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One of the most ambitious goals of quantum simulation of quantum field theory is the description of scattering in real time, which would allow not only for computation of scattering amplitudes, but also for studying the collision process step by step. The initial state of such simulation is made of typically two wavepackets moving on top of the vacuum, whose preparation is hard. Some proposals are based on a modified adiabatic transformation of free wavepackets into interacting wavepackets, but this is not suitable for quantum chromodynamics (QCD). Other approaches used in one-dimensional lattice gauge theories rely on an adiabatic transformation from the strong coupling limit, or on ansatzes to create the wavepackets from the full, interacting vacuum. Here we extend a previous work to create wavepackets of a general kind of particle from the vacuum in lattice gauge theories in one and three dimensions, including QCD. The conceptual foundation of this approach is the Haag-Ruelle scattering theory, and the only theoretical limitation is given by massless particles. In the context of digital quantum computation, the wavepacket creation from the vacuum is implemented with the technique known as LCU (linear combination of unitaries). The preparation is performed successfully with a certain success probability, which may represent the main obstacle of our approach., Comment: 17 pages, 4 figures. Key words: quantum simulation, lattice QCD, scattering

This summary of the second Terrestrial Very-Long-Baseline Atom Interferometry (TVLBAI) Workshop provides a comprehensive overview of our meeting held in London in April 2024, building on the initial discussions during the inaugural workshop held at CERN in March 2023. Like the summary of the first workshop, this document records a critical milestone for the international atom interferometry community. It documents our concerted efforts to evaluate progress, address emerging challenges, and refine strategic directions for future large-scale atom interferometry projects. Our commitment to collaboration is manifested by the integration of diverse expertise and the coordination of international resources, all aimed at advancing the frontiers of atom interferometry physics and technology, as set out in a Memorandum of Understanding signed by over 50 institutions., Comment: Summary of the second Terrestrial Very-Long-Baseline Atom Interferometry Workshop held at Imperial College London: https://indico.cern.ch/event/1369392/

We introduce and investigate a data access model (approximate sample and query) that is satisfiable by the preparation and measurement of block encoded states, as well as in contexts such as classical quantum circuit simulation or Pauli sampling. We illustrate that this abstraction is compositional and has some computational power. We then apply these results to obtain polynomial improvements over the state of the art in the sample and computational complexity of distributed inner product estimation. By doing so, we provide a new interpretation for why Pauli sampling is useful for this task. Our results partially characterize the power of time-limited fault-tolerant quantum circuits aided by classical computation. They are a first step towards extending the classical data Quantum Singular Value Transform dequantization results to a quantum setting., Comment: 31 pages, 1 figure. Keywords: sample and query, hybrid quantum-classical algorithms, distributed inner product, Pauli sampling, limited coherence

Distributed quantum sensing enables the estimation of multiple parameters encoded in spatially separated probes. While traditional quantum sensing is often focused on estimating a single parameter with maximum precision, distributed quantum sensing seeks to estimate some function of multiple parameters that are only locally accessible for each party involved. In such settings it is natural to not want to give away more information than is necessary. To address this, we use the concept of privacy with respect to a function, ensuring that only information about the target function is available to all the parties, and no other information. We define a measure of privacy (essentially how close we are to this condition being satisfied), and show it satisfies a set of naturally desirable properties of such a measure. Using this privacy measure, we identify and construct entangled resources states that ensure privacy for a given function under different resource distributions and encoding dynamics, characterized by Hamiltonian evolution. For separable and parallel Hamiltonians, we prove that the GHZ state is the only private state for certain linear functions, with the minimum amount of required resources, up to SLOCC. Recognizing the vulnerability of this state to particle loss, we create families of private states, that remain robust even against loss of qubits, by incorporating additional resources. We then extend our findings to different resource distribution scenarios and Hamiltonians, resulting in a comprehensive set of private and robust states for distributed quantum estimation. These results advance the understanding of privacy and robustness in multi-parameter quantum sensing., Comment: Keywords: Quantum Sensing, GHZ states, Private Sensing, Quantum Information

