrated to converge to the ground state of the system.

quant-ph↗

arXiv2023

Quantum hardware calculations of the activation and dissociation of nitrogen on iron clusters and surfaces

Catalytic processes are vital in the chemical industry, with nitrogen-to-ammonia conversion being a major industrial process. Designing catalysts relies on computational chemistry methods like Density Functional Theory (DFT), which have limitations in accuracy, especially for complex materials. Quantum computing advancements offer promise for precise ab-initio methods. We introduce a hybrid quantum-classical workflow to model chemical reactions on surfaces, demonstrated on nitrogen activation and dissociation on small Fe clusters and an iron surface. We decoupled key electronic structures using CASSCF, translated them into qubits, and estimated energies with quantum and classical simulations, showing potential for quantum computing in catalysis research as technology scales up.

physics.chem-ph↗