Catálogo de publicaciones - revistas

<jats:title>Abstract</jats:title> <jats:p>The resurgence of self-supervised learning, whereby a deep learning model generates its own supervisory signal from the data, promises a scalable way to tackle the dramatically increasing size of real-world data sets without human annotation. However, the staggering computational complexity of these methods is such that for state-of-the-art performance, classical hardware requirements represent a significant bottleneck to further progress. Here we take the first steps to understanding whether quantum neural networks (QNNs) could meet the demand for more powerful architectures and test its effectiveness in proof-of-principle hybrid experiments. Interestingly, we observe a numerical advantage for the learning of visual representations using small-scale QNN over equivalently structured classical networks, even when the quantum circuits are sampled with only 100 shots. Furthermore, we apply our best quantum model to classify unseen images on the <jats:italic>ibmq_paris</jats:italic> quantum computer and find that current noisy devices can already achieve equal accuracy to the equivalent classical model on downstream tasks.</jats:p>

<jats:title>Abstract</jats:title> <jats:p>Fully internal and motional state controlled and individually manipulable polar molecules are desirable for many quantum science applications leveraging the rich state space and intrinsic interactions of molecules. While prior efforts at assembling molecules from their constituent atoms individually trapped in optical tweezers achieved such a goal for exactly one molecule (Zhang J T <jats:italic>et al</jats:italic> 2020 <jats:italic>Phys. Rev. Lett.</jats:italic> <jats:bold>124</jats:bold> 253401; Cairncross W B <jats:italic>et al</jats:italic> 2021 <jats:italic>Phys. Rev. Lett.</jats:italic> <jats:bold>126</jats:bold> 123402; He X <jats:italic>et al</jats:italic> 2020 <jats:italic>Science</jats:italic> <jats:bold>370</jats:bold> 331–5), here we extend the technique to an array of five molecules, unlocking the ability to study molecular interactions. We detail the technical challenges and solutions inherent in scaling this system up. With parallel preparation and control of multiple molecules in hand, this platform now serves as a starting point to harness the vast resources and long-range dipolar interactions of molecules.</jats:p>

<jats:title>Abstract</jats:title> <jats:p>In superconducting quantum circuits (SQCs), chiral routing quantum information is often realized with the ferrite circulators, which are usually bulky, lossy and require strong magnetic fields. To overcome those problems, we propose a novel method to realize chiral quantum networks by exploiting giant atom effects in SQC platforms. By assuming each coupling point being modulated with time, the interaction becomes momentum-dependent, and giant atoms will chirally emit photons due to interference effects. The chiral factor can approach 1, and both the emission direction and rate can be freely tuned by the modulating signals. We demonstrate that a high-fidelity state transfer between remote giant atoms can be realized. Our proposal can be integrated on the superconducting chip easily, and has the potential to work as a tunable toolbox for quantum information processing in future chiral quantum networks.</jats:p>

<jats:title>Abstract</jats:title> <jats:p>Many near-term quantum computing algorithms are conceived as variational quantum algorithms, in which parameterized quantum circuits are optimized in a hybrid quantum–classical setup. Examples are variational quantum eigensolvers, quantum approximate optimization algorithms as well as various algorithms in the context of quantum-assisted machine learning. A common bottleneck of any such algorithm is constituted by the optimization of the variational parameters. A popular set of optimization methods work on the estimate of the gradient, obtained by means of circuit evaluations. We will refer to the way in which one can combine these circuit evaluations as gradient rules. This work provides a comprehensive picture of the family of gradient rules that vary parameters of quantum gates individually. The most prominent known members of this family are the parameter shift rule (PSR) and the finite differences method. To unite this family, we propose a generalized PSR that expresses all members of the aforementioned family as special cases, and discuss how all of these can be seen as providing access to a linear combination of exact first- and second-order derivatives. We further prove that a PSR with one non-shifted evaluation and only one shifted circuit evaluation does not exist, and introduce a novel perspective for approaching new gradient rules.</jats:p>

<jats:title>Abstract</jats:title> <jats:p>In the present work, the evolution of a three state quantum walk without decoherence is investigated. Despite being a closed quantum system under unitary evolution, its Hilbert space can be divided in two subspaces, which enables the analysis of the subsystems (the coin or the walker) as an open system in contact with a reservoir. We calculate the asymptotic reduced density matrix of the coin space of the three-state quantum walk in an infinite line, and use that result to analyze the entanglement between the chirality, and position space. We calculate the von Neumann entropy and the entanglement temperature per mean energy of the system in the asymptotic limit.</jats:p>

