Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “gradient boosting”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Skip-Connected Self-Recurrent Spiking Neural Networks with Joint Intrinsic Parameter and Synaptic Weight Training

As an important class of spiking neural networks (SNNs), recurrent spiking neural networks (RSNNs) possess great computational power and have been widely used for processing sequential data like audio and text. However, most RSNNs suffer from two problems. 1. Due to the lack of architectural guidance, random recurrent connectivity is often adopted, which does not guarantee good performance. 2. Training of RSNNs is in general challenging, bottlenecking achievable model accuracy. To address these problems, we propose a new type of RSNNs called Skip-Connected Self-Recurrent SNNs (ScSr-SNNs). Recurrence in ScSr-SNNs is introduced in a stereotyped manner by adding self-recurrent connections to spiking neurons. The SNNs with self-recurrent connections can realize recurrent behaviors similar to those of more complex RSNNs while the error gradients can be more straightforwardly calculated due to the mostly feedforward nature of the network. The network dynamics is enriched by skip connections between nonadjacent layers. Moreover, we propose a new backpropagation (BP) method called backpropagated intrinsic plasticity (BIP) to further boost the performance of ScSr-SNNs by training intrinsic model parameters. Unlike standard intrinsic plasticity rules that adjust the neuron's intrinsic parameters according to neuronal activity, the proposed BIP method optimizes intrinsic parameters based on the backpropagated error gradient of a well-defined global loss function in addition to synaptic weight training. Here, based on challenging speech, neuromorphic speech, and neuromorphic image datasets, the proposed ScSr-SNNs can boost performance by up to 2.85% compared with other types of RSNNs trained by state-of-the-art BP methods.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Unraveling the Effects of Melt–Mantle Interactions on the Gold Fertility of Magmas

The oxidation state of the Earth’s mantle and its partial melting products exert a key control on the behavior and distribution of sulfur and chalcophile and siderophile elements between the mantle and crust, underpinning models of ore deposit formation. Whether the oxidized nature of magmas is inherited from the asthenospheric mantle source or acquired during ascent and differentiation is vigorously debated, limiting our understanding of the mechanisms of extraction of sulfur and metals from the mantle. Here, we focused on the redox-sensitive behavior of sulfur in apatite crystallized from quenched alkaline basaltic melts preserved within a peridotite xenolith from the El Deseado Massif auriferous province in southern Patagonia. We took advantage of this unique setting to elucidate the redox evolution of melts during their ascent through the subcontinental lithospheric mantle (SCLM) and grasp the inner workings of the Earth’s mantle during gold metallogenesis. Our data reveal that an initially reduced silicate melt (ΔFMQ -2.2 to -1.2) was oxidized to ΔFMQ between 0 and 1.2 during percolation and interaction with the surrounding peridotite wall-rock (ΔFMQ 0 to +0.8). This process triggered changes in sulfur speciation and solubility in the silicate melt, boosting the potential of the melt to scavenge ore metals such as gold. We suggest that large redox gradients resulting from the interaction between ascending melts and the surrounding mantle can potentially modify the oxidation state of primitive melts and enhance their metallogenic fertility. Among other factors including an enriched metal source and favorable geodynamic conditions, redox gradients in the mantle may exert a first-order control on the global-scale localization of crustal provinces endowed with gold deposits.

58 GEOSCIENCES↗
DOE OSTI2026

JAXtronomy: A JAX port of lenstronomy

Gravitational lensing is a phenomenon where light bends around massive objects, resulting in distorted images seen by an observer. Studying gravitationally lensed systems provides insights into cosmology and astrophysics, including constraints of the expansion rate of the Universe and the distribution of dark matter. Thus, we introduce JAXtronomy, a re-implementation of the gravitational lensing software package lenstronomy (Birrer, 2021; Birrer & Amara, 2018) using JAX (Bradbury et al., 2018). JAX is a Python library that uses an accelerated linear algebra (XLA) compiler to improve the performance of computing software. Our core design principle of JAXtronomy is to maintain an identical API to that of lenstronomy. The main JAX features utilized in JAXtronomy are just-in-time compilation, which can lead to significant reductions in execution time, and automatic differentiation, which allows for the implementation of gradient-based algorithms that were previously impossible. Additionally, JAX allows code to be run on GPUs or parallelized across CPU cores, further boosting the performance of JAXtronomy.

