In the talk I will present examples of projects which have leveraged fundamental quantum physics for developing technologies that have gone into products for cybersecurity, large-scale computation and biological detection
In recent years, quantum key distribution (QKD) has become a fully fledged application of quantum information science, and QKD services are being supplied by different companies/institutions around the world. However, the practical security of QKD is not well-established yet, mainly due to the difficulty of guaranteeing that real QKD implementations stick to the assumptions and models on which...
We implemented a simplified time-bin BB84 quantum key distribution protocol with the purpose of achieving the highest possible secret key rate at short distances. The sender Alice emits signals at a rate of 2.5 GHz. In the key-generating basis, we use a superconducting nanowire single photon detector (SNSPD) with a novel design optimized for fast count rates. The in-house designed and...
We consider a heterogeneous network of quantum computing modules, sparsely connected via Bell states. Operations across these connections constitute a computational bottleneck and they are likely to add more noise to the computation than operations performed within a module. We introduce several techniques for transforming a given quantum circuit into one implementable on a network of the...
In recent years, the study of Bell-type nonlocality on networks has led to an array of intriguing foundational results. Nonetheless the field still faces difficulties in finding a justified application. One of the key barriers for this is the assumption of independent sources in network nonlocality, which is difficult to enforce. In our work we examine a possible operational interpretation for...
Quantum technologies promise interesting new approaches to areas such as computing and communication. A branch that is becoming increasingly interesting is that of quantum networks. The technological assets for quantum networks have been developing rapidly in recent years and many implementations, often geared towards quantum cryptography, have been reported. In order to demonstrate security...
In a Mach-Zehnder-type light pulse atom interferometer, matter waves are split, mirrored, and recombined using coherent atom optics. With the leading order phase shift scaling with the enclosed space-time area, the momentum transfer induced by the atom optics light pulses as well as the free evolution time are key to significantly enhanced sensitivity to inertial forces and motivate...
Continuous variable quantum key distribution with discrete modulation has the potential to provide unconditional security using widely available optical elements and existing telecom infrastructure, while allowing for the use of well studied error correction protocols. However, proving finite-size security against coherent attacks poses a challenge. In this work we apply the entropy...
In quantum metrology, the usefulness of a quantum state is determined by how much it outperforms separable states. For the maximal metrological usefulness genuine multipartite entanglement (GME) is required. In order to improve the usefulness of a quantum state we consider a scheme of having several of its copies. With this scheme, it is possible to find a large class of practically important...
In this contribution I will present ideas and ongoing project to enhance the capabilities of particle detectors using quantum systems [1]. The presented technologies could not only improve the accuracy of measurements but also provide a new dimension by directly sensing properties as spin of individual particles. The level of maturity and applicability of ideas range from those already proved...
As important branches in quantum technologies, quantum sensing and quantum metrology have experienced significant progress, placing themselves at the forefront of the new generation of technologies harnessing quantum effects. In this presentation, different quantum magnetometers assisted by neural networks are introduced. Our results show that neural networks are valuable in distinct quantum...
We present a method to identify energy shifts which contain structural information in solid-state systems using Nitrogen-Vacancy (NV) centers combined with synchronization techniques. To achieve this, we have developed a theory for Lee-Goldburg based decoupling schemes in microscale-NMR scenarios with NV centers at large static magnetic fields. The introduced RF fields serve two purposes: (i)...
The well-known spin squeezing coefficient efficiently quantifies the sensitivity and entanglement of Gaussian states [1,2]. However, this coefficient is insufficient to characterize the much wider class of non-Gaussian quantum states that can generate even larger sensitivity gains. In this talk, we present a non-Gaussian extension of spin squeezing based on reduced variances of nonlinear...
We present a method to detect bipartite entanglement based on number-phase-like uncertainty relations in split spin ensembles. First, we derive an uncertainty relation that plays the role of a number-phase uncertainty for spin systems. It is important that the relation is given with well-defined and easily measurable quantities, and that it does not need assuming infinite dimensional systems....
While current research in quantum theory focuses on the exploitation of quantum effects in communication and computation scenarios, quantum systems are also known to be advantageous for some mechanical tasks. The most known effect is that of tunneling, but there are other less well known effects. One of those is quantum backflow [1], a phenomenon in which a free quantum particle with positive...
