Strange Metals from Melting Correlated Insulators in Twisted Bilayer Graphene

Even as the understanding of the mechanism behind correlated insulating states in magic-angle twisted bilayer graphene converges towards various kinds of spontaneous symmetry breaking, the metallic normal state above the insulating transition temperature remains mysterious, with its excessively high entropy and linear-in-temperature resistivity. In this work, we focus on the effects of fluctuations of the order-parameters describing correlated insulating states at integer fillings of the low-energy flat bands on charge transport. Motivated by the observation of heterogeneity in the order-parameter landscape at zero magnetic field in certain samples, we conjecture the existence of frustrating extended range interactions in an effective Ising model of the order-parameters on a triangular lattice. The competition between short-distance ferromagnetic interactions and frustrating extended range antiferromagnetic interactions leads to an emergent length scale that forms stripe-like mesoscale domains above the ordering transition. The gapless fluctuations of these heterogeneous configurations are found to be responsible for the linear-in-temperature resistivity as well as the enhanced low temperature entropy. Our insights link experimentally observed linear-in-temperature resistivity and enhanced entropy to the strength of frustration, or equivalently, to the emergence of mesoscopic length scales characterizing order-parameter domains.

$T$-linear resistivity in models with local self-energy

A theoretical understanding of the enigmatic linear-in-temperature ($T$) resistivity, ubiquitous in strongly correlated metallic systems, has been a long sought-after goal. Furthermore, the slope of this robust $T$-linear resistivity is also observed to stay constant through crossovers between different temperature regimes: a phenomenon we dub slope invariance. Recently, several solvable models with $T$-linear resistivity have been proposed, putting us in an opportune moment to compare their inner workings in various explicit calculations. We consider two strongly correlated models with local self-energies that demonstrate $T$-linearity: a lattice of coupled Sachdev-Ye-Kitaev (SYK) models and the Hubbard model in single-site dynamical mean-field theory (DMFT). We find that the two models achieve $T$-linearity through distinct mechanisms at intermediate temperatures. However, we also find that these mechanisms converge to an identical form at high temperatures. Surprisingly, both models exhibit slope invariance across the two temperature regimes. We thus not only reveal some of the diversity in the theoretical inner workings that can lead to $T$-linear resistivity, but we also establish that different mechanisms can result in slope invarance.

Can Pairwise Testing Perform Comparably to Manually Handcrafted Testing Carried Out by Industrial Engineers?

Testing is an important activity in engineering of industrial software. For such software, testing is usually performed manually by handcrafting test suites based on specific design techniques and domain-specific experience. To support developers in testing, different approaches for producing good test suites have been proposed. In the last couple of years combinatorial testing has been explored with the goal of automatically combining the input values of the software based on a certain strategy. Pairwise testing is a combinatorial technique used to generate test suites by varying the values of each pair of input parameters to a system until all possible combinations of those parameters are created. There is some evidence suggesting that these kinds of techniques are efficient and relatively good at detecting software faults. Unfortunately, there is little experimental evidence on the comparison of these combinatorial testing techniques with, what is perceived as, rigorous manually handcrafted testing. In this study we compare pairwise test suites with test suites created manually by engineers for 45 industrial programs. The test suites were evaluated in terms of fault detection, code coverage and number of tests. The results of this study show that pairwise testing, while useful for achieving high code coverage and fault detection for the majority of the programs, is almost as effective in terms of fault detection as manual testing. The results also suggest that pairwise testing is just as good as manual testing at fault detection for 64% of the programs.