The metrological limits of thermometry operated in nonequilibrium dynamical regimes are analyzed. We consider a finite-dimensional quantum system, employed as a quantum thermometer, in contact with a thermal bath inducing Markovian thermalization dynamics. The quantum thermometer is initialized in a generic quantum state, possibly including quantum coherence w.r.t. the Hamiltonian basis. We prove that the sensitivity of the thermometer, quantified by the quantum Fisher information, is enhanced by the quantum coherence in its initial state. We analytically show this in the specific case of qubit thermometers for which the maximization of the quantum Fisher information occurs at a finite time during the transient of the thermalization dynamics. Such a finite-time sensitivity enhancement can be better than the sensitivity that is achieved asymptotically., Comment: 19 pages, 5 figures. Comments and feedback are welcome

The question of the energetic efficiency of quantum computers has gained some attention only recently. A precise understanding of the resources required to operate a quantum computer with a targeted computational performance and how the energy requirements can impact the scalability is still missing. In this work, one implementation of the quantum Fourier transform (QFT) algorithm in a trapped ion setup was studied. The main focus was to obtain a theoretical characterization of the energetic costs of quantum computation. The energetic cost of the experiment was estimated by analyzing the components of the setup and the steps involved in a quantum computation, from the cooling and preparation of the ions to the implementation of the algorithm and readout of the result. A potential scaling of the energetic costs was argued and used to find a possible threshold for an energetic quantum advantage against state-of-the-art classical supercomputers., Comment: Keywords: Quantum Energetics; Quantum Advantage; Quantum Computation; Quantum Fourier Transform; Trapped Ions

This document presents a summary of the 2023 Terrestrial Very-Long-Baseline Atom Interferometry Workshop hosted by CERN. The workshop brought together experts from around the world to discuss the exciting developments in large-scale atom interferometer (AI) prototypes and their potential for detecting ultralight dark matter and gravitational waves. The primary objective of the workshop was to lay the groundwork for an international TVLBAI proto-collaboration. This collaboration aims to unite researchers from different institutions to strategize and secure funding for terrestrial large-scale AI projects. The ultimate goal is to create a roadmap detailing the design and technology choices for one or more km-scale detectors, which will be operational in the mid-2030s. The key sections of this report present the physics case and technical challenges, together with a comprehensive overview of the discussions at the workshop together with the main conclusions., Comment: Summary of the Terrestrial Very-Long-Baseline Atom Interferometry Workshop held at CERN: https://indico.cern.ch/event/1208783/

Despite the promise that fault-tolerant quantum computers can efficiently solve classically intractable problems, it remains a major challenge to find quantum algorithms that may reach computational advantage in the present era of noisy, small-scale quantum hardware. Thus, there is substantial ongoing effort to create new quantum algorithms (or adapt existing ones) to accommodate depth and space restrictions. By adopting a hybrid query perspective, we identify and characterize two methods of ``breaking down'' quantum algorithms into rounds of lower (query) depth, designating these approaches as ``parallelization'' and ``interpolation''. To the best of our knowledge, these had not been explicitly identified and compared side-by-side, although one can find instances of them in the literature. We apply them to two problems with known quantum speedup: calculating the $k$-threshold function and computing a NAND tree. We show that for the first problem parallelization offers the best performance, while for the second interpolation is the better choice. This illustrates that no approach is strictly better than the other, and so that there is more than one good way to break down a quantum algorithm into a hybrid quantum-classical algorithm., Comment: 13 pages, 1 figure. Keywords: hybrid quantum-classical algorithms, quantum singular value transformations, quantum algorithms, limited coherence, oracle complexity, algorithm design