Quantum machine learning (QML) is often put forward as one of the most likely quantum applications to bring about useful advantages, perhaps even in the near term.
Large-scale quantum computers, once available, will give definite answers to whether this is true, but to make the most out of the significant investments in experimental quantum computing, it is important to try to learn as much...
Quantum Key Distribution (QKD) has the potential to play a significant role in improving security in communication networks in the near future. Since the first experimental demonstration [1], multiple QKD experiments have been carried out, the majority of which were proof-of-concept demonstrations that continually broke new records in terms of transmission distance, in both fibre [2,3] and...
The biggest challenge that quantum computing and quantum machine learning are currently facing is the presence of noise in quantum devices. As a result, big efforts have been put into correcting or mitigating the induced errors. But, can these two fields benefit from noise? Surprisingly, we demonstrate that under some circumstances, quantum noise can be used to improve the performance of...
In recent years, there has been a growing interest in utilizing hole spins in silicon and germanium for quantum information processing. One reason for this is the strong spin-orbit interaction present in the valence band of these materials, which allows for versatile interactions with electric fields. As a result, there have been demonstrations of fast electrical manipulation of hole spin...
Combinatorial optimization problems (CO) have a strong impact on a wide range of disciplines such as finance, machine learning, logistics, etc. In addition to finding a solution with minimum cost, problems of high relevance involve a number of constraints that the solution must satisfy. Variational quantum algorithms (VQA) have emerged as promising candidates for solving these problems in the...
Enhanced coherence in HoW$_{10}$ molecular spin qubits has been demonstrated by use of clock-transitions (CTs) . More recently it was shown by some of us that, while operating at the CTs, it was possible to use an electrical field to selectively address HoW$_{10}$ molecules pointing in a given direction, within a crystal that contains two kinds of identical but inversion-related molecules [2]....
Quantum illumination is one of the main paradigms for implementing quantum radar in the low-frequency spectrum. Here, we contribute towards an open-air application of the protocol, by notably easing its experimental requirements. We first define an experimentally feasible receiver for an entangled signal-idler transmitter. This consists in measuring heterodyne the received signal and...
In recent years, hole spins in silicon and germanium have attracted increasing interest for quantum information processing. In this talk, I will describe recent advances in hole spin qubits for both silicon and germanium towards intermediate- or large-scale quantum processors.
First, I will present the coherent interaction of a hole spin in silicon with a microwave photon. This coupling...
I will review the recent advances of TN algorithms that allow to compute the out-of-equilibrium dynamics of local observables after a quantum quench and discuss entropies, generalized entropies and coherence of the states generated.
Shortcuts to adiabaticity [1] are well-known methods for controlling the quantum dynamics beyond the adiabatic criteria, where counter-diabatic (CD) driving provides a promising means to speed up quantum many-body systems. In this talk, we show the applicability of CD driving to enhance the digitized adiabatic quantum computing paradigm in terms of fidelity and total simulation time. Firstly,...
Variational Quantum Algorithms (VQAs) [1] use a classical optimizer to train a parametrized quantum circuit (PQC). These have emerged as a practical way to exploit state-of-the-art quantum computers. Currently, most VQAs have been designed for fully digital approaches, in which the error ends up accumulating for circuits with many parameters. A possible way out is the use of analogue...
Theoretical and algorithmic advances, availability of data, and computing power have opened the door to exceptional perspectives for application of classical Machine Learning in the most diverse fields of science, business and society at large, and notably in High Energy Physics (HEP). In particular, Machine Learning is among the most promising approaches to analyse and understand the data...
We present our first steps towards the coherent coupling between inhomogeneous magnon excitations and resonant photons living in a superconducting cavity. Using a coplanar superconducting transmission line, we perform broad-band ferromagnetic resonance of thin-film mesoscopic magnets. This allows identifying the low-energy Kittel spin-wave excitation (with infinite wavelength). By patterning...
Quantum machine learning (QML) is recently gaining interest in both theory and experiment thanks to variational circuits implemented in the noisy intermediate-scale quantum computers (NISQs) [1]. Since we are in such an era, algorithms capable of being implemented in small circuits are of great interest. In pursuit of this objective, we explore QML algorithms that are implementable in circuits...