CfA4: Light Curves for 94 Type Ia Supernovae

We present multi-band optical photometry of 94 spectroscopically-confirmed Type Ia supernovae (SN Ia) in the redshift range 0.0055 to 0.073, obtained between 2006 and 2011. There are a total of 5522 light curve points. We show that our natural system SN photometry has a precision of roughly 0.03 mag or better in BVri, 0.06 mag in u, and 0.07 mag in U for points brighter than 17.5 mag and estimate that it has a systematic uncertainty of 0.014, 0.010, 0.012, 0.014, 0.046, and 0.073 mag in BVriuU, respectively. Comparisons of our standard system photometry with published SN Ia light curves and comparison stars reveal mean agreement across samples in the range of ~0.00-0.03 mag. We discuss the recent measurements of our telescope-plus-detector throughput by direct monochromatic illumination by Cramer et al (in prep.). This technique measures the whole optical path through the telescope, auxiliary optics, filters, and detector under the same conditions used to make SN measurements. Extremely well-characterized natural-system passbands (both in wavelength and over time) are crucial for the next generation of SN Ia photometry to reach the 0.01 mag accuracy level. The current sample of low-z SN Ia is now sufficiently large to remove most of the statistical sampling error from the dark energy error budget. But pursuing the dark-energy systematic errors by determining highly-accurate detector passbands, combining optical and near-infrared (NIR) photometry and spectra, using the nearby sample to illuminate the population properties of SN Ia, and measuring the local departures from the Hubble flow will benefit from larger, carefully measured nearby samples.

Lightcurves of Type Ia Supernovae from Near the Time of Explosion

We present a set of 11 type Ia supernova (SN Ia) lightcurves with dense, pre-maximum sampling. These supernovae (SNe), in galaxies behind the Large Magellanic Cloud (LMC), were discovered by the SuperMACHO survey. The SNe span a redshift range of z = 0.11 - 0.35. Our lightcurves contain some of the earliest pre-maximum observations of SNe Ia to date. We also give a functional model that describes the SN Ia lightcurve shape (in our VR-band). Our function uses the expanding fireball model of Goldhaber et al. (1998) to describe the rising lightcurve immediately after explosion but constrains it to smoothly join the remainder of the lightcurve. We fit this model to a composite observed VR-band lightcurve of three SNe between redshifts of 0.135 to 0.165. These SNe have not been K-corrected or adjusted to account for reddening. In this redshift range, the observed VR-band most closely matches the rest frame V-band. Using the best fit to our functional description of the lightcurve, we find the time between explosion and observed VR-band maximum to be 17.6+-1.3(stat)+-0.07(sys) rest-frame days for a SN Ia with a VR-band Delta m_{-10} of 0.52mag. For the redshifts sampled, the observed VR-band time-of-maximum brightness should be the same as the rest-frame V-band maximum to within 1.1 rest-frame days.

Observational Evidence from Supernovae for an Accelerating Universe and a Cosmological Constant

We present observations of 10 type Ia supernovae (SNe Ia) between 0.16 < z < 0.62. With previous data from our High-Z Supernova Search Team, this expanded set of 16 high-redshift supernovae and 34 nearby supernovae are used to place constraints on the Hubble constant (H_0), the mass density (Omega_M), the cosmological constant (Omega_Lambda), the deceleration parameter (q_0), and the dynamical age of the Universe (t_0). The distances of the high-redshift SNe Ia are, on average, 10% to 15% farther than expected in a low mass density (Omega_M=0.2) Universe without a cosmological constant. Different light curve fitting methods, SN Ia subsamples, and prior constraints unanimously favor eternally expanding models with positive cosmological constant (i.e., Omega_Lambda > 0) and a current acceleration of the expansion (i.e., q_0 < 0). With no prior constraint on mass density other than Omega_M > 0, the spectroscopically confirmed SNe Ia are consistent with q_0 <0 at the 2.8 sigma and 3.9 sigma confidence levels, and with Omega_Lambda >0 at the 3.0 sigma and 4.0 sigma confidence levels, for two fitting methods respectively. Fixing a ``minimal mass density, Omega_M=0.2, results in the weakest detection, Omega_Lambda>0 at the 3.0 sigma confidence level. For a flat-Universe prior (Omega_M+Omega_Lambda=1), the spectroscopically confirmed SNe Ia require Omega_Lambda >0 at 7 sigma and 9 sigma level for the two fitting methods. A Universe closed by ordinary matter (i.e., Omega_M=1) is ruled out at the 7 sigma to 8 sigma level. We estimate the size of systematic errors, including evolution, extinction, sample selection bias, local flows, gravitational lensing, and sample contamination. Presently, none of these effects reconciles the data with Omega_Lambda=0 and q_0 > 0.