arXiv subjects

Jonas Maziero

Publications and source records attributed to Jonas Maziero.

At least 19 recordsLinked to original sources

arXiv2026

Prime Number Identification Demonstrated with Quantum Processors Using a New Rescaling-Based Noise Mitigation Technique

We implement a quantum protocol for prime number identification based on entanglement dynamics, using IBM quantum processors. The method links the primality of an integer to specific Fourier components extracted from the time evolution of entanglement in a bipartite quantum system. To mitigate experimental noise, we introduce a noise-mitigation method based on a global rescaling factor, which is calibrated on a subset of circuits and extrapolated across different configurations. Theoretical support is provided by a new analytical bound for the Fourier modes derived assuming an initial uniform superposition state. This new bound enhances the separation between prime and composite numbers under moderate experimental deviations. These results represent a step toward practical number-theoretic applications on noisy intermediate-scale quantum (NISQ) devices.

quant-ph↗

arXiv2026

Bohr's complementarity

Quantum complementarity is a fundamental feature of quantum systems and has captivated the physics research community for nearly a century, with significant advancements emerging in recent decades. This review traces the historical evolution of the concept of complementarity, beginning with Bohr's original formulation. It then explores its modern quantification through complementarity relations and its profound connection to the foundational postulates of quantum theory. Furthermore, it delves into key related developments, such as the operational definition of complementarity in the context of incompatible observables, its potential links with quantum uncertainty relations and contextuality, its various applications, and other pertinent topics. This review aims to serve physicists interested in quantum resources, quantum correlations, and the foundational principles of quantum mechanics.

quant-ph↗

arXiv2025

Screening in the Heitler-London Model: Revisiting the Bonding and Antibonding States of the Hydrogen Molecule

The present manuscript revisits one of the earliest approaches to treating molecular systems within the Schr\"odinger formalism of quantum mechanics: the Heitler-London (HL) model. Originally proposed in 1927 and based on a linear combination of atomic orbitals, the HL model provided a foundational description of covalent bonds and has served as the basis for numerous variational methods. Focusing on the hydrogen molecule, we begin by revisiting the analytical calculations of the original HL model, from which the qualitative physics of bonding and antibonding states can be obtained. Subsequently, we propose including electronic screening effects directly in the original HL wave function. We then compare our proposal with variational quantum Monte Carlo (VQMC) calculations, whose trial wave function allows us to optimize the electronic screening potential as a function of the inter-proton distance. We obtain the bond length, binding energy, and vibrational frequency of the H$_2$ molecule. Beyond revisiting this foundational approach in quantum mechanics, our proposal can serve as improved input for constructing new, but still analytically simple, variational wave functions to describe dissociation or bond formation.

physics.chem-ph↗

arXiv2025

Work distribution of quantum fields in static curved spacetimes

We investigate the formulation of work distributions for quantum scalar fields in static curved spacetimes by extending the Ramsey interferometric protocol originally developed in previous works for flat spacetimes. The use of Unruh-DeWitt particle detectors provides a causally consistent framework to define and measure work statistics, avoiding the limitations of the two-time projective measurement scheme in relativistic quantum field theory. We derive a non-perturbative expression for the characteristic function of the quantum field and apply it to thermal Kubo-Martin-Schwinger (KMS) states, showing that the resulting work distributions satisfy both the Crooks fluctuation theorem and the Jarzynski equality. Furthermore, we analyse the case of a pointlike detector, obtaining compact expressions for the first two moments of the work distribution, allowing us to recover the standard fluctuation-dissipation relation in the high-temperature limit. Our results demonstrate that fluctuation theorems hold for quantum fields interacting with Unruh-DeWitt particle detectors in static curved spacetimes.

quant-ph↗

arXiv2025

Entanglement distribution in quantum networks via swapping of partially entangled pure states

