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Johan Henaff

Publications and source records attributed to Johan Henaff.

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Experimental quantum state learning with pairs of photons

Tomography allows one to estimate the density matrix describing the state an ensemble of quantum systems are prepared in (for example, polarization tomography determines the polarization state of a beam of identically prepared photons). In general, it is not possible to uniquely decompose the density matrix into its pure state components. Agarwal et al. proposed a protocol which, for a mixture composed of any two pure states of a qubit (with arbitrary probabilities), allows an observer to infer not only the density matrix but the identity of those specific pure states and their weights - the additional requirement being that the qubits arrive in pairs, where both qubits in each pair are in the same state. We experimentally demonstrate this learning-from-pairs concept using photons in the polarization degree of freedom. We use tomography to measure a sequence of single photons and make use of their time-of-arrival information to 'pair up' the photons after the measurement. From here we are able to infer the photons' polarization states and their respective probabilities, and we demonstrate this for various different choices of polarization states and ratios. Finally, we investigate our ability to discriminate between two equal mixtures of distinct pairs of orthogonal polarization states. We find that on the order of approx. 10e4 photons is typically enough to achieve tomography fidelities of approximately 0.9999. This is sufficient to discriminate between two different preparations of the same mixed state, differing by angles of less than 5 degrees between the pure states used in the two preparations.

quant-ph

Experimental memory control in continuous variable optical quantum reservoir computing

Quantum reservoir computing (QRC) offers a promising framework for online quantum-enhanced machine learning tailored to temporal tasks, yet practical implementations with native memory capabilities remain limited. Here, we demonstrate an optical QRC platform based on deterministically generated multimode squeezed states, exploiting both spectral and temporal multiplexing in a fully continuous-variable (CV) setting, and enabling controlled fading memory. Data is encoded via programmable phase shaping of the pump in an optical parametric process and retrieved through mode-selective homodyne detection. Real-time memory is achieved through feedback using electro-optic phase modulation, while long-term dependencies are achieved via spatial multiplexing. This architecture with minimal post-processing performs nonlinear temporal tasks, including parity checking and chaotic signal forecasting, with results corroborated by a high-fidelity Digital Twin. We show that leveraging the entangled multimode structure significantly enhances the expressivity and memory capacity of the quantum reservoir. This work establishes a scalable photonic platform for quantum machine learning, operating in CV encoding and supporting practical quantum-enhanced information processing.

quant-ph

Optical phase encoding in pulsed approach to reservoir computing

The exploitation of the full structure of multimode light fields enables compelling capabilities in many fields including classical and quantum information science. We exploit data-encoding on the optical phase of the pulses of a femtosecond laser source for a photonic implementation of a reservoir computing protocol. Rather than intensity detection, data-reading is done via homodyne detection that accesses combinations of amplitude and phase of the field. Numerical and experimental results on NARMA tasks and laser dynamic predictions are shown. We discuss perspectives for quantum enhanced protocols.

quant-ph

Spectrally shaped and pulse-by-pulse multiplexed multimode squeezed states of light

Spectral- and time- multiplexing are currently explored to generate large multipartite quantum states of light for quantum technologies. In the continuous variable approach, the deterministic generation of large entangled states demands the generation of a large number of squeezed modes. Here, we demonstrate the simultaneous generation of 21 squeezed spectral modes at 156 MHz. We exploit the full repetition rate and the ultrafast shaping of a femtosecond light source to combine, for the first time, frequency- and time- multiplexing in multimode squeezing. This paves the way to the implementation of multipartite entangled states that are both scalable and fully reconfigurable.

quant-ph