Programmable entanglement oscillations in a non Markovian channel

We suggest and demonstrate an all-optical experimental setup to observe and engineer entanglement oscillations of a pair of polarization qubits in a non-Markovian channel. We generate entangled photon pairs by spontaneous parametric downconversion (SPDC), and then insert a programmable spatial light modulator in order to impose a polarization dependent phase-shift on the spatial domain of the SPDC output and to create an effective non-Markovian environment. Modulation of the enviroment spectrum is obtained by inserting a spatial grating on the signal arm. In our experiment, programmable oscillations of entanglement are achieved, with the maximally revived state that violates Bell's inequality by 17 standard deviations.Comment: 4 pages, 4 figure

Produzione syngas ad alto contenuto di H2 tramite gassificazione di biomassa proveniente da trattamenti di biorimedio fitoassistito

L’attività di ricerca descritta nasce dall’esigenza di tutelare il territorio e di reperire fonti di energia alternative sostenibili. La gassificazione è una tecnica di conversione energetica termochimica della biomassa che permette di ottenere un gas di sintesi, detto appunto syngas, che può essere stoccato o direttamente impiegato come combustibile. Il principale svantaggio nell’utilizzo di questa tecnologia risiede nel fatto che la produzione e l’utilizzo del syngas richiedono che si adottino misure di monitoraggio affinché il biofuel prodotto abbia gli standard qualitativi necessari per l’impiego come combustibile. È necessario, perciò, utilizzare sistemi di abbattimento e purificazione per ridurre inquinanti e contaminanti che solitamente si generano ed accompagnano al syngas nel processo di gassificazione della biomassa (tar, metalli pesanti, ceneri volatili, ecc.). D’altro canto, il poter ottenere un biofuel da un prodotto di scarto, come la biomassa residuale, rappresenta un indiscusso vantaggio per ridurre l’impatto ambientale, nonché un processo virtuoso in un’ottica di sviluppo di strategie agroindustriali volte alla circular economy. Sulla base di ciò, l’attività di ricerca condotta ha sfruttato il processo di gassificazione, ottimizzandolo, per poter produrre syngas da biomasse residuali di scarto provenienti da terreni contaminanti e in via di bonifica attraverso strategie di biorimedio fitoassistito (o Plant-Assisted BioRemediation, PABR). Tra le varie tecniche di bonifica, il PABR è un'eccellente strategia verde per il recupero dei terreni contaminati. Esso si basa infatti sulla coltivazione di piante che in fase di crescita agiscono in sinergia con i microrganismi presenti nel suolo, promuovendo il sequestro degli inquinanti dal terreno (Metalli pesanti, PCB, ecc.) che vengono letteralmente assorbiti dall’apparato radicale delle colture. Le potature di tali piante sono però considerate, da un punto di vista normativo, prodotti contaminati e quindi il loro smaltimento è una tematica di notevole interesse scientifico. L’obbiettivo del lavoro proposto è stato quello di sfruttare il processo di gassificazione, per il trattamento di potature PABR, col fine di dimostrare che la tecnica proposta produce un syngas comparabile a quello ottenuto con biomasse tradizionali, poiché l’eccesso di contaminanti ed inquinanti presenti viene naturalmente concentrato nelle ceneri residuali durante il processo di gassificazione. L’attività è stata condotta in tre diversi step a TRL crescente: - Test in scala di laboratorio (TRL 3) - Test in scala prototipale (TRL 4-5) - Test in scala reale (TRL 6-7) I risultati ottenuti hanno mostrato come la gassificazione di biomasse PABR sia un’ottima alternativa per lo smaltimento di prodotti contaminanti che permette di ottenere un syngas dalla composizione chimica del tutto comparabile con quello tradizionale. Ulteriore obbiettivo è stato quello di valutare l’impiego di tecnologie volte ad un ulteriore purificazione del syngas prodotto, al fine di aumentarne il contenuto di idrogeno. In particolare, sono stati testati e simulati processi di splitting di CO2 e H2Ov in un reattore a base di catalizzatore metallico (Fe) e di Sorption Enhanced Water Gas Shift (SEWGS) sul syngas prodotto. L’attività svolta nel triennio è il frutto di un lavoro che ha coinvolto, oltre alle facoltà DIAEE (Dipartimento d’Ingegneria Astronautica, Elettrica ed Energetica) e DIMA (Dipartimento d’Ingegneria Meccanica) dell’Università La Sapienza di Roma, anche il LASER-B (Laboratorio Attività Sperimentali Energie Rinnovabili – Biomassa) del CREA-IT (Consiglio per la ricerca in agricoltura e l’analisi dell’economia agraria – ingegneria e trasformazioni agroalimentari) di Monterotondo (RM)

