arXiv subjects

Inés de Vega

Publications and source records attributed to Inés de Vega.

At least 19 recordsLinked to original sources

arXiv2026

Characterizing Physical Error Contributions of Quantum Gates

Large-scale quantum computation requires a reliable assessment of the main sources of error in the implemented quantum gates. To this aim, we provide a learning-based framework that extracts the contribution of each physical error source to the infidelity of a series of gates, together with an uncertainty estimate for every contribution. Crucially, the uncertainties provided by the underlying Gaussian Process Regression serve as a diagnostic of the assumed noise model itself: if the physical model does not fully explain the experimental observations, the framework signals this instead of returning a falsely precise error budget. We demonstrate the proposed budget learning procedure on a pair of qubits in a transmon array architecture, where we compute the error budgets of the native single- and two-qubit gates. For this purpose, we have also developed an advanced noise model based on the first-principles understanding of the error processes in current superconducting processors, including complex (e.g. non-Markovian) error sources. While the single-qubit budgets are reconstructed with high confidence, the same diagnostic reveals that even this detailed noise model does not fully capture the error dynamics of a state-of-the-art two-qubit gate --- quantitative evidence that uncertainty-aware error budgeting is necessary for the characterization of current quantum hardware.

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arXiv2026

Near-Term Fermionic Simulation with Subspace Noise Tailored Quantum Error Mitigation

Quantum error mitigation (QEM) has emerged as a powerful tool for the extraction of useful quantum information from quantum devices. Here, we introduce the Subspace Noise Tailoring (SNT) algorithm, which efficiently combines the cheap cost of Symmetry Verification (SV) and low bias of Probabilistic Error Cancellation (PEC) QEM techniques. We study the performance of our method by simulating the Trotterized time evolution of the spin-1/2 Fermi-Hubbard model (FHM) using a variety of local fermion-to-qubit encodings, which define a computational subspace through a set of stabilizers, the measurement of which can be used to post-select noisy quantum data. We study different combinations of QEM and encodings and uncover a rich state diagram of optimal combinations, depending on the hardware performance, system size and available shot budget. We then demonstrate how SNT extends the reach of current noisy quantum computers in terms of the number of fermionic lattice sites and the number of Trotter steps, and quantify the required hardware performance beyond which a noisy device may compete with current state-of-the-art classical computational methods.

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arXiv2026

Noise-Robust Estimation of Quantum Observables in Noisy Hardware

Error mitigation is essential for extracting reliable results from quantum computations performed on noisy intermediate-scale quantum hardware. Here we introduce Noise-Robust Estimation (NRE), a noise-agnostic framework that suppresses estimation bias through a two-stage post-processing protocol. The method combines measurement data from a target circuit and a corresponding noise-canceling companion circuit to construct a baseline estimator with reduced sensitivity to noise. We show that the residual bias of this estimator is governed by the variation of an auxiliary quantity across amplified noise realizations, motivating the use of a measurable diagnostic quantity: the normalized dispersion of this auxiliary estimator. When the dispersion approaches zero, contributions arising from imperfect noise amplification vanish and the remaining bias terms are expected to diminish for smooth stationary noise profiles. Leveraging this relationship, NRE performs a final extrapolation to the zero-dispersion limit using bootstrapped measurement data. We experimentally validate the method on a 20-qubit IQM superconducting quantum processor using circuits containing up to 480 entangling CZ gates. Across a variety of circuits and noise levels, NRE consistently achieves substantially reduced bias compared to existing mitigation techniques while maintaining moderate sampling overhead. These results establish NRE as a practical and broadly applicable error-mitigation strategy for quantum computations on noisy hardware.

