arXiv subjects

Jorge Casanova

Publications and source records attributed to Jorge Casanova.

At least 19 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.

quant-ph↗

arXiv2026

Enhanced sensitivity in microscale high-field NMR via nuclear-spin locking with NV centers

Solid state defects such as nitrogen vacancy (NV) centers in diamond have been utilized for NMR sensing at ambient temperatures for samples at the nano-scale and up to the micro-scale. Similar to standard NMR, NV-sensitivities can be increased using tesla-valued magnetic fields to boost nuclear thermal polarization, while structural parameters, such as chemical shifts, are also enhanced. However, with standard microwave (MW) based sensing techniques, NV centers struggle to track fast megahertz Larmor frequencies encountered in high-field scenarios. Previous protocols have addressed this by mapping target NMR parameters to the signal amplitude rather than the frequency, using a mediating RF field. Although successful, protocol sensitivities are limited by the coherence time ($T_2^*$) of the NMR signal owing to the presence of stages where the sample magnetization freely evolves. In this work, we propose extending this coherence time, and consequently improving sensitivity, via amplitude encoding with weak nuclear spin locking instead of free evolution, thereby taking advantage of the longer sample coherence times ($T_{1ρ}$). We demonstrate this can enhance protocol sensitivities by $\gtrsim 4$ times.

quant-ph↗

arXiv2025

Suppressing Fast Dipolar Noise in Solid-State Spin Qubits

Spin qubit coherence is a fundamental resource for the realization of quantum technologies. For solid-state platforms, spin decoherence is dominated by the magneto-active environment in the lattice, limiting their applicability. While standard dynamical decoupling techniques, such as the Hahn echo, extend central spin coherence, they fail to suppress the fast noise arising from strong dipolar interactions within the bath. Here, we present a decoupling mechanism, Hybrid-LG, that suppresses intra-bath dipolar interactions -- thus, fast noise acting on spin qubits- and demonstrate its effectiveness in extending spin coherence through efficient in-house CCE simulations. Specifically, we investigate one of the most widely exploited solid-state quantum platforms: an ensemble of nitrogen-vacancy (NV) centers in diamond coupled to a large and dense bath of substitutional nitrogen paramagnetic impurities (P1 centers). Our results reveal at least a twofold enhancement in NV coherence time relative to standard techniques including P1 center driving, without requiring additional control power.

quant-ph↗

arXiv2025

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.

quant-ph↗

arXiv2025

Quantum control of exciton motion in electric field

We study quantum control of classical motion of a two-dimensional exciton by optimizing the time-dependent electric field of a stripe-like gate acting on the exciton and inducing its time-dependent quantum dipole moment. We propose a search method that significantly reduces computational requirements while efficiently identifying optimal control parameters. By leveraging this method, one can precisely manipulate the exciton's final position and velocity over a specified evolution time. These results can be applied for control of exciton fluxes and population, and for spatially resolved light emission in two-dimensional semiconducting structures.

cond-mat.mes-hall↗

arXiv2025

Pulse sequence design for high field NMR with NV centers in dipolarly coupled samples

Diamond-based quantum sensors have enabled high-resolution NMR spectroscopy at the microscale in scenarios where fast molecular motion averages out dipolar interactions among target nuclei. However, in samples with low-diffusion, ubiquitous dipolar couplings challenge the extraction of relevant spectroscopic information. In this work we present a protocol that enables the scanning of nuclear spins in dipolarly-coupled samples at high magnetic fields with a sensor based on nitrogen vacancy (NV) ensembles. Our protocol is based on the synchronized delivery of radio frequency (RF) and microwave (MW) radiation to eliminate couplings among nuclei in the scanned sample and to efficiently extract target energy-shifts from the sample's magnetization dynamics. In addition, the method is designed to operate at high magnetic fields leading to a larger sample thermal polarization, thus to an increased NMR signal. The precision of our method is ultimately limited by the coherence time of the sample, allowing for accurate identification of relevant energy shifts in solid-state systems.

quant-ph↗

arXiv2025

Robust microwave cavity control for NV ensemble manipulation

Nitrogen-vacancy (NV) center ensembles have the potential to improve a wide range of applications, including nuclear magnetic resonance spectroscopy at the microscale and nanoscale, wide-field magnetometry, and hyperpolarization of nuclear spins via the transfer of optically induced NV polarization to nearby nuclear spin clusters. These NV ensembles can be coherently manipulated with microwave cavities, that deliver strong and homogeneous drivings over large volumes. However, the pulse shaping for microwave cavities presents the added challenge that the external controls and intra-cavity field amplitudes are not identical, leading to adverse effects on the accuracy of operations on the NV ensemble. In this work, we introduce a method based on Gradient Ascent Pulse Engineering (GRAPE) to optimize external controls, resulting in robust pulses within the cavity while minimizing the effects of cavity ringings. The effectiveness of the method is demonstrated by designing both $π$ and $π/2$ pulses. These optimized controls are then integrated into a PulsePol sequence, where numerical simulations reveal a resilience to detunings five times larger than those tolerated by the sequence constructed using standard controls.