The entanglement swapping protocol (ESP) is a fundamental primitive for distributing quantum correlations across distant nodes in a quantum network. Recent studies have demonstrated that even when the involved qubit pairs are only partially entangled, it is still possible to concentrate and transmit entanglement via Bell-basis measurements. In this work, we extend these ideas to quantum networks with various topologies--including linear, star, and hybrid configurations--by analysing the application of the ESP to initially partially entangled pure states. We investigate how entanglement evolves under such protocols by considering the transformations of the initial states and evaluating the success probabilities for generating maximally entangled states at the output. Our results offer new insights into the dynamics of the entanglement distribution in quantum networks.

quant-ph↗

arXiv2025

Entanglement swapping for partially entangled qudits and the role of quantum complementarity

We extend the entanglement swapping protocol (ESP) to partially entangled qudit states and analyze the process within the framework of complete complementarity relations (CCRs). Building on previous results for qubits, we show that the average distributed entanglement between two parties via ESP is bounded above by the initial entanglement of one of the input pairs, and also by the product of the initial entanglements. Notably, we find that using initial states with vanishing local quantum coherence is sufficient to capture the essential features of the protocol, simplifying the analysis. By exploring the cases of qubits and qutrits, we observe that the upper bound on the average distributed entanglement -- expressed in terms of the product of the initial entanglements -- can be improved, and we conjecture what this tighter bound might be. Finally, we discuss the role of quantum complementarity in the ESP and show how local predictability constrains the entanglement that can be operationally distributed via ESP.

quant-ph↗

arXiv2025

Efficient detection of localization transitions using predictability

Identifying phase transition points is a fundamental challenge in condensed matter physics, particularly for transitions driven by quantum interference effects, such as Anderson and many-body localization. Recent studies have demonstrated that quantum coherence provides an effective means of detecting localization transitions, offering a practical alternative to full quantum state tomography and related approaches. Building on this idea, we investigate localization transitions through complementarity relations that connect local predictability, local coherence, and entanglement in bipartite pure states. Our results show that predictability serves as a robust and efficient marker for localization transitions. Crucially, its experimental determination requires exponentially fewer measurements than coherence or entanglement, making it a powerful tool for probing quantum phase transitions.

quant-ph↗

arXiv2025

A variational quantum algorithm for entanglement quantification

Quantum entanglement is a foundational resource in quantum information science, underpinning applications across physics. However, detecting and quantifying entanglement remains a significant challenge. In this article, we introduce a variational quantum algorithm inspired by Uhlmann's theorem to quantify the Bures entanglement of general quantum states, a method that naturally extends to other quantum resources, including genuine multipartite entanglement, quantum discord, quantum coherence, and total correlations, while also enabling reconstruction of the closest free states. The algorithm requires a polynomial number of ancillary qubits and circuit depth relative to the system size, dimensionality, and free state cardinality, making it scalable for practical implementations. Thus, it provides a versatile framework for quantifying quantum resources, demonstrated here through several applications.

quant-ph↗

arXiv2025

QuForge: A Library for Qudits Simulation

Quantum computing with qudits, an extension of qubits to multiple levels, is a research field less mature than qubit-based quantum computing. However, qudits can offer some advantages over qubits, by representing information with fewer separated components. In this article, we present QuForge, a Python-based library designed to simulate quantum circuits with qudits. This library provides the necessary quantum gates for implementing quantum algorithms, tailored to any chosen qudit dimension. Built on top of differentiable frameworks, QuForge supports execution on accelerating devices such as GPUs and TPUs, significantly speeding up simulations. It also supports sparse operations, leading to a reduction in memory consumption compared to other libraries. Additionally, by constructing quantum circuits as differentiable graphs, QuForge facilitates the implementation of quantum machine learning algorithms, enhancing the capabilities and flexibility of quantum computing research.

quant-ph↗

arXiv2025

Quantum neural network with ensemble learning to mitigate barren plateaus and cost function concentration

