arXiv subjects

Simone Montangero

Publications and source records attributed to Simone Montangero.

At least 55 records · Page 3Linked to original sources

arXiv2023

A Set of Annealing Protocols for Optimized System Dynamics and Classification of Fully Connected Spin Glass Problems

We perform exact diagonalization and time evolution of the Lechner-Hauke-Zoller (LHZ) annealing architecture [Science Advances 1(9), e1500838 (2015)] for ten physical qubits. Thereby, on a training set consisting of $2400$ problem instances, we perform the optimization task of tuning the local fields with the goal to identify a set of fixed optimal annealing protocols, that outperforms linear protocols on a large class of arbitrary LHZ problem instances. We show that average ground state fidelities of $0.9$ can be achieved by applying optimized protocols onto groups of problem instances with similar energy landscapes. Particularly, the set of optimized annealing protocols reduces annealing time required to reach a predefined threshold ground state fidelity by an average of $\sim72\%$, corresponding to a speed-up of factor $\sim3.5$. Moreover, as these protocols are meant to be readily applicable in experimental setups, they can be used as a starting point for problem-specific protocol optimization. In reverse, we discuss how previously optimized protocols can potentially be used to gauge the instantaneous energy landscape of a spin glass problem. Albeit simulations were performed on the LHZ architecture, identification of optimized protocols is not limited to either simulations or local connectivity only.

quant-ph↗

arXiv2023

A randomized measurement toolbox for an interacting Rydberg-atom quantum simulator

We present a toolbox to probe quantum many-body states implemented on Rydberg-atoms quantum hardware via randomized measurements. We illustrate the efficacy of this measurement toolbox in the context of probing entanglement, via the estimation of the purity, and of verifying a ground-state preparation using measurements of the Hamiltonian variance. To achieve this goal, we develop and discuss in detail a protocol to realize independent, local unitary rotations. We benchmark the protocol by investigating the ground state of the one-dimensional SSH model, recently realized on a chain of Rydberg atom, and the state resulting after a sudden quench in a staggered XY chain. We probe the robustness of our toolbox by taking into account experimental imperfections, such as pulse fluctuations and measurement errors.

quant-ph↗

arXiv2023

Entanglement generation in $(1+1)D$ QED scattering processes

We study real-time meson-meson scattering processes in $(1+1)$-dimensional QED by means of Tensor Networks. We prepare initial meson wave packets with given momentum and position introducing an approximation based on the free fermions model. Then, we compute the dynamics of two initially separated colliding mesons, observing a rich phenomenology as the interaction strength and the initial states are varied in the weak and intermediate coupling regimes. Finally, we consider elastic collisions and measure some scattering amplitudes as well as the entanglement generated by the process. Remarkably, we identify two different regimes for the asymptotic entanglement between the outgoing mesons: it is perturbatively small below a threshold coupling, past which its growth as a function of the coupling abruptly accelerates.

hep-lat↗

arXiv2023

Hadrons in (1+1)D Hamiltonian hardcore lattice QCD

We study 2-flavor Hamiltonian lattice QCD in (1+1)D with hardcore gluons, at zero and finite density, by means of matrix product states. We introduce a formulation of the theory where gauge redundancy is absent and construct a gauge invariant tensor network ansatz. We show that the model is critical in an extended subregion of parameter space and identify at least two distinct phases, one of which embeds the continuum limit location. We reconstruct a subset of the particle spectrum in each phase, identifying edge and bulk gapless modes. We thereby show that the studied model provides a minimal SU(3) gauge theory whilst reproducing known phenomena of (3+1)D QCD. Most notably, it features charged pions.

hep-lat↗

arXiv2023

Quantum Computing for High-Energy Physics: State of the Art and Challenges. Summary of the QC4HEP Working Group

