Levy group
Bar-Ilan University, Ramat Gan, Israel
- PI
- Amikam Levy
- Website
- ch.biu.ac.il/node/2157
- Tracked papers
- 6 (2016–2026)
Topics
The most frequent field-map topics among the PI' tracked papers.
Recent papers
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Dynamical onset of quasiprobability negativity in quantum many-body systems
Abstract
Time-dependent quasiprobability distributions provide a quasiprobabilistic description of sequential measurement statistics generated by quantum dynamics, and can reveal nonclassical features with no classical probabilistic counterpart. Yet the dynamical emergence of their negativity in many-body systems remains largely unexplored. We introduce the \emph{first-time negativity} (FTN) of the Margenau-Hill quasiprobability as a dynamical indicator of when local measurement sequences in an interacting quantum system begin to exhibit genuinely nonclassical behavior. Using the Ising chain, we show that FTN discriminates clearly between interaction-dominated and field-dominated regimes, is systematically reshaped by temperature, and responds sensitively to the breaking of integrability. For spatially separated measurements, FTN appears abruptly near the interaction-field crossover, while measurements at opposite boundaries exhibit a distinct weak-field branch whose onset time grows with chain length and is consistent with ballistic propagation across the system. We further compare the numerical onset of negativity with a recently proposed quantum speed limit (QSL) for quasiprobabilities, which provides a geometric benchmark for the observed dynamics. Our results identify FTN as a practical and experimentally accessible probe of the real-time onset of quasiprobability negativity and contextual sequential measurement statistics, directly suited to current platforms capable of sequential weak and strong measurements.
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Theory and Experimental Demonstration of Quantum Invariant Filtering
Abstract
Quantum control protocols are typically devised in the time domain, leaving their spectral behavior to emerge only a posteriori. Here, we invert this paradigm. Starting from a target frequency-domain filter, we employ the dynamical-invariant framework to derive the continuous driving fields that enact the chosen spectral response on a qubit. This approach, Quantum Invariant Filtering (QIF), maps arbitrary finite-impulse responses, including multi-band and phase-sensitive profiles, into experimentally feasible Hamiltonian modulations. Implemented on a single nitrogen-vacancy center in diamond, the method realizes the prescribed passbands with high fidelity, suppresses noise, and preserves coherence for milliseconds, two orders of magnitude longer than Carr-Purcell-Meiboom-Gill sequences, while remaining robust to 50% drive-amplitude errors. Our results establish QIF as a broadly applicable framework for enhanced quantum control and sensing across diverse physical platforms, including superconducting qubits, trapped ions, and nuclear magnetic resonance systems.
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Control of open quantum systems via dynamical invariants
Abstract
In this study, we address the challenge of controlling quantum systems under environmental influences using the theory of dynamical invariants. We employ a reverse engineering approach to develop control protocols designed to be robust against environmental noise and dissipation. This technique offers significant improvements over traditional quantum control methods by accounting for the time-dependent dissipation factor in the master equation, which results from modulating the system's Hamiltonian (the control fields). Additionally, our method obviates the need for iterative propagation of the system state, a resource-intensive process. The method can be applied to any open system dynamics that can be described using a time-dependent Master equation. We demonstrate the effectiveness and practicality of our approach through applications to two fundamental models: a two-level quantum system and a quantum harmonic oscillator, both interacting with a thermal bath.
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Noise Resistant Quantum Control Using Dynamical Invariants
Abstract
A systematic approach to design robust control protocols against the influence of different types of noise is introduced. We present control schemes which protect the decay of the populations avoiding dissipation in the adiabatic and non-adiabatic regimes and minimize the effect of dephasing. The effectiveness of the protocols is demonstrated in two different systems. Firstly we present the case of population inversion of a two level system in the presence of either one or two simultaneous noise sources. Secondly, we present an example of the expansion of coherent and thermal states in harmonic traps, subject to noise arising from monitoring and modulation of the control respectively.
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Action-Noise-Assisted Quantum Control
Abstract
We study the effect of action noise on state-to-state control protocols. Action noise creates dephasing in the instantaneous eigenbasis of the Hamiltonian and hampers the fidelity of the final state with respect to the target state. We find that for shorter protocols the noise more strongly influences the dynamics and degrades fidelity. We suggest improving the fidelity by inducing stronger dephasing rates along the process. The effects of action noise on the dynamics and its manipulation is described for a general Hamiltonian and is then studied by examples.
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Quantum Flywheel
Abstract
A quantum flywheel is studied with the purpose of storing useful work in quantum levels, while additional power is extracted continuously from the device. The flywheel gains its energy form a quantum heat engine. Generally, when a work repository is quantized the work exchange with the engine is accompanied with heat exchange, which may degrade the charging efficiency. In the particular realization of a quantum harmonic oscillator work repository, quantum and thermal fluctuations dominates the dynamics. Quantum monitoring and feedback control are applied to the flywheel, as it is shown to be an essential part of stabilizing and regulating its state of operation, and bringing the system to a steady state. A particular balance between information gained by measuring the system and the information fed back to the system is found to maximize the charging efficiency. The dynamics of the flywheel are described by a stochastic master equation that accounts for the engine, the external driving, the measurement, and the feedback operations.