Extreme Light Research Articles

Shining leaf chafers (Scarabaeidae: Rutelinae) and rhino beetles (Scarabaeidae: Dynastinae) of the Macau SAR, China

ABSTRACT Recent observations and a review of historical collections and literature have revealed that the diversity of scarab beetles in the Macau Special Administrative Region (SAR) of South China is substantially higher than previously reported. In this latest account, nine identified species are reported from this area in the Rutelinae subfamily, within the genera Adoretus, Anomala, Mimela, Pseudosinghala and Popillia. The subfamily Dynastinae appears to be locally represented by two species within the complex oriental genus Xylotrupes and the more widespread genus Alissonotum, respectively. With the exception of A. rubripes rubripes, P. mutans and X. siamensis, which are observed regularly and in reasonable numbers, all the other species are recorded very infrequently and often as single individuals. Thus, while the biodiversity potential of the region is relatively high, most species appear to be under threat of local extinction. This can be attributed mainly to the rapid habitat degradation, use of pesticides and extreme light pollution that are currently occurring in this SAR.

Classification of Breast Tumors Based on Histopathology Images Using Deep Features and Ensemble of Gradient Boosting Methods

Breast cancer is the most common cancer among women worldwide. Early-stage diagnosis of this disease can significantly improve the efficiency of treatment. Computer-Aided Diagnosis (CAD) Systems are adopted widely in this regard due to their reliability, accuracy and affordability. There are different imaging techniques for a breast cancer diagnosis; one of the most accurate ones is histopathology which is used in this paper. Deep feature transfer learning is used as the main idea of the proposed CAD system’s feature extractor. As such, the present paper works on sixteen different pre-trained networks with a focus on their classification phase, something that has not been studied enough. The Inception-ResNet-v2, which has both residual and inception networks profits together, has shown the best feature extraction capability in the case of breast cancer histopathology images among all tested Convolutional neural networks (CNNs). In the classification phase, the ensemble of Categorical Boosting (CatBoost), Extreme Gradient Boosting (XGBoost) and Light Gradient boosting Machine (LightGBM) has given the best average accuracy. The Breast Cancer Histopathological Image Classification (BreakHis) dataset helps evaluating the proposed method, i.e., IRv2-CXL, with the experimental results indicating that IRv2-CXL outperforms other state-of-the-art methods.

Continuous-variable quantum state tomography of photoelectrons

We propose a continuous variable quantum state tomography protocol of electrons which result from the ionization of atoms or molecules by the absorption of extreme ultraviolet light pulses. Our protocol is benchmarked against a direct calculation of the quantum state of photoelectrons ejected from helium and argon in the vicinity of a Fano resonance. In the latter case, we furthermore distill ion-photoelectron entanglement due to spin-orbit splitting. This opens routes toward the investigation of quantum coherence and entanglement properties on the ultrafast timescale.

Empirically testing the influence of light regime on diel activity patterns in a marine predator reveals complex interacting factors shaping behaviour

Abstract Diel cycles in marine predator diving behaviour centre around the light‐mediated diel vertical migration (DVM) of prey, and are considered critical for optimizing foraging and limiting competition across global seascapes. Yet, our understanding of predator diel behaviour is based primarily on examining relative depth usage between constant day/night cycles with no formal investigation of how varying light regimes interact with abiotic factors to shape diel activity. The extreme seasonal light regimes (midnight sun, polar night, day/night cycle) in the Arctic provide a unique natural experimental setting to empirically investigate the occurrence and intensity of diel behaviour in marine predators relative to changing light levels while concomitantly assessing interacting abiotic factors. Depth time series data from satellite‐linked tags deployed on six beluga whales (Delphinapterus leucas) for up to 12 months were used to quantify diel behaviour by calculating dissimilarity in time‐at‐depth between periods of low and high solar altitude on each day. Generalized additive mixed effects models were used to examine the influence of hours of daylight across extreme light cycles, coupled with bathymetry and sea ice concentration; focal diel patterns were further examined relative to the thermal structure of the water column. As predicted, belugas exhibited cathemerality during the midnight sun, and initiated diel behaviour with the onset of the fall day/night cycle, with a marked increase in its intensity with the progression to equal day/night length. Occurrence of diel patterns, however, was complex; ceasing in regions with seafloor depths <700 m, and occurring with greatest intensity when the water column was thermally homogeneous within the upper 150 m. Through empirical investigation, this study demonstrates that the onset of day/night light cycles and presumably associated prey DVM can modulate predator diel dive behaviour under certain circumstances, but highlights how the complex interaction of abiotic factors with light regime shape dynamic spatiotemporal patterns. These findings, building on a body of recent work, emphasize that the traditional view of the ubiquitous occurrence of diel behaviour tied to DVM at the base of the food web oversimplifies vertical predator–prey interactions, identifying the need for more structured investigation. Read the free Plain Language Summary for this article on the Journal blog.