Variational quantum algorithms (VQAs) are one of the most promising NISQ-era algorithms due to their feasibility for their application in vastly diverse fields. Machine learning, quantum chemistry, mathematics, finance or combinatorial problems can be tackled through VQAs. However, the underlying optimization processes within these algorithms usually deal with local minima and barren plateau...
Recent progress in the development of quantum technologies has enabled the direct investigation of dynamics of increasingly complex quantum many-body systems. This motivates the study of the complexity of classical algorithms for this problem in order to benchmark quantum simulators and to delineate the regime of quantum advantage. Here we present classical algorithms for approximating the...
In recent years, a lot of effort has been put into expanding established jet-quenching formalisms to account for higher-order or energy-suppressed medium-induced effects. Understanding how such contributions emerge is important to have a more complete picture of jet evolution in the medium and to extract more detailed properties of the underlying matter. However, such efforts are in general...
We propose a new variational ansatz for the ground state preparation of the two-dimensional $\mathbb{Z}_2$ lattice gauge theory in digital quantum computers. It is similar to the well known QAOA, but it contains half Trotter step of an imaginary time propagator, which increases the fidelities reached around the phase transition of the gauge theory. We propose a non-probabilistic...
This talk explores the integration of Quantum Computers (QCs) within High-Performance Computing (HPC) environments and its significance for Italy and Europe. Representing CINECA, the largest Italian supercomputing center and an EuroHPC selected quantum computer hosting entity, we will discuss about the EuroQCS initiative, an European collaboration involving different countries (including...
Classical simulation of quantum dynamics from many-body systems with tensor networks is hindered by the exponential growth of entanglement contained at the bonds of a chosen wavefunction factorization (typically Matrix Product States). Modern algorithms try to overcome this entanglement barrier by folding and contracting transversely the network [1], or optimizing schemes to exploit only...
The field of cavity qed materials seeks to modify the properties of bulk materials by coupling them to an electromagnetic cavity at equilibrium. When the material is, e.g., composed of magnetic dipoles, the resulting system is described by a generalized Dicke model. Under certain conditions, the cavity modes can be traced out, leaving a spin Hamiltonian with cavity-mediated (effective)...
Quantum computers in the NISQ era (noisy, intermediate-scale, quantum) still offer a relatively small amount of qubits. The largest quantum computers so far, dedicated to binary optimization, do not surpass a few thousands qubits. We nevertheless are willing and able to probe such computers in real-life tasks with their high demand in number of variables to optimize over.
We tackle a binary...
Quantum walks (QWs) play an important role in quantum computing. On the one hand, some algoritmical problems can be recast as a QW. On the other hand, many physical phenomena can be simulated with the help of a QW. Here we concentrate on discrete-time QWs, and we discuss quantum circuits that can implement discrete-time quantum walks having an arbitrary position-dependent coin operator [1]....
Hybrid quantum-classical algorithms emerge as one promising approach to improve the performance of current quantum computers. In this work, we consider the method to execute general quantum algorithms on two different QPUs connected via classical communication. The optimal protocol for such computation consists of two steps: First, a quasi-probabilistic simulation scheme generates the required...
In this talk I will provide a tutorial introduction to quantum simulation with quantum computers. I will review the failure of conventional computing to address many-body problems and how this prevents progress in many scientific areas. I will discuss whether and how quantum computers, either fault tolerant in the future or noisy intermediate scale state of the art, can help to solve...
Quantum reservoir computing (QRC) is a machine learning technique where complex quantum systems are exploited to solve temporal tasks, such as predicting chaotic time series and complex spatiotemporal dynamics. Most existing results in the analysis of QRC systems with classical inputs have been obtained using the density matrix formalism. This paper shows that alternative representations can...
Pattern matching of quantum circuits, the task of finding sub-circuits of a quantum circuit that match a given pattern, is an essential tool of quantum circuit compilation. It can be used for instance to find redundant gate sequences that can be rewritten as more efficient computations. We propose an algorithm that performs this task for many patterns simultaneously, independently of the...
We present a general strategy for mapping fermionic systems to quantum hardware with square qubit connectivity which yields low-depth quantum circuits, counted in the number of native two-qubit fSIM gates. We achieve this by leveraging novel operator decomposition and circuit compression techniques paired with specifically chosen fermion-to-qubit mappings that allow for a high degree of gate...