The last few years have seen rapid development of applications of quantum computation to quantum field theory. The first algorithms for quantum simulation of scattering have been proposed in the context of scalar and fermionic theories, requiring thousands of logical qubits. These algorithms are not suitable to simulate scattering of incoming bound states, as the initial-state preparation relies typically on adiabatically transforming wavepackets of the free theory into wavepackets of the interacting theory. In this paper we present a strategy to excite wavepackets of the interacting theory directly from the vacuum of the interacting theory, allowing the preparation of states of composite particles. This is the first step towards digital quantum simulation of scattering of bound states. The approach is based on the Haag-Ruelle scattering theory, which provides a way to construct creation and annihilation operators of a theory in a full, nonperturbative framework. We provide a quantum algorithm requiring a number of ancillary qubits that is logarithmic in the size of the wavepackets, and with a success probability vanishing at most like a polynomial in the lattice parameters and the energy of the wavepacket. The gate complexity for a single iteration of the circuit is equivalent to that of a time evolution for a fixed time. Furthermore, we propose a complete protocol for scattering simulation using this algorithm. We study its efficiency and find improvements with respect to previous algorithms in the literature., Comment: Published version. 22 pages, 3 figures. Key words: quantum simulation, lattice field theory, scattering, bound states

The transfer of information between two physical locations is an essential component of both classical and quantum computing. In quantum computing the transfer of information must be coherent to preserve quantum states and hence the quantum information. We establish a simple protocol for transferring one- and two-electron encoded logical qubits in quantum dot arrays. The theoretical energetic cost of this protocol is calculated - in particular, the cost of freezing and unfreezing tunnelling between quantum dots. Our results are compared with the energetic cost of shuttling qubits in quantum dot arrays and transferring classical information using classical information buses. Only our protocol can manage constant dissipation for any chain length. This protocol could reduce the cooling requirements and constraints on scalable architectures for quantum dot quantum computers., Comment: 10 pages, 6 figures

Quantum Annealing has proven to be a powerful tool to tackle several optimization problems. However, its performance is severely impacted by the limited connectivity of the underlying quantum hardware, compromising the quantum speedup. In this work, we present a novel approach to address these issues, by describing a method to implement non-local couplings throught the lens of Local Operations and Classical Communcations (LOCC). Non-local couplings are very versatile, harnessing the configurability of distributed quantum networks, which in turn lead to great enhancement of the physical connectivity of the underlying hardware. Furthermore, the realization of non-local couplings between distinct quantum annealing processors activates the scalability potential of distributed systems, i.e. allowing for a distributed quantum annealing system. Finally, in a more distant vision, we also show that secure multi-party quantum annealing algorithms are possible, allowing for cooperation of distrusting parties through optimization with quantum annealing and a particular type of non-local couplings., Comment: Revised version discussing more applications

Giovannetti, Lloyd, and Maccone [Phys. Rev. Lett. 100, 160501] proposed a quantum random access memory (QRAM) architecture to retrieve arbitrary superpositions of $N$ (quantum) memory cells via $O(\log(N))$ quantum switches and $O(\log(N))$ address qubits. Towards physical QRAM implementations, Chen et al. [PRX Quantum 2, 030319] recently showed that QRAM maps natively onto optically connected quantum networks with $O(\log(N))$ overhead and built-in error detection. However, modeling QRAM on large networks has been stymied by exponentially rising classical compute requirements. Here, we address this bottleneck by: (i) introducing a resource-efficient method for simulating large-scale noisy entanglement, allowing us to evaluate hundreds and even thousands of qubits under various noise channels; and (ii) analyzing Chen et al.'s network-based QRAM as an application at the scale of quantum data centers or near-term quantum internet; and (iii) introducing a modified network-based QRAM architecture to improve quantum fidelity and access rate. We conclude that network-based QRAM could be built with existing or near-term technologies leveraging photonic integrated circuits and atomic or atom-like quantum memories., Comment: Keywords: Quantum RAM, Distributed Quantum Computation, Photonic Quantum Networks; Revised version with new section discussing the validity of the results

Reversible computation has been proposed as a future paradigm for energy efficient computation, but so far few implementations have been realised in practice. Quantum circuits, running on quantum computers, are one construct known to be reversible. In this work, we provide a proof-of-principle of classical logical gates running on quantum technologies. In particular, we propose, and realise experimentally, Toffoli and Half-Adder circuits suitable for classical computation, using radiofrequency-controlled $^{171}$Yb$^+$ ions in a macroscopic linear Paul-trap as qubits. We analyse the energy required to operate the logic gates, both theoretically and experimentally, with a focus on the control energy. We identify bottlenecks and possible improvements in future platforms for energetically-efficient computation, e.g., trap chips with integrated antennas and cavity QED. Our experimentally verified energetic model also fills a gap in the literature of the energetics of quantum information, and outlines the path for its detailed study, as well as its potential applications to classical computing., Comment: This article may be downloaded for personal use only. Any other use requires prior permission of the author and AIP Publishing. This article appeared in S. S. Pratapsi, P. H. Huber, P. Barthel, S. Bose, C. Wunderlich, Y. Omar; Classical half-adder using trapped-ion quantum bits: Toward energy-efficient computation. Appl. Phys. Lett. 123 (15): 154003, and may be found at doi.org/10.1063/5.0176719