<jats:title>Abstract</jats:title> <jats:p>Phase transitions represent a compelling tool for classical and quantum sensing applications. It has been demonstrated that quantum sensors can in principle saturate the Heisenberg scaling, the ultimate precision bound allowed by quantum mechanics, in the limit of large probe number and long measurement time. Due to the critical slowing down, the protocol duration time is of utmost relevance in critical quantum metrology. However, how the long-time limit is reached remains in general an open question. So far, only two dichotomic approaches have been considered, based on either static or dynamical properties of critical quantum systems. Here, we provide a comprehensive analysis of the scaling of the quantum Fisher information for different families of protocols that create a continuous connection between static and dynamical approaches. In particular, we consider fully-connected models, a broad class of quantum critical systems of high experimental relevance. Our analysis unveils the existence of universal precision-scaling regimes. These regimes remain valid even for finite-time protocols and finite-size systems. We also frame these results in a general theoretical perspective, by deriving a precision bound for arbitrary time-dependent quadratic Hamiltonians.</jats:p>

<jats:title>Abstract</jats:title> <jats:p>In probabilistic quantum metrology, one aims at finding measurements that <jats:italic>concentrate</jats:italic> the Fisher information on the resulting conditional quantum states, i.e. those states post-selected according to the outcome of the measurement. The quantum Cramér–Rao (QCR) bound itself cannot be surpassed this way, but it could be possible to improve the information-cost ratio (where <jats:italic>cost</jats:italic> refers to the experimental implementation), or even the total Fisher information. In this paper, we propose a post-selection protocol achieving this goal using single-photon subtraction and thermal states of radiation. In particular, we achieve a larger information-cost ratio for the estimation of temperature than the strategy attaining the QCR bound. Our scheme involves only classical states of radiation and this contrasts with (but does not contradict) recent results proving that for <jats:italic>unitary</jats:italic> quantum statistical models, post-selection strategies can outperform direct protocols only exploiting nonclassical states.</jats:p>

<jats:title>Abstract</jats:title> <jats:p>Cavity quantum optomechanics has emerged as a new platform for quantum science and technology with applications ranging from quantum-information processing to tests of the foundations of physics. Of crucial importance for optomechanics is the generation and verification of non-Gaussian states of motion and a key outstanding challenge is the observation of a canonical two-mode Schrödinger-cat state in the displacement of two mechanical oscillators. In this work, we introduce a pulsed approach that utilizes the nonlinearity of the radiation–pressure interaction combined with photon-counting measurements to generate this entangled non-Gaussian mechanical state, and, importantly, describe a protocol using subsequent pulsed interactions to verify the non-Gaussian entanglement generated. Our pulsed verification protocol allows quadrature moments of the two mechanical oscillators to be measured up to any finite order providing a toolset for experimental characterisation of bipartite mechanical quantum states and allowing a broad range of inseparability criteria to be evaluated. Key experimental factors, such as optical loss and open-system dynamics, are carefully analyzed and we show that the scheme is feasible with only minor improvements to current experiments that operate outside the resolved-sideband regime. Our scheme provides a new avenue for quantum experiments with entangled mechanical oscillators and offers significant potential for further research and development that utilizes such non-Gaussian states for quantum-information and sensing applications, and for studying the quantum-to-classical transition.</jats:p>

<jats:title>Abstract</jats:title> <jats:p>L0-regularization-based compressed sensing (L0-RBCS) has the potential to outperform L1-regularization-based compressed sensing (L1-RBCS), but the optimization in L0-RBCS is difficult because it is a combinatorial optimization problem. To perform optimization in L0-RBCS, we propose a quantum–classical hybrid system consisting of a quantum machine and a classical digital processor. The coherent Ising machine (CIM) is a suitable quantum machine for this system because this optimization problem can only be solved with a densely connected network. To evaluate the performance of the CIM-classical hybrid system theoretically, a truncated Wigner stochastic differential equation (W-SDE) is introduced as a model for the network of degenerate optical parametric oscillators, and macroscopic equations are derived by applying statistical mechanics to the W-SDE. We show that the system performance in principle approaches the theoretical limit of compressed sensing and this hybrid system may exceed the estimation accuracy of L1-RBCS in actual situations, such as in magnetic resonance imaging data analysis.</jats:p>

<jats:title>Abstract</jats:title> <jats:p>Hybrid quantum–classical algorithms are a promising candidate for developing uses for NISQ devices. In particular, parametrised quantum circuits (PQCs) paired with classical optimizers have been used as a basis for quantum chemistry and quantum optimization problems. Tensor network methods are being increasingly used as a classical machine learning tool, as well as a tool for studying quantum systems. We introduce a circuit pre-training method based on matrix product state machine learning methods, and demonstrate that it accelerates training of PQCs for both supervised learning, energy minimization, and combinatorial optimization.</jats:p>