arXiv subjects

Ana Martin

Publications and source records attributed to Ana Martin.

9 recordsLinked to original sources

arXiv2026

Coherent Control of Nanoscale Nuclear Spin Ensembles in the Spin Noise Regime

Spin defects in solids, such as the nitrogen-vacancy (NV) center in diamond, have emerged as a key tool for detecting nuclear spins at the nanoscale. While active nuclear spin control via radio-frequency (RF) irradiation is often unnecessary for standard spin-noise detection, it becomes essential for advanced protocols like multidimensional nanoscale NMR. In this work, we investigate nuclear spin control using correlation spectroscopy techniques. We demonstrate, both theoretically and experimentally, that the resulting nuclear spin dynamics depend critically on the initial RF phase and its orientation relative to the NV crystalline axis. Depending on these parameters, identical nuclear rotations can yield full, partial, or even vanishing contrast in the NV readout. These findings highlight a previously underappreciated aspect of spin manipulation in the spin-noise regime: the link between the phase and direction of the applied RF field and its direct impact on correlation-based experiments. Consequently, imperfect calibration of these parameters can lead to ambiguous signal contrasts and misinterpretation of the underlying nuclear spin dynamics. Our results provide deeper insight into nanoscale spin control and pave the way toward reliable multidimensional spin resonance experiments.

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arXiv2024

Microscale Sensing with Strongly Interacting NV Ensembles at High Fields

Advances in sensing devices that utilize nitrogen-vacancy (NV) center ensembles in diamond are driving progress in microscale nuclear magnetic resonance spectroscopy. Utilizing quantum sensing techniques in the high-field regime significantly boosts sensitivity by increasing thermal polarization and improves spectral quality via enhanced energy shifts. Compatible with the latter, a straightforward manner to further raise sensor sensitivity is to increase NV concentration, although this intensifies detrimental dipole-dipole interactions among NVs. In this Letter, we present a method for detecting NMR signals in high-field scenarios while effectively suppressing dipole-dipole couplings in the NV ensemble. Thus, this approach enhances sensitivity by combining highly doped diamond substrates and elevated magnetic fields.

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arXiv2024

Digital-Analog Quantum Computing and Algorithms

This Thesis delves into the development and implementation of quantum algorithms using the digital-analog quantum computing (DAQC) paradigm. It provides a comparative analysis of the performance of DAQC versus traditional digital approaches, particularly in the presence of noise sources from current noisy intermediate-scale quantum (NISQ) devices. The DAQC paradigm combines the strengths of digital and analog quantum computing, offering greater efficiency and precision for implementing quantum algorithms on real hardware. The Thesis focuses on the comparison of four relevant quantum algorithms using digital and digital-analog approaches, and the results show significant advantages in favor of the latter. Furthermore, the Thesis investigates the cross-resonance effect to achieve efficient and high-precision Hamiltonian simulations. The findings indicate that the digital-analog paradigm is promising for practical quantum computing applications. Its ability to deliver greater efficiency and accuracy in implementing quantum algorithms on real hardware is a significant advantage over traditional digital approaches.

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arXiv2022

Digital-analog co-design of the Harrow-Hassidim-Lloyd algorithm

The Harrow-Hassidim-Lloyd quantum algorithm was proposed to solve linear systems of equations $A\vec{x} = \vec{b}$ and it is the core of various applications. However, there is not an explicit quantum circuit for the subroutine which maps the inverse of the problem matrix $A$ into an ancillary qubit. This makes challenging the implementation in current quantum devices, forcing us to use hybrid approaches. Here, we propose a systematic manner to implement this subroutine, which can be adapted to other functions $f(A)$ of the matrix $A$, we present a co-designed quantum processor which reduces the depth of the algorithm, and we introduce its digital-analog implementation. The depth of our proposal scales with the precision $\epsilon$ as $\mathcal{O}(\epsilon^{-1})$, which is bounded by the number of samples allowed for a certain experiment. The co-design of the Harrow-Hassidim-Lloyd algorithm leads to a "kite-like" architecture, which allows us to reduce the number of required SWAP gates. Finally, merging a co-design quantum processor architecture with a digital-analog implementation contributes to the reduction of noise sources during the experimental realization of the algorithm.

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arXiv2021

Mitigating noise in digital and digital-analog quantum computation

Noisy Intermediate-Scale Quantum (NISQ) devices lack error correction, limiting scalability for quantum algorithms. In this context, digital-analog quantum computing (DAQC) offers a more resilient alternative quantum computing paradigm that outperforms digital quantum computation by combining the flexibility of single-qubit gates with the robustness of analog simulations. This work explores the impact of noise on both digital and DAQC paradigms and demonstrates DAQC's effectiveness in error mitigation. We compare the quantum Fourier transform and quantum phase estimation algorithms under a wide range of single and two-qubit noise sources in superconducting processors. DAQC consistently surpasses digital approaches in fidelity, particularly as processor size increases. Moreover, zero-noise extrapolation further enhances DAQC by mitigating decoherence and intrinsic errors, achieving fidelities above 0.95 for 8 qubits, and reducing computation errors to the order of $10^{-3}$. These results establish DAQC as a viable alternative for quantum computing in the NISQ era.