Clustering algorithms are of fundamental importance when dealing with large unstructured datasets and discovering new patterns and correlations therein, with applications ranging from scientific research to medical imaging and marketing analysis. In this work, we introduce a quantum version of the density peak clustering algorithm, built upon a quantum routine for minimum finding. We prove a quantum speedup for a decision version of density peak clustering depending on the structure of the dataset. Specifically, the speedup is dependent on the heights of the trees of the induced graph of nearest-highers, i.e., the graph of connections to the nearest elements with higher density. We discuss this condition, showing that our algorithm is particularly suitable for high-dimensional datasets. Finally, we benchmark our proposal with a toy problem on a real quantum device.

We show how a minimization principle of quantum entanglement between the oscillating flavors of a neutrino leads to a unique prediction for the CP-violation phase in the neutrino sector without assuming extra symmetries in the Standard Model. We find a theoretical prediction consistent with either no CP-violation or a very small presence of it., Comment: 5 pages, 3 figures

We present a proposal for a one-bit full-adder to process classical information based on the quantum reversible dynamics of a triple quantum dot system. The device works via the repeated execution of a Fredkin gate implemented through the dynamics of a single time-independent Hamiltonian. Our proposal uses realistic parameter values and could be implemented on currently available quantum dot architectures. We compare the estimated energy requirements for operating our full-adder with those of well-known fully classical devices, and argue that our proposal may provide a consistently better energy efficiency. Our work serves as a proof of principle for the development of energy-efficient information technologies operating through coherent quantum dynamics., Comment: V2: Minor updates. -- Keywords: energy-efficient computing, quantum dynamics, quantum gates, semiconductor quantum dots, quantum technologies

The field of propagating quantum microwaves has started to receive considerable attention in the past few years. Motivated at first by the lack of an efficient microwave-to-optical platform that could solve the issue of secure communication between remote superconducting chips, current efforts are starting to reach other areas, from quantum communications to sensing. Here, we attempt at giving a state-of-the-art view of the two, pointing at some of the technical and theoretical challenges we need to address, and while providing some novel ideas and directions for future research. Hence, the goal of this paper is to provide a bigger picture, and -- we hope -- to inspire new ideas in quantum communications and sensing: from open-air microwave quantum key distribution to direct detection of dark matter, we expect that the recent efforts and results in quantum microwaves will soon attract a wider audience, not only in the academic community, but also in an industrial environment.

The third law of thermodynamics, also known as the Nernst unattainability principle, puts a fundamental bound on how close a system, whether classical or quantum, can be cooled to a temperature near to absolute zero. On the other hand, a fundamental assumption of quantum computing is to start each computation from a register of qubits initialized in a pure state, i.e., at zero temperature. These conflicting aspects, at the interface between quantum computing and thermodynamics, are often overlooked or, at best, addressed only at a single-qubit level. In this work, we argue how the existence of a small, but finite, effective temperature, which makes the initial state a mixed state, poses a real challenge to the fidelity constraints required for the scaling of quantum computers. Our theoretical results, carried out for a generic quantum circuit with $N$-qubit input states, are validated by test runs performed on a real quantum processor., Comment: 9 pages, 5 figures