Noisy quantum walks of two indistinguishable interacting particles

We investigate the dynamics of continuous-time two-particle quantum walks on a one-dimensional noisy lattice. Depending on the initial condition, we show how the interplay between particle indistinguishability and interaction determines distinct propagation regimes. A realistic model for the environment is considered by introducing non-Gaussian noise as time-dependent fluctuations of the tunneling amplitudes between adjacent sites. We observe that the combined effect of particle interaction and fast noise (weak coupling with the environment) provides a faster propagation compared to the noiseless case. This effect can be understood in terms of the band structure of the Hubbard model, and a detailed analysis as a function of both noise and system parameters is presented.Comment: 9 pages, 8 figure

GPU-accelerated algorithms for many-particle continuous-time quantum walks

Many-particle continuous-time quantum walks (CTQWs) represent a resource for several tasks in quantum technology, including quantum search algorithms and universal quantum computation. In order to design and implement CTQWs in a realistic scenario, one needs effective simulation tools for Hamiltonians that take into account static noise and fluctuations in the lattice, i.e. Hamiltonians containing stochastic terms. To this aim, we suggest a parallel algorithm based on the Taylor series expansion of the evolution operator, and compare its performances with those of algorithms based on the exact diagonalization of the Hamiltonian or a 4th order Runge–Kutta integration. We prove that both Taylor-series expansion and Runge–Kutta algorithms are reliable and have a low computational cost, the Taylor-series expansion showing the additional advantage of a memory allocation not depending on the precision of calculation. Both algorithms are also highly parallelizable within the SIMT paradigm, and are thus suitable for GPGPU computing. In turn, we have benchmarked 4 NVIDIA GPUs and 3 quad-core Intel CPUs for a 2-particle system over lattices of increasing dimension, showing that the speedup provided by GPU computing, with respect to the OPENMP parallelization, lies in the range between 8x and (more than) 20x, depending on the frequency of post-processing. GPU-accelerated codes thus allow one to overcome concerns about the execution time, and make it possible simulations with many interacting particles on large lattices, with the only limit of the memory available on the device. Program summary Program Title: cuQuWa Licensing provisions: GNU General Public License, version 3 Program Files doi: http://dx.doi.org/10.17632/vjpnjgycdj.1 Programming language: CUDA C Nature of problem: Evolution of many-particle continuous-time quantum-walks on a multidimensional grid in a noisy environment. The submitted code is specialized for the simulation of 2-particle quantum-walks with periodic boundary conditions. Solution method: Taylor-series expansion of the evolution operator. The density-matrix is calculated by averaging multiple independent realizations of the system. External routines: cuBLAS, cuRAND Unusual features: Simulations are run exclusively on the graphic processing unit within the CUDA environment. An undocumented misbehavior in the random-number generation routine (cuRAND package) can corrupt the simulation of large systems, though no problems are reported for small and medium-size systems. Compiling the code with the -arch=sm_30 flag for compute capability 3.5 and above fixes this issue

Quantum walks of two interacting particles on percolation graphs

We address the dynamics of two indistinguishable interacting particles moving on a dynamical percolation graph, i.e., a graph where the edges are independent random telegraph processes whose values jump between 0 and 1, thus mimicking percolation. The interplay between the particle interaction strength, initial state and the percolation rate determine different dynamical regimes for the walkers. We show that, whenever the walkers are initially localised within the interaction range, fast noise enhances the particle spread compared to the noiseless case