Evidence of temperature control on mesopelagic fish and zooplankton communities at high latitudes

Across temperate and equatorial oceans, a diverse community of fish and zooplankton occupies the mesopelagic zone, where they are detectable as sound-scattering layers. At high latitudes, extreme day-night light cycles may limit the range of some species, while at lower latitudes communities are structured by dynamic ocean processes, such as temperature. Using acoustic and oceanographic measurements, we demonstrate that latitudinal changes in mesopelagic communities align with polar boundaries defined by deep ocean temperature gradients. At the transition to cold polar water masses we observe abrupt weakening and vertical dispersion of acoustic backscatter of mesopelagic organisms, thereby altering the structure of the mesopelagic zone. In the Canadian Arctic, we used biological sampling to show that this boundary is associated with a significant change in the pelagic fish community structure. Rapid ocean warming projected at mesopelagic depths could shift these boundaries with far-reaching effects on ecosystem function and biogeochemical cycles.

A charge-integration pixel readout chip features IR-drop effect mitigation by distributed LDOs

HYLITE (High dYnamic range free electron Laser Imaging deTEctor) is a charge-integration pixel detector readout chip, which is designed for SHINE (Shanghai high repetition rate XFEL and extreme light facility). The targeting pixel array of a full-size chip is 128 × 128 with a pixel pitch of 100 μm. The dynamic range of HYLITE is 1 ∼ 10000 photons at 12 keV, and the frame rate is 10 kHz. Large array size, high dynamic range, and high readout speed result in a big challenge of large power consumption and a significant IR-Drop effect. We implemented HYLITE0.2, which is the second prototype chip fabricated in a CMOS 130 nm process. Compared with HYLITE0.1, HYLITE0.2 aims to implement a full-function chip with a further shrunk pixel size, while the foreseen problem of severe IR-Drop effect of the full-size chip must be solved. To mitigate the IR-Drop effect, we proposed a novel architecture of distributed in-array Low-Dropout Regulators (LDOs). The pixel array consists of 16 × 24 pixels, and the full functionality was implemented within a pixel pitch of 100 μm. Measurements show that pixels powered by the proposed architecture work well, and the gain gradient of those pixels is 31.8% of the pixels powered by the conventional architecture.

The UDP-glycosyltransferase MtUGT84A1 regulates anthocyanin accumulation and plant growth via JA signaling in Medicago truncatula

Anthocyanins confer plants beneficial qualities and play protective roles under extreme light conditions. Here, we characterized a novel UDP flavonoid 3- O -glucosyltransferase ( UFGT ) gene MtUGT84A1 and demonstrated its involvement in anthocyanin accumulation and feedback inhibition of JA signaling in M. truncatula. The loss-of-function mutants mtugt84a1–1 and mtugt84a1–2 exhibited emerald hypocotyls and dwarfism. In vitro and in vivo assays revealed that MtUGT84A1 glycosylated peonidin and delphinidin at the 3-OH position. Constitutive expression of MtUGT84A1 rescued the phenotypic abnormalities of mtugt84a1 and significantly increased the anthocyanin content in the MtUGT84A1 -overexpression plants. Moreover, in mtugt84a1 , the contents of JA and JA isoleucine (JA-Ile) were doubled. The transcription level of MtMYC2 was significantly increased in mtugt84a1 , while decreased in the MtUGT84A1- overexpression plants, indicating MtUGT84A1 inhibits JA pathway. Under high-intensity light or MeJA treatment, MtUGT84A1 was elevated causing drastic accumulation of anthocyanins in the wildtype, but the pigments in mtugt84a1 did not alter clearly. Therefore, MtUGT84A1 not only functions as a structural gene for the final step of anthocyanin biosynthesis, but also regulates JA signaling by feedback inhibition. The findings unveil the critical roles of MtUGT84A1 -modulated glycosylation of anthocyanidins and shed light on the feedback regulatory loop of MtUGT84A1 in JA-mediated biosynthesis of natural products. • MtUGT84A1 encodes UDP flavonoid 3- O -glucosyltransferase. • MtUGT84A1 glucosylates peonidin and delphinidin at the 3-OH position. • MtUGT84A1 regulates JA signaling by feedback inhibition. • MtUGT84A1 modulates both anthocyanin accumulation and shoot growth of M. truncatula.

