arXiv subjects

Luca Pezzè

Publications and source records attributed to Luca Pezzè.

At least 37 records · Page 2Linked to original sources

arXiv2023

Stabilizing persistent currents in an atomtronic Josephson junction necklace

Arrays of Josephson junctions are at the forefront of research on quantum circuitry for quantum computing, simulation and metrology. They provide a testing bed for exploring a variety of fundamental physical effects where macroscopic phase coherence, nonlinearities and dissipative mechanisms compete. Here we realize finite-circulation states in an atomtronic Josephson junction necklace, consisting of a tunable array of tunneling links in a ring-shaped superfluid. We study the stability diagram of the atomic flow by tuning both the circulation and the number of junctions. We predict theoretically and demonstrate experimentally that the atomic circuit withstands higher circulations (corresponding to higher critical currents) by increasing the number of Josephson links. The increased stability contrasts with the trend of the superfluid fraction -- quantified by Leggett's criterion -- which instead decreases with the number of junctions and the corresponding density depletion. Our results demonstrate atomic superfluids in mesoscopic structured ring potentials as excellent candidates for atomtronics applications, with prospects towards the observation of non-trivial macroscopic superpositions of current states.

cond-mat.quant-gas↗

arXiv2023

Sub-unity superfluid fraction of a supersolid from self-induced Josephson effect

Recently, a new category of superfluids and superconductors has been discovered in various systems. These could be linked to the idea of a supersolid phase, featuring a macroscopic wavefunction with spatial modulation resulting from simultaneous, spontaneous breaking of gauge and translational symmetries. However, this relation has only been recognized in some cases and there is the need for universal properties quantifying the differences between supersolids and ordinary superfluids/superconductors or crystals. A key property is the superfluid fraction, which measures the reduction in superfluid stiffness due to spatial modulation, leading to the non-standard superfluid dynamics of supersolids. Here we employ the Josephson effect, common in superfluids and superconductors, to measure the superfluid fraction in a supersolid. Even without a physical barrier, the Josephson effect arises spontaneously in a supersolid due to spatial modulation. Individual lattice cells act as self-induced Josephson junctions, allowing the direct determination of the local superfluid fraction. We studied a cold-atom dipolar supersolid, revealing a significant sub-unity superfluid fraction. Our results open new research directions, enabling the exploration of novel phenomena like partially quantized vortices and supercurrents, potentially unifying the understanding of supersolid-like systems, and introducing a new type of Josephson junction.

cond-mat.quant-gas↗

arXiv2023

Quantum-enhanced differential atom interferometers and clocks with spin-squeezing swapping

Thanks to common-mode noise rejection, differential configurations are crucial for realistic applications of phase and frequency estimation with atom interferometers. Currently, differential protocols with uncorrelated particles and mode-separable settings reach a sensitivity bounded by the standard quantum limit (SQL). Here we show that differential interferometry can be understood as a distributed multiparameter estimation problem and can benefit from both mode and particle entanglement. Our protocol uses a single spin-squeezed state that is mode-swapped among common interferometric modes. The mode swapping is optimized to estimate the differential phase shift with sub-SQL sensitivity. Numerical calculations are supported by analytical approximations that guide the optimization of the protocol. The scheme is also tested with simulation of noise in atomic clocks and interferometers.

quant-ph↗

arXiv2022

Genuine multipartite nonlocality with causal-diagram postselection

The generation and verification of genuine multipartite nonlocality (GMN) is of central interest for both fundamental research and quantum technological applications, such as quantum privacy. To demonstrate GMN in measurement data, the statistics are commonly postselected by neglecting undesired data. Until now, valid postselection strategies have been restricted to local postselection. A general postselection that is decided after communication between parties can mimic nonlocality, even though the complete data are local. Here, we establish conditions under which GMN is demonstrable even if observations are postselected collectively. Intriguingly, certain postselection strategies that require communication among several parties still offer a demonstration of GMN shared between all parties. The results are derived using the causal structure of the experiment and the no-signalling condition imposed by relativity. Finally, we apply our results to show that genuine three-partite nonlocality can be created with independent particle sources.

