arXiv subjects

Francesco Morichetti

Publications and source records attributed to Francesco Morichetti.

At least 19 recordsLinked to original sources

arXiv2025

Sequential Monitoring and Control of a Silicon Photonic Coherent Beam Adder and Analyzer

Joint communication and sensing applications require devices that can analyze multiple electromagnetic waves and process them in real time directly in the analog domain. In optics, the growing maturity of photonic integrated platforms allows the fabrication of complex circuits that can perform such operations, but their large number of sensors and actuators requires scalable control strategies to efficiently monitor and actively stabilize their functionality at runtime. In this work, we report on a multi-aperture silicon photonic programmable circuit that operates both as a coherent beam adder and a multi-aperture beam analyzer. The circuit consists of a reconfigurable mesh of Mach-Zehnder interferometers controlled through monolithically integrated electronic circuits, which are used to serialize/deserialize the readout of integrated sensors and the driving of actuators with a time-multiplexed addressing scheme. The circuit operation is validated in a communication and sensing scenario, where the photonic chip is used to simultaneously receive a 25 Gbit/s high-speed transmission and to measure the phase difference between the input light beams.

physics.optics↗

arXiv2025

Data Driven Programming of Photonic Integrated Circuits

Programming photonic integrated hardware often reveals as a challenging task because of the presence of non-idealities in the photonic chip. These include fabrication imper- fections and parasitic effects such as thermal crosstalk, which cause unwanted coupling between control signals. Traditional control methods based on idealized models often fail to account for these phenomana, leading to significant discrepancies between the desired and actual circuit behaviour. In this work, we propose a data-driven approach for control- ling meshes of thermally tuneable Mach Zehnder interferometers (MZIs), which exploits a machine learning (ML) model trained to compensate for these non-idealities by pre- adjusting the electrical power given to integrated phase shifters. The proposed ML system is assessed using synthetic datasets and experimentally validated on a 3 x 3 triangular MZI mesh. Results demonstrate that the data-driven controller significantly improves program- ming accuracy, offering a robust solution for accurate programming of photonic integrated circuits.

physics.optics↗

arXiv2025

High-precision automated setting of arbitrary magnitude and phase of Mach-Zehnder interferometers for scalable optical computing

Photonic technologies offer promising solutions to the power consumption, bandwidth constraints and latency limits of electronic hardware used in high-performance computing and artificial intelligence. Recently, many studies have proposed and successfully demonstrated photonic accelerators based on integrated meshes of Mach-Zehnder interferometers (MZIs), enabling matrix-vector multiplications directly in the optical domain. While being fast and energy efficient, these photonic architectures still struggle to get the required precision for such applications, because setting the complex coefficients of MZI tunable gates with a high accuracy is still an unsolved problem. This work demonstrates high-precision automated setting and stabilization of MZI-based optical gates with a resolution of 7.01 and 8.04 bits for the output power and phase, respectively. Demonstration is achieved on a multistage silicon photonic circuit comprising a coherent input vector generator, an MZI matrix-vector multiplier, and a coherent receiver for phase measurement. The proposed control strategy can configure the MZIs to any desired working point, without any prior calibration or complex algorithm for the correction of hardware non-idealities, and prevents the propagation of programming errors, thus allowing scalability towards optical processors of large size.

physics.optics↗

arXiv2025

Integrated electronic controller for dynamic self-configuration of photonic circuits

Reconfigurable photonic integrated circuits (PICs) can implement arbitrary operations and signal processing functionalities directly in the optical domain. Run-time configuration of these circuits requires an electronic control layer to adjust the working point of their building elements and make them compensate for thermal drifts or degradations of the input signal. As the advancement of photonic foundries enables the fabrication of chips of increasing complexity, developing scalable electronic controllers becomes crucial for the operation of complex PICs. In this paper, we present an electronic application-specific integrated circuit (ASIC) designed for reconfiguration of PICs featuring numerous tuneable elements. Each channel of the ASIC controller independently addresses one optical component of the PIC, as multiple parallel local feedback loops are operated to achieve full control. The proposed design is validated through real-time reconfiguration of a 16-channel silicon photonics adaptive beam coupler. Results demonstrate automatic coupling of an arbitrary input beam to a single-mode waveguide, dynamic compensation of beam wavefront distortions and successful transmission of a 50 Gbit/s signal through an optical free-space link. The low power consumption and compactness of the electronic chip provide a scalable paradigm that can be seamlessly extended to larger photonic architectures.

physics.optics↗

arXiv2024

Self-Adaptive Integrated Photonic Receiver for Turbulence Compensation in Free Space Optical Links