Prediction of low cardiac output syndrome in patients following cardiac surgery using machine learning.

BackgroundThis study aimed to develop machine learning models to predict Low Cardiac Output Syndrome (LCOS) in patients following cardiac surgery using machine learning algorithms.MethodsThe clinical data of cardiac surgery patients in Nanjing First Hospital between June 2019 and November 2020 were retrospectively extracted from the electronic medical records. Six conventional machine learning algorithms, including logistic regression, support vector machine, decision tree, random forest, extreme gradient boosting and light gradient boosting machine, were employed to construct the LCOS predictive models with all predictive features (full models) and selected predictive features (reduced models). The discrimination of these models was evaluated by the area under the receiver operating characteristic curve (AUC) and the calibration of the models was assessed by the calibration curve. Shapley Additive explanation (SHAP) and Local Interpretable Model-Agnostic Explanations (LIME) were used to interpret the predictive models.ResultsData from 1,585 patients [982 (62.0%) were male, aged 18 to 88, 212 (13.4%) with LCOS] were employed to train and validate the LCOS models. Among the full models, the RF model (AUC: 0.909, 95% CI: 0.875–0.943; Sensitivity: 0.849, 95% CI: 0.724–0.933; Specificity: 0.835, 95% CI: 0.796–0.869) and the XGB model (AUC: 0.897, 95% CI: 0.859–0.935; Sensitivity: 0.830, 95% CI: 0.702–0.919; Specificity: 0.809, 95% CI: 0.768–0.845) exhibited well predictive power for LCOS. Eleven predictive features including left ventricular ejection fraction (LVEF), first post-operative blood lactate (Lac), left ventricular diastolic diameter (LVDd), cumulative time of mean artery blood pressure (MABP) lower than 65 mmHg (MABP < 65 time), hypertension history, platelets level (PLT), age, blood creatinine (Cr), total area under curve above threshold central venous pressure (CVP) 12 mmHg and 16 mmHg, and blood loss during operation were used to build the reduced models. Among the reduced models, RF model (AUC: 0.895, 95% CI: 0.857–0.933; Sensitivity: 0.830, 95% CI: 0.702–0.919; Specificity: 0.806, 95% CI: 0.765–0.843) revealed the best performance. SHAP and LIME plot showed that LVEF, Lac, LVDd and MABP < 65 time significantly contributed to the prediction model.ConclusionIn this study, we successfully developed several machine learning models to predict LCOS after surgery, which may avail to risk stratification, early detection and management of LCOS after cardiac surgery.

Electric field enhancement by a hybrid dielectric-metal nanoantenna with a toroidal dipole contribution.

Plasmonic nanocavities enable extreme light-matter interactions by pushing light down to the nanoscale. The numerical simulation is carried out systematically on the slotted Φ-shaped Si disk system with the super-dipole mode based on the analysis of the scattering strength of electric and toroidal dipoles. New blocks are introduced to the zero-field strength region of a slotted Si disk system as a function of the field enhancement factors. The far-field scattering characteristics and near-field electromagnetic field distributions are investigated by a multipole decomposition analysis to elucidate the intrinsic causes of the field enhancement. In the hybrid metal-dielectric nanoantenna, the Φ-shaped Si structure is prepared by superimposing Au nanoantennas for further field enhancement. In addition, the effects of the placement of an electric dipole emitter on the Purcell factor are derived. The geometric volume of the system is increased, and the electric field strength is improved, leading to an electric field increase of ∼30. Coupling between the super-dipole mode of the dielectric nanostructure and plasmonic modes of the metallic nanoantenna produces an enhancement as large as 16 times. Our results reveal a greatly enhanced super-dipole mode by electromagnetic coupling in composite structures, which will play a significant role in enhanced nonlinear photonics, near-field enhancement spectroscopy, and strong photon-exciton coupling.