GPU-accelerated algorithms for many-particle continuous-time quantum walks

Many-particle continuous-time quantum walks (CTQWs) represent a resource for several tasks in quantum technology, including quantum search algorithms and universal quantum computation. In order to design and implement CTQWs in a realistic scenario, one needs effective simulation tools for Hamiltonians that take into account static noise and fluctuations in the lattice, i.e.\ua0Hamiltonians containing stochastic terms. To this aim, we suggest a parallel algorithm based on the Taylor series expansion of the evolution operator, and compare its performances with those of algorithms based on the exact diagonalization of the Hamiltonian or a 4th order Runge\u2013Kutta integration. We prove that both Taylor-series expansion and Runge\u2013Kutta algorithms are reliable and have a low computational cost, the Taylor-series expansion showing the additional advantage of a memory allocation not depending on the precision of calculation. Both algorithms are also highly parallelizable within the SIMT paradigm, and are thus suitable for GPGPU computing. In turn, we have benchmarked 4 NVIDIA GPUs and 3 quad-core Intel CPUs for a 2-particle system over lattices of increasing dimension, showing that the speedup provided by GPU computing, with respect to the OPENMP parallelization, lies in the range between 8x and (more than) 20x, depending on the frequency of post-processing. GPU-accelerated codes thus allow one to overcome concerns about the execution time, and make it possible simulations with many interacting particles on large lattices, with the only limit of the memory available on the device. Program summary Program Title: cuQuWa Licensing provisions: GNU General Public License, version 3 Program Files doi: http://dx.doi.org/10.17632/vjpnjgycdj.1 Programming language: CUDA C Nature of problem: Evolution of many-particle continuous-time quantum-walks on a multidimensional grid in a noisy environment. The submitted code is specialized for the simulation of 2-particle quantum-walks with periodic boundary conditions. Solution method: Taylor-series expansion of the evolution operator. The density-matrix is calculated by averaging multiple independent realizations of the system. External routines: cuBLAS, cuRAND Unusual features: Simulations are run exclusively on the graphic processing unit within the CUDA environment. An undocumented misbehavior in the random-number generation routine (cuRAND package) can corrupt the simulation of large systems, though no problems are reported for small and medium-size systems. Compiling the code with the -arch=sm_30 flag for compute capability 3.5 and above fixes this issue

In Silico Identification of MYB and bHLH Families Reveals Candidate Transcription Factors for Secondary Metabolic Pathways in Cannabis sativa L

Plant secondary metabolic pathways are finely regulated by the activity of transcription factors, among which members of the bHLH and MYB subfamilies play a main role. Cannabis sativa L. is a unique officinal plant species with over 600 synthesized phytochemicals having diverse scale-up industrial and pharmaceutical usage. Despite comprehensive knowledge of cannabinoids\u2019 metabolic pathways, very little is known about their regulation, while the literature on flavonoids\u2019 metabolic pathways is still scarce. In this study, we provide the first genome-wide analysis of bHLH and MYB families in C. sativa reference cultivar CBDRx and identification of candidate coding sequences for these transcription factors. Cannabis sativa bHLHs and MYBs were then classified into functional subfamilies through comparative phylogenetic analysis with A. thaliana transcription factors. Analyses of gene structure and motif distribution confirmed that CsbHLHs and CsMYBs belonging to the same evolutionary clade share common features at both gene and amino acidic level. Candidate regulatory genes for key metabolic pathways leading to flavonoid and cannabinoid synthesis in Cannabis were also retrieved. Furthermore, a candidate gene approach was used to identify structural enzyme-coding genes for flavonoid and cannabinoid synthesis. Taken as a whole, this work represents a valuable resource of candidate genes for further investigation of the C. sativa cannabinoid and flavonoid metabolic pathways for genomic studies and breeding programs

An open real-time photoacoustic imaging scanner

International audienc