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arXiv2020

Digital-Analog Quantum Simulations Using The Cross-Resonance Effect

Digital-analog quantum computation aims to reduce the currently infeasible resource requirements needed for near-term quantum information processing by replacing sequences of one- and two-qubit gates with a unitary transformation generated by the systems' underlying Hamiltonian. Inspired by this paradigm, we consider superconducting architectures and extend the cross-resonance effect, up to first order in perturbation theory, from a two-qubit interaction to an analog Hamiltonian acting on 1D chains and 2D square lattices which, in an appropriate reference frame, results in a purely two-local Hamiltonian. By augmenting the analog Hamiltonian dynamics with single-qubit gates we show how one may generate a larger variety of distinct analog Hamiltonians. We then synthesize unitary sequences, in which we toggle between the various analog Hamiltonians as needed, simulating the dynamics of Ising, $XY$, and Heisenberg spin models. Our dynamics simulations are Trotter error-free for the Ising and $XY$ models in 1D. We also show that the Trotter errors for 2D $XY$ and 1D Heisenberg chains are reduced, with respect to a digital decomposition, by a constant factor. In order to realize these important near-term speedups, we discuss the practical considerations needed to accurately characterize and calibrate our analog Hamiltonians for use in quantum simulations. We conclude with a discussion of how the Hamiltonian toggling techniques could be extended to derive new analog Hamiltonians which may be of use in more complex digital-analog quantum simulations for various models of interacting spins.

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arXiv2020

Approximating the quantum approximate optimization algorithm with digital-analog interactions

The quantum approximate optimisation algorithm was proposed as a heuristic method for solving combinatorial optimisation problems on near-term quantum computers and may be among the first algorithms to perform useful computations in the post-supremacy, noisy, intermediate scale era of quantum computing. In this work, we exploit the recently proposed digital-analog quantum computation paradigm, in which the versatility of programmable universal quantum computers and the error resilience of quantum simulators are combined to improve platforms for quantum computation. We show that the digital-analog paradigm is suited to the variational quantum approximate optimisation algorithm, due to its inherent resilience against coherent errors, by performing large-scale simulations and providing analytical bounds for its performance in devices with finite single-qubit operation times. We observe regimes of single-qubit operation speed in which the considered variational algorithm provides a significant improvement over non-variational counterparts.

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arXiv2019

Digital-analog quantum algorithm for the quantum Fourier transform

Quantum computers will allow calculations beyond existing classical computers. However, current technology is still too noisy and imperfect to construct a universal digital quantum computer with quantum error correction. Inspired by the evolution of classical computation, an alternative paradigm merging the flexibility of digital quantum computation with the robustness of analog quantum simulation has emerged. This universal paradigm is known as digital-analog quantum computing. Here, we introduce an efficient digital-analog quantum algorithm to compute the quantum Fourier transform, a subroutine widely employed in several relevant quantum algorithms. We show that, under reasonable assumptions about noise models, the fidelity of the quantum Fourier transformation improves considerably using this approach when the number of qubits involved grows. This suggests that, in the Noisy Intermediate-Scale Quantum (NISQ) era, hybrid protocols combining digital and analog quantum computing could be a sensible approach to reach useful quantum supremacy.

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arXiv2019

Towards Pricing Financial Derivatives with an IBM Quantum Computer

Pricing interest-rate financial derivatives is a major problem in finance, in which it is crucial to accurately reproduce the time-evolution of interest rates. Several stochastic dynamics have been proposed in the literature to model either the instantaneous interest rate or the instantaneous forward rate. A successful approach to model the latter is the celebrated Heath-Jarrow-Morton framework, in which its dynamics is entirely specified by volatility factors. On its multifactor version, this model considers several noisy components to capture at best the dynamics of several time-maturing forward rates. However, as no general analytical solution is available, there is a trade-off between the number of noisy factors considered and the computational time to perform a numerical simulation. Here, we employ the quantum principal component analysis to reduce the number of noisy factors required to accurately simulate the time evolution of several time-maturing forward rates. The principal components are experimentally estimated with the $5$-qubit IBMQX2 quantum computer for $2\times 2$ and $3\times 3$ cross-correlation matrices, which are based on historical data for two and three time-maturing forward rates. This manuscript is a first step towards the design of a general quantum algorithm to fully simulate on quantum computers the Heath-Jarrow-Morton model for pricing interest-rate financial derivatives. It shows indeed that practical applications of quantum computers in finance will be achievable in the near future.

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