Engineering the Dispersion of Surface Plasmon Polariton/Epsilon‐Near‐Zero Modes through Modal Separation and Optical Confinement

Doped cadmium oxide (CdO) films support tunable, low‐loss surface plasmon polaritons (SPPs) and epsilon‐near‐zero (ENZ) modes throughout the mid‐infrared. Prior work demonstrated that polaritonic strong coupling could be realized in bilayer films of CdO supporting adjacent SPP and ENZ modes. The hybridized SPP‐ENZ dispersion displays a prominent anti‐crossing with an amplitude dependent on the spectral and spatial overlap of the modes. Here, we leverage the low carrier diffusivity, in concert with the broad tunability of the plasma frequency in CdO to control the SPP‐ENZ dispersion within monolithic, multilayer CdO structures featuring dielectric, unintentionally doped CdO coatings or spacer layers. In the case of the former, the coating induces further compression of the polaritonic fields, altering the dielectric environment. In contrast, when incorporated as a spacer layer, the spatial overlap of the constituent polaritonic near‐fields is reduced. In all cases, the anti‐crossing behavior of the hybrid SPP‐ENZ modes is maintained, thus inheriting the extreme light confinement of the ENZ mode and extended propagation length of the SPPs. Through simultaneous control over the SPP‐ENZ coupling strength and group velocities, significant tunability over the SPP‐ENZ dispersion is demonstrated, enabling applications such as in‐plane waveguiding, tailored thermal emission, and tunable near‐field heat transfer.

Effect of oxygen content on structural and optoelectronic properties of ZnS1- xOx alloy in the wurtzite structure

The tunability of the physical parameters of ZnS1-xOx alloy in the wurtzite phase makes this semiconductor potentially useful as an absorbent layer and antireflection coating. A deviation of the bulk modulus from Vegard's law is observed in ZnS1-xOx alloy. Based on the density functional theory as implemented in the Wien2k code under the virtual crystal approximation, the lattice constant, bulk modulus and band gap have been calculated with both GGA and the modified Becke-Johnson potential (mBJ). The ternary ZnS1-xOx alloy becomes more stable with the increase in the oxygen content x. The in-plane and out-of-plane imaginary components of the dielectric function attain non-zero magnitude at energy identical to the fundamental band gap value. The intense peaks in the in-plane and out-of-plane dielectric function located at 6.5 eV and 7.75 eV suggest inter band transition, and no photon emission in this material. ZnS1-xOx absorbs ultraviolet light in the range 4 eV–10 eV, which validates its candidature for optical and photovoltaic devices. The refractive index is more important when photons move through the material and when bonds between atoms are covalent. The anisotropic optical parameters, the fundamental band gap range (2.7–3.7 eV) and absorption of extreme ultraviolet light make ZnS1-xOx alloy as windows, lenses and absorber material.

On-the-fly investigation of XUV excited large molecular ions using a high harmonic generation light source

We present experiments where extreme ultraviolet femtosecond light pulses are used to photoexcite large molecular ions at high internal energy. This is done by combining an electrospray ionization source and a mass spectrometer with a pulsed light source based on high harmonic generation. This allows one to study the interaction between high energy photons and mass selected ions in conditions that are accessible on large-scale facilities. We show that even without an ion trapping device, systems as large as a protein can be studied. We observe light induced dissociative ionization and proton migration in model systems such as reserpine, insulin and cytochrome c. These results offer new perspectives to perform time-resolved experiments with ultrashort pulses at the heart of the emerging field of attosecond chemistry.

Unidirectional bound states in the continuum in Weyl semimetal nanostructures

Recently studied bound states in the continuum (BICs) enable perfect localization of light and enhance light–matter interactions although systems are optically open. They have found applications in numerous areas, including optical nonlinearity, light emitters, and nano-sensors. However, their unidirectional nature in nonreciprocal devices is still elusive because such trapping states are easily destroyed when the symmetry of an optical system is broken. Herein, we propose nonreciprocal and dynamically tunable BICs for unidirectional confinement of light and symmetry-protected BICs at Γ -point by introducing antiparallel magnetism into the optical system. We demonstrate that such BICs can be achieved by using topological magnetic Weyl semimetals near zero-index frequency without any structural asymmetry, and are largely tunable via modifying the Fermi level. Our results reveal a regime of extreme light manipulation and interaction with emerging quantum materials for various practical applications.