astronomy↗
DOE OSTI2022

EQC: Ensembled Quantum Computing for Variational Quantum Algorithms

Variational quantum algorithms (VQA), which are comprised of a classical optimizer and a parameterized quantum circuit, emerges as one of the most promising approaches of harvesting quantum power in the noisy-intermediate-scale-quantum (NISQ) era. However, the deployment of VQAs on today's NISQ devices often faces considerable system noise and prohibitively slow training speeds. On the other hand, the expensive supporting sources and infrastructure make quantum computers extremely keen on high utilization. In this paper, we propose a novel way of thinking about a quantum backend: rather than relying on one physical device which tends to introduce platform-specific noise and bias, a quantum ensemble, which distributes quantum tasks across parallel devices, can serve as a virtualized quantum computer for offering reduced noise levels through an adaptive mixture and also provide significantly improved training speeds through parallelization. With this idea, we build a distributive VQA optimization framework called DVQA, serving as the first effort in adopting parallel quantum devices for cooperative VQA training. To further constraint noise and speed-up convergence, we design a model for individual NISQ devices concerning their properties and running conditions, and propose a weighting mechanism for regularizing the returned gradients. Extensive evaluations on 10 IBM-Q quantum devices using the VQE example show that the distributive VQA training framework can substantially boost the training speed by 10.5x on average (up to 86x and at least 5.2x) with improved training accuracy.

Stein, Samuel A.↗
NASA NTRS2013

NanoTHOR: Low-Cost Launch of Nanosatellites to Deep Space

The rapid development of high-performance nanosatellite platforms is enabling NASA and commercial ventures to consider performing missions to the asteroids, the Moon, and Mars at lower cost and on shorter timelines than traditional large spacecraft platforms. Currently, however, opportunities to launch secondary payloads to Earth escape are rare, and using chemical rockets to propel secondary payloads from LEO rideshares to escape is problematic due to the risks posed to primary payloads. The NanoTHOR effort has explored the technical feasibility and value proposition for using a simple momentum-exchange tether system to scavenge orbital energy from an upper stage in geostationary transfer orbit in order to boost nanosatellites to Earth escape. A NanoTHOR module will accomplish rapid transfer of a nanosatellite to an escape trajectory by deploying the nanosat at the end of a long, slender, high-strength tether and then using winching in the Earth's gravity!gradient to convert orbital angular momentum into rotational angular momentum. In the Phase I effort, we developed and simulated methods for controlling tether deployment and retraction to spin up a tether system, and these simulations demonstrated the feasibility of providing delta-Vs on the order of 800 m/s with a simple, low-mass tether system. Moreover, the NanoTHOR tether can act as a reusable in-space upper stage, boosting multiple nanosatellites on a single launch and doing so with a mass requirement lower than that of conventional rocket technologies. Serving as an escape-injection stage, NanoTHOR can enable a 6U CubeSat to deliver small payloads to Mars orbit, lunar orbit, and rendezvous with at least 110 of the known near-Earth asteroids. Evaluation of the technology readiness of the component technologies required for NanoTHOR indicate that the hardware required is all mid-TRL, and the lower-TRL controls and integration components can be advanced to mid-TRL with modest investment. By scavenging orbital energy from upper stages without any stored energy or propellant requirements, NanoTHOR permits deep-space nanosat missions to launch on rideshare opportunities, enabling NASA and commercial ventures to conduct affordable and frequent missions to explore deep space destinations.