The rapid development of quantum computers promises transformative impacts across diverse fields of science and technology. Quantum neural networks (QNNs), as a forefront application, hold substantial potential. Despite the multitude of proposed models in the literature, persistent challenges, notably the vanishing gradient (VG) and cost function concentration (CFC) problems, impede their widespread success. In this study, we introduce a novel approach to quantum neural network construction, specifically addressing the issues of VG and CFC. Our methodology employs ensemble learning, advocating for the simultaneous deployment of multiple quantum circuits with a depth equal to $1$, a departure from the conventional use of a single quantum circuit with depth $L$. We assess the efficacy of our proposed model through a comparative analysis with a conventionally constructed QNN. The evaluation unfolds in the context of a classification problem, yielding valuable insights into the potential advantages of our innovative approach.

quant-ph↗

arXiv2025

A short review on qudit quantum machine learning

As quantum devices scale toward practical machine learning applications, the binary qubit paradigm faces expressivity and resource efficiency limitations. Multi-level quantum systems, or qudits, offer a promising alternative by harnessing a larger Hilbert space, enabling richer data embeddings, more compact variational circuits, and support for multi-valued problem structures. In this work, we review the role of qudits in quantum machine learning techniques, mainly variational quantum algorithms and quantum neural networks. Drawing on recent experimental demonstrations, including high-level superconducting transmons, qutrit-based combinatorial optimization, and single-qudit classifiers, we highlight how qudit architectures can reduce circuit depth and parameter counts while maintaining competitive fidelity. We further assess the evolving software ecosystem, from specialized simulators and differentiable-programming libraries to extensions of mainstream frameworks. We also identify key challenges in control complexity, noise management, and tooling maturity.

quant-ph↗

arXiv2025

Barren plateaus are amplified by the dimension of qudits

Variational Quantum Algorithms (VQAs) have emerged as pivotal strategies for attaining quantum advantage in diverse scientific and technological domains, notably within Quantum Neural Networks. However, despite their potential, VQAs encounter significant obstacles, chief among them being the vanishing gradient problem, commonly referred to as barren plateaus. In this article, through meticulous analysis, we demonstrate that existing literature implicitly suggests the intrinsic influence of qudit dimensionality on barren plateaus. To instantiate these findings, we present numerical results that exemplify the impact of qudit dimensionality on barren plateaus. Therefore, despite the proposition of various error mitigation techniques, our results call for further scrutiny about their efficacy in the context of VQAs with qudits.

quant-ph↗

arXiv2025

MixFunn: A Neural Network for Differential Equations with Improved Generalization and Interpretability

We introduce MixFunn, a novel neural network architecture designed to solve differential equations with enhanced precision, interpretability, and generalization capability. The architecture comprises two key components: the mixed-function neuron, which integrates multiple parameterized nonlinear functions to improve representational flexibility, and the second-order neuron, which combines a linear transformation of its inputs with a quadratic term to capture cross-combinations of input variables. These features significantly enhance the expressive power of the network, enabling it to achieve comparable or superior results with drastically fewer parameters and a reduction of up to four orders of magnitude compared to conventional approaches. We applied MixFunn in a physics-informed setting to solve differential equations in classical mechanics, quantum mechanics, and fluid dynamics, demonstrating its effectiveness in achieving higher accuracy and improved generalization to regions outside the training domain relative to standard machine learning models. Furthermore, the architecture facilitates the extraction of interpretable analytical expressions, offering valuable insights into the underlying solutions.

cs.LG↗

arXiv2025

Learning to learn with an evolutionary strategy applied to variational quantum algorithms

Variational Quantum Algorithms (VQAs) employ parameterized quantum circuits optimized using classical methods to minimize a cost function. While VQAs have found broad applications, certain challenges persist. Notably, a significant computational burden arises during parameter optimization. The prevailing ``parameter shift rule'' mandates a double evaluation of the cost function for each parameter. In this article, we introduce a novel optimization approach named ``Learning to Learn with an Evolutionary Strategy'' (LLES). LLES unifies ``Learning to Learn'' and ``Evolutionary Strategy'' methods. ``Learning to Learn'' treats optimization as a learning problem, utilizing recurrent neural networks to iteratively propose VQA parameters. Conversely, ``Evolutionary Strategy'' employs gradient searches to estimate function gradients. Our optimization method is applied to two distinct tasks: determining the ground state of an Ising Hamiltonian and training a quantum neural network. The obtained results underscore the efficacy of this novel approach. Additionally, we identify a key hyperparameter that significantly influences gradient estimation using the ``Evolutionary Strategy'' method.