An Ensemble-Based Machine Learning Model for Estimation of Subsurface Thermal Structure in the South China Sea

Reconstructing the vertical structures of the ocean from sea surface information is of great importance for ocean and climate studies. In this study, an ensemble machine learning (Ens-ML) model is proposed to retrieve ocean subsurface thermal structure (OSTS) by using satellite-derived sea surface data and Argo data in the South China Sea (SCS). The input data include sea surface height (SSH), sea surface temperature (SST), sea surface salinity (SSS), sea surface wind (SSW), and geographic information (including longitude and latitude). We select three stable machine learning models, namely, extreme gradient boosting (XGBoost), RandomForest and light gradient boosting machine (LightGBM) as our benchmark models, and then use an artificial neural network (ANN) technique to combine outputs from the three individual models. The proposed Ens-ML model using sea surface data only by SSH, SST, SSS, and SSW performs less satisfactorily than that considering the contribution of geographical information, indicating that the geographical information is essential to estimate the OSTS accurately. The estimated OSTS from the Ens-ML model are compared with Argo data. The results show that the proposed Ens-ML model can accurately estimate the OSTS (upper 1000 m) in the SCS, which is relatively more accurate and precise than the individual models. The performance of the Ens-ML model also varies with season, and better estimation is obtained in winter, which is probably due to stronger mixing and weaker stratification. This study shows the great potential and advantage of the multi-model ensemble of machine learning algorithm for the ocean’s interior information retrieving, showing great potential in expanding the scope of ocean observations.

Liquid nitrogen cooling, control and monitoring system for the ELIADE HPGe clover detectors at ELI-NP

We present a liquid nitrogen (LN2) cooling station for the high-purity germanium (HPGe) segmented clover detectors of the ELI-NP Array of DEtectors (ELIADE) spectrometer, including its associated filling control and monitoring systems, all designed and built in-house at Extreme Light Infrastructure - Nuclear Physics (ELI-NP), Măgurele, Romania. The automated LN2 filling process is controlled by a CompactRIO (cRIO) system from National Instruments through a custom LabVIEW software used for monitoring both the internal germanium crystal temperatures as well as the temperatures of external Pt100 sensors (used for detection of overflow of LN2 from detectors during a filling process). The detectors are filled with LN2 by opening their individual filling valves (which are mounted on the cooling station) and the process is automatically stopped once an overflow condition is fulfilled by the corresponding external Pt100 sensor located downstream. A twelve-hour cycle is used to periodically fill all of the detector dewars and keep their germanium crystals cool at all times. The associated Graphic User Interface (GUI), Command Line Interface (CLI) and Text User Interface (TUI) are used for both controlling and monitoring the above mentioned process. Alert and warning email messages were also enabled via the cRIO system so that users can be alerted in real-time in the event of any cooling malfunction. In this way, any issues related to the cyclic filling procedure, as well as any abnormal observations regarding the germanium crystal temperatures can be quickly and efficiently addressed before the detectors have a chance to warm back up to room temperature. Temperature data of all the Pt100 sensors corresponding to detectors as well as to the solenoid valves are made available in an influx database by the cRIO control system. The web application Grafana access the database and plots them in real-time for online monitoring.

Liquid-cooled modular gas cell system for high-order harmonic generation using high average power laser systems.

We present the design and implementation of a new, modular gas target suitable for high-order harmonic generation using high average power lasers. To ensure thermal stability in this high heat load environment, we implement an appropriate liquid cooling system. The system can be used in multiple-cell configurations, allowing us to control the cell length and aperture size. The cell design was optimized with heat and flow simulations for thermal characteristics, vacuum compatibility, and generation medium properties. Finally, the cell system was experimentally validated by conducting high-order harmonic generation measurements using the 100kHz high average power HR-1 laser system at the Extreme Light Infrastructure Attosecond Light Pulse Source (ELI ALPS) facility. Such a robust, versatile, and stackable gas cell arrangement can easily be adapted to different experimental geometries in both table-top laboratory systems and user-oriented facilities, such as ELI ALPS.

