arXiv subjects

Daniel May

Publications and source records attributed to Daniel May.

12 recordsLinked to original sources

arXiv2026

Shocks, Winds, and a Torus: The Large Binocular Telescope Interferometer (LBTI) Resolves the Active Nucleus of NGC 4151

We present mid-infrared (MIR) observations of the Seyfert 1 galaxy NGC 4151 using the Large Binocular Telescope Interferometer (LBTI). We took open-loop Fizeau images with 66-104 mas (5.8-9.1 pc) resolution in the N-band (at $8.7$ and $10.5~\mu m$), using the full resolution of the LBTI -- equivalent to that of a 28.8 m telescope. These images were complemented by AO imaging in the LM-bands ($3.7$ and $4.8~\mu m$), with 50-62 mas (4.4-5.4 pc) resolution. These images bridge the scales between previous Very Large Telescope Interferometer (VLTI)/MIDI and VLT/VISIR data, delivering ELT-like imaging resolution in the N-band. We resolve a dusty torus, (diameter 32 pc, PA$=125^{\circ}$), and detect dusty clouds within the narrow line region. Matching the resolution across four bands, we measured spatially-resolved SEDs of the central $\sim 100$ pc. Modified blackbody fitting revealed dust temperature and extinction profiles, indicating both heating from the accretion disk and additional shock heating due to the radio jet. The spatial coincidence of ionized emission (e.g., [Fe II] and [O III]), extended MIR structures, and radio features further supports the interpretation of shock heating. Comparison with NGC 1068 tests the Unified Model of Active Galactic Nuclei (Unified Model of AGN): Structures are similar, despite differences in orientation and Eddington ratio. NGC 4151's torus is smaller than NGC 1068's following a $r\propto L^{0.5}$ scaling. These thirty-meter-telescope class observations of NGC 4151 and NGC 1068 highlight the need to revise MIR radiative transfer models of AGN to account for jet-related heating.

astro-ph.GA↗

arXiv2025

Feeding frenzy in the mighty black holes: what we could learn from them?

Eddington ratio is a paramount parameter governing the accretion history and life cycles of Active Galactic Nuclei (AGNs). This short review presents a multi-faceted view of the importance of the Eddington ratio spanning varied AGN studies. We find that the Eddington ratio is crucial for standardizing the Radius-Luminosity (R-L) relation - a necessary step for employing quasars (QSOs) as standardizable cosmological probes to help clarify the standing of the Hubble tension. In this data-driven era, we consolidated disparate aspects by developing novel relations borne out of large datasets, such as the robust, nearly universal anti-correlation between fractional variability and Eddington ratio derived from Zwicky Transient Facility (ZTF) data, which is vital for interpreting forthcoming high-cadence surveys like Rubin Observatory's LSST. Addressing the conundrum where JWST results suggest an overabundance of massive high-redshift black holes, we demonstrate that local AGNs offer clarification: Changing-Look AGNs (CLAGNs), driven by rapid Eddington ratio shifts, cluster in the low-accretion regime, a rate independently confirmed by our integral field spectroscopy and photoionization modeling of a well-known Seyfert 2 galaxy, rich in high-ionization, forbidden, coronal lines. Conversely, for the high-redshift, high-luminosity population where traditional reverberation mapping (RM) is highly impractical, photometric reverberation mapping (PRM) offers a rapid alternative to constrain accretion disk sizes, enabling efficient estimates of black hole masses and Eddington ratios. Finally, we developed tailored semi-empirical spectral energy distributions (SEDs) for extremely high-accretion quasars, successfully validating their characteristic extreme physical conditions.

astro-ph.GA↗

arXiv2024

DynaSplit: A Hardware-Software Co-Design Framework for Energy-Aware Inference on Edge