In Free Space Optical (FSO) communication systems, atmospheric turbulence distorts the propagating beams, causing a random fading in the received power. This perturbation can be compensated using a multi-aperture receiver that samples the distorted wavefront on different points and adds the various signals coherently. In this work, we report on an adaptive optical receiver that compensates in real time for scintillation in FSO links. The optical front-end of the receiver is entirely integrated in a silicon photonic chip hosting a 2D Optical Antenna Array and a self-adaptive analog Programmable Optical Processor made of a mesh of tunable Mach-Zehnder interferometers. The photonic chip acts as an adaptive interface to couple turbulent FSO beams to single-mode guided optics, enabling energy and cost-effective operation, scalability to systems with a larger number of apertures, modulation-format and data-protocol transparency, and pluggability with commercial fiber optics transceivers. Experimental results demonstrate the effectiveness of the proposed receiver with optical signals at a data rate of 10 Gbit/s transmitted in indoor FSO links where different turbulent conditions, even stronger than those expected in outdoor links of hundreds of meters, are reproduced.

physics.optics↗

arXiv2024

Training of Physical Neural Networks

Physical neural networks (PNNs) are a class of neural-like networks that leverage the properties of physical systems to perform computation. While PNNs are so far a niche research area with small-scale laboratory demonstrations, they are arguably one of the most underappreciated important opportunities in modern AI. Could we train AI models 1000x larger than current ones? Could we do this and also have them perform inference locally and privately on edge devices, such as smartphones or sensors? Research over the past few years has shown that the answer to all these questions is likely "yes, with enough research": PNNs could one day radically change what is possible and practical for AI systems. To do this will however require rethinking both how AI models work, and how they are trained - primarily by considering the problems through the constraints of the underlying hardware physics. To train PNNs at large scale, many methods including backpropagation-based and backpropagation-free approaches are now being explored. These methods have various trade-offs, and so far no method has been shown to scale to the same scale and performance as the backpropagation algorithm widely used in deep learning today. However, this is rapidly changing, and a diverse ecosystem of training techniques provides clues for how PNNs may one day be utilized to create both more efficient realizations of current-scale AI models, and to enable unprecedented-scale models.

physics.app-ph↗

arXiv2023

Scalable Low-latency Optical Phase Sensor Array

Optical phase measurement is critical for many applications and traditional approaches often suffer from mechanical instability, temporal latency, and computational complexity. In this paper, we describe compact phase sensor arrays based on integrated photonics, which enable accurate and scalable reference-free phase sensing in a few measurement steps. This is achieved by connecting multiple two-port phase sensors into a graph to measure relative phases between neighboring and distant spatial locations. We propose an efficient post-processing algorithm, as well as circuit design rules to reduce random and biased error accumulations. We demonstrate the effectiveness of our system in both simulations and experiments with photonic integrated circuits. The proposed system measures the optical phase directly without the need for external references or spatial light modulators, thus providing significant benefits for applications including microscope imaging and optical phased arrays.

physics.optics↗

arXiv2023

Brillouin and Kerr nonlinearities of a low-index silicon oxynitride platform

Nonlinear optical effects including stimulated Brillouin scattering (SBS) and four-wave mixing (FWM) play an important role in microwave photonics, optical frequency combs, and quantum photonics. Harnessing SBS and FWM in a low-loss and versatile integrated platform would open the path to building large-scale Brillouin/Kerr-based photonic integrated circuits. In this letter, we investigate the Brillouin and Kerr properties of a low-index (n=1.513 @ 1550 nm) silicon oxynitride (SiON) platform. We observed, for the first time, backward SBS in SiON waveguides with a Brillouin gain coefficient of 0.3$\rm m^{-1}W^{-1}$, which can potentially be increased to 0.95$\rm m^{-1}W^{-1}$ by just tailoring the waveguide cross-section. We also performed FWM experiments in SiON rings and obtained the nonlinear parameter $γ$, of 0.02 $\rm m^{-1}W^{-1}$. Our results point to a low-loss and low-index photonic integrated platform that is both Brillouin and Kerr active.

physics.optics↗

arXiv2022

Experimental evaluation of digitally-verifiable photonic computing for blockchain and cryptocurrency

As blockchain technology and cryptocurrency become increasingly mainstream, ever-increasing energy costs required to maintain the computational power running these decentralized platforms create a market for more energy-efficient hardware. Photonic cryptographic hash functions, which use photonic integrated circuits to accelerate computation, promise energy efficiency for verifying transactions and mining in a cryptonetwork. Like many analog computing approaches, however, current proposals for photonic cryptographic hash functions that promise similar security guarantees as Bitcoin are susceptible to systematic error, so multiple devices may not reach a consensus on computation despite high numerical precision (associated with low photodetector noise). In this paper, we theoretically and experimentally demonstrate that a more general family of robust discrete analog cryptographic hash functions, which we introduce as LightHash, leverages integer matrix-vector operations on photonic mesh networks of interferometers. The difficulty of LightHash can be adjusted to be sufficiently tolerant to systematic error (calibration error, loss error, coupling error, and phase error) and preserve inherent security guarantees present in the Bitcoin protocol. Finally, going beyond our proof-of-concept, we define a ``photonic advantage'' criterion and justify how recent developments in CMOS optoelectronics (including analog-digital conversion) provably achieve such advantage for robust and digitally-verifiable photonic computing and ultimately generate a new market for decentralized photonic technology.