ЭНДЕМИЧЕСКИЙ ЗОБ В РЕСПУБЛИКЕ САХА (ЯКУТИЯ)

The authors conducted a study of the prevalence and features of the course of endemic goiter in the Republic of Sakha (Yakutia). According to the classification, the area is considered endemic for goiter if a goiter-altered gland is observed in more than 10 % of the population. There are light, medium and severe goiter endemias. It was revealed that, on average, the prevalence of endemic goiter in the republic is 28 %, which corresponds to the average severity of endemia, but the level of endemia is heterogeneous: there are areas of Yakutia with a severe degree. The peculiarities of endemic goiter in the Republic of Sakha (Yakutia) should also include the predominance of euthyroid forms (92.8 %) and a high (up to 57.3 %) proportion of thyroid nodules in areas with severe endemia. An important feature is the significant frequency of histologically confirmed thyroid malignancies: 8.2 % of the number of operated. In addition to the lack of iodine and a number of other trace elements in the environment, the body as a whole and, in particular, the thyroid is affected by a number of specific features of Yakutia: extreme temperature and light conditions, pronounced seasonality of climate, anomalies of geomagnetic fields. The predominance of nodular formations of the thyroid gland in endemic areas, especially polynodose (up to 86.9 %), is one of the prerequisites for the more frequent development of cervical-thoracic goiter. Cervical-thoracic goiter requires surgical intervention due to manifestations of compression of the mediastinal organs or the threat of their development. Unlike cervical goiter, with cervical-thoracic goiter, there is a problem of differential diagnosis with other intra-thoracic formations.

Optimization and stability analysis of the cascaded EEHG-HGHG free-electron laser

X-ray free-electron lasers (XFELs) are powerful tools to explore and study nature for achieving remarkable advances. Generally, seeded FELs are ideal sources for supplying fully coherent soft x-ray pulses. Benefiting from the high-frequency up-conversion efficiency, the cascading configuration with echo-enabled harmonic generation (EEHG) and high-gain harmonic generation (HGHG) holds promising prospects for generating fully coherent radiation at 1 nm wavelength. In this paper, we design and optimize EEHG-HGHG configuration using parameters of Shanghai High-Repetition-Rate XFEL and Extreme Light Facility. In addition, we systematically analyze the effect of relative timing jitter on the output FEL performance based on various start-to-end electron beams. The intensive numerical simulations show that the cascaded EEHG-HGHG scheme can achieve 1 nm FEL pulses with peak power up to 15 GW. Further sensitivity analysis indicates that the relative timing jitter between the electron beam and seed laser has a significant impact on the FEL performance. The RMS timing jitter of 3 fs can lead to the final output pulse energy fluctuations of 29%.

Interference of two-photon transitions induced by XUV light

The relative phase of first ( ω 1 ) and third harmonics ( ω 3 ) extreme ultraviolet light pulses was varied to control the population of the 2 s 2 state in helium through the interference of ω 1 + ω 1 and ω 3 − ω 1 two-photon excitation paths. The population was monitored by observing the total electron yield due to the 2 s 2 autoionization decay. Maximum yield occurs when the relative phase of the two harmonics matches the phase difference of complex atomic amplitudes governing the two excitation paths. The calculated trend of atomic phase differences agrees well with the measured data in the spectral region of the resonance, provided that time-reversed − ω 1 + ω 3 path is also taken into account. These results open the way to accessing phase differences of two-photon ionization paths involving energetically distant intermediate states and to perform interferometry in the extreme ultraviolet range by monitoring final state populations.

Optimal thermal actuation for mirror temperature control

The latest generation wafer scanners use extreme ultraviolet light to project a pattern of electronic connections onto a silicon wafer. A significant part of the projection light is absorbed by the mirrors in the projection system. This causes the mirrors to heat up and expand, which leads to a significant reduction in the imaging quality of the wafer scanner. The imaging quality can be improved by applying an additional actuation heat load to the mirrors. Because the wafer scanner can be used with a large number of different illumination settings (which lead to different load cases) and the number of thermal actuators is limited, designing an effective actuation heater layout is an important but nontrivial task. To assist this design process, this paper proposes a computational framework to optimize a small number of spatial actuation heat load shapes with their corresponding intensities for a large number of load cases. It is guaranteed that the obtained actuation heat load shapes can keep the steady-state temperature in the optical surface of the mirror sufficiently close to a desired temperature in all considered load cases. The proposed computational framework is applied to a representative three-dimensional finite element model of a mirror. The obtained actuation heat load shapes and their corresponding intensities provide insights for the design of a thermal actuation layout for mirror heating.