quant-ph↗

arXiv2025

Quantum fluctuation theorem in a curved spacetime

The interplay between thermodynamics, general relativity and quantum mechanics has long intrigued researchers. Recently, important advances have been obtained in thermodynamics, mainly regarding its application to the quantum domain through fluctuation theorems. In this letter, we apply Fermi normal coordinates to report a fully general relativistic detailed quantum fluctuation theorem based on the two point measurement scheme. We demonstrate how the spacetime curvature can produce entropy in a localized quantum system moving in a general spacetime. The example of a quantum harmonic oscillator living in an expanding universe is presented. This result implies that entropy production is strongly observer dependent and deeply connects the arrow of time with the causal structure of the spacetime.

gr-qc↗

arXiv2025

Digital quantum simulation of bosonic systems and quantum complementarity

Digital quantum simulation (DQS) has emerged as a powerful approach to investigate complex quantum systems using digital quantum computers. Such systems, like many-particle bosonic systems and intricate optical experimental setups, pose significant challenges for classical simulation methods. In this paper, we utilize a general formalism for the DQS of bosonic systems, which consists of mapping bosonic operators to Pauli operators using the Gray code, in order to simulate interferometric variants of Afshar's experiment -- an intricate optical experiment -- on IBM's quantum computers. We investigated experiments analogous to Afshar's double-slit experiment performed by Unruh and Pessoa J\'unior, exploring discussions on the apparent violation of Bohr's complementarity principle when considering the entire experimental setup. Based on the aforementioned experiments, we construct a variation of a delayed-choice setup. We also explore another experiment starting with a two-photon initial state. Finally, we analyze these experiments within the framework of an updated quantum complementarity principle, which applies to specific quantum state preparations and remains consistent with the foundational principles of Quantum Mechanics.

quant-ph↗

arXiv2024

An Updated Quantum Complementarity Principle

Bohr's complementarity principle has long been a fundamental concept in quantum mechanics, positing that, within a given experimental setup, a quantum system (or quanton) can exhibit either its wave-like character, denoted as $W$, or its particle-like character, denoted as $P$, but not both simultaneously. Modern interpretations of Bohr's complementarity principle acknowledge the coexistence of these aspects in the same experiment while introducing the constraint $W + P \le α$. Notably, estimations of $W$ or $P$ frequently rely on indirect retrodiction methods, a practice that has led to the claim of the violation of Bohr's complementarity principle. By taking a different route, recent advancements demonstrate that quantum complementarity relations can be rigorously derived from the axioms of quantum mechanics. To reconcile these observations and eliminate potential paradoxes or violations, we propose an updated formulation for the quantum complementarity principle, which is stated as follows: \textit{For a given quantum state preparation $ρ_t$ at a specific instant of time $t$, the wave and particle behaviors of a quanton are constrained by a complementarity relation $\mathfrak{W}(ρ_t) + \mathfrak{P}(ρ_t) \le α(d)$, which is derived directly from the axioms of quantum mechanics.}

quant-ph↗

arXiv2024

Non-binary artificial neuron with phase variation implemented on a quantum computer

The first artificial quantum neuron models followed a similar path to classic models, as they work only with discrete values. Here we introduce an algorithm that generalizes the binary model manipulating the phase of complex numbers. We propose, test, and implement a neuron model that works with continuous values in a quantum computer. Through simulations, we demonstrate that our model may work in a hybrid training scheme utilizing gradient descent as a learning algorithm. This work represents another step in the direction of evaluation of the use of artificial neural networks efficiently implemented on near-term quantum devices.

quant-ph↗