Hoyt, Robert↗
DOE OSTI2021

Boosting the signal-to-noise of low-field MRI with deep learning image reconstruction

Recent years have seen a resurgence of interest in inexpensive low magnetic field (< 0.3 T) MRI systems mainly due to advances in magnet, coil and gradient set designs. Most of these advances have focused on improving hardware and signal acquisition strategies, and far less on the use of advanced image reconstruction methods to improve attainable image quality at low field. We describe here the use of our end-to-end deep neural network approach (AUTOMAP) to improve the image quality of highly noise-corrupted low-field MRI data. We compare the performance of this approach to two additional state-of-the-art denoising pipelines. We find that AUTOMAP improves image reconstruction of data acquired on two very different low-field MRI systems: human brain data acquired at 6.5 mT, and plant root data acquired at 47 mT, demonstrating SNR gains above Fourier reconstruction by factors of 1.5- to 4.5-fold, and 3-fold, respectively. In these applications, AUTOMAP outperformed two different contemporary image-based denoising algorithms, and suppressed noise-like spike artifacts in the reconstructed images. The impact of domain-specific training corpora on the reconstruction performance is discussed. The AUTOMAP approach to image reconstruction will enable significant image quality improvements at low-field, especially in highly noise-corrupted environments.

42 ENGINEERING↗
DOE OSTI2025

Photon acceleration of high-intensity vector vortex beams into the extreme ultraviolet

Extreme ultraviolet (XUV) light sources allow for the probing of bound electron dynamics on attosecond scales, interrogation of high-energy-density matter, and access to novel regimes of strong-field quantum electrodynamics. Despite the importance of these applications, coherent XUV sources remain relatively rare, and those that do exist are limited in their peak intensity and spatio-polarization structure. Here, we demonstrate that photon acceleration of an optical vector vortex pulse in the moving density gradient of an electron beam–driven plasma wave can produce a high-intensity, tunable-wavelength XUV pulse with the same vector vortex structure as the original pulse. Quasi-3D, boosted-frame particlein- cell simulations show the transition of optical vector vortex pulses with 800-nm wavelengths and intensities below 10 18 W/cm 2 to XUV vector vortex pulses with 36-nm wavelengths and intensities exceeding 10 20 W/cm 2 over a distance of 1.2 cm. The XUV pulses have sub-femtosecond durations and nearly flat phase fronts. The production of such high-quality, high-intensity XUV vector vortex pulses could expand the utility of XUV light as a diagnostic and driver of novel light–matter interactions.

43 PARTICLE ACCELERATORS↗
DOE OSTI2022

Gradient Doping in Sn–Pb Perovskites by Barium Ions for Efficient Single-Junction and Tandem Solar Cells

Narrow bandgap tin-lead (NBG Sn-Pb) perovskites generally have a high density of unintentional p-type self-doping, which reduces the charge carrier lifetimes, diffusion lengths and device efficiencies. Here, we demonstrate a p-n homojunction across the Sn-Pb perovskite resulted from a gradient doping by Ba 2+ . We report that 0.1 mol% Ba 2+ can effectively compensate the p-doping of Sn-Pb perovskites or even turns it to n-type without changing its bandgap. Ba 2+ cations are found to stay at the interstitial sites and work as shallow electron donor. In addition, Ba 2+ cations show a unique heterogeneous distribution in perovskite film. Most of the barium ions stay in the top 600 nanometer region of the perovskite films and turn it into weakly n-type, while the bottom portion of the film remains to be p-type. The gradient doping forms of a homojunction from top to bottom of the perovskite films with a built-in field that facilitates extraction of photogenerated carriers, resulting an increased carrier extraction length. Furthermore, this strategy enhanced the efficiency of Sn-Pb perovskite single-junction solar cells to over 21.0% and boosted the efficiencies of monolithic perovskite-perovskite tandem solar cells to 25.3% and 24.1%, for active areas of 5.9 mm2 and 0.94 cm 2 , respectively.

14 SOLAR ENERGY↗
NASA NTRS1972

Computerized optimal control system design for reusable and expendable boost vehicles.

