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Transmon qubits experience open-system effects that manifest as noise at a broad range of frequencies. We present a model of these effects using the Redfield master equation with a hybrid bath consisting of low- and high-frequency components. We use two-level fluctuators to simulate 1/f-like noise behavior, which is a dominant source of decoherence for superconducting qubits. By measuring quantum state fidelity under free evolution with and without dynamical decoupling (DD), we can fit the low- and high-frequency noise parameters in our model. We train and test our model using experiments on quantum devices available through IBM quantum experience. Our model accurately predicts the fidelity decay of random initial states, including the effect of DD pulse sequences. We compare our model with two simpler models and confirm the importance of including both high frequency and 1/f noise in order to accurately predict transmon behavior. 

Observations and theory suggest that core-collapse supernovae can span a range of explosion energies, and when sub-energetic the shockwave initiating the explosion can decelerate to speeds comparable to the escape speed of the progenitor. In these cases, gravity will complicate the explosion hydrodynamics and conceivably cause the shock to stall at large radii within the progenitor star. To understand these unique properties of weak explosions, we develop a perturbative approach for modeling the propagation of an initially strong shock into a time-steady, infalling medium in the gravitational field of a compact object. This method writes the shock position and the post-shock velocity, density, and pressure as series solutions in the (time-dependent) ratio of the freefall speed to the shock speed, and predicts that the shock stalls within the progenitor if the explosion energy is below a critical value. We show that our model agrees very well with hydrodynamic simulations, and accurately predicts (for example) the time-dependent shock position and velocity and the radius at which the shock stalls. Our results have implications for black hole formation and the newly detected class of fast X-ray transients (FXTs). In particular, we propose that a “phantom shock breakout”—where the outer edge of the star falls through a stalled shock—can yield a burst of X-rays without a subsequent optical/UV signature, similar to FXTs. This model predicts the rise time of the X-ray burst,t_d, and the mean photon energy,kT, are anticorrelated, approximately as$T\propto t_{\mathrm{d}}^{-5/8}$.

 

Observing the actions of others engages a core action observation network (AON) that includes the bilateral inferior frontal cortex (IFC), posterior superior temporal sulcus (pSTS) and inferior parietal lobule (IPL) (Caspers et al., 2010). Each region in the AON has functional properties that are heterogeneous and include representing the perceptual properties of action, predicting action outcomes and making inferences as to the goals of the actor. Critically, recent evidence shows that neural representations within the pSTS are sharpened when attending to the kinematics of the actor, such that the top-down guided attention reshapes underlying neural representations. In this study we evaluate how attention alters network connectivity within the AON as a system. Cues directed participant's attention to the goal, kinematics, or identity depicted in short action animations while brain responses were measured by fMRI. We identified those parcels within the AON with functional connectivity modulated by task. Results show that connectivity between the right pSTS and right IFC, and bilateral extended STS (STS+) were modulated during action observation such that connections were strengthened when the participant was attending to the action than goal. This finding is contrasted by the univariate results, which no univariate modulations in these brain regions except for right IFC. Using the functional networks defined by Yeo et al. (2011), we identified the parcels that are modulated by the attention to consist mainly of the fronto-parietal control network and default mode networks. These results are consistent with models of top-down feedback from executive system in the IFC to pSTS and implicates a right lateralized dual pathway model for action observation when focused on whole-body kinematics. 

Visual virtual reality (VR) systems for head-fixed mice offer advantages over real-world studies for investigating the neural circuitry underlying behavior. However, current VR approaches do not fully cover the visual field of view of mice, do not stereoscopically illuminate the binocular zone, and leave the lab frame visible. To overcome these limitations, we developed iMRSIV (Miniature Rodent Stereo Illumination VR)—VR goggles for mice. Our system is compact, separately illuminates each eye for stereo vision, and provides each eye with an ∼180° field of view, thus excluding the lab frame while accommodating saccades. Mice using iMRSIV while navigating engaged in virtual behaviors more quickly than in a current monitor-based system and displayed freezing and fleeing reactions to overhead looming stimulation. Using iMRSIV with two-photon functional imaging, we found large populations of hippocampal place cells during virtual navigation, global remapping during environment changes, and unique responses of place cell ensembles to overhead looming stimulation. 

