arXiv subjects

Olatz Sanz Larrarte

Publications and source records attributed to Olatz Sanz Larrarte.

9 recordsLinked to original sources

arXiv2026

A quantum generative model for in silico clinical trials using scarce training datasets

In silico methods have emerged as a strategy to complement clinical trials. These are particularly relevant for rare or heterogeneous diseases for which traditional methods are costly or difficult to apply. While classical generative models have shown an extremely good ability to generate high fidelity data when trained using extensive databases, they often struggle when the available samples for training are scarce. In this work, we leverage the potential of quantum computers to represent complex probability distributions to generate high fidelity in silico patients. We propose a pipeline able to combine asymmetric databases into a quantum circuit that serves as a quantum generative model. We evaluate the efficacy of our proposal using a database of Myelodysplastic Syndrome (MDS) patients with 7 clinical variables as a proof-of-concept. We executed our quantum generative model in the IBM Heron r2 ``ibm\_basquecountry'' superconducting quantum computer and compare our method with well known classical baselines. Our results show that the quantum generative model surpasses the classical generative models in generalization and expressivity metrics, indicating its potential validity to generate high fidelity in silico patients for clinical trials.

quant-ph↗

arXiv2026

Forecasting Quantum Observables: A Compressed Sensing Approach with Performance Guarantees

Data-driven extrapolation methods aim to extend the dynamics of quantum observables from measurements, but they often lack guarantees on prediction accuracy. We introduce a framework based on atomic norm minimization that can certify whether the spectral model learned by a forecasting algorithm -- i.e., Bohr frequencies and amplitudes -- is consistent with unitary quantum time evolution. Certification holds when the dynamics are governed by a small number of well-separated Bohr frequencies. We validate the approach on multiple forecasting algorithms applied to spin-chain Hamiltonians with 8--20 sites. Comparing with exact diagonalization, certified models yield an average forecasting error below 0.1 (observable range $[-1, 1]$) in 97\% of cases and below 0.05 in 91--99\% of cases. Even in the presence of noise, certified models remain robust at the 0.1 error threshold.

quant-ph↗

arXiv2026

Noise mitigation of quantum observables via learning from Hamiltonian symmetry decays

We present a new quantum error mitigation technique (QEM), called GUiding Extrapolations from Symmetry decayS (GUESS), which exploits Hamiltonian symmetries to improve accuracy of noisy quantum computations. This method is explicitly designed for quantum algorithms that estimate expectation values of observables and consists in learning the extrapolation coefficients from a symmetry observable of the system to then estimate the value of a target observable. Furthermore, we propose a Hamiltonian impurity technique to enforce symmetries allowing the mitigation of local observables of interest. We employ the IBM Heron r2 quantum processing unit '\texttt{ibm\_basquecountry}' to simulate the time evolution of average magnetization and nearest-neighbor correlator observables for transverse field Ising and $XZ$ Heisenberg models in 1D with open boundary conditions. We benchmark the accuracy of our method against baseline Zero Noise Extrapolation (ZNE) and tensor network simulations for systems of $100$ qubits. Remarkably, GUESS achieves a relative error around $10\%$ for circuits containing up to $8000$ CZ gates, while showcasing lower variance than ZNE on average across $20$ observables and requiring only twice the number of shots per observable compared to baseline ZNE. Furthermore, we demonstrate that GUESS enables statistical post-selection based on the outcomes of the symmetry observable, which provides critical information about the quality of the target qubits by means of its mean and variance. These results indicate that GUESS is a powerful QEM technique capable of mitigating utility-scale circuit outcomes, delivering high accuracy and reduced variance for large-scale circuits with minimal quantum overhead.

quant-ph↗

arXiv2026

Impact of leakage on the dynamics of a ST$_0$ qubit implemented in a Double Quantum Dot device

Spin qubits in quantum dots are a promising technology for quantum computing due to their fast response time and long coherence times. An electromagnetic pulse is applied to the system for a specific duration to perform a desired rotation. To avoid decoherence, the amplitude and gate time must be highly accurate. In this work, we aim to study the impact of leakage during the gate time evolution of a spin qubit encoded in a double quantum dot device. We prove that, in the weak interaction regime, leakage introduces a shift in the phase of the time evolution operator, causing over- or under-rotations. Indeed, controlling the leakage terms is useful for adjusting the time needed to perform a quantum computation and increasing the coherence time of the readout process. This is crucial for running fault-tolerant algorithms and is beneficial for Quantum Error Mitigation techniques.

quant-ph↗

arXiv2025

Tensor Network based Gene Regulatory Network Inference for Single-Cell Transcriptomic Data