An optimization technique has been developed which combines the practical features of hybrid simulation of the dynamic system under study with the systematic approach of modern control theory where a mathematically formulated design criterion is optimized by functional minimization. Standard hybrid computer optimization methods using high-speed repetitive simulations and gradient minimization schemes have been extended to obtain time-varying optimal gain schedules and reduce the sensitivity of the optimized system to parameter and disturbance uncertainties. In this approach the performance index is expressed in meaningful engineering terms that reflect the interactions among all major disciplines, structures, control/actuation system design, aerodynamics and performance. The basic optimization technique is developed and its application to current aerospace control problems including the space shuttle is presented in detail. In the discussion of the application, the controllers resulting from the technique are compared with controllers developed by conventional methods. The paper concludes with a review of the advantages and disadvantages of the technique and plans for future applications.

Connor, C. L.↗
DOE OSTI2023

Fluoride-Rich, Organic–Inorganic Gradient Interphase Enabled by Sacrificial Solvation Shells for Reversible Zinc Metal Batteries

Zinc metal batteries are strongly hindered by water corrosion, as solvated zinc ions would bring the active water molecules to the electrode/electrolyte interface constantly. Herein, we report a sacrificial solvation shell to repel active water molecules from the electrode/electrolyte interface and assist in forming a fluoride-rich, organic-inorganic gradient solid electrolyte interface (SEI) layer. Additionally, the simultaneous sacrificial process of methanol and Zn(CF 3 SO 3 ) 2 results in the gradient SEI layer with an organic-rich surface (CH 2 OC- and C 5 product) and an inorganic-rich (ZnF 2 ) bottom, which combines the merits of fast ion diffusion and high flexibility. As a result, the methanol additive enables corrosion-free zinc stripping/plating on copper foils for 300 cycles with an average coulombic efficiency of 99.5%, a record high cumulative plating capacity of 10 A h/cm 2 at 40 mA/cm 2 in Zn/Zn symmetrical batteries. More importantly, at an ultralow N/P ratio of 2, the practical VO 2 //20 mu m thick Zn plate full batteries with a high areal capacity of 4.7 mAh/cm 2 stably operate for over 250 cycles, establishing their promising application for grid-scale energy storage devices. Furthermore, directly utilizing the 20 μm thick Zn for the commercial-level areal capacity (4.7 mAh/cm 2 ) full zinc battery in our work would simplify the manufacturing process and boost the development of the commercial zinc battery for stationary storage.

25 ENERGY STORAGE↗
DOE OSTI2023

Scalable Manufacturing of Efficient Perovskite/Silicon Tandem Modules

Crystalline-Si (c-Si) technology produces excellent solar cells with conversion efficiencies of up to 26.7%—nearly their practical limit of 27%—and has been commercialized extensively to produce panels below $\$0.40$/W. Techno-economic analysis shows that module efficiency will continue to be a primary cost driver because of high balance-ofsystems costs, and there is no path to higher efficiencies with single-junction silicon cells. In this project, three research teams from University of North Carolina, Arizona State University and National Renewable National Laboratory worked together to develop perovskite-silicon tandem cells with a high throughput process which can handle 5000 wafers per hour, enabled by very low added CAPEX of ~$20k for a doctor-blade coater. This can potentially increase the module efficiency to 30% (with grid) with small increase of cost, which will drive down the cost of silicon modules to be at least 16% cheaper than present silicon PERC modules. We also explored the alternative narrow bandgap perovskites as silicon replacement for all perovskite tandem cells. This project has substantially advanced the progress of solution-process perovskitessilicon tandem solar cells and perovskite-perovskite tandem solar cells with many inventions and discoveries, evidenced by 18 publications and 6 invention disclosures. Several notable examples include 1) we developed the new idea of small pyramid in combination with solution grown perovskites and demonstrated record-efficiency of 28.5% for 1 cm2 on textured silicon bottom cells and 25.2% for 24 cm2 on chemically etched silicon bottom cells for perovskite-silicon tandem cells. 2) We developed perovskite ink that can coat perovskites onto texture silicon without voids;, and new device structure to enhance the yield of fabrication by reducing shunting 3) We identified the origin of open circuit voltage on mixed halide wide bandgap perovskites, and came with a solution for this problem, reducing the voltage loss to a record small value, which can potentially push the perovskite-silicon tandem cell efficiency to over 31%; 4) We have developed efficient alternative low bandgap semiconductors, i.e. gradient-doped Sn based perovskites by Ba ions, new oxide hole transport layers which increase the efficiency of perovskite/perovskite tandem cells reached record efficiency of 26.3%; 5) We developed bifacial perovskite/perovskite tandem cells by overcoming contacts issues and regaining light absorption, further boosting the equivalent efficiency to 29.3% under 1 sun illumination with 30% albedo light; 6) We developed the first all perovskite tandem module fabricated in air by discovery a combination of oxidization and reduction couples, yield an aperture efficiency of 21.6% for all perovskite mininodules, exceeding that of single junction perovskite minimodules. These discoveries not only accelerate the commercialization of perovskite-silicon tandem solar cells, but also provide guidance in designing other type of perovskite solar cell technologies.