The Earth’s Coriolis force has been well-known to impact surface waves and normal modes, which is essential to accurately interpret these waves. However, the Coriolis force on body waves has been assumed to be negligible and mostly ignored. It has been previously shown that the Coriolis force impacts polarizations of shear waves, whereas the wavefronts remain unaffected. We expand on the potential influences of Earth’s Coriolis force on shear-wave polarization measurements by conducting 3D numerical simulations for elastic waves generated by earthquake and explosive sources in a radially symmetric, and 3D mantle and crustal models. The Coriolis force can produce polarization anomalies of mantle shear waves up to 7° and core phases, such as SKS and SKKS, up to 4°. Uncorrected shear-wave polarizations due to the Coriolis force can cause an additional source of error (5°–10° in fast direction, and 0.2–0.3 s delay time depending on the method and seismic phase), inaccurate interpretation of station misalignments, and imprecise estimates of the core–mantle boundary topography. We show how to correct for the Coriolis force on teleseismic shear waves using 1D ray tracing for well-isolated phases. We recommend the use of full waveform simulations to accurately account for earthquake sources parameters, poorly isolated phases that could include interfering phase arrivals within the measurement time window, and the effect of the Coriolis force on the polarizations of shear waves.

 

We introduce the Weak-form Estimation of Nonlinear Dynamics (WENDy) method for estimating model parameters for non-linear systems of ODEs. Without relying on any numerical differential equation solvers, WENDy computes accurate estimates and is robust to large (biologically relevant) levels of measurement noise. For low dimensional systems with modest amounts of data, WENDy is competitive with conventional forward solver-based nonlinear least squares methods in terms of speed and accuracy. For both higher dimensional systems and stiff systems, WENDy is typically both faster (often by orders of magnitude) and more accurate than forward solver-based approaches. The core mathematical idea involves an efficient conversion of the strong form representation of a model to its weak form, and then solving a regression problem to perform parameter inference. The core statistical idea rests on the Errors-In-Variables framework, which necessitates the use of the iteratively reweighted least squares algorithm. Further improvements are obtained by using orthonormal test functions, created from a set of$$C^{\infty }$$$C^{\infty }$bump functions of varying support sizes.We demonstrate the high robustness and computational efficiency by applying WENDy to estimate parameters in some common models from population biology, neuroscience, and biochemistry, including logistic growth, Lotka-Volterra, FitzHugh-Nagumo, Hindmarsh-Rose, and a Protein Transduction Benchmark model. Software and code for reproducing the examples is available athttps://github.com/MathBioCU/WENDy.

 

A star completely destroyed in a tidal disruption event (TDE) ignites a luminous flare that is powered by the fallback of tidally stripped debris to a supermassive black hole (SMBH) of massM_•. We analyze two estimates for the peak fallback rate in a TDE, one being the “frozen-in” model, which predicts a strong dependence of the time to peak fallback rate,t_peak, on both stellar mass and age, with 15 days ≲t_peak≲ 10 yr for main sequence stars with masses 0.2 ≤M_⋆/M_⊙≤ 5 andM_•= 10⁶M_⊙. The second estimate, which postulates that the star is completely destroyed when tides dominate the maximum stellar self-gravity, predicts thatt_peakis very weakly dependent on stellar type, with$t_{\mathrm{peak}}=\left(23.2\pm 4.0\mathrm{days}\right){\left(M_{•}/{10}^6{M}_{\odot }\right)}^{1/2}$for 0.2 ≤M_⋆/M_⊙≤ 5, while$t_{\mathrm{peak}}=\left(29.8\pm 3.6\mathrm{days}\right){\left(M_{•}/{10}^6{M}_{\odot }\right)}^{1/2}$for a Kroupa initial mass function truncated at 1.5M_⊙. This second estimate also agrees closely with hydrodynamical simulations, while the frozen-in model is discrepant by orders of magnitude. We conclude that (1) the time to peak luminosity in complete TDEs is almost exclusively determined by SMBH mass, and (2) massive-star TDEs power the largest accretion luminosities. Consequently, (a) decades-long extra-galactic outbursts cannot be powered by complete TDEs, including massive-star disruptions, and (b) the most highly super-Eddington TDEs are powered by the complete disruption of massive stars, which—if responsible for producing jetted TDEs—would explain the rarity of jetted TDEs and their preference for young and star-forming host galaxies.