Weak measurements can give us partial information about the state of a quantum system with a ``partial collapse'' of the wave function. As in every practical measurement, this is done by partially entangling the system of interest with a measurement apparatus, followed by an unavoidable discard of the state of the system. Although the quantum logic gates to perform that on qubits are...
Variational quantum algorithms (VQAs) (Cerezo et al. [2021]) are hybrid approaches between classical and quantum computation, where a classical optimizer proposes parameter configurations for a quantum parametric circuit which is iteratively measured. Each measured solution is assessed according to a cost function that evaluates the energy of the system, which is sought to be optimized. The...
Common wisdom suggests that, in order to entangle two quantum emitters, it is desirable that these have identical natural frequencies, since this facilitates cross talk between them and enables the type of collective dynamics that leads to entanglement [1]. However, the fabrication of quantum emitters with identical properties is a significant challenge in solid state physics.
In this work,...
Quantum research is focused on using quantum systems to perform computations and tasks that are impossible with a classical approach. These quantum computational advantages are a result of exponential differences in the resources needed for classical and quantum systems to perform the same task. However, quantum information processing offers more than just computational power. There is a...
A quantum-controlled device may produce a scenario in which two general quantum operations can be performed in such a way that it is not possible to associate a definite order for their application. Such an indefinite causal order can be explored to produce nontrivial effects in quantum thermal devices. In this poster, we discuss a measurement-powered thermal device that consists of...
This work discusses the solution of partial differential equations using matrix-product states (MPS). The study focuses on the search for the lowest eigenstates of a Hamiltonian equation, for which five algorithms are introduced: imaginary time evolution, steepest gradient descent, an improved gradient descent, an implicitly restarted Arnoldi method and density-matrix renormalization group...
One of the goals within the quantum information community is the development of robust and reliable quantum networks. On those networks we will be able to perform quantum communication protocols and quantum computations. As quantum network technology becomes commonplace, the need for certification tools will arise to answer questions regarding the properties of the network.
Our goal is to...
Quantum state transfer is a key operation for quantum information processing. The original pitch-and-catch protocols rely on flying qubits or single photons with engineered wavepacket shapes to achieve a deterministic, fast and high-fidelity transfer. Yet, these protocols overlook two important factors, namely, the distortion of the wavepacket during the propagation and non-Markovian effects...
Light-matter entanglement plays a fundamental role in many applications of quantum information science. Thus, finding processes where it can be observed is an important task. Here, we address this matter by theoretically investigating the entanglement between light, and electrons generated in above-threshold ionization (ATI) process, where an input strong-laser field rips out an electron from...
Assuming an open quantum system consisting of two coupled oscillators, we investigate the evolution of quantum correlations and purity in an equilibrium thermal environment with regard to the Born-Markov approximation. We assume squeezed vacuum state as the initial state of the system and study the effect of repulsive and attraction interaction on the correlations. In addition, their...
Quantum Machine Learning is the field that aims to integrate machine learning into quantum computation. In the past years, some works have shown that we can naturally generate one-dimensional Fourier series with a simple supervised quantum learning model. However, there is a lack of explanation of such models for generating Fourier series of larger data-dimension. In this work, we provide a...
Quantum abstract detecting systems (QADS) provide a common framework to address detection problems in quantum computers [1]. A particular QADS family, that of combinatorial QADS [2], has been proved to be useful for decision problems on eigenvalues or phase estimation methods. In this work, we consider functional QADS, which not only have interesting theoretical properties (intrinsic detection...
We introduce a simple algorithm that efficiently computes tensor products of Pauli matrices. This is done by tailoring the calculations to this specific case, which allows to avoid unnecessary calculations. The strength of this strategy is benchmarked against state-of-the-art techniques, showing a remarkable acceleration. As a side product, we provide an optimized method for one key calculus...
Algorithms for associative memory typically rely on a network of many connected units. The prototypical example is the Hopfield model, whose generalizations to the quantum realm are mainly based on open quantum Ising models. We propose a realization of associative memory with a single driven-dissipative non-linear quantum oscillator exploiting its infinite degrees of freedom in phase space....
Weak values [1] and the Kirkwood-Dirac (KD) quasiprobability distribution [5, 3], recently connected with one another, have been associated with both foundational issues in quantum theory as well as advantages in quantum metrology. For example, the nonclassicality of weak values and KD distributions has been linked to quantum advantage in metrology [2] and quantification of quantum information...
Solving complex optimization problems remains, to this day, an area of intense research and a challenge for professionals in science, engineering, and industry. This context motivates the emergence of methods that efficiently deal with very diverse problems: multiobjective, with a large number of constraints, nonlinear or with uncertainty, among others. Bio-inspired and metaheuristic...
In this talk I present the Real Quantum Amplitude Estimation algorithm, an extension of Quantum Amplitude Estimation which is sensitive to the sign of the amplitude. Moreover, I propose an extension of the methodology which recovers the complex amplitude.
Connecting quantum computers to a quantum network opens a wide array of new applications, such as securely performing computations on distributed data sets. Near-term quantum networks will however remain noisy and hence correctness and security of protocols is not guaranteed.
Therefore, we consider noisy protocols with imperfect shared entangled states. This paper takes a first step in...
Most security proofs of quantum key distribution (QKD) disregard the effect of information leakage from the users’ devices, and, thus, do not protect against Trojan-horse attacks (THAs). In a THA, the eavesdropper injects strong light into the QKD apparatuses, and then analyzes the back-reflected light to learn information about their internal setting choices. Only a few recent works consider...