Deciphering complex gene-gene interactions remains challenging in transcriptomics as traditional methods often miss higher-order and nonlinear dependencies. This study introduces a quantum-inspired framework leveraging tensor networks (TNs) to optimally map expression data into a lower dimensional representation preserving biological locality. Using Quantum Mutual Information (QMI), a nonparametric measure natural for tensor networks, we quantify gene dependencies and establish statistical significance via permutation testing. This constructs robust interaction networks where the edges reflect biologically meaningful relationships that are resilient to random chance. The approach effectively distinguishes true regulatory patterns from experimental noise and biological stochasticity. To test the proposed method, we recover a gene regulatory network consisted of six pathway genes from single-cell RNA sequencing data comprising over $28.000$ lymphoblastoid cells. Furthermore, we unveil several triadic regulatory mechanisms. By merging quantum physics inspired techniques with computational biology, our method provides novel insights into gene regulation, with applications in disease mechanisms and precision medicine.

q-bio.MN↗

arXiv2025

Generalized Bicycle Codes with Low Connectivity: Minimum Distance Bounds and Hook Errors

We present new upper and lower bounds on the minimum distance of certain generalized bicycle (GB) codes beyond the reach of techniques for classical codes capable of even capturing the true minimum distance for some cases. These bounds are then applied to illustrate the existence and analyze two highly degenerate GB code families with parameters $[[d^2+1,2,d]]$ for odd $d \geq 3$ and $[[d^2,2,d]]$ for even $d \geq 4$, both having the property that each check qubit is connected to exactly four data qubits similar to surface codes. For the odd-distance family, we analyze the structure of low-weight logical Pauli operators and demonstrate the existence of a fault-tolerant logical CNOT gate between the two logical qubits, achievable through a simple relabeling of data qubits. We further construct a syndrome extraction pattern for both families that does not imply minimum distance reduction arising from extraction circuit faults that propagate from the check qubits to the data qubits. Finally, we numerically evaluate their logical error rates under a code capacity depolarizing noise model using the belief propagation ordered statistics decoding (BP-OSD) and minimum-weight perfect-matching (MWPM) decoders, yielding thresholds of approximately $14-16\%$ for the odd and even families, very similar to those of rotated surface codes.

cs.IT↗

arXiv2025

Asymptotically good CSS-T codes and a new construction of triorthogonal codes

We propose a new systematic construction of CSS-T codes from any given CSS code using a map $ϕ$. When $ϕ$ is the identity map $I$, we retrieve the construction of [1] and use it to prove the existence of asymptotically good binary CSS-T codes, resolving a previously open problem in the literature, and of asymptotically good quantum LDPC CSS-T codes. We analyze the structure of the logical operators corresponding to certain non-Clifford gates supported by the quantum codes obtained from this construction ($ϕ= I$), concluding that they always result in the logical identity. An immediate application of these codes in dealing with coherent noise is discussed. We then develop a new doubling transformation for obtaining triorthogonal codes, which generalizes the doubling construction presented in [2]. Our approach permits using self-orthogonal codes, instead of only doubly-even codes, as building blocks for triorthogonal codes. This broadens the range of codes available for magic state distillation.

quant-ph↗

arXiv2024

Comment on "Recovering noise-free quantum observables"

Zero-noise extrapolation (ZNE) stands as the most widespread quantum error mitigation technique in order to aim the recovery of noise-free expectation values of observables of interest by means of Noisy Intermediate-Scale Quantum (NISQ) machines. Recently, Otten and Gray proposed a multidimensional generalization of polynomial ZNE for systems where there is not a tunable global noise source [Phys. Rev. A \textbf{99,} 012338 (2019)]. Specifically, the authors refer to multiqubit systems where each of the qubits experiences several noise processes with different rates, i.e. a non-identically distributed noise model. The authors proposed a hypersurface method for mitigating such noise, which is technically correct. While effective, the proposed method presents an unbearable experiment repetition overhead, making it impractical, at least from the perspective of quantum computing. In this comment, we show that the traditional extrapolation techniques can be applied for such non-identically distributed noise setting consisted of many different noise sources, implying that the measurement overhead is reduced considerably. For doing so, we clarify what it is meant by a tunable global noise source in the context of ZNE, concept that we consider important to be clarified for a correct understanding about how and why these methods work.

quant-ph↗

arXiv2024

Quantum CSS Duadic and Triadic Codes: New Insights and Properties

In this study, we investigate the construction of quantum CSS duadic codes with dimensions greater than one. We introduce a method for extending smaller splittings of quantum duadic codes to create larger, potentially degenerate quantum duadic codes. Furthermore, we present a technique for computing or bounding the minimum distances of quantum codes constructed through this approach. Additionally, we introduce quantum CSS triadic codes, a family of quantum codes with a rate of at least $\frac{1}{3}$.

cs.IT↗