The deployment of ML models on edge devices is challenged by limited computational resources and energy availability. While split computing enables the decomposition of large neural networks (NNs) and allows partial computation on both edge and cloud devices, identifying the most suitable split layer and hardware configurations is a non-trivial task. This process is in fact hindered by the large configuration space, the non-linear dependencies between software and hardware parameters, the heterogeneous hardware and energy characteristics, and the dynamic workload conditions. To overcome this challenge, we propose DynaSplit, a two-phase framework that dynamically configures parameters across both software (i.e., split layer) and hardware (e.g., accelerator usage, CPU frequency). During the Offline Phase, we solve a multi-objective optimization problem with a meta-heuristic approach to discover optimal settings. During the Online Phase, a scheduling algorithm identifies the most suitable settings for an incoming inference request and configures the system accordingly. We evaluate DynaSplit using popular pre-trained NNs on a real-world testbed. Experimental results show a reduction in energy consumption up to 72% compared to cloud-only computation, while meeting ~90% of user request's latency threshold compared to baselines.

cs.DC↗

arXiv2024

Dust beyond the torus: Revealing the mid-infrared heart of local Seyfert ESO 428-G14 with JWST/MIRI

Polar dust has been discovered in a number of local Active Galactic Nuclei (AGN), with radiation-driven torus models predicting a wind to be its main driver. However, little is known about its characteristics, spatial extent, or connection to the larger scale outflows. We present the first JWST/MIRI study aimed at imaging polar dust by zooming onto the centre of ESO 428-G14, part of the Galaxy Activity, Torus, and Outflow Survey (GATOS) survey of local AGN. We detect extended mid-infrared (MIR) emission within 200 pc from the nucleus. This polar structure is co-linear with a radio jet and lies perpendicular to a molecular gas lane that feeds and obscures the nucleus. Its morphology bears a striking resemblance to that of gas ionised by the AGN in the narrow-line region. We demonstrate that part of this spatial correspondence is due to contamination within the JWST filter bands from strong emission lines. Correcting for the contamination, we find the morphology of the dust continuum to be more compact, though still clearly extended out to ~ 100 pc. We estimate the emitting dust has a temperature of ~ 120 K. Using simple models, we find that the heating of small dust grains by the radiation from the central AGN and/or radiative jet-induced shocks is responsible for the extended MIR emission. Radiation-driven dusty winds from the torus is unlikely to be important. This has important implications for scales to which AGN winds can carry dust and dense gas out into their host galaxies.

astro-ph.GA↗

arXiv2024

Decentralized Coordination of Distributed Energy Resources through Local Energy Markets and Deep Reinforcement Learning

As distributed energy resources (DERs) grow, the electricity grid faces increased net load variability at the grid edge, impacting operability and reliability. Transactive energy, facilitated through local energy markets, offers a decentralized, indirect demand response solution, with model-free control techniques, such as deep reinforcement learning (DRL), enabling automated, decentralized participation. However, existing studies largely overlook community-level net load variability, focusing instead on socioeconomic metrics. This study addresses this gap by using DRL agents to automate end-user participation in a local energy market (ALEX), where agents act independently to minimize individual energy bills. Results reveal a strong link between bill reduction and decreased net load variability, assessed across metrics such as ramping rate, load factor, and peak demand over various time horizons. Using a no-control baseline, DRL agents are benchmarked against a near-optimal dynamic programming approach. The dynamic programming benchmark achieves reductions of 22.05 percent, 83.92 percent, and 24.09 percent in daily import, export, and peak demand, respectively, while the DRL agents show comparable or superior results with reductions of 21.93 percent, 84.46 percent, and 27.02 percent. This study demonstrates the effectiveness of DRL in decentralized grid management, highlighting its scalability and near-optimal performance in reducing net load variability within community-driven energy markets.

eess.SY↗

arXiv2020

Forecasting Photovoltaic Power Production using a Deep Learning Sequence to Sequence Model with Attention