Some of the biggest achievements of the modern era of particle physics, such as the discovery of the Higgs boson, have been made possible by the tremendous effort in building and operating large-scale experiments like the Large Hadron Collider or the Tevatron. In these facilities, the ultimate theory to describe matter at the most fundamental level is constantly probed and verified. These experiments often produce large amounts of data that require storing, processing, and analysis techniques that often push the limits of traditional information processing schemes. Thus, the High-Energy Physics (HEP) field has benefited from advancements in information processing and the development of algorithms and tools for large datasets. More recently, quantum computing applications have been investigated in an effort to understand how the community can benefit from the advantages of quantum information science. In this manuscript, we provide an overview of the state-of-the-art applications of quantum computing to data analysis in HEP, discuss the challenges and opportunities in integrating these novel analysis techniques into a day-to-day analysis workflow, and whether there is potential for a quantum advantage., Comment: 23 pages, initially submitted to Snowmass 2021

Microwave technology plays a central role in current wireless communications, standing among them mobile communication and local area networks (LANs). The microwave range shows relevant advantages with respect to other frequencies in open-air transmission, such as low absorption losses and low energy consumption, and it is additionally the natural working frequency in superconducting quantum technologies. Entanglement distribution between separate parties is at the core of secure quantum communications. Therefore, understanding its limitations in realistic open-air settings, specially in the rather unexplored microwave regime, is crucial for transforming microwave quantum communications into a mainstream technology. Here, we investigate the feasibility of an open-air entanglement distribution scheme with microwave two-mode squeezed states. First, we study the reach of direct entanglement transmission in open-air, obtaining a maximum distance of approximately 500 meters in a realistic setting with state-of-the-art experimental parameters. Afterwards, we adapt entanglement distillation and entanglement swapping protocols to microwave technology in order to reduce environmental entanglement degradation. While entanglement distillation helps to increase quantum correlations in the short-distance low-squeezing regime by up to $46\%$, entanglement swapping increases the reach by $14\%$. Then, we compute the fidelity of a continuous-variable quantum teleportation protocol using open-air-distributed entanglement as a resource. Finally, we adapt the machinery to explore the limitations of quantum communication between satellites, where the thermal noise impact is substantially reduced and diffraction losses are dominant.

Predicting new links in physical, biological, social, or technological networks has a significant scientific and societal impact. Path-based link prediction methods utilize explicit counting of even and odd-length paths between nodes to quantify a score function and infer new or unobserved links. Here, we propose a quantum algorithm for path-based link prediction, QLP, using a controlled continuous-time quantum walk to encode even and odd path-based prediction scores. Through classical simulations on a few real networks, we confirm that the quantum walk scoring function performs similarly to other path-based link predictors. In a brief complexity analysis we identify the potential of our approach in uncovering a quantum speedup for path-based link prediction., Comment: Keywords: Complex Networks, Quantum Algorithms, Link Prediction, Social Networks, Protein-Protein Interaction Networks

We introduce a novel quadratic unconstrained binary optimization (QUBO) formulation for a classical problem in electrical engineering -- the optimal reconfiguration of distribution grids. For a given graph representing the grid infrastructure and known nodal loads, the problem consists in finding the spanning tree that minimizes the total link ohmic losses. A set of constraints is initially defined to impose topologically valid solutions. These constraints are then converted to a QUBO model as penalty terms. The electrical losses terms are finally added to the model as the objective function to minimize. In order to maximize the performance of solution searching with classical solvers, with hybrid quantum-classical solvers and with quantum annealers, our QUBO formulation has the goal of being very efficient in terms of variables usage. A standard 33-node test network is used as an illustrative example of our general formulation. Model metrics for this example are presented and discussed. Finally, the optimal solution for this example was obtained and validated through comparison with the optimal solution from an independent method., Comment: 21 pages, 9 figures. v2: Added new sections on model scaling and validation. Minor editorial changes

Quantum phase estimation is a paradigmatic problem in quantum sensing andmetrology. Here we show that adaptive methods based on classical machinelearning algorithms can be used to enhance the precision of quantum phase estimation when noisy non-entangled qubits are used as sensors. We employ the Differential Evolution (DE) and Particle Swarm Optimization (PSO) algorithms to this task and we identify the optimal feedback policies which minimize the Holevo variance. We benchmark these schemes with respect to scenarios that include Gaussian and Random Telegraph fluctuations as well as reduced Ramsey-fringe visibility due to decoherence. We discuss their robustness against noise in connection with real experimental setups such as Mach-Zehnder interferometry with optical photons and Ramsey interferometry in trapped ions,superconducting qubits and nitrogen-vacancy (NV) centers in diamond.