quant-ph↗

arXiv2025

Coherent signal detection in the statistical polarization regime enables high-resolution nanoscale NMR spectroscopy

Nitrogen-vacancy (NV) centers in diamond have emerged as quantum sensors capable of detecting nuclear magnetic resonance (NMR) signals at unprecedented length scales, ranging from picoliter sample volumes down to single spins at the diamond surface. While high-resolution (few hertz) NV-NMR spectroscopy has been demonstrated at the micrometer scale, it has remained elusive at the nanometer scale. In this regime, only the detection of statistical polarization has been achieved, limiting spectral resolution due to molecular diffusion in liquid samples. Here, we demonstrate that detecting coherent signals from a uniformly polarized nanoscale sample, where polarization is enhanced beyond thermal levels, successfully overcomes this limitation, enabling single-digit hertz spectral resolution and the capacity to resolve scalar couplings. These results pave the way for high-resolution nanoscale NMR spectroscopy at interfaces, surfaces, and potentially even single molecules.

physics.chem-ph↗

arXiv2024

Versatile quadrature antenna for precise control of large electron spin ensembles in diamond

We present an easily reproducible inexpensive microwave antenna that can generate a strong and homogeneous magnetic field of arbitrary polarization, which enables fast and coherent control of electron spins over a large volume. Unlike preceding works, we present a resonant antenna that maintains its resonant behaviour regardless of the proximity of other experimental hardware components. This robustness is crucial as it enables, amongst others, using microscope objectives with short working distances to perform wide field imaging/sensing with bulk diamonds. The antenna generates a magnetic field strength of 22.3 A/m for 1 W total driving power, which doubles the power efficiency compared with previously reported patch antenna designs. The magnetic field homogeneity in a volume of $0.3 \text{mm}^3$, $0.5 \text{mm}^3$ and $1 \text{mm}^3$ is within 6\%, 8\% and 13\%, respectively. The antenna has a full width at half maximum bandwidth of $\sim$160 MHz and its resonant frequency can be tuned over a 400 MHz range via four capacitors or varactors. The antenna has been tested and found to remain within safe handling temperatures during continuous-wave operation at 8 W. The files required to reproduce this antenna, which can be built on a standard and affordable double sided PCB, are provided open-source. This work facilitates a robust and versatile piece of instrumentation, being particularly appealing for applications such as high sensitivity magnetometry and wide field imaging/sensing with Nitrogen Vacancy centers.

physics.ins-det↗

arXiv2023

Regressions on quantum neural networks at maximal expressivity

We analyze the expressivity of a universal deep neural network that can be organized as a series of nested qubit rotations, accomplished by adjustable data re-uploads. While the maximal expressive power increases with the depth of the network and the number of qubits, it is fundamentally bounded by the data encoding mechanism. Focusing on regression problems, we systematically investigate the expressivity limits for different measurements and architectures. The presence of entanglement, either by entangling layers or global measurements, saturate towards this bound. In these cases, entanglement leads to an enhancement of the approximation capabilities of the network compared to local readouts of the individual qubits in non-entangling networks. We attribute this enhancement to a larger survival set of Fourier harmonics when decomposing the output signal.

quant-ph↗

arXiv2023

Characterization of the photon emission statistics in nitrogen-vacancy centers

We model and experimentally demonstrate the full time-dependent counting statistics of photons emitted by a single nitrogen-vacancy (NV) center in diamond under non-resonant laser excitation and resonant microwave control. A generalization of the quantum jump formalism for the seven electronic states involved in the fast intrinsic dynamics of an NV center provides a self-contained model that allows for the characterization of its emission and clarifies the relation between the quantum system internal states and the measurable detected photon counts. The model allows the elaboration of detection protocols to optimize the energy and time resources while maximizing the system sensitivity to magnetic-field measurements.

quant-ph↗

arXiv2022

A Neural Network Assisted $^{171}$Yb$^{+}$ Quantum Magnetometer

A versatile magnetometer must deliver a readable response when exposed to target fields in a wide range of parameters. In this work, we experimentally demonstrate that the combination of $^{171}$Yb$^{+}$ atomic sensors with adequately trained neural networks enables to investigate target fields in distinct challenging scenarios. In particular, we characterize radio frequency (RF) fields in the presence of large shot noise, including the limit case of continuous data acquisition via single-shot measurements. Furthermore, by incorporating neural networks we significantly extend the working regime of atomic magnetometers into scenarios in which the RF driving induces responses beyond their standard harmonic behavior. Our results indicate the benefits to integrate neural networks at the data processing stage of general quantum sensing tasks to decipher the information contained in the sensor responses.

