Switching Quantum Dynamics for Fast Stabilization

Control strategies for dissipative preparation of target quantum states, both pure and mixed, and subspaces are obtained by switching between a set of available semigroup generators. We show that the class of problems of interest can be recast, from a control--theoretic perspective, into a switched-stabilization problem for linear dynamics. This is attained by a suitable affine transformation of the coherence-vector representation. In particular, we propose and compare stabilizing time-based and state-based switching rules for entangled state preparation, showing that the latter not only ensure faster convergence with respect to non-switching methods, but can designed so that they retain robustness with respect to initialization, as long as the target is a pure state or a subspace.Comment: 15 pages, 4 figure

Switching control of quantum dynamics

This work introduces a solution based on switching techniques for controlling open quantum systems. Assuming the existence of a shared steady state for a set of marginally stable generators of quantum Markov semigroups, we propose algorithms for asymptotically stabilizing such state by suitably switching between the dynamical generators

Modellistica e controllo del sistema "Ball and Hoop"

L'argomento di questa tesina e' la modellistica ed il controllo di un sistema fisico composto da un cilindro e da una pallina libera di rotolare al suo interno. Il movimento della pallina approssima abbastanza bene l'oscillazione di un liquido all'interno di un contenitore cilindrico libero di ruotare attorno al suo asse. Nella prima parte della tesina si deriva il modello ingresso-uscita del sistema, se ne analizzano stabilità asintotica e BIBO-stabilità e se ne ricavano i parametri della risposta in frequenza e della risposta al gradino. Nella seconda parte della tesina si studiano alcune soluzioni di controllo ottenute attraverso sintesi per tentativi e controllo PI

Density-oriented diagnostic data compression strategy for characterization of embedded memories in Automotive Systems-on-Chip

Embedded System-on-Chip (SoC) memory requirements in the Automotive industry are constantly growing. For this reason, memories occupy a significant part of Automotive SoC's die area, increasing the defect probability inside the embedded storage. Automotive SoC manufacturers need to deeply test their embedded memories as they are one of the significant contributors to the yield of their devices. The test effort increases for the characterization of new technologies and new families of devices that need to be characterized by the manufacturers. These tests generate a massive quantity of diagnostic information that is incredibly valuable for designers and technology experts. This diagnostic information can be analyzed to identify and correct possible weaknesses and misbehavior. The easiest way to collect memory diagnostic information consists of failure bitmaps in which each fault is saved as coordinates. This method is the simplest solution to implement. However, logging the coordinates of every fault may generate an unmanageable quantity of data. This problem is exacerbated when there is an on-chip limitation on the amount of data that can be saved or transmitted to the external world. This paper presents an optimized on-chip compression algorithm that allows to reduce the required on-chip memory to store diagnostic information during embedded memory testing. This solution allows the reconstruction of a failure bitmap, generating a topological representation of the density of the failings bits in the embedded on-chip memory. The proposed approach effectively reduces the used storage to a fraction with respect to the one used by the original failing bitmap. The algorithm uses a coordinates-based approach, in which the memory is logically divided into equally divided sectors. The small time overhead introduced by the algorithm is compensated by the ability to achieve optimal space utilization

Optimized diagnostic strategy for embedded memories of Automotive Systems-on-Chip

Embedded memories in Automotive Systems-on-Chip usually occupy a large die area portion. Consequently, their defectivity can strongly impact production yield for any automotive device. Along with the technology ramp-up phase and for statistical process control reasons during volume production, it is a good automotive industry practice to collect diagnostic information in addition to pure testing data. Designers and technology experts must receive accurate diagnostic results from failing devices to react to misbehavior by identifying and correcting the related issues at their source and drawing correct repair strategy conclusions. A commonly used approach resorts to the generation of failure bitmaps based on collecting all failing bits coordinates to be sent one by one to the tester. More efficiently, the encountered faults can be compacted or compressed in on-chip memory resources to be retrieved by the tester at the end of the memory test.This paper presents an on-chip method to compact diagnostic information during embedded memory testing. More specifically, the method is applied to diagnose embedded FLASH memories. This strategy permits the reconstruction of failure bitmaps without any loss, while compression approaches obtain an approximation. The proposed method uses a fraction of the memory requested by a coordinate-based bit mapping approach and is comparable to compression methods. At the cost of a moderate test time overhead, the proposed strategy permits dramatically increasing the number of devices that can be fully diagnosed without any bitmap reconstruction loss. Most failing devices in a real embedded FLASH production scenario were diagnosed after a single transfer from on-chip to the tester host computer

Novel lentiviral vectors for gene therapy of sickle cell disease combining gene addition and gene silencing strategies

Sickle cell disease (SCD) is due to a mutation in the β-globin gene causing production of the toxic sickle hemoglobin (HbS; α2βS2). Transplantation of autologous hematopoietic stem and progenitor cells (HSPCs) transduced with lentiviral vectors (LVs) expressing an anti-sickling β-globin (βAS) is a promising treatment; however, it is only partially effective, and patients still present elevated HbS levels. Here, we developed a bifunctional LV expressing βAS3-globin and an artificial microRNA (amiRNA) specifically downregulating βS-globin expression with the aim of reducing HbS levels and favoring βAS3 incorporation into Hb tetramers. Efficient transduction of SCD HSPCs by the bifunctional LV led to a substantial decrease of βS-globin transcripts in HSPC-derived erythroid cells, a significant reduction of HbS+ red cells, and effective correction of the sickling phenotype, outperforming βAS gene addition and BCL11A gene silencing strategies. The bifunctional LV showed a standard integration profile, and neither HSPC viability, engraftment, and multilineage differentiation nor the erythroid transcriptome and miRNAome were affected by the treatment, confirming the safety of this therapeutic strategy. In conclusion, the combination of gene addition and gene silencing strategies can improve the efficacy of current LV-based therapeutic approaches without increasing the mutagenic vector load, thus representing a novel treatment for SCD

FTLD‐TDP assemblies seed neoaggregates with subtype‐specific features via a prion‐like cascade

Morphologically distinct TDP-43 aggregates occur in clinically different FTLD-TDP subtypes, yet the mechanism of their emergence and contribution to clinical heterogeneity are poorly understood. Several lines of evidence suggest that pathological TDP-43 follows a prion-like cascade, but the molecular determinants of this process remain unknown. We use advanced microscopy techniques to compare the seeding properties of pathological FTLD-TDP-A and FTLD-TDP-C aggregates. Upon inoculation of patient-derived aggregates in cells, FTLD-TDP-A seeds amplify in a template-dependent fashion, triggering neoaggregation more efficiently than those extracted from FTLD-TDP-C patients, correlating with the respective disease progression rates. Neoaggregates are sequentially phosphorylated with N-to-C directionality and with subtype-specific timelines. The resulting FTLD-TDP-A neoaggregates are large and contain densely packed fibrils, reminiscent of the pure compacted fibrils present within cytoplasmic inclusions in postmortem brains. In contrast, FTLD-TDP-C dystrophic neurites show less dense fibrils mixed with cellular components, and their respective neoaggregates are small, amorphous protein accumulations. These cellular seeding models replicate aspects of the patient pathological diversity and will be a useful tool in the quest for subtype-specific therapeutics