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...
In recent years research has been carried out on algorithms to simulate quantum many-body systems in current NISQ devices. In particular, for the ground state finding problem, known to be QMA-complete, a quantum adiabatic algorithm can be used. On the other hand, the Bose-Hubbard model has gained impact lately because of the prediction of exotic phases of matter and because its experimental...
The development of new sensing techniques that reach nanoscale resolution would habilitate the detection of single molecules as well as their dynamics. In this regard, we present a detection protocol using a nitrogen vacancy center quantum sensor to measure the coupling between two electronic targets on a macromolecule via a dangling bond. The latter is an unpaired immobilized electron, which...
Although quantum annealing has shown promising results, it still
struggles to outperform classical optimization algorithms. One of the
reasons for this is that the qubit connectivities in superconducting
circuits, which are one of the most promising platforms for quantum
annealing, are not complex enough. This work focuses on the analysis
of different architectures for quantum...
One potential way to achieve significant progress in quantum computing is by using quantum devices to simulate quantum systems instead of relying on classical computers to perform the simulation. However, a challenge is to demonstrate that there is a fundamental difference between simulating physical systems using classical computers versus quantum computers. Formal complexity arguments often...
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 coherence has been shown to impact the operational capabilities of quantum systems performing thermodynamic tasks in a significant way, and yet the possibility of genuine coherence-enhanced thermodynamic operation remains unclear. Here we show that only the presence of energetic coherence ---coherence between levels with different energies--- in steady-state quantum thermal machines...
Contextuality is a fundamental, rigorous marker of non-classicality exhibited by quantum theory. Therefore, it seems natural to expect this non-classical feature to play a vital role as a resource for quantum computational advantage. Indeed, many such links have been unveiled recently, and many of these results boil down to contextuality relative to Pauli observables. For example, in [1] it...
Nanoscale NMR is a technique that enables the study of the structure and properties of materials at the nanoscale level. In this regime, NV centers can be utilized as highly sensitive magnetic sensors to detect the magnetic fields produced by nearby nuclei. By placing a target sample close enough to the NV ensemble (i.e. at tens of nanometers), standard thermal polarization is replaced by...
Quantum circuit simulations on classical computers are essential to develop better quantum computers and algorithms. Evenmore when there are few noisy and small quantum computers available. Different approaches have been proposed to simulate quantum circuits such as full amplitude-vector evolution, Feynman paths, decisión diagrams or tensor networks.
We can simulate a quantum circuit by...
The possibility of discriminating the statistics of a thermal bath using indirect measurements performed on quantum probes is presented. The scheme relies on the fact that, when weakly coupled with the environment of interest, the transient evolution of the probe toward its final thermal configuration is strongly affected by the fermionic or bosonic nature of the bath excitations. Using...
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...
Dispersive readout in superconducting circuits is a limiting factor in the performance of current quantum processors. Experimentally, it has been observed that increasing the intensity of the readout pulses improves the signal-to-noise ratio of the measurement up to some threshold, where non-dispersive effects and leakage to higher levels enter into play. In this work, we perform a numerical...
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...
Rydberg atoms in arrays of optical tweezers offer a new perspective for quantum simulation of many body problems. In this talk, I will give a brief overview about this platform and describe our efforts to control Rydberg interactions to explore different types of spin Hamiltonians. I will report on our recent implementations of the 2D Ising Hamiltonian [1] and the dipolar XY model [2] with...
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...
This paper investigates a semi-device-independent protocol for quantum randomness generation constructed on the prepare-and-measure scenario based on the on-off-keying encoding scheme and with various detection methods, i.e., homodyne, heterodyne, and single photon detection schemes. The security estimation is based on lower bounding the guessing probability for a general case and is...
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...
In a Mach-Zehnder-type light pulse atom interferometer, matter waves are split, mirrored, and recombined using coherent atom optics. With the leading order phase shift scaling with the enclosed space-time area, the momentum transfer induced by the atom optics light pulses as well as the free evolution time are key to significantly enhanced sensitivity to inertial forces and motivate...
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...