Quantum computers offer an intriguing path for a paradigmatic change of computing in the natural sciences and beyond, with the potential for achieving a so-called quantum advantage, namely a significant (in some cases exponential) speed-up of numerical simulations. The rapid development of hardware devices with various realizations of qubits enables the execution of small scale but representative applications on quantum computers. In particular, the high-energy physics community plays a pivotal role in accessing the power of quantum computing, since the field is a driving source for challenging computational problems. This concerns, on the theoretical side, the exploration of models which are very hard or even impossible to address with classical techniques and, on the experimental side, the enormous data challenge of newly emerging experiments, such as the upgrade of the Large Hadron Collider. In this roadmap paper, led by CERN, DESY and IBM, we provide the status of high-energy physics quantum computations and give examples for theoretical and experimental target benchmark applications, which can be addressed in the near future. Having the IBM 100 x 100 challenge in mind, where possible, we also provide resource estimates for the examples given using error mitigated quantum computing.

quant-ph↗

arXiv2023

Entanglement entropy production in Quantum Neural Networks

Quantum Neural Networks (QNN) are considered a candidate for achieving quantum advantage in the Noisy Intermediate Scale Quantum computer (NISQ) era. Several QNN architectures have been proposed and successfully tested on benchmark datasets for machine learning. However, quantitative studies of the QNN-generated entanglement have been investigated only for up to few qubits. Tensor network methods allow to emulate quantum circuits with a large number of qubits in a wide variety of scenarios. Here, we employ matrix product states to characterize recently studied QNN architectures with random parameters up to fifty qubits showing that their entanglement, measured in terms of entanglement entropy between qubits, tends to that of Haar distributed random states as the depth of the QNN is increased. We certify the randomness of the quantum states also by measuring the expressibility of the circuits, as well as using tools from random matrix theory. We show a universal behavior for the rate at which entanglement is created in any given QNN architecture, and consequently introduce a new measure to characterize the entanglement production in QNNs: the entangling speed. Our results characterise the entanglement properties of quantum neural networks, and provides new evidence of the rate at which these approximate random unitaries.

quant-ph↗

arXiv2023

Information Theoretical Limits for Quantum Optimal Control Solutions: Error Scaling of Noisy Channels

Accurate manipulations of an open quantum system require a deep knowledge of its controllability properties and the information content of the implemented control fields. By using tools of information and quantum optimal control theory, we provide analytical bounds (information-time bounds) to characterize our capability to control the system when subject to arbitrary sources of noise. Moreover, since the presence of an external noise field induces open quantum system dynamics, we also show that the results provided by the information-time bounds are in very good agreement with the Kofman-Kurizki universal formula describing decoherence processes. Finally, we numerically test the scaling of the control accuracy as a function of the noise parameters, by means of the dressed chopped random basis (dCRAB) algorithm for quantum optimal control.

quant-ph↗

arXiv2022

QuOCS: The Quantum Optimal Control Suite

Quantum optimal control includes the family of pulse-shaping algorithms that aim to unlock the full potential of a variety of quantum technologies. Our Quantum Optimal Control Suite (QuOCS) unites experimental focus and model-based approaches in a unified framework. The easy usage and installation of QuOCS and the availability of various combinable optimization strategies is designed to improve the performance of many quantum technology platforms, such as color defects in diamond, superconducting qubits, atom- or ion-based quantum computers. It can also be applied to the study of more general phenomena in physics. In this paper, we describe the software and the main toolbox of gradient-free and gradient-based algorithms. We then show how the user can connect it to their experiment. In addition, we provide illustrative examples where our optimization suite solves typical quantum optimal control problems, in both open- and closed-loop settings. Integration into existing experimental control software is already provided for the experiment control software Qudi [J. M. Binder et al., SoftwareX, 6, 85-90, (2017)], and further extensions are investigated and highly encouraged. QuOCS is available from GitHub, under Apache License 2.0, and can be found on the PyPI repository.

quant-ph↗

arXiv2022

Is quantum computing green? An estimate for an energy-efficiency quantum advantage