quant-ph↗

arXiv2022

Tomography of a number-resolving detector by reconstruction of an atomic many-body quantum state

The high-fidelity analysis of many-body quantum states of indistinguishable atoms requires the accurate counting of atoms. Here we report the tomographic reconstruction of an atom-number-resolving detector. The tomography is performed with an ultracold rubidium ensemble that is prepared in a coherent spin state by driving a Rabi coupling between the two hyperfine clock levels. The coupling is followed by counting the occupation number in one level. We characterize the fidelity of our detector and show that a negative-valued Wigner function is associated with it. Our results offer an exciting perspective for the high-fidelity reconstruction of entangled states and can be applied for a future demonstration of Heisenberg-limited atom interferometry.

quant-ph↗

arXiv2021

A machine learning approach to Bayesian parameter estimation

Bayesian estimation is a powerful theoretical paradigm for the operation of quantum sensors. However, the Bayesian method for statistical inference generally suffers from demanding calibration requirements that have so far restricted its use to proof-of-principle experiments. In this theoretical study, we formulate parameter estimation as a classification task and use artificial neural networks to efficiently perform Bayesian estimation. We show that the network's posterior distribution is centered at the true (unknown) value of the parameter within an uncertainty given by the inverse Fisher information, representing the ultimate sensitivity limit for the given apparatus. When only a limited number of calibration measurements are available, our machine-learning based procedure outperforms standard calibration methods. Thus, our work paves the way for Bayesian quantum sensors which can benefit from efficient optimization methods, such as in adaptive schemes, and take advantage of complex non-classical states. These capabilities can significantly enhance the sensitivity of future devices.

quant-ph↗

arXiv2021

Distributed Quantum Sensing with Squeezed-Vacuum Light in a Configurable Network of Mach-Zehnder Interferometers

We study a sensor network of distributed Mach-Zehnder interferometers (MZIs) for the parallel (simultaneous) estimation of an arbitrary number $d \geq 1$ of phase shifts. The scheme uses a squeezed-vacuum state that is split between $d$ modes by a quantum circuit (QC). Each output mode of the QC is the input of one of $d$ MZIs, the other input of each MZI being a coherent state. In particular, ${\it i}$) we identify the optimal configuration of the sensor network that allows the estimation of any linear combination of the $d$ phases with maximal sensitivity. The protocol overcomes the shot-noise limit and reaches Heisenberg scalings with respect to the total average number of particles in the overall probe state, the multiphase estimation only requiring local photocounting. Furthermore, the parallel multiphase estimation overcomes optimal separable strategies for the estimation of any linear combination of the phases: the sensitivity gain being a factor $d$, at most. Viceversa, ${\it ii}$) given a specific QC, we identify the optimal linear combination of the phases that maximizes the sensitivity and show that results are robust against random choices of the QC. Our scheme paves the ways to a variety of applications in distributed quantum sensing.

quant-ph↗

arXiv2021

Bayesian Quantum Multiphase Estimation Algorithm

Quantum phase estimation (QPE) is the key subroutine of several quantum computing algorithms as well as a central ingredient in quantum computational chemistry and quantum simulation. While QPE strategies have focused on the estimation of a single phase, applications to the simultaneous estimation of several phases may bring substantial advantages; for instance, in the presence of spatial or temporal constraints. In this work, we study a Bayesian algorithm for the parallel (simultaneous) estimation of multiple arbitrary phases. The protocol gives access to correlations in the Bayesian multi-phase distribution resulting in covariance matrix elements scaling inversely proportional to the square of the total number of quantum resources. The parallel estimation allows to surpass the sensitivity of sequential single-phase estimation strategies for optimal linear combinations of phases. Furthermore, the algorithm proves a certain noise resilience and can be implemented using single photons and standard optical elements in currently accessible experiments.