14 SOLAR ENERGY↗
NASA NTRS1989

Boost-phase discrimination research activities

Theoretical research in two areas was performed. The aerothermodynamics research focused on the hard-body and rocket plume flows. Analytical real gas models to describe finite rate chemistry were developed and incorporated into the three-dimensional flow codes. New numerical algorithms capable of treating multi-species reacting gas equations and treating flows with large gradients were also developed. The computational chemistry research focused on the determination of spectral radiative intensity factors, transport properties and reaction rates. Ab initio solutions to the Schrodinger equation provided potential energy curves transition moments (radiative probabilities and strengths) and potential energy surfaces. These surfaces were then coupled with classical particle reactive trajectories to compute reaction cross-sections and rates.

Cooper, David M.↗
DOE OSTI2023

SwitchX : Gmin-Gmax Switching for Energy-efficient and Robust Implementation of Binarized Neural Networks on ReRAM Xbars

Memristive crossbars can efficiently implement Binarized Neural Networks (BNNs) wherein the weights are stored in high-resistance states (HRS) and low-resistance states (LRS) of the synapses. We propose SwitchX mapping of BNN weights onto ReRAM crossbars such that the impact of crossbar non-idealities, that lead to degradation in computational accuracy, are minimized. Essentially, SwitchX maps the binary weights in such a manner that a crossbar instance comprises of more HRS than LRS synapses. We find BNNs mapped onto crossbars with SwitchX to exhibit better robustness against adversarial attacks than the standard crossbar mapped BNNs, the baseline. Finally, we combine SwitchX with state-aware training (that further increases the feasibility of HRS states during weight mapping) to boost the robustness of a BNN on hardware. We find that this approach yields stronger defense against adversarial attacks than adversarial training, a state-of the-art software defense. We perform experiments on a VGG16 BNN with benchmark datasets (CIFAR-10, CIFAR-100 and TinyImagenet) and use Fast Gradient Sign Method (ϵ = 0.05 to 0.3) and Projected Gradient Descent (ϵ = $\frac{2}{255}$ to $\frac{32}{255}$, α = $\frac{2}{255}$) adversarial attacks. We show that SwitchX combined with state-aware training can yield upto ~35% improvements in clean accuracy and ~6–16% in adversarial accuracies against conventional BNNs. Furthermore, an important by-product of SwitchX mapping is increased crossbar power savings, owing to an increased proportion of HRS synapses, which is furthered with state-aware training. We obtain upto ~21–22% savings in crossbar power consumption for state-aware trained BNN mapped via SwitchX on 16 × 16 and 32 × 32 crossbars using the CIFAR-10 and CIFAR-100 datasets.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Climate-Driven Divergence in Biophysical and Economic Impacts of Agrivoltaics