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arXiv2025

Opportunities and challenges of quantum computing for climate modelling

Adaptation to climate change requires robust climate projections, yet the uncertainty in these projections performed by ensembles of Earth system models (ESMs) remains large. This is mainly due to uncertainties in the representation of subgrid-scale processes such as turbulence or convection that are partly alleviated at higher resolution. New developments in machine learning-based hybrid ESMs demonstrate great potential for systematically reduced errors compared to traditional ESMs. Building on the work of hybrid (physics + AI) ESMs, we here discuss the additional potential of further improving and accelerating climate models with quantum computing. We discuss how quantum computers could accelerate climate models by solving the underlying differential equations faster, how quantum machine learning could better represent subgrid-scale phenomena in ESMs even with currently available noisy intermediate-scale quantum devices, how quantum algorithms aimed at solving optimization problems could assist in tuning the many parameters in ESMs, a currently time-consuming and challenging process, and how quantum computers could aid in the analysis of climate models. We also discuss hurdles and obstacles facing current quantum computing paradigms. Strong interdisciplinary collaboration between climate scientists and quantum computing experts could help overcome these hurdles and harness the potential of quantum computing for this urgent topic.

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arXiv2025

Fermion-to-qubit encodings with arbitrary code distance

We introduce a framework which allows to systematically and arbitrarily scale the code distance of local fermion-to-qubit encodings in one and two dimensions without growing the weights of stabilizers. This is achieved by embedding low-distance encodings into the surface code in the form of topological defects. We introduce a family of Ladder Encodings (LE), which is optimal in the sense that the code distance is equal to the weights of density and nearest-neighbor hopping operators of a one-dimensional Fermi-Hubbard model. In two dimensions, we show how to scale the code distance of LE as well as other low-distance encodings such as Verstraete-Cirac and Derby-Klassen. We further introduce Perforated Encodings, which locally encode two fermionic spin modes within the same surface code structure. We show that our strategy is also extendable to other topological codes by explicitly embedding the LE into a 6.6.6 color code.

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arXiv2025

Improving and benchmarking NISQ qubit routers

Quantum computers with a limited qubit connectivity require inserting SWAP gates for qubit routing, which increases gate execution errors and the impact of environmental noise due to an overhead in circuit depth. In this work, we benchmark various routing techniques considering random quantum circuits on one-dimensional and square lattice connectivities, employing both analytical and numerical methods. We introduce circuit fidelity as a comprehensive metric that captures the effects of SWAP and circuit depth overheads. Leveraging a novel approach based on the SABRE algorithm, we achieve up to $84\%$ higher average circuit fidelity for large devices within the NISQ range, compared to previously existing methods. Additionally, our results highlight that the optimal routing choice critically depends on the qubit count and the hardware characteristics, including gate fidelities and coherence times.

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arXiv2024

Estimating the coherence of noise in mid-scale quantum systems

While the power of quantum computers is commonly acknowledged to rise exponentially, it is often overlooked that the complexity of quantum noise mechanisms generally grows much faster. In particular, quantifying whether the instructions on a quantum processor are close to being unitary has important consequences concerning error rates, e.g., for the confidence in their estimation, the ability to mitigate them efficiently, or their relation to fault-tolerance thresholds in error correction. However, the complexity of estimating the coherence, or unitarity, of noise generally scales exponentially in system size. Here, we obtain an upper bound on the average unitarity of Pauli noise and develop a protocol allowing us to estimate the average unitarity of operations in a digital quantum device efficiently and feasibly for mid-size quantum systems. We demonstrate our results through both experimental execution on IQM Spark (TM), a 5-qubit superconducting quantum computer, and in simulation with up to 10 qubits, discussing the prospects for extending our technique to arbitrary scales.

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arXiv2024

Performance and scaling analysis of variational quantum simulation

We present an empirical analysis of the scaling of the minimal quantum circuit depth required for a variational quantum simulation (VQS) method to obtain a solution to the time evolution of a quantum system within a predefined error tolerance. In a comparison against a non-variational method based on Trotterized time evolution, we observe a better scaling of the depth requirements using the VQS approach with respect to both the size of the system and the simulated time. Results are also put into perspective by discussing the corresponding classical complexity required for VQS. Our results allow us to identify a possible advantage region for VQS over Trotterization.

