Non-contact direct measurement of the magnetocaloric effect in thin samples

An experimental setup, based on a non-contact temperature sensor, is proposed to directly measure the magnetocaloric effect of samples few micrometers thick. The measurement of the adiabatic temperature change of foils and ribbons is fundamental to design innovative devices based on magnetocaloric thin materials or micro-structuring bulk samples. The reliability of the proposed setup is demonstrated by comparing the measurements performed on a bulk gadolinium sample with the results obtained by an experimental setup based on a Cernox bare chip thermoresistance and by in-field differential scanning calorimetry. We show that this technique can measure the adiabatic temperature variation on gadolinium sheets as thin as 27 µm. Heat transfer simulations are added to describe the capability of the presented technique

Spectral Gap Superposition States

This work introduces a novel NISQ-friendly procedure for estimating spectral gaps in quantum systems. By leveraging Adiabatic Thermalization, we are able to create the Spectral Gap Superposition state, a newly defined quantum state exhibiting observable fluctuations in time that allow for the accurate estimation of any energy gap. Our method is tested by estimating the energy gap between the ground and the first excited state for the 1D and 2D Ising model, the Hydrogen molecule H2 and Helium molecule He2. Despite limiting our circuit design to have at most 40 Trotter steps, our numerical experiments of both noiseless and noisy devices for the presented systems give relative errors in the order of $10^{-2}$ and $10^{-1}$. Further experiments on the IonQ Aria device lead to spectral gap estimations with a relative error of $10^{-2}$ for a 4-site Ising chain, demonstrating the validity of the procedure for NISQ devices and charting a path towards a new way of calculating energy gaps

Scale-Up of Magnetocaloric NiCoMnIn Heuslers by Powder Metallurgy for Room Temperature Magnetic Refrigeration

We present a new approach for a large-scale production of the rare-earth free NiCoMnIn Heusler alloy for room temperature magnetic refrigeration applications. This class of compounds has recently attracted attention, thanks to the large reversible isothermal entropy change (ΔSiso) and adiabatic temperature change (ΔTad) associated to a first-order magnetostructural phase transition. A large-scale production method, however, has not yet been proposed. For giant magnetocaloric materials and especially for Heusler compounds, the synthesis has a predominant role in tailoring the physical–chemical properties, due to the high sensitivity of the first-order transition characteristics on chemical composition and microstructure. Up to 250 g of the nominal composition Ni45.7Co4.2Mn36.6In13.3 alloy was prepared in a unique sample starting from industrial-grade powdered elements. The phase transition temperatures and magnetocaloric properties were investigated by magnetic and direct adiabatic temperature measurements and were found to be homogeneous in the whole sample. The mechanical stability of the produced alloy and its workability were investigated. A low-temperature thermal treatment was identified and showed promising results by reducing hysteresis and transition width

Experimental Demonstration of Impairment-Aware PCE for Multi-Bit-Rate WSONs

In emerging multi-bit-rate wavelength switched optical networks (WSONs), the coexistence of lightpaths operating at different bit-rates and modulation formats (e.g., based on amplitude and phase modulation) induces relevant traffic dependent detrimental effects that need to be considered during impairment-aware routing and wavelength assignment (IA-RWA). The considerable complexity of IA-RWA computation has driven the Internet Engineering Task Force (IETF) to propose specific path computation element (PCE) architectures in support of IA-RWA for WSONs. In this paper, following the IETF indications, we expand two PCE architectures and experimentally evaluate five different PCE architectural solutions, performing either combined or separated impairment estimation and RWA, with on-line and off-line computation of impairment validated paths, and with the possible utilization of a novel PCE Protocol (PCEP) extension. Results in terms of traffic engineering performance, path computation delivery time and amount of exchanged PCEP messages are reported and discussed to highlight the benefits and application scenarios of the considered PCE architectures

Segment routing for effective recovery and multi-domain traffic engineering

Segment routing is an emerging traffic engineering technique relying on Multi-protocol Label-Switched (MPLS) label stacking to steer traffic using the source-routing paradigm. Traffic flows are enforced through a given path by applying a specifically designed stack of labels (i.e., the segment list). Each packet is then forwarded along the shortest path toward the network element represented by the top label. Unlike traditional MPLS networks, segment routing maintains a per-flow state only at the ingress node; no signaling protocol is required to establish new flows or change the routing of active flows. Thus, control plane scalability is greatly improved. Several segment routing use cases have recently been proposed. As an example, it can be effectively used to dynamically steer traffic flows on paths characterized by low latency values. However, this may suffer from some potential issues. Indeed, deployed MPLS equipment typically supports a limited number of stacked labels. Therefore, it is important to define the proper procedures to minimize the required segment list depth. This work is focused on two relevant segment routing use cases: dynamic traffic recovery and traffic engineering in multi-domain networks. Indeed, in both use cases, the utilization of segment routing can significantly simplify the network operation with respect to traditional Internet Protocol (IP)/MPLS procedures. Thus, two original procedures based on segment routing are proposed for the aforementioned use cases. Both procedures are evaluated including a simulative analysis of the segment list depth. Moreover, an experimental demonstration is performed in a multi-layer test bed exploiting a software-defined-networking-based implementation of segment routing

Extending P4 in-band telemetry to user equipment for latency-and localization-aware autonomous networking with AI forecasting

In beyond-5G networks, detailed end-to-end monitoring of specific application traffic will be required along with the access-backhaul-cloud continuum to enable low latency service due to local edge steering. Current monitoring solutions are confined to specific network segments. In-band network telemetry (INT) technologies for software defined network (SDN) programmable data planes based on the P4 language are effective in the backhaul network segment, although limited to inter-switch latency; therefore, link latencies including wireless and optical segments are excluded from INT monitoring. Moreover, information such as user equipment (UE) geolocation would allow detailed mobility monitoring and improved cloud-edge steering policies. However, the synchronization between latency and location information, typically provided by different platforms, is hard to achieve with current monitoring systems. In this paper, P4-based INT is proposed to be thoroughly extended involving UE. The INT mechanism is designed to provide synchronized and accurate end-to-end latency and geolocation information, enabling decentralized steering policies, i.e., involving UE and selected switches, without SDN controller intervention. The proposal also includes an artificial-intelligence-assisted forecast system able to predict latency and geolocation in advance and trigger faster edge steering