quant-ph↗

arXiv2021

Frequentist Parameter Estimation with Supervised Learning

Recently there has been a great deal of interest surrounding the calibration of quantum sensors using machine learning techniques. In this work, we explore the use of regression to infer a machine-learned point estimate of an unknown parameter. Although the analysis is neccessarily frequentist - relying on repeated esitmates to build up statistics - we clarify that this machine-learned estimator converges to the Bayesian maximum a-posterori estimator (subject to some regularity conditions). When the number of training measurements are large, this is identical to the well-known maximum-likelihood estimator (MLE), and using this fact, we argue that the Cram{é}r-Rao sensitivity bound applies to the mean-square error cost function and can therefore be used to select optimal model and training parameters. We show that the machine-learned estimator inherits the desirable asymptotic properties of the MLE, up to a limit imposed by the resolution of the training grid. Furthermore, we investigate the role of quantum noise the training process, and show that this noise imposes a fundamental limit on number of grid points. This manuscript paves the way for machine-learning to assist the calibration of quantum sensors, thereby allowing maximum-likelihood inference to play a more prominent role in the design and operation of the next generation of ultra-precise sensors.

quant-ph↗

arXiv2021

Multiparticle Entanglement Dynamics of Quantum Chaos in a Bose-Einstein condensate

We study the particle-entanglement dynamics witnessed by the quantum Fisher information (QFI) of a trapped Bose-Einstein condensate governed by the kicked rotor Hamiltonian. The dynamics is investigated with a beyond mean-field approach. We link the time scales of the validity of this approximation in, both, classical regular and chaotic regions, with the maximum Lyapunov exponents of the classical system. This establishes an effective connection between the classical chaos and the QFI. We finally study the critical point of a quantum phase transition using the beyond mean-field approximation by considering a two-mode bosonic Josephson junction with attractive interparticle interaction.

quant-ph↗

arXiv2021

Improved absolute clock stability by the joint interrogation of two atomic states

Improving the clock stability is of fundamental importance for the development of quantum-enhanced metrology. One of the main limitations arises from the randomly-fluctuating local oscillator (LO) frequency, which introduces "phase slips" for long interrogation times and hence failure of the frequency-feedback loop. Here we propose a strategy to improve the stability of atomic clocks by interrogating two out-of-phase state sharing the same LO. While standard Ramsey interrogation can only determine phases unambiguously in the interval $[-π/2,π/2]$, the joint interrogation allows for an extension to $[-π,π]$, resulting in a relaxed restriction of the Ramsey time and improvement of absolute clock stability. Theoretical predictions are supported by ab-initio numerical simulation for white and correlated LO noise. While our basic protocol uses uncorrelated atoms, we have further extended it to include spin-squeezing and further improving the scaling of clock stability with the number of atoms. Our protocol can be readily tested in current state-of-the-art experiments.

quant-ph↗

arXiv2021

Delta-kick Squeezing

We explore the possibility to overcome the standard quantum limit (SQL) in a free-fall atom interferometer using a Bose-Einstein condensate (BEC) in either of the two relevant cases of Bragg or Raman scattering light pulses. The generation of entanglement in the BEC is dramatically enhanced by amplifying the atom-atom interactions via the rapid action of an external trap focusing the matter-waves to significantly increase the atomic densities during a preparation stage -- a technique we refer to as delta-kick squeezing (DKS). The action of a second DKS operation at the end of the interferometry sequence allows to implement a non-linear readout scheme making the sub-SQL sensitivity highly robust against imperfect atom counting detection. We predict more than 30 dB of sensitivity gain beyond the SQL for the variance, assuming realistic parameters and $10^6$ atoms.

quant-ph↗

arXiv2021

Quantifying Computational Advantage of Grover's Algorithm with the Trace Speed

Despite intensive research, the physical origin of the speed-up offered by quantum algorithms remains mysterious. No general physical quantity, like, for instance, entanglement, can be singled out as the essential useful resource. Here we report a close connection between the trace speed and the quantum speed-up in Grover's search algorithm implemented with pure and pseudo-pure states. For a noiseless algorithm, we find a one-to-one correspondence between the quantum speed-up and the polarization of the pseudo-pure state, which can be connected to a wide class of quantum statistical speeds. For time-dependent partial depolarization and for interrupted Grover searches, the speed-up is specifically bounded by the maximal trace speed that occurs during the algorithm operations. Our results quantify the quantum speed-up with a physical resource that is experimentally measurable and related to multipartite entanglement and quantum coherence.