Rising penetration levels of (residential) photovoltaic (PV) power as distributed energy resource pose a number of challenges to the electricity infrastructure. High quality, general tools to provide accurate forecasts of power production are urgently needed. In this article, we propose a supervised deep learning model for end-to-end forecasting of PV power production. The proposed model is based on two seminal concepts that led to significant performance improvements of deep learning approaches in other sequence-related fields, but not yet in the area of time series prediction: the sequence to sequence architecture and attention mechanism as a context generator. The proposed model leverages numerical weather predictions and high-resolution historical measurements to forecast a binned probability distribution over the prognostic time intervals, rather than the expected values of the prognostic variable. This design offers significant performance improvements compared to common baseline approaches, such as fully connected neural networks and one-block long short-term memory architectures. Using normalized root mean square error based forecast skill score as a performance indicator, the proposed approach is compared to other models. The results show that the new design performs at or above the current state of the art of PV power forecasting.

cs.LG↗

arXiv2019

Analytical and Numerical study of the out-of-equilibrium current through a helical edge coupled to a magnetic impurity

We study the conductance of a time-reversal symmetric helical electronic edge coupled antiferromagnetically to a magnetic impurity, employing analytical and numerical approaches. The impurity can reduce the perfect conductance $G_0$ of a noninteracting helical edge by generating a backscattered current. The backscattered steady-state current tends to vanish below the Kondo temperature $T_K$ for time-reversal symmetric setups. We show that the central role in maintaining the perfect conductance is played by a global $U(1)$ symmetry. This symmetry can be broken by an anisotropic exchange coupling of the helical modes to the local impurity. Such anisotropy, in general, dynamically vanishes during the renormalization group (RG) flow to the strong coupling limit at low-temperatures. The role of the anisotropic exchange coupling is further studied using the time-dependent Numerical Renormalization Group (TD-NRG) method, uniquely suitable for calculating out-of-equilibrium observables of strongly correlated setups. We investigate the role of finite bias voltage and temperature in cutting the RG flow before the isotropic strong-coupling fixed point is reached, extract the relevant energy scales and the manner in which the crossover from the weakly interacting regime to the strong-coupling backscattering-free screened regime is manifested. Most notably, we find that at low temperatures the conductance of the backscattering current follows a power-law behavior $G\sim (T/T_K)^2$, which we understand as a strong nonlinear effect due to time-reversal symmetry breaking by the finite-bias.

cond-mat.str-el↗

arXiv2018

Powerful mechanical-driven outflows in the central parsecs of the Low-Luminosity Active Galactic Nucleus ESO428-G14

Low-Luminosity Active Galactic Nuclei (LLAGN) are characterized for low radiative efficiency, much less than one percent of their Eddington limit. Nevertheless, their main energy release may be mechanical, opposite to powerful AGN classes like Seyfert and Quasars. This work reports on the jet-driven mechanical energy and the corresponding mass outflow deposited by the jet in the central 170~parsecs of the nearby LLAGN ESO428-G14. The jet kinetic output is traced through the coronal line [Si vi] $\lambda$19641 \AA. It is shown that its radial extension, up to hundreds of parsecs, requires a combination of photoionization by the central source and shock excitation as its origin. From the energetics of the ionized gas it is found that the mass outflow rate of the coronal gas is in the range from 3$-8$~M$\odot$~yr$^{-1}$, comparable to those estimated from H I gas at kiloparsec scales in powerful radio galaxies.

astro-ph.GA↗

arXiv2018

Microfabricated sensor platform with through-glass vias for bidirectional 3-omega thermal characterization of solid and liquid samples

