Thermodynamic constraints on the amplitude of quantum oscillations

Magneto-quantum oscillation experiments in high temperature superconductors show a strong thermally-induced suppression of the oscillation amplitude approaching critical dopings---in support of a quantum critical origin of their phase diagrams. We suggest that, in addition to a thermodynamic mass enhancement, these experiments may directly indicate the increasing role of quantum fluctuations that suppress the oscillation amplitude through inelastic scattering. We show that the traditional theoretical approaches beyond Lifshitz-Kosevich to calculate the oscillation amplitude in correlated metals result in a contradiction with the third law of thermodynamics and suggest a way to rectify this problem.Comment: PRB Rapid commun. (2017

Quantum-corrected ultraextremal horizons and validity of WKB in massless limit

We consider quantum backreaction of the quantized scalar field with an arbitrary mass and curvature coupling on ultraextremal horizons. The problem is distinguished in that (in contrast to non-extremal or extremal black holes) the WKB approximation remains valid near $r_{+}$ (which is the radius of the horizon) even in the massless limit. We examine the behavior of the stress-energy tensor of the quantized field near $r_{+}$ and show that quantum-corrected objects under discussion do exist. In the limit of the large mass our results agree with previous ones known in literature.Comment: revtex4, 9 page

Extreme plasma states in laser-governed vacuum breakdown

Triggering vacuum breakdown at the upcoming laser facilities can provide rapid electron-positron pair production for studies in laboratory astrophysics and fundamental physics. However, the density of the emerging plasma should seemingly stop rising at the relativistic critical density, when the plasma becomes opaque. Here we identify the opportunity of breaking this limit using optimal beam configuration of petawatt-class lasers. Tightly focused laser fields allow plasma generation in a small focal volume much less than ${\lambda}^3$, and creating extreme plasma states in terms of density and produced currents. These states can be regarded as a new object of nonlinear plasma physics. Using 3D QED-PIC simulations we demonstrate the possibility of reaching densities of more than $10^{25}$ cm$^{-3}$, which is an order of magnitude higher than previously expected. Controlling the process via the initial target parameters gives the opportunity to reach the discovered plasma states at the upcoming laser facilities

Universality of the single-particle spectra of cuprate superconductors

All the available data for the dispersion and linewidth of the single-particle spectra above the superconducting gap and the pseudogap in metallic cuprates for any doping has universal features. The linewidth is linear in energy below a scale $\omega_c$ and constant above. The cusp in the linewidth at $\omega_c$ mandates, due to causality, a "waterfall", i.e., a vertical feature in the dispersion. These features are predicted by a recent microscopic theory. We find that all data can be quantitatively fitted by the theory with a coupling constant $\lambda_0$ and an upper cutoff at $\omega_c$ which vary by less than 50% among the different cuprates and for varying dopings. The microscopic theory also gives these values to within factors of O(2).Comment: 4 pages, 4 figures; accepted by Phys. Rev. Let

S-MART, A Software Toolbox to Aid RNA-seq Data Analysis

High-throughput sequencing is now routinely performed in many experiments. But the analysis of the millions of sequences generated, is often beyond the expertise of the wet labs who have no personnel specializing in bioinformatics. Whereas several tools are now available to map high-throughput sequencing data on a genome, few of these can extract biological knowledge from the mapped reads. We have developed a toolbox called S-MART, which handles mapped RNA-Seq data. S-MART is an intuitive and lightweight tool which performs many of the tasks usually required for the analysis of mapped RNA-Seq reads. S-MART does not require any computer science background and thus can be used by all of the biologist community through a graphical interface. S-MART can run on any personal computer, yielding results within an hour even for Gb of data for most queries. S-MART may perform the entire analysis of the mapped reads, without any need for other ad hoc scripts. With this tool, biologists can easily perform most of the analyses on their computer for their RNA-Seq data, from the mapped data to the discovery of important loci

Extent of Fermi-surface reconstruction in the high-temperature superconductor HgBa2_2CuO4+δ_{4+\delta}

High magnetic fields have revealed a surprisingly small Fermi-surface in underdoped cuprates, possibly resulting from Fermi-surface reconstruction due to an order parameter that breaks translational symmetry of the crystal lattice. A crucial issue concerns the doping extent of this state and its relationship to the principal pseudogap and superconducting phases. We employ pulsed magnetic field measurements on the cuprate HgBa$_2$CuO$_{4+\delta}$ to identify signatures of Fermi surface reconstruction from a sign change of the Hall effect and a peak in the temperature-dependent planar resistivity. We trace the termination of Fermi-surface reconstruction to two hole concentrations where the superconducting upper critical fields are found to be enhanced. One of these points is associated with the pseudogap end-point near optimal doping. These results connect the Fermi-surface reconstruction to both superconductivity and the pseudogap phenomena.Comment: 5 pages. 3 Figures. PNAS (2020

Reading-out the state of a flux qubit by Josephson transmission line solitons

We describe the read-out process of the state of a Josephson flux qubit via solitons in Josephson transmission lines (JTL) as they are in use in the standard rapid single flux quantum (RSFQ) technology. We consider the situation where the information about the state of the qubit is stored in the time delay of the soliton. We analyze dissipative underdamped JTLs, take into account their jