arXiv subjects

Giorgio Ferrari

Publications and source records attributed to Giorgio Ferrari.

At least 55 records · Page 3Linked to original sources

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↗

arXiv2022

A unifying framework for submodular mean field games

We provide an abstract framework for submodular mean field games and identify verifiable sufficient conditions that allow to prove existence and approximation of strong mean field equilibria in models where data may not be continuous with respect to the measure parameter and common noise is allowed. The setting is general enough to encompass qualitatively different problems, such as mean field games for discrete time finite space Markov chains, singularly controlled and reflected diffusions, and mean field games of optimal timing. Our analysis hinges on Tarski's fixed point theorem, along with technical results on lattices of flows of probability and sub-probability measures.

math.OC↗

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

Cryogenic characterization and modeling of a CMOS floating-gate device for quantum control hardware

We perform the characterization and modeling of a floating-gate device realized with a commercial 350-nm CMOS technology at cryogenic temperature. The programmability of the device offers a solution in the realization of a precise and flexible cryogenic system for qubits control in large-scale quantum computers. The device stores onto a floating-gate node a non-volatile charge, which can be bidirectionally modified by Fowler-Nordheim tunneling and impact-ionized hotelectron injection. These two injection mechanisms are characterized and modeled in compact equations both at 300 K and 15 K. At cryogenic temperature, we show a fine-tuning of the stored charge compatible with the operation of a precise analog memory. Moreover, we developed accurate simulation models of the proposed floating-gate device that set the stage for designing a programmable analog circuit with better performances and accuracy at a few Kelvin. This work offers a solution in the design of configurable analog electronics to be employed for accurately read out the qubit state at deep-cryogenic temperature.

physics.app-ph↗

arXiv2021

On an Irreversible Investment Problem with Two-Factor Uncertainty

We consider a real options model for the optimal irreversible investment problem of a profit maximizing company. The company has the opportunity to invest into a production plant capable of producing two products, of which the prices follow two independent geometric Brownian motions. After paying a constant sunk investment cost, the company sells the products on the market and thus receives a continuous stochastic revenue-flow. This investment problem is set as a two-dimensional optimal stopping problem. We find that the optimal investment decision is triggered by a convex curve, which we characterize as the unique continuous solution to a nonlinear integral equation. Furthermore, we provide analytical and numerical comparative statics results of the dependency of the project's value and investment decision with respect to the model's parameters.

q-fin.MF↗

arXiv2021

Optimal Dividend Payout under Stochastic Discounting

Adopting a probabilistic approach we determine the optimal dividend payout policy of a firm whose surplus process follows a controlled arithmetic Brownian motion and whose cash-flows are discounted at a stochastic dynamic rate. Dividends can be paid to shareholders at unrestricted rates so that the problem is cast as one of singular stochastic control. The stochastic interest rate is modelled by a Cox-Ingersoll-Ross (CIR) process and the firm's objective is to maximize the total expected flow of discounted dividends until a possible insolvency time. We find an optimal dividend payout policy which is such that the surplus process is kept below an endogenously determined stochastic threshold expressed as a decreasing continuous function $r \mapsto b(r)$ of the current interest rate value. We also prove that the value function of the singular control problem solves a variational inequality associated to a second-order, non-degenerate elliptic operator, with a gradient constraint.

math.OC↗

arXiv2021

Nonlinear Filtering of Partially Observed Systems arising in Singular Stochastic Optimal Control

This paper deals with a nonlinear filtering problem in which a multi-dimensional signal process is additively affected by a process $ν$ whose components have paths of bounded variation. The presence of the process $ν$ prevents from directly applying classical results and novel estimates need to be derived. By making use of the so-called reference probability measure approach, we derive the Zakai equation satisfied by the unnormalized filtering process, and then we deduce the corresponding Kushner-Stratonovich equation. Under the condition that the jump times of the process $ν$ do not accumulate over the considered time horizon, we show that the unnormalized filtering process is the unique solution to the Zakai equation, in the class of measure-valued processes having a square-integrable density. Our analysis paves the way to the study of stochastic control problems where a decision maker can exert singular controls in order to adjust the dynamics of an unobservable Itô-process.

math.OC↗

arXiv2021

Stationary Discounted and Ergodic Mean Field Games of Singular Control

We study stationary mean field games with singular controls in which the representative player interacts with a long-time weighted average of the population through a discounted and an ergodic performance criterion. This class of games finds natural applications in the context of optimal productivity expansion in dynamic oligopolies. We prove existence and uniqueness of the mean field equilibria, which are completely characterized through nonlinear equations. Furthermore, we relate the mean field equilibria for the discounted and the ergodic games by showing the validity of an Abelian limit. The latter allows also to approximate Nash equilibria of - so far unexplored - symmetric N-player ergodic singular control games through the mean field equilibrium of the discounted game. Numerical examples finally illustrate in a case study the dependency of the mean field equilibria with respect to the parameters of the games.

math.OC↗

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↗

arXiv2021

Position-controlled functionalization of vacancies in silicon by single-ion implanted germanium atoms

Special point defects in semiconductors have been envisioned as suitable components for quantum-information technology. The identification of new deep centers in silicon that can be easily activated and controlled is a main target of the research in the field. Vacancy-related complexes are suitable to provide deep electronic levels but they are hard to control spatially. With the spirit of investigating solid state devices with intentional vacancy-related defects at controlled position, here we report on the functionalization of silicon vacancies by implanting Ge atoms through single-ion implantation, producing Ge-vacancy (GeV) complexes. We investigate the quantum transport through an array of GeV complexes in a silicon-based transistor. By exploiting a model based on an extended Hubbard Hamiltonian derived from ab-initio results we find anomalous activation energy values of the thermally activated conductance of both quasi-localized and delocalized many-body states, compared to conventional dopants. We identify such states, forming the upper Hubbard band, as responsible of the experimental sub-threshold transport across the transistor. The combination of our model with the single-ion implantation method enables future research for the engineering of GeV complexes towards the creation of spatially controllable individual defects in silicon for applications in quantum information technologies.

cond-mat.mtrl-sci↗

arXiv2020

Optimal switch from a fossil-fueled to an electric vehicle

In this paper we propose and solve a real options model for the optimal adoption of an electric vehicle. A policymaker promotes the abeyance of fossil-fueled vehicles through an incentive, and the representative fossil-fueled vehicle's owner decides the time at which buying an electric vehicle, while minimizing a certain expected cost. This involves a combination of various types of costs: the stochastic opportunity cost of driving one unit distance with a traditional fossil-fueled vehicle instead of an electric one, the cost associated to traffic bans, and the net purchase cost. After determining the optimal switching time and the minimal cost function for a general diffusive opportunity cost, we specialize to the case of a mean-reverting process. In such a setting, we provide a model calibration on real data from Italy, and we study the dependency of the optimal switching time with respect to the model's parameters. Moreover, we study the effect of traffic bans and incentive on the expected optimal switching time. We observe that incentive and traffic bans on fossil-fueled transport can be used as effective tools in the hand of the policymaker to encourage the adoption of electric vehicles, and hence to reduce air pollution.

econ.GN↗

arXiv2020

Optimal Consumption with Intertemporal Substitution under Knightian Uncertainty

We study an intertemporal consumption and portfolio choice problem under Knightian uncertainty in which agent's preferences exhibit local intertemporal substitution. We also allow for market frictions in the sense that the pricing functional is nonlinear. We prove existence and uniqueness of the optimal consumption plan, and we derive a set of sufficient first-order conditions for optimality. With the help of a backward equation, we are able to determine the structure of optimal consumption plans. We obtain explicit solutions in a stationary setting in which the financial market has different risk premia for short and long positions.

math.OC↗

arXiv2020

Taming the spread of an epidemics by lockdown policies

We study the problem of a policymaker who aims at taming the spread of an epidemic while minimizing its associated social costs. The main feature of our model lies in the fact that the disease's transmission rate is a diffusive stochastic process whose trend can be adjusted via costly confinement policies. We provide a complete theoretical analysis, as well as numerical experiments illustrating the structure of the optimal lockdown policy. In all our experiments the latter is characterized by three distinct periods: the epidemic is first let freely evolve, then vigorously tamed, and finally a less stringent containment should be adopted. Moreover, the optimal containment policy is such that the product "reproduction number x percentage of susceptible" is kept after a certain date strictly below the critical level of one, although the reproduction number is let oscillate above one in the last more relaxed phase of lockdown. Finally, an increase in the fluctuations of the transmission rate is shown to give rise to an earlier beginning of the optimal lockdown policy, which is also diluted over a longer period of time.