The quantum advantage threshold determines when a quantum processing unit (QPU) is more efficient with respect to classical computing hardware in terms of algorithmic complexity. The "green" quantum advantage threshold $-$ based on a comparison of energetic efficiency between the two $-$ is going to play a fundamental role in the comparison between quantum and classical hardware. Indeed, its characterization would enable better decisions on energy-saving strategies, e.g. for distributing the workload in hybrid quantum-classical algorithms. Here, we show that the green quantum advantage threshold crucially depends on (i) the quality of the experimental quantum gates and (ii) the entanglement generated in the QPU. Indeed, for NISQ hardware and algorithms requiring a moderate amount of entanglement, a classical tensor network emulation can be more energy-efficient at equal final state fidelity than quantum computation. We compute the green quantum advantage threshold for a few paradigmatic examples in terms of algorithms and hardware platforms, and identify algorithms with a power-law decay of singular values of bipartitions $-$ with power-law exponent $α\lesssim 1$ $-$ as the green quantum advantage threshold in the near future.

quant-ph↗

arXiv2022

Robust Magnetometry with Single NV Centers via Two-step Optimization

Shallow Nitrogen-Vacancy (NV) centers are promising candidates for high-precision sensing applications; these defects, when positioned a few nanometers below the surface, provide an atomic-scale resolution along with substantial sensitivity. However, the dangling bonds and impurities on the diamond surface result in a complex environment which reduces the sensitivity and is unique to each shallow NV center. To avoid the environment's detrimental effect, we apply feedback-based quantum optimal control. We first show how a direct search can improve the initialization/readout process. In a second step, we optimize microwave pulses for pulsed Optically Detected Magnetic Resonance (ODMR) and Ramsey measurements. Throughout the sensitivity optimizations, we focus on robustness against errors in the control field amplitude. This feature not only protects the protocols' sensitivity from drifts but also enlarges the sensing volume. The resulting ODMR measurements produce sensitivities below 1$μ$T\,Hz$^{-\frac{1}{2}}$ for an 83\% decrease in control power, increasing the robustness by approximately one third. The optimized Ramsey measurements produce sensitivities below 100\,nT\,Hz$^{-\frac{1}{2}}$ giving a two-fold sensitivity improvement. Being on par with typical sensitivities obtained via single NV magnetometry, the complementing robustness of the presented optimization strategy may provide an advantage for other NV-based applications.

quant-ph↗

arXiv2022

Experimental realization of optimal time-reversal on an atom chip for quantum undo operations

We report on the use of the dCRAB optimal control algorithm to realize time-reversal procedures for the implementation of quantum undo operations, to be applied in quantum technology contexts ranging from quantum computing to quantum communications. By means of the undo command, indeed, the last performed operation can be time-reversed so as to perfectly restore a condition in which an arbitrary new operation, chosen by the external user, can be applied. Moreover, by further generalizing this concept, the undo command can also allow for the reversing of a quantum operation in a generic instant of the past. Here, thanks to optimal time-reversal routines, all these functionalities are experimentally implemented on the five-fold F=2 Hilbert space of a Bose-Einstein condensate (BEC) of non-interacting $^{87}$Rb atoms in the ground state, realized with an atom chip. Specifically, each time-reversal transformation is attained by designing an optimal modulated radio frequency field, achieving on average an accuracy of around 92% in any performed test. The experimental results are accompanied by a thermodynamic interpretation based on the Loschmidt echo. Our findings are expected to promote the implementation of time-reversal operations in a real scenario of gate-based quantum computing with a more complex structure than the five-level system here considered.

quant-ph↗

arXiv2022

Adaptive-weighted tree tensor networks for disordered quantum many-body systems

We introduce an adaptive-weighted tree tensor network, for the study of disordered and inhomogeneous quantum many-body systems. This ansatz is assembled on the basis of the random couplings of the physical system with a procedure that considers a tunable weight parameter to prevent completely unbalanced trees. Using this approach, we compute the ground state of the two-dimensional quantum Ising model in the presence of quenched random disorder and frustration, with lattice size up to $32 \times 32$. We compare the results with the ones obtained using the standard homogeneous tree tensor networks and the completely self-assembled tree tensor networks, demonstrating a clear improvement of numerical precision as a function of the weight parameter, especially for large system sizes.

cond-mat.dis-nn↗

arXiv2022

Quantum optimal control in quantum technologies. Strategic report on current status, visions and goals for research in Europe