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arXiv2024

Operational Markovianization in Randomized Benchmarking

A crucial task to obtain optimal and reliable quantum devices is to quantify their overall performance. The average fidelity of quantum gates is a particular figure of merit that can be estimated efficiently by Randomized Benchmarking (RB). However, the concept of gate-fidelity itself relies on the crucial assumption that noise behaves in a predictable, time-local, or so-called Markovian manner, whose breakdown can naturally become the leading source of errors as quantum devices scale in size and depth. We analytically show that error suppression techniques such as Dynamical Decoupling (DD) and Randomized Compiling (RC) can operationally Markovianize RB: i) fast DD reduces non-Markovian RB to an exponential decay plus longer-time corrections, while on the other hand, ii) RC generally does not affect the average, but iii) it always suppresses the variance of such RB outputs. We demonstrate these effects numerically with a qubit noise model. Our results show that simple and efficient error suppression methods can simultaneously tame non-Markovian noise and allow for standard and reliable gate quality estimation, a fundamentally important task in the path toward fully functional quantum devices.

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arXiv2024

Charge-parity switching effects and optimisation of transmon-qubit design parameters

Enhancing the performance of noisy quantum processors requires improving our understanding of error mechanisms and the ways to overcome them. In this study, we identify optimal ranges for qubit design parameters, grounded in comprehensive noise modeling. To this end, we also analyze a previously unexplored error mechanism that can perturb two-qubit gates due to charge-parity switches caused by quasiparticles. Due to the utilization of the higher levels of a transmon, where the charge dispersion is significantly larger, a charge-parity switch will affect the conditional phase of the two-qubit gate. We derive an analytical expression for the infidelity of a diabatic controlled-Z gate and see effects of similar magnitude in adiabatic controlled phase gates in the tunable coupler architecture. Moreover, we show that the effect of a charge-parity switch can be the dominant quasiparticle-related error source of a two-qubit gate. We also demonstrate that charge-parity switches induce a residual longitudinal interaction between qubits in a tunable-coupler circuit. We present a performance metric for quantum circuit execution, encompassing the fidelity and number of single and two-qubit gates in an algorithm, as well as the state preparation fidelity. This comprehensive metric, coupled with a detailed noise model, empowers us to determine an optimal range for the qubit design parameters Substantiating our findings through exact numerical simulations, we establish that fabricating quantum chips within this optimal parameter range not only augments the performance metric but also ensures its continued improvement with the enhancement of individual qubit coherence properties. Our systematic analysis offers insights and serves as a guiding framework for the development of the next generation of transmon-based quantum processors.

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arXiv2023

Benchmarking Digital-Analog Quantum Computation

Digital-Analog Quantum Computation (DAQC) has recently been proposed as an alternative to the standard paradigm of digital quantum computation. DAQC creates entanglement through a continuous or analog evolution of the whole device, rather than by applying two-qubit gates. This manuscript describes an in-depth analysis of DAQC by extending its implementation to arbitrary connectivities and by performing the first systematic study of its scaling properties. We specify the analysis for three examples of quantum algorithms, showing that except for a few specific cases, DAQC is in fact disadvantageous with respect to the digital case.

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arXiv2022

Co-Design quantum simulation of nanoscale NMR

Quantum computers have the potential to efficiently simulate the dynamics of nanoscale NMR systems. In this work we demonstrate that a noisy intermediate-scale quantum computer can be used to simulate and predict nanoscale NMR resonances. In order to minimize the required gate fidelities, we propose a superconducting application-specific Co-Design quantum processor that reduces the number of SWAP gates by over 90 % for chips with more than 20 qubits. The processor consists of transmon qubits capacitively coupled via tunable couplers to a central co-planar waveguide resonator with a quantum circuit refrigerator (QCR) for fast resonator reset. The QCR implements the non-unitary quantum operations required to simulate nuclear hyperpolarization scenarios.

