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The construction of a better exchange-correlation potential in time-dependent density functional theory (TDDFT) can improve the accuracy of TDDFT calculations and provide more accurate predictions of the properties of many-electron systems. Here, we propose a machine learning method to develop the energy functional and the Kohn–Sham potential of a time-dependent Kohn–Sham (TDKS) system is proposed. The method is based on the dynamics of the Kohn–Sham system and does not require any data on the exact Kohn–Sham potential for training the model. We demonstrate the results of our method with a 1D harmonic oscillator example and a 1D two-electron example. We show that the machine-learned Kohn–Sham potential matches the exact Kohn–Sham potential in the absence of memory effect. Our method can still capture the dynamics of the Kohn–Sham system in the presence of memory effects. The machine learning method developed in this article provides insight into making better approximations of the energy functional and the Kohn–Sham potential in the TDKS system.

We present multiwavelength characterization of 65 high-mass X-ray binary (HMXB) candidates in M33. We use the Chandra ACIS survey of M33 (ChASeM33) catalog to select hard X-ray point sources that are spatially coincident with UV-bright point-source optical counterparts in the Panchromatic Hubble Andromeda Treasury: Triangulum Extended Region catalog, which covers the inner disk of M33 at near-IR, optical, and near-UV wavelengths. We perform spectral energy distribution fitting on multiband photometry for each point-source optical counterpart to measure its physical properties including mass, temperature, luminosity, and radius. We find that the majority of the HMXB companion star candidates are likely B-type main-sequence stars, suggesting that the HMXB population of M33 is dominated by Be X-ray binaries (Be-XRBs), as is seen in other Local Group galaxies. We use spatially resolved recent star formation history maps of M33 to measure the age distribution of the HMXB candidate sample and the HMXB production rate for M33. We find a bimodal distribution for the HMXB production rate over the last 80 Myr, with a peak at ∼10 and ∼40 Myr, which match theoretical formation timescales for the most massive HMXBs and Be-XRBs, respectively. We measure an HMXB production rate of 107–136 HMXBs/(M_⊙yr⁻¹) over themore »last 50 Myr and 150–199 HMXBs/(M_⊙yr⁻¹) over the last 80 Myr. For sources with compact object classifications from overlapping NuSTAR observations, we find a preference for giant/supergiant companion stars in black hole HMXBs and main-sequence companion stars in neutron star HMXBs.

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Abstract 167 Er 3+ doped solids are a promising platform for quantum technology due to erbium’s telecom C-band optical transition and its long hyperfine coherence times. We experimentally study the spin Hamiltonian and dynamics of 167 Er 3+ spins in Y 2 O 3 using electron paramagnetic resonance (EPR) spectroscopy. The anisotropic electron Zeeman, hyperfine and nuclear quadrupole matrices are fitted using data obtained by X-band (9.5 GHz) EPR spectroscopy. We perform pulsed EPR spectroscopy to measure spin relaxation time T 1 and coherence time T 2 for the 3 principal axes of an anisotropic g tensor. Long electronic spin coherence time up to 24.4 μ s is measured for lowest g transition at 4 K, exceeding previously reported values at much lower temperatures. Measurements of decoherence mechanism indicates T 2 limited by spectral diffusion and instantaneous diffusion. Long spin coherence times, along with a strong anisotropic hyperfine interaction makes 167 Er 3+ :Y 2 O 3 a rich system and an excellent candidate for spin-based quantum technologies.