A novel microfabricated, all-electrical measurement platform is presented for a direct, accurate and rapid determination of the thermal conductivity and diffusivity of liquid and solid materials. The measurement approach is based on the bidirectional 3-omega method. The platform is composed of glass substrates on which sensor structures and a very thin dielectric nanolaminate passivation layer are fabricated. Using through-glass vias for contacting the sensors from the chip back side leaves the top side of the platform free for deposition, manipulation and optical inspection of the sample during 3-omega measurements. The thin passivation layer, which is deposited by atomic layer deposition on the platform surface, provides superior chemical resistance and allows for the measurement of electrically conductive samples, while maintaining the conditions for a simple thermal analysis. We demonstrate the measurement of thermal conductivities of borosilicate glass, pure water, glycerol, 2-propanol, PDMS, cured epoxy, and heat-sink compounds. The results compare well with both literature values and values obtained with the steady-state divided bar method. Small sample volumes (~0.02 mm$^2$) suffice for accurate measurements using the platform, allowing rapid temperature-dependent measurements of thermal properties, which can be useful for the development, optimization and quality testing of many materials, such as liquids, gels, pastes and solids.

physics.ins-det↗

arXiv2018

Modeling of gate controlled Kondo effect at carbon point-defects in graphene

We study the magnetic properties in the vicinity of a single carbon defect in a monolayer of graphene. We include the unbound $\sigma$ orbital and the vacancy induced bound $\pi$ state in an effective two-orbital single impurity model. The local magnetic moments are stabilized by the Coulomb interaction as well as a significant ferromagnetic Hund's rule coupling between the orbitals predicted by a density functional theory calculation. A hybridization between the orbitals and the Dirac fermions is generated by the curvature of the graphene sheet in the vicinity of the vacancy. We present results for the local spectral function calculated using Wilson's numerical renormalization group approach for a realistic graphene band structure and find three different regimes depending on the filling, the controlling chemical potential, and the hybridization strength. These different regions are characterized by different magnetic properties. The calculated spectral functions qualitatively agree with recent scanning tunneling spectra on graphene vacancies.

cond-mat.mes-hall↗

arXiv2017

Quantum Critical Transition and Kondo Screening of Magnetic Moments in Graphene

In normal metals, the magnetic moment of impurity spins disappears below a characteristic Kondo temperature, TK, where coupling with the conduction-band electrons produces an entangled state that screens the local moment. In contrast, moments embedded in insulators remain unscreened at all temperatures. This raises the question about the fate of magnetic moments in intermediate, pseudogap systems, such as graphene. In these systems theory predicts a quantum phase-transition at a critical coupling strength which separates a local magnetic-moment phase from a Kondo screened phase. However, attempts to experimentally confirm these predictions and their intriguing consequences such as the ability to electrostatically control magnetic moments, have thus far been elusive. Here we report the observation of Kondo screening and the quantum phase-transition between screened and unscreened phases of vacancy magnetic-moments in graphene. Using scanning tunneling microscopy (STM), spectroscopy (STS) and numerical renormalization group (NRG) calculations, we identified Kondo screening by its spectroscopic signature and mapped the phase-transition as a function of coupling strength and chemical potential. We show that this transition makes it possible to turn the magnetic-moment on and off electrostatically through a gate voltage or mechanically through variations in local curvature.

cond-mat.mes-hall↗

arXiv2016

Carrier induced ferromagnetism in the insulating Mn doped III-V semiconductor InP

Although InP and GaAs have very similar band-structure their magnetic properties appear to drastically differ. Critical temperatures in (In,Mn)P are much smaller than that of (Ga,Mn)As and scale linearly with Mn concentration. This is in contrast to the square root behaviour found in (Ga,Mn)As. Moreover the magnetization curve exhibits an unconventional shape in (In,Mn)P contrasting with the conventional one of well annealed (Ga,Mn)As. By combining several theoretical approaches, the nature of ferromagnetism in Mn doped InP is investigated. It appears that the magnetic properties are essentially controlled by the position of the Mn acceptor level. Our calculations are in excellent agreement with recent measurements for both critical temperatures and magnetizations. The results are only consistent with a Fermi level lying in an impurity band, ruling out the possibility to understand the physical properties of Mn doped InP within the valence band scenario. The quantitative success found here reveals a predictive tool of choice that should open interesting pathways to address magnetic properties in other compounds

cond-mat.dis-nn↗