Recently, the European Commission supported by many European countries has announced large investments towards the commercialization of quantum technology (QT) to address and mitigate some of the biggest challenges facing today's digital era - e.g. secure communication and computing power. For more than two decades the QT community has been working on the development of QTs, which promise landmark breakthroughs leading to commercialization in various areas. The ambitious goals of the QT community and expectations of EU authorities cannot be met solely by individual initiatives of single countries, and therefore, require a combined European effort of large and unprecedented dimensions comparable only to the Galileo or Copernicus programs. Strong international competition calls for a coordinated European effort towards the development of QT in and for space, including research and development of technology in the areas of communication and sensing. Here, we aim at summarizing the state of the art in the development of quantum technologies which have an impact in the field of space applications. Our goal is to outline a complete framework for the design, development, implementation, and exploitation of quantum technology in space., Comment: 13 pages, 1 figure

To investigate the fundamental nature of matter and its interactions, particles are accelerated to very high energies and collided inside detectors, producing a multitude of other particles that are scattered in all directions. As charged particles traverse the detector, they leave signals of their passage. The problem of track reconstruction is to recover the original trajectories from these signals. This challenging data analysis task will become even more demanding as the luminosity of future accelerators increases, leading to collision events with a more complex structure. We identify four fundamental routines present in every local tracking method and analyse how they scale in the context of a standard tracking algorithm. We show that for some of these routines we can reach a lower computational complexity with quantum search algorithms. Although the found quantum speedups are mild, this constitutes, to the best of our knowledge, the first rigorous evidence of a quantum advantage for a high-energy physics data processing task., Comment: See our talk about the paper at https://www.youtube.com/watch?v=6fJe_5kMUCU&t=1s. Version 2 contains slight generalization to local track reconstruction algorithms. Version 3 includes an appendix comparing our approach with previous works

A quantum internet aims at harnessing networked quantum technologies, namely by distributing bipartite entanglement between distant nodes. However, multipartite entanglement between the nodes may empower the quantum internet for additional or better applications for communications, sensing, and computation. In this work, we present an algorithm for generating multipartite entanglement between different nodes of a quantum network with noisy quantum repeaters and imperfect quantum memories, where the links are entangled pairs. Our algorithm is optimal for GHZ states with 3 qubits, maximising simultaneously the final state fidelity and the rate of entanglement distribution. Furthermore, we determine the conditions yielding this simultaneous optimality for GHZ states with a higher number of qubits, and for other types of multipartite entanglement. Our algorithm is general also in the sense that it can optimise simultaneously arbitrary parameters. This work opens the way to optimally generate multipartite quantum correlations over noisy quantum networks, an important resource for distributed quantum technologies., Comment: Additional metrics for W-states and new numerical proofs of optimality, in comparison to other methods available. Keywords: Quantum Internet, QLANs, Multipartite Entanglement, Entanglement Distribution, Multi-objective Routing, Quantum Networks

Quantum networks are a new paradigm of complex networks, allowing us to harness networked quantum technologies and to develop a quantum internet. But how robust is a quantum network when its links and nodes start failing? We show that quantum networks based on typical noisy quantum-repeater nodes are prone to discontinuous phase transitions with respect to the random loss of operating links and nodes, abruptly compromising the connectivity of the network, and thus significantly limiting the reach of its operation. Furthermore, we determine the critical quantum-repeater efficiency necessary to avoid this catastrophic loss of connectivity as a function of the network topology, the network size, and the distribution of entanglement in the network. In particular, our results indicate that a scale-free topology is a crucial design principle to establish a robust large-scale quantum internet., Comment: quantum Internet, complex quantum networks, phase transitions, percolation theory

Experimental High-Energy Physics (HEP), especially the Large Hadron Collider (LHC) programme at the European Organization for Nuclear Research (CERN), is one of the most computationally intensive activities in the world. This demand is set to increase significantly with the upcoming High-Luminosity LHC (HL-LHC), and even more in future machines, such as the Future Circular Collider (FCC). As a consequence, event reconstruction, and in particular jet clustering, is bound to become an even more daunting problem, thus challenging present day computing resources. In this work, we present the first digital quantum algorithm to tackle jet clustering, opening the way for digital quantum processors to address this challenging problem. Furthermore, we show that, at present and future collider energies, our algorithm has comparable, yet generally lower complexity relative to the classical state-of-the-art $k_t$ clustering algorithm.