cs.ET↗

arXiv2022

Experimentally realized in situ backpropagation for deep learning in nanophotonic neural networks

Neural networks are widely deployed models across many scientific disciplines and commercial endeavors ranging from edge computing and sensing to large-scale signal processing in data centers. The most efficient and well-entrenched method to train such networks is backpropagation, or reverse-mode automatic differentiation. To counter an exponentially increasing energy budget in the artificial intelligence sector, there has been recent interest in analog implementations of neural networks, specifically nanophotonic neural networks for which no analog backpropagation demonstration exists. We design mass-manufacturable silicon photonic neural networks that alternately cascade our custom designed "photonic mesh" accelerator with digitally implemented nonlinearities. These reconfigurable photonic meshes program computationally intensive arbitrary matrix multiplication by setting physical voltages that tune the interference of optically encoded input data propagating through integrated Mach-Zehnder interferometer networks. Here, using our packaged photonic chip, we demonstrate in situ backpropagation for the first time to solve classification tasks and evaluate a new protocol to keep the entire gradient measurement and update of physical device voltages in the analog domain, improving on past theoretical proposals. Our method is made possible by introducing three changes to typical photonic meshes: (1) measurements at optical "grating tap" monitors, (2) bidirectional optical signal propagation automated by fiber switch, and (3) universal generation and readout of optical amplitude and phase. After training, our classification achieves accuracies similar to digital equivalents even in presence of systematic error. Our findings suggest a new training paradigm for photonics-accelerated artificial intelligence based entirely on a physical analog of the popular backpropagation technique.

cs.ET↗

arXiv2022

Spatially resolving amplitude and phase of light with a reconfigurable photonic integrated circuit

Photonic integrated circuits (PICs) play a pivotal role in many applications. Particularly powerful are circuits based on meshes of reconfigurable Mach-Zehnder interferometers as they enable active processing of light. Various possibilities exist to get light into such circuits. Sampling an electromagnetic field distribution with a carefully designed free-space interface is one of them. Here, a reconfigurable PIC is used to optically sample and process free-space beams so as to implement a spatially resolving detector of amplitudes and phases. In order to perform measurements of this kind we develop and experimentally implement a versatile method for the calibration and operation of such integrated photonics based detectors. Our technique works in a wide parameter range, even when running the chip off the design wavelength. Amplitude, phase and polarization sensitive measurements are of enormous importance in modern science and technology, providing a vast range of applications for such detectors.

physics.optics↗

arXiv2022

Amorphous-silicon visible-light detector integrated in silicon nitride waveguides

Visible light integrated photonics is emerging as a promising technology for the realization of optical devices for applications in sensing, quantum information and communications, imaging and displays. Among the existing photonic platforms, high-index contrast silicon nitride ($Si_{3}N_{4}$) waveguides offer broadband transparency in the visible spectral range and a high scale of integration. As far as the complexity of photonic integrated circuits (PICs) increases, on-chip detectors are required to monitor their working point for reconfiguration and stabilization operations. In this work we present a compact in-line power monitor integrated in $Si_{3}N_{4}$ waveguides that operates in the red-light wavelength range (660 nm). The proposed device exploits the photoconductivity of a hydrogenated amorphous silicon (a-Si:H) film employed as a coating layer of the optical waveguide. Experimental results show a responsivity of 30 mA/W, a sensitivity of -45 dBm and a sub-$μ$s time response. These features enable the use of the proposed photoconductor for high-sensitivity monitoring and control of visible-light $Si_{3}N_{4}$ PICs.

physics.optics↗

arXiv2021

Multibeam Free Space Optics Receiver Enabled by a Programmable Photonic Mesh

Free-space optics (FSO) is an attractive technology to meet the ever-growing demand for wireless bandwidth in next generation networks. To increase the spectral efficiency of FSO links, transmission over spatial division multiplexing (SDM) can be exploited, where orthogonal light beams have to be shaped according to suitable amplitude, phase, and polarization profiles. In this work, we show that a programmable photonic circuits, consisting of a silicon photonic mesh of tunable Mach-Zehnder Interferometers (MZIs) can be used as an adaptive multibeam receiver for a FSO communication link. The circuit can self-configure to simultaneously receive and separate, with negligible mutual crosstalk, signals carried by orthogonal FSO beams sharing the same wavelength and polarization. This feature is demonstrated on signal pairs either arriving at the receiver from orthogonal directions (direction-diversity) or being shaped according to different orthogonal spatial modes (mode-diversity), even in the presence of some mixing during propagation. The performance of programmable mesh as an adaptive multibeam receiver is assessed by means of data channel transmission at 10 Gbit/s a wavelength of 1550 nm, but the optical bandwidth of the receiver (>40 nm) allows its use at much higher data rates as well as in wavelength-division multiplexing SDM communication links.