Increasing global demands for food and energy necessitate innovative land-use solutions. Agrivoltaics, colocating solar photovoltaics with agriculture, shows promise, but its widespread adoption faces complex biophysical and economic trade-offs in a changing climate. Here, we develop an integrated biophysical-economic modeling framework to quantify how agrivoltaics affect biophysical and economic impacts across the Midwestern United States under both current and project climate conditions. We find strong regional divergences driven by climate gradients. In the humid eastern Midwest, solar panel shading limits photosynthesis, leading to reduced yields (maize -24%; soybean -16%) and lower farmers' profitability (maize -16%; soybean -2%) compared to conventional agriculture. Conversely, in the semiarid western region, shading alleviates heat and water stress, moderating yield reductions for maize (-12%) and even boosting soybean yields (+6%), resulting in improved economic returns (-6% for maize; +9% for soybean), for a scenario with 33% photovoltaic ground coverage ratio. Although agrivoltaics generate substantial electrical energy across all regions, high upfront installation costs challenge solar developers compared to standalone solar photovoltaics. However, our analysis identifies “win-win” opportunities where soybean-based agrivoltaics in the semiarid region produce economic benefits for both farmers and solar developers, highlighting the necessity for region-specific designs tailored to local climate conditions. Critically, future climate projections indicate eastward expansion of semiarid conditions, broadening areas where agrivoltaics can mitigate crop yield penalties (even boosting yield) and improve overall profitability, especially under high-emission scenarios. The results provide a mechanistic and economically integrated understanding essential for developing evidence-based and region-specific strategies to scale agrivoltaics in a changing climate.

14 SOLAR ENERGY↗
NASA NTRS1977

Seasat-A attitude control system

The Seasat-A attitude control system controls the attitude of the satellite system during injection into final circular orbit after Atlas boost, during orbit adjust and trim phases, and throughout the 3-year mission. Ascent and injection guidance and attitude control are provided by the Agena spacecraft with a gyrocompassed mass expulsion system. On-orbit attitude control functions are performed by a system that has its functional roots in the gravity-gradient momentum bias technology. The paper discusses hardware, control laws, and simulation results.

Weiss, R.↗
DOE OSTI2020

Carbon nanotube (CNT) metal composites exhibit greatly reduced radiation damage

Radiation damage of structural materials leads to mechanical property degradation, eventually inducing failure. Secondary-phase dispersoids or other radiation defect sinks are often added to materials to boost their radiation resistance. We demonstrate that a metal composite made by adding 1D carbon nanotubes (CNTs) to aluminum (Al) exhibits superior radiation resistance. In situ ion irradiation with transmission electron microscopy (TEM) and atomistic simulations together reveal the mechanisms of rapid defect migration to CNTs, facilitating defect recombination and enhancing radiation tolerance. The origin of this effect is an evolving stress gradient in the Al matrix resulting from CNT transformation under irradiation, and the stability of resulting carbides. Extreme value statistics of large defect behavior in our simulations highlight the role of CNTs in reducing accumulated damage. Furthermore, this approach to controlling defect migration represents a promising opportunity to enhance the radiation resistance of nuclear materials without detrimental effects.

36 MATERIALS SCIENCE↗
DOE OSTI2023

UVCGAN: UNet Vision Transformer cycle-consistent GAN for unpaired image-to-image translation

Unpaired image-to-image translation has broad applications in art, design, and scientific simulations. One early breakthrough was CycleGAN that emphasizes one-to-one mappings between two unpaired image domains via generative-adversarial networks (GAN) coupled with the cycle-consistency constraint, while more recent works promote one-to-many mapping to boost diversity of the translated images. Motivated by scientific simulation and one-to-one needs, this work revisits the classic CycleGAN framework and boosts its performance to outperform more contemporary models without relaxing the cycle-consistency constraint. To achieve this, we equip the generator with a Vision Transformer (ViT) and employ necessary training and regularization techniques. Compared to previous best-performing models, our model performs better and retains a strong correlation between the original and translated image. An accompanying ablation study shows that both the gradient penalty and self-supervised pre-training are crucial to the improvement. To promote reproducibility and open science, the source code, hyperparameter configurations, and pre-trained model are available at https: //github.com/LS4GAN/uvcgan.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Solid State Quantum Refrigeration Superconducting, Absorption and Measurement Based (Final Technical Report)