quant-ph↗

arXiv2020

Non-linear Bragg trap interferometer

We propose a scheme for trapped atom interferometry using an interacting Bose-Einstein condensate. The condensate is controlled and spatially split in two confined external momentum modes through a series Bragg pulses. The proposed scheme (i) allows the generation of large entanglement in a trapped-interferometer configuration via one-axis twisting dynamic induced by interatomic interaction, and (ii) avoids the suppression of interactions during the interferometer sequence by a careful manipulation of the state before and after phase encoding. The interferometer can be used for the measurement of gravity with a sensitivity beyond the standard quantum limit.

quant-ph↗

arXiv2020

Quantum Phase Estimation Algorithm with Gaussian Spin States

Quantum phase estimation (QPE) is one of the most important subroutines in quantum computing. In general applications, current QPE algorithms either suffer an exponential time overload or require a set of - notoriously quite fragile - GHZ states. These limitations have prevented so far the demonstration of QPE beyond proof-of-principles. Here we propose a new QPE algorithm that scales linearly with time and is implemented with a cascade of Gaussian spin states (GSS). GSS are renownedly resilient and have been created experimentally in a variety of platforms, from hundreds of ions up to millions of cold/ultracold neutral atoms. We show that our protocol achieves a QPE sensitivity overcoming previous bounds, including those obtained with GHZ states, and is robustly resistant to several sources of noise and decoherence. Our work paves the way toward realistic quantum advantage demonstrations of the QPE, as well as applications of atomic squeezed states for quantum computation.

quant-ph↗

arXiv2020

Multiparameter squeezing for optimal quantum enhancements in sensor networks

Squeezing currently represents the leading strategy for quantum enhanced precision measurements of a single parameter in a variety of continuous- and discrete-variable settings and technological applications. However, many important physical problems including imaging and field sensing require the simultaneous measurement of multiple unknown parameters. The development of multiparameter quantum metrology is yet hindered by the intrinsic difficulty in finding saturable sensitivity bounds and feasible estimation strategies. Here, we derive the general operational concept of multiparameter squeezing, identifying metrologically useful states and optimal estimation strategies. When applied to spin- or continuous-variable systems, our results generalize widely-used spin- or quadrature-squeezing parameters. Multiparameter squeezing provides a practical and versatile concept that paves the way to the development of quantum-enhanced estimation of multiple phases, gradients, and fields, and for the efficient characterization of multimode quantum states in atomic and optical sensor networks.

quant-ph↗

arXiv2020

Heisenberg-limited noisy atomic clock using a hybrid coherent and squeezed states protocol

We propose a hybrid quantum-classical atomic clock protocol where the interrogation of an ensemble of uncorrelated atoms in a spin-coherent state is used to feedback one (or more) spin-squeezed atomic ensembles toward their optimal phase sensitivity point. This protocol overcomes the stability of a single Ramsey clock and it reaches a Heisenberg-limited stability while avoiding non-destructive measurements. Analytical predictions are compared with numerical simulations of clocks operations including correlated 1/f local oscillator noise.

quant-ph↗

arXiv2019

Adiabatic Sensing Enhanced by Quantum Criticality

We propose an optimal method exploiting second order quantum phase transitions to perform high precision measurements of the control parameter at criticality. Our approach accesses the high fidelity susceptibility via the measurement of first- and second-moments of the order parameter and overcomes the difficulties of existing methods based on the overlap between nearby quantum states, which is hardly detectable in many-body systems. We experimentally demonstrate the feasibility of the method with a Bose-Einstein condensate undergoing a symmetry-breaking quantum phase transition as a function of the attractive inter-particle interaction strength. Our moment-based fidelity susceptibility shows a clear peak that, at the same time, detects the quantum critical point at finite temperature without any model-dependent fit to the data and certifies high sensitivity in parameter-estimation.

quant-ph↗