Nuclear Magnetic Resonance (NMR) experiments traditionally require high magnetic fields to achieve sufficient signal contrast. However, there is a growing interest to develop low-field NMR. On the one hand, because it is lower-cost and less-invasive than standard NMR; and on the other hand, due to its potential to resolve J couplings and Quadrupolar interactions with higher resolution. These...
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...
The teleportation model of quantum computation introduced by Gottesman and Chuang [1] motivated the development of the Clifford hierarchy, an increasing sequence of sets of quantum gates critical for fault-tolerant quantum computation based on Clifford circuits. We propose an analogous hierarchy in the context of matchgate circuits, another restricted class of quantum circuits that can be...
The multi-armed bandit problem is a simple model of decision-making with uncertainty that lies in the
class of classical reinforcement learning problems. Given a set of arms, a learner interacts sequentially
with these arms sampling a reward at each round and the objective of the learner is to identify the arm
with largest expected reward while maximizing the total cumulative reward. The...
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 key distribution (QKD) is the fundamental method employed in quantum communications to guarantee total security in the transmission of information. This is achieved by the utilization of different proposed cryptographic protocols (like BB84, Ekert, MDI…) with different advantages and problems, as well as different strategies of codification (polarization, time-bin, phase, spatial…),...
In research concerning quantum networks, it is often assumed that the parties can classically communicate with each other. However, classical communication might introduce substantial delay to the network, especially if it is large. As the latency of a network is one of its most important characteristics, it is interesting to consider quantum networks in which parties cannot communicate...
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...
Temperature estimation is crucial for characterizing samples in all natural sciences. A standard
approach is provided by probe thermometry, where a probe is brought into contact with the sample
and examined after a certain amount of time has passed. In many situations however, continuously
monitoring the probe may be preferred. Here we consider a minimal model, where the probe is...
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....
Solid state quantum computing and quantum sensing technologies are based on the strong coupling between qubits and a quantized field of excitations. Besides photons, the solid state offers a wide variety of bosonic excitations that can be emitted or absorbed such as, e.g., magnons, the quantum version of spin waves.
Magnonic cavities offer the advantage of operating at reduced wavelengths...
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...
We investigate the problem of quantum edge detection, which aims to identify the abrupt change between two domains composed of unknown quantum states. This task can be viewed as an extension of the quantum change point problem in more feasible scenarios.
We use the Schur-Weyl duality to compute the optimal success probability of detecting the edge in the asymptotic limit of a large number of...
Arguably, the largest class of stochastic processes generated by means of a finite memory consists of those that are sequences of observations produced by sequential measurements in a suitable generalized probabilistic theory (GPT). These are constructed from a finite-dimensional memory evolving under a set of possible linear maps, and with probabilities of outcomes determined by linear...
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...
Quantum computation has sparked a revolution in solving problems ranging from combinatorial
optimization or quantum chemistry to industrial applications. Numerous algorithm proposals have
emerged in recent years, including adiabatic and variational quantum algorithms, which have shown
promising results in current NISQ devices. To further reduce the quantum resources required,
digitalized...
The NEASQC (NExt ApplicationS of Quantum Computing) project investigates and develops Quantum-enabled applications that can take advantage of NISQ (Noise Intermediate-Scale Quantum) systems in fields such as drug discovery, CO2 capture, smart energy management, natural language processing, breast cancer detection, probabilistic risk assessment for energy infrastructures or inventory...
In open quantum systems, in order to establish the impact of quantum fluctuations during the evolution of a system, one needs to continuously monitor it while minimizing disturbance. The thermodynamics of systems which are subjected to continuous quantum measurement can be described using the formalism of quantum trajectories. However, in realistic scenarios, this measurement is not ideal:...
Quantum machine learning (QML) is often put forward as one of the most likely quantum applications to bring about useful advantages, perhaps even in the near term.
Large-scale quantum computers, once available, will give definite answers to whether this is true, but to make the most out of the significant investments in experimental quantum computing, it is important to try to learn as much...
We have demonstrated, using a single crystal of diamond, spin manipulation, polarization, and reading of electrons using a microwave antenna. The microwave field is used to manipulate the orientation of electron spins through electron spin resonance tuned by an external magnetic field. The electron spin is initialized optically using laser radiation and the photoluminescence spin reading of...