During this DOE grant, DE-SC0017890, in place for the past six years, all proposed research was carried out and published in peer-reviewed papers, as well as other projects that emerged during the research. In that effort the research team accomplished all proposed research, as well as many closely related research projects discovered and conceived of during the grant. These works included “Efficient Quantum Measurement Engines”, a work published in Physical Review Letters, giving a theory of quantum measurement-based engines, which uses quantum measurement as a resource. These engines are designed to efficiently convert energy from the stochastic quantum measurement process into useful work. Further publications include “Experimental Realization of a Quantum Dot Energy Harvester”, a joint theory and experimental work in collaboration with the group of Charles Smith in Cambridge, UK, as well as long time theoretical collaborators, Rafael Sánchez and Björn Sothmann. This work, featured as an Editor’s Suggestion in Physical Review Letters, realized an earlier theoretical proposal of ours, whereby two resonant tunneling quantum dots are connected to a central electronic cavity that is heated by a hot energy source. We also published “Superconducting Quantum Refrigerator: Breaking and Rejoining Cooper Pairs with Magnetic Field Cycles” a work done in collaboration with experimentalist Francesco Giazotto from ENS Pisa, Italy, which also resulted in a patent. This paper, published in Phys. Rev. Applied, advanced the concept of a cyclic fridge based on the normal/superconducting phase transition together with layered materials separated by tunnel junctions. We also completed the proposed research on a heat transistor, publishing “Thermal transistor and thermometer based on Coulomb-coupled conductors”, carried out as a collaboration between my group and theorists Splettstoesser (Lund U., Sweden), Sothmann (U. Duisburg-Essen, Germany), and Sánchez (U. Autónoma de Madrid, Spain). We carried out an analysis of a quantum coupled to a quantum point contact as a sensitive thermometer and heat transistor. We found the optimal statistical estimator for the temperature and compared it with experiments on the same type of devices. We also investigated autonomous quantum absorption refrigerators using quantum dots to cool by using a very hot thermal reservoir to drive heat between two other reservoirs. In the article “Quantifying the quantum heat contribution from a driven superconducting circuit”, we demonstrated that for a driven superconducting circuit, we showed heat flow provided by a hot source to the qubit can be switched on and off by varying external parameters, the frequency and the intensity of the driving. In the work “Stochastic thermodynamic cycles of a mesoscopic thermoelectric engine”, we reconsidered the autonomous thermoelectric heat engine in terms of underlying cycles. Rather than periodic behavior, the cycles were stochastic in nature. Nevertheless, by undertaking a graph theoretical analysis of the elementary transport processed, great quantitative and qualitative insight could be found. We also considered the quantum measurement process and showed that a quantum version of Maxwell’s demon could be related to the work extraction of a quantum system, closely related to arrow-of-time measures for quantum measurement, as described in our article “Thermodynamics of quantum measurement and Maxwell's demon's arrow of time”. This work was selected in Phys. Rev. A as an Editor’s Suggestion. A recent preprint titled “Cyclic Superconducting Quantum Refrigerators Using Guided Fluxon Propagation” accomplished an important piece of this grant: to propose a new kind of quantum refrigerator using the dynamics of fluxons in a type II superconductor. This invention envisioned a race-track type geometry where fluxons are confined. By applying a gradient of magnetic field together with electric current in a Corbino geometry, the circulating fluxons can actively cool a cold reservoir, realizing a new type of cyclic superconducting refrigerator. We also investigated the possibility of thermal control from different points of view. The application of quantum measurement to the system gives a new kind of control on the system of interest – we have pioneered this approach and shown that measurement can boost the thermal power of quantum engines as described in “Continuous measurement boosted adiabatic quantum thermal machines”. The ability to have heat flows on demand is an outstanding challenge, and we have provided new solutions to this problem in Thermal control across a chain of electronic nanocavities” for a chain of electron cavities using gating voltage control. The control methods using qubit/qubit coupling to create absorption fridges at their most fundamental level have also been developed.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