The currently predicted increase in computational demand for the upcoming High-Luminosity Large Hadron Collider (HL-LHC) event reconstruction, and in particular jet clustering, is bound to challenge present day computing resources, becoming an even more complex combinatorial problem. In this paper, we show that quantum annealing can tackle dijet event clustering by introducing a novel quantum annealing binary clustering algorithm. The benchmarked efficiency is of the order of $96\%$, thus yielding substantial improvements over the current quantum state-of-the-art. Additionally, we also show how to generalize the proposed objective function into a more versatile form, capable of solving the clustering problem in multijet events.

Quantum-enhanced, idler-free sensing protocol to measure the response of a target object to the frequency of a probe in a noisy and lossy scenario is proposed. In this protocol, a target with frequency-dependent reflectivity embedded in a thermal bath is considered. The aim is to estimate the parameter $\lambda = \eta(\omega_2)-\eta(\omega_1)$, since it contains relevant information for different problems. For this, a bi-frequency quantum state is employed as the resource, since it is necessary to capture the relevant information about the parameter. Computing the quantum Fisher information $H$ relative to the parameter $\lambda$ in an assumed neighborhood of $\lambda \sim 0$ for a two-mode squeezed state ($H_Q$), and a coherent state ($H_C$), a quantum enhancement is shown in the estimation of $\lambda$. This quantum enhancement grows with the mean reflectivity of the probed object, and is noise-resilient. Explicit formulas are derived for the optimal observables, and an experimental scheme based on elementary quantum optical transformations is proposed. Furthermore, this work opens the way to applications in both radar and medical imaging, in particular in the microwave domain., Comment: Published version: includes new results and figures

The scale-free property emerges in various real-world networks and is an essential property which characterizes the dynamics or features of such networks. In this work we investigate the effect of this scale-free property on a quantum information processing task of finding a marked node in the network, known as the quantum spatial search. We analyze the quantum spatial search algorithm using continuous-time quantum walk on the Bollob\'{a}s network, and evaluate the time $T$ to localize the quantum walker on the marked node starting from an unbiased initial state. Our main finding is that $T$ is determined by the global structure around the marked node, while some local information of the marked node such as degree does not identify $T$. We discuss this by examining the correlation between $T$ and some centrality measures of the network, and show that the closeness centrality of the marked node is highly correlated with $T$. We also characterize the distribution of $T$ by marking different nodes in the network, which displays a multi-mode lognormal distribution. Especially on the Bollob\'{a}s network, $T$ is magnitude of orders shorter depending whether the marked node is adjacent to the largest degree hub node or not. However, as $T$ depends on the property of the marked node, one requires some amount of prior knowledge about such property of the marked node in order to identify the optimal time to measure the quantum walker and achieve fast search. These results indicate that the existence of the hub node in the scale-free network is playing a crucial role on the quantum spatial search., Comment: 10 pages, 6 figures

Text classification plays a vital role today especially with the intensive use of social networking media. Recently, different architectures of convolutional neural networks have been used for text classification in which one-hot vector, and word embedding methods are commonly used. This paper presents a new language independent word encoding method for text classification. The proposed model converts raw text data to low-level feature dimension with minimal or no preprocessing steps by using a new approach called binary unique number of word "BUNOW". BUNOW allows each unique word to have an integer ID in a dictionary that is represented as a k-dimensional vector of its binary equivalent. The output vector of this encoding is fed into a convolutional neural network (CNN) model for classification. Moreover, the proposed model reduces the neural network parameters, allows faster computation with few network layers, where a word is atomic representation the document as in word level, and decrease memory consumption for character level representation. The provided CNN model is able to work with other languages or multi-lingual text without the need for any changes in the encoding method. The model outperforms the character level and very deep character level CNNs models in terms of accuracy, network parameters, and memory consumption; the results show total classification accuracy 91.99% and error 8.01% using AG's News dataset compared to the state of art methods that have total classification accuracy 91.45% and error 8.55%, in addition to the reduction in input feature vector and neural network parameters by 62% and 34%, respectively., Comment: Accepted @ 14th International Computer Engineering Conference (ICENCO2018), Faculty of Engineering , Cairo University, Egypt, Dec. 29-30, 2018