quant-ph↗

arXiv2022

Neural networks for Bayesian quantum many-body magnetometry

Entangled quantum many-body systems can be used as sensors that enable the estimation of parameters with a precision larger than that achievable with ensembles of individual quantum detectors. Typically, the parameter estimation strategy requires the microscopic modelling of the quantum many-body system, as well as a an accurate description of its dynamics. This entails a complexity that can hinder the applicability of Bayesian inference techniques. In this work we show how to circumvent these issues by using neural networks that faithfully reproduce the dynamics of quantum many-body sensors, thus allowing for an efficient Bayesian analysis. We exemplify with an XXZ model driven by magnetic fields, and show that our method is capable to yield an estimation of field parameters beyond the standard quantum limit scaling. Our work paves the way for the practical use of quantum many-body systems as black-box sensors exploiting quantum resources to improve precision estimation.

quant-ph↗

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.

quant-ph↗

arXiv2022

Robust Two-Qubit Gates Using Pulsed Dynamical Decoupling

We present the experimental implementation of a two-qubit phase gate, using a radio frequency (RF) controlled trapped-ion quantum processor. The RF-driven gate is generated by a pulsed dynamical decoupling sequence applied to the ions' carrier transitions only. It allows for a tunable phase shift with high-fidelity results, in particular a fringe contrast up to $99_{-2}^{+1}\%$ is observed in Ramsey-type measurements. We also prepare a Bell state using this laser-free gate. The phase gate is robust against common sources of error. We investigate the effect of the excitation of the center-of-mass (COM) mode, errors in the axial trap frequency, pulse area errors and errors in sequence timing. The contrast of the phase gate is not significantly reduced up to a COM mode excitation $<20$ phonons, trap frequency errors of +10%, and pulse area errors of -8%. The phase shift is not significantly affected up to $<10$ phonons and pulse area errors of -2%. Both, contrast and phase shift are robust to timing errors up to -30% and +15%. The gate implementation is resource efficient, since only a single driving field is required per ion. Furthermore, it holds the potential for fast gate speeds (gate times on the order of $100~μ$s) by using two axial motional modes of a two-ion crystal through improved setups.

quant-ph↗

arXiv2022

Mutual Reinforcement between Neural Networks and Quantum Physics

Quantum machine learning emerges from the symbiosis of quantum mechanics and machine learning. In particular, the latter gets displayed in quantum sciences as: (i) the use of classical machine learning as a tool applied to quantum physics problems, (ii) or the use of quantum resources such as superposition, entanglement, or quantum optimization protocols to enhance the performance of classification and regression tasks compare to their classical counterparts. This paper reviews examples in these two scenarios. On the one hand, a classical neural network is applied to design a new quantum sensing protocol. On the other hand, the design of a quantum neural network based on the dynamics of a quantum perceptron with the application of shortcuts to adiabaticity gives rise to a short operation time and robust performance. These examples demonstrate the mutual reinforcement of both neural networks and quantum physics.

quant-ph↗

arXiv2021

Neural-network-based parameter estimation for quantum detection

Artificial neural networks bridge input data into output results by approximately encoding the function that relates them. This is achieved after training the network with a collection of known inputs and results leading to an adjustment of the neuron connections and biases. In the context of quantum detection schemes, neural networks find a natural playground. In particular, in the presence of a target, a quantum sensor delivers a response, i.e., the input data, which can be subsequently processed by a neural network that outputs the target features. We demonstrate that adequately trained neural networks enable to characterize a target with minimal knowledge of the underlying physical model, in regimes where the quantum sensor presents complex responses, and under a significant shot noise due to a reduced number of measurements. We exemplify the method with a development for $^{171}$Yb$^{+}$ atomic sensors. However, our protocol is general, thus applicable to arbitrary quantum detection scenarios.

quant-ph↗

arXiv2021

Phase-adaptive dynamical decoupling methods for robust spin-spin dynamics in trapped ions

Quantum platforms based on trapped ions are main candidates to build a quantum hardware with computational capacities that largely surpass those of classical devices. Among the available control techniques in these setups, pulsed dynamical decoupling (pulsed DD) revealed as a useful method to process the information encoded in ion registers, whilst minimising the environmental noise over them. In this work, we incorporate a pulsed DD technique that uses random pulse phases, or correlated pulse phases, to significantly enhance the robustness of entangling spin-spin dynamics in trapped ions. This procedure was originally conceived in the context of nuclear magnetic resonance for nuclear spin detection purposes, and here we demonstrate that the same principles apply for robust quantum information processing in trapped-ion settings.

quant-ph↗