math.OC↗

arXiv2020

Numerical approximation of the value of a stochastic differential game with asymmetric information

We consider a convexity constrained Hamilton-Jacobi-Bellman-type obstacle problem for the value function of a zero-sum differential game with asymmetric information. We propose a convexity-preserving probabilistic numerical scheme for the approximation of the value function which is discrete w.r.t. the time and convexity variables, and show that the scheme converges to the unique viscosity solution of the considered problem. Furthermore, we generalize the semi-discrete scheme to obtain an implementable fully discrete numerical approximation of the value function and present numerical experiments to demonstrate the properties of the proposed numerical scheme.

math.NA↗

arXiv2020

Observation of single phonon-mediated quantum transport in a silicon single-electron CMOS transistor by RMS noise analysis

We explore phonon-mediated quantum transport through electronic noise characterization of a commercial CMOS transistor. The device behaves as a single electron transistor thanks to a single impurity atom in the channel. A low noise cryogenic CMOS transimpedance amplifier is exploited to perform low-frequency noise characterization down to the single electron, single donor and single phonon regime simultaneously, not otherwise visible through standard stability diagrams. Single electron tunneling as well as phonon-mediated features emerges in rms-noise measurements. Phonons are emitted at high frequency by generation-recombination phenomena by the impurity atom. The phonon decay is correlated to a Lorentzian $1/f^2$ noise at low frequency.

cond-mat.mes-hall↗

arXiv2020

A Singular Stochastic Control Problem with Interconnected Dynamics

In this paper we study a Markovian two-dimensional bounded-variation stochastic control problem whose state process consists of a diffusive mean-reverting component and of a purely controlled one. The main problem's characteristic lies in the interaction of the two components of the state process: the mean-reversion level of the diffusive component is an affine function of the current value of the purely controlled one. By relying on a combination of techniques from viscosity theory and free-boundary analysis, we provide the structure of the value function and we show that it satisfies a second-order smooth-fit principle. Such a regularity is then exploited in order to determine a system of functional equations solved by the two monotone continuous curves (free boundaries) that split the control problem's state space in three connected regions. Further properties of the free boundaries are also obtained.

math.OC↗

arXiv2020

A Knightian Irreversible Investment Problem

In this paper, we study an irreversible investment problem under Knightian uncertainty. In a general framework, in which Knightian uncertainty is modeled through a set of multiple priors, we prove existence and uniqueness of the optimal investment plan, and derive necessary and sufficient conditions for optimality. This allows us to construct the optimal policy in terms of the solution to a stochastic backward equation under the worst-case scenario. In a time-homogeneous setting - where risk is driven by a geometric Brownian motion and Knightian uncertainty is realized through a so-called "k-ignorance" - we are able to provide the explicit form of the optimal irreversible investment plan.

math.OC↗

arXiv2019

Optimal Control of Debt-to-GDP Ratio in an N-state Regime Switching Economy

We solve an infinite time-horizon bounded-variation stochastic control problem with regime switching between $N$ states. This is motivated by the problem of a government that wants to control the country's debt-to-GDP (gross domestic product) ratio. In our formulation, the debt-to-GDP ratio evolves stochastically in continuous time, and its drift -- given by the interest rate on government debt, net of the growth rate of GDP -- is affected by an exogenous macroeconomic risk process modelled by a continuous-time Markov chain with $N$ states. The government can act on the public debt by increasing or decreasing its level, and it aims at minimising a net expected regime-dependent cost functional. Without relying on a guess-and-verify approach, but performing a direct probabilistic study, we show that it is optimal to keep the debt-to-GDP ratio in an interval, whose boundaries depend on the states of the risk process. These boundaries are given through a zero-sum optimal stopping game with regime switching with $N$ states and are characterised through a system of nonlinear algebraic equations with constraints. To the best of our knowledge, such a result appears here for the first time. Finally, we put in practice our methodology in a case study of a Markov chain with $N=2$ states; we provide a thorough analysis and we complement our theoretical results by a detailed numerical study on the sensitivity of the optimal debt ratio management policy with respect to the problem's parameters.

math.OC↗