physics.app-ph↗

arXiv2021

Automated manipulation of free space optical beams with integrated silicon photonic meshes

Free-space optics (FSO) offer promising solutions in wireless systems where many different devices need to communicate and interoperate, exchanging massive amounts of data as in communication and sensor networks, and in technologies for positioning and ranging. In these applications, control and manipulation of the light field is required for properly generating and correctly receiving FSO beams even in the presence of unpredictable objects and turbulence in the light path. In this work, we use a programmable mesh of Mach-Zehnder Interferometers (MZIs) to automatically control the complex field radiated and captured by an array of optical antennas. Several functionalities are demonstrated, including the generation of perfectly shaped beams with non-perfect optical antennas, the imaging of a desired field pattern through an obstacle or a diffusive medium, and the identification of an unknown obstacle inserted in the FSO path. Compared to conventional devices used for the manipulation of FSO beams, such as spatial light modulators (SLMs), our programmable circuit can self-configure through automated control strategies and can be integrated with other functionalities implemented onto the same photonic chip.

physics.optics↗

arXiv2020

Characterization of photon pairs generated by a silicon ring resonator under electrical self-pumping

We report on the generation of nonclassical states of light in a silicon ring resonator in a selfpumping scheme. The ring is inserted in a lasing cavity, for which it acts as a filter, so that the lasing always occurs within a selected ring resonance, without active stabilization of the resonance frequency. We show the emission of coincident photon pairs and study their correlation properties through the reconstruction of the measurements via stimulated emission.

quant-ph↗

arXiv2018

Metasurface reconfiguration through lithium ion intercalation in a transition metal oxide

In the latest years the optical engineer's toolbox has welcomed a new concept, the metasurface. In a metasurface, properly tailored material inclusions are able to reshape the electromagnetic field of an incident beam. Change of amplitude, phase and polarization can be addressed within a thickness of only a fraction of a wavelength. By means of this concept, a radical gain in compactness of optical components is foreseen, even of the most complex ones; other unique features like that of analog computing have also been identified. With this huge potential ready to be disclosed, lack of tunability is still a main barrier to be broken. Metasurfaces must now be made reconfigurable, i.e. able to modify and memorize their state, possibly with a small amount of energy. In this Communication we report low-energy, self-holding metasurface reconfiguration through lithium intercalation in a vanadium pentoxide layer integrated within the photonic device. By a proper meta-atom design, operation on amplitude and phase of linearly polarized light has been demonstrated. In addition, manipulation of circularly polarized light in the form of tunable chirality and tunable handedness-preserving reflection has been implemented. These operations are accomplished using as low as 50 pJ/μm^{2}, raising lithium intercalation in transition metal oxides as one of the most energy efficient self-holding tuning mechanisms known so far for metasurfaces, with significant perspectives in the whole field of nanophotonics.

physics.optics↗

arXiv2018

Fundamental limits on the losses of phase and amplitude optical actuators

Amplitude and phase are the basic properties of every wave phenomena; as long as optical waves are concerned, the ability to act on these variables is at the root of a wealth of switching devices. To quantify the performance of an optical switching device, an essential aspect is to determine the tradeoff between the insertion loss and the amplitude or phase modulation depth. Here it is shown that every switching optical device is subject to such a tradeoff, intrinsically connected to the dielectric response of the materials employed inside the switching element itself. This limit finds its roots in fundamental physics, as it directly derives from Maxwell's equations for linear dielectrics, and is hence applicable to a wide class of optical components. Furthermore it results that concepts as filtering, resonance and critical coupling could be of advantage in approaching the limit.

physics.optics↗

arXiv2017

All-optical mode unscrambling on a silicon photonic chip

Propagation of light beams through scattering or multimode systems may lead to randomization of the spatial coherence of the light. Although information is not lost, its recovery requires a coherent interferometric reconstruction of the original signals, which have been scrambled into the modes of the scattering system. Here, we show that we can automatically unscramble four optical beams that have been arbitrarily mixed in a multimode waveguide, undoing the scattering and mixing between the spatial modes through a mesh of silicon photonics Mach-Zehnder interferometers. Using embedded transparent detectors and a progressive tuning algorithm, the mesh self-configures automatically and reset itself after significantly perturbing the mixing, without turning off the beams. We demonstrate the recovery of four separate 10 Gbits/s information channels, with residual cross-talk between beams of -20dB. This principle of self-configuring and self-resetting in optical systems should be applicable in a wide range of optical applications.

physics.ins-det↗