Quantum optimal control, a toolbox for devising and implementing the shapes of external fields that accomplish given tasks in the operation of a quantum device in the best way possible, has evolved into one of the cornerstones for enabling quantum technologies. The last few years have seen a rapid evolution and expansion of the field. We review here recent progress in our understanding of the controllability of open quantum systems and in the development and application of quantum control techniques to quantum technologies. We also address key challenges and sketch a roadmap for future developments.

quant-ph↗

arXiv2022

Error-budgeting for a controlled-phase gate with strontium-88 Rydberg atoms

We study the implementation of a high fidelity controlled-phase gate in a Rydberg quantum computer. The protocol is based on a symmetric gate with respect to the two qubits as experimentally realized by Levine et al [Phys. Rev. Lett. 123, 170503 (2019)], but allows for arbitrary pulse shapes with time-dependent detuning. Optimizing the pulse shapes, we introduce laser pulses which shorten the time spent in the Rydberg state by 10% and reduce the leading contribution to the gate infidelity, i.e., the decay from the Rydberg state. Remarkably, this reduction can be achieved for smooth pulses in detuning and smooth turning on of the Rabi frequency as required in any experimental realization. We carefully analyze the influence of fundamental error sources such as the photon recoil, the microscopic interaction potential, as well as the harmonic trapping of the atoms for an experimentally realistic setup based on strontium-88 atoms. We find that an average gate fidelity above 99.9% is possible for a very conservative estimation of experimental parameters.

quant-ph↗

arXiv2022

Macroscopic Hyperpolarization Enhanced with Quantum Optimal Control

Hyperpolarization of nuclear spins enhances nuclear magnetic resonance signals, which play a key role for imaging and spectroscopy in the natural and life sciences. This signal amplification unlocks previously inaccessible techniques, such as metabolic imaging of cancer cells. In this work, electron spins from the photoexcited triplet state of pentacene-doped naphthalene crystals are used to polarize surrounding protons. As existing strategies are rendered less effective by experimental constraints, they are replaced with optimal control pulses designed with RedCRAB. In contrast to previous optimal control approaches, which consider an average single nucleus, this closed-loop optimization is macroscopic. A 28% improvement in signal and 15% faster polarization rate is observed. Additionally, a strategy called Autonomously-optimized Repeated Linear Sweep (ARISE) is introduced to efficiently tailor existing hyperpolarization sequences in the presence of experimental uncertainty to enhance their performance. ARISE is expected to be broadly applicable in many experimental settings.

quant-ph↗

arXiv2022

Optimized state transfer in systems of ultrastrongly coupled matter and radiation

Ultrastrong coupling may allow faster operations for the development of quantum technologies at the expenses of increased sensitivity to new kind of intrinsic errors. We study state transfer in superconducting circuit QED architectures in the ultrastrong coupling regime. Using optimal control methods we find a protocol resilient to the main source of errors, coming from the interplay of the dynamical Casimir effect with cavity losses.

quant-ph↗

arXiv2022

Entanglement in the Quantum Game of Life

We investigate the quantum dynamics of a spin chain that implements a quantum analog of Conway's game of life. We solve the time-dependent Schrödinger equation starting with initial separable states and analyse the evolution of quantum correlations across the lattice. We report examples of evolutions leading to all-entangled chains and/or to time oscillating entangling structures and characterize them by means of entanglement and network measures. The quantum patterns result to be quite different from the classical ones, even in the dynamics of local observables. A peculiar instance is a structure behaving as the quantum analog of a blinker, but that has no classical counterpart.

quant-ph↗

arXiv2021

Entanglement of formation of mixed many-body quantum states via Tree Tensor Operators

We present a numerical strategy to efficiently estimate bipartite entanglement measures, and in particular the Entanglement of Formation, for many-body quantum systems on a lattice. Our approach exploits the Tree Tensor Operator tensor network ansatz, a positive loopless representation for density matrices which, as we demonstrate, efficiently encodes information on bipartite entanglement, enabling the up-scaling of entanglement estimation. Employing this technique, we observe a finite-size scaling law for the entanglement of formation in 1D critical lattice models at finite temperature for up to 128 spins, extending to mixed states the scaling law for the entanglement entropy.

quant-ph↗