The transport of a particle in the presence of a potential that changes periodically in space and in time can be characterized by the amount of work needed to shift a particle by a single spatial period of the potential. In general, this amount of work, when averaged over a single temporal period of the potential, can take any value in a continuous fashion. Here we present a topological effect inducing the quantization of the average work. We find that this work is equal to the first Chern number calculated in a unit cell of a space-time lattice. Hence, this quantization of the average work is topologically protected. We illustrate this phenomenon with the example of an atom whose center of mass motion is coupled to its internal degrees of freedom by electromagnetic waves., Comment: 10 pages (including Supplemental Material), 1 figure, 1 table; closer to published version

Memristors, resistors with memory whose outputs depend on the history of their inputs, have been used with success in neuromorphic architectures, particularly as synapses and non-volatile memories. However, to the best of our knowledge, no model for a network in which both the synapses and the neurons are implemented using memristors has been proposed so far. In the present work we introduce models for single and multilayer perceptrons based exclusively on memristors. We adapt the delta rule to the memristor-based single-layer perceptron and the backpropagation algorithm to the memristor-based multilayer perceptron. Our results show that both perform as expected for perceptrons, including satisfying Minsky-Papert's theorem. As a consequence of the Universal Approximation Theorem, they also show that memristors are universal function approximators. By using memristors for both the neurons and the synapses, our models pave the way for novel memristor-based neural network architectures and algorithms. A neural network based on memristors could show advantages in terms of energy conservation and open up possibilities for other learning systems to be adapted to a memristor-based paradigm, both in the classical and quantum learning realms., Comment: Added new result on universality of memristors, minor changes in the introduction and algorithm, references updated

We study the performance of a quantum Otto cycle using a harmonic work medium and undergoing collisional dynamics with finite-size reservoirs. We span the dynamical regimes of the work strokes from strongly non-adiabatic to quasi-static conditions, and address the effects that non-Markovianity of the open-system dynamics of the work medium can have on the efficiency of the thermal machine. While such efficiency never surpasses the classical upper bound valid for finite-time stochastic engines, the behaviour of the engine shows clear-cut effects induced by both the finiteness of the evolution time, and the memory-bearing character of the system-environment evolution., Comment: Close to published version. Added Figure 8b

Two main obstacles for observing quantum advantage in noisy intermediate-scale quantum computers (NISQ) are the finite precision effects due to control errors, or disorders, and decoherence effects due to thermal fluctuations. It has been shown that dissipative quantum computation is possible in presence of an idealized fully-engineered bath. However, it is not clear, in general, what performance can be achieved by NISQ when internal bath degrees of freedom are not controllable. In this work, we consider the task of quantum search of a marked node on a complete graph of $n$ nodes in the presence of both static disorder and non-zero coupling to an environment. We show that, given fixed and finite levels of disorder and thermal fluctuations, there is an optimal range of bath temperatures that can significantly improve the success probability of the algorithm. Remarkably for a fixed disorder strength $\sigma$, the system relaxation time decreases for higher temperatures within a robust range of parameters. In particular, we demonstrate that for strong disorder, the presence of a thermal bath increases the success probability from $1/(n \sigma^2)$ to at least $1/2$. While the asymptotic running time is approximately maintained, the need to repeat the algorithm many times and issues associated with unitary over-rotations can be avoided as the system relaxes to an absorbing steady state. Furthermore, we discuss for what regimes of disorder and bath parameters quantum speedup is possible and mention conditions for which similar phenomena can be observed in more general families of graphs. Our work highlights that in the presence of static disorder, even non-engineered environmental interactions can be beneficial for a quantum algorithm.