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arXiv2021

Neural Network Based Qubit Environment Characterization

The exact microscopic structure of the environments that produces $1/f$ noise in superconducting qubits remains largely unknown, hindering our ability to have robust simulations and harness the noise. In this paper we show how it is possible to infer information about such an environment based on a single measurement of the qubit coherence, circumventing any need for separate spectroscopy experiments. Similarly to other spectroscopic techniques, the qubit is used as a probe which interacts with its environment. The complexity of the relationship between the observed qubit dynamics and the impurities in the environment makes this problem ideal for machine learning methods - more specifically neural networks. With our algorithm we are able to reconstruct the parameters of the most prominent impurities in the environment, as well as differentiate between different environment models, paving the way towards a better understanding of $1/f$ noise in superconducting circuits.

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arXiv2021

Impurity dephasing in a Bose-Hubbard model

We study the dynamics of a two-level impurity embedded in a two-dimensional Bose-Hubbard model at zero temperature from an open quantum system perspective. Results for the decoherence across the whole phase diagram are presented, with a focus on the critical region close to the transition between superfluid and Mott insulator. In particular, we show how the decoherence and the deviation from a Markovian behaviour are sensitive to whether the transition is crossed at commensurate or incommensurate densities. The role of the spectrum of the Bose-Hubbard environment and its non-Gaussian statistics, beyond the standard independent boson model, is highlighted. Our analysis resorts on a recently developed method [Phys. Rev. Research 2, 033276 (2020)] - closely related to slave boson approaches - that enables us to capture the correlations across the whole phase diagram. This semi-analytical method provides us with a deep insight into the physics of the spin decoherence in the superfluid and Mott phases as well as close to the phase transitions.

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arXiv2020

The quantum dynamical map of the spin boson model

One of the main frameworks to analyze the effects of the environment in a quantum computer is that of pure dephasing, where the dynamics of qubits can be characterised in terms of a well-known dynamical map. In this work we present a non-peturbative extension of such map beyond this simple pure-dephasing case, i.e. that is valid for a general spin coupled to a bosonic environment in a thermal state. To this aim, we use a Trotter decomposition and a Magnus expansion to simplify the unitary evolution operator in interaction picture. The proposed derivation can be extended to other finite-level open quantum systems including many body, initial system-environment correlated states, multiple-time correlation functions or quantum information protocols.

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arXiv2019

Open quantum systems in thermal non-ergodic environments

The dynamics of an open system crucially depends on the correlation function of its environment, $C_B(t)$. We show that for thermal non-Harmonic environments $C_B(t)$ may not decay to zero but to an offset, $C_0>0$. The presence of such offset is determined by the environment eigenstate structure, and whether it fulfills or not the eigenstate thermalization hypothesis. Moreover, we show that a $C_0>0$ could render the weak coupling approximation inaccurate and prevent the open system to thermalize. Finally, for a realistic environment of dye molecules, we show the emergence of the offset by using matrix product states (MPS), and discuss its link to a 1/f noise spectrum that, in contrast to previous models, extends to zero frequencies. Thus, our results may be relevant in describing dissipation in quantum technological devices like superconducting qubits, which are known to be affected by such noise.

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arXiv2018

Nonreciprocal Quantum Transport at Junctions of Structured Leads

We propose and analyze a mechanism for rectification of spin transport through a small junction between two spin baths or leads. For interacting baths we show that transport is conditioned on the spacial asymmetry of the quantum junction mediating the transport, and attribute this behavior to a gapped spectral structure of the lead-system-lead configuration. For non-interacting leads a minimal quantum model that allows for spin rectification requires an interface of only two interacting two-level systems. We obtain approximate results with a weak-coupling Born-master-equation in excellent agreement with matrix-product-state calculations that are extrapolated in time by mimicking absorbing boundary conditions. These results should be observable in controlled spin systems realized with cold atoms, trapped ions, or in electrons in quantum dot arrays.

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arXiv2017

Collective dynamics of accelerated atoms

We study the collective dynamics of accelerated atoms interacting with a massless field via an Unruh-deWitt-type interaction. We first derive a general Hamiltonian describing such a system and then, employing a Markovian master equation, we study the corresponding collective dynamics. In particular, we observe that the emergence of entanglement between two-level atoms is linked to the building up of coherences between them and to superradiant emission. In addition, we show that the derived Hamiltonian can be experimentally implemented by employing impurities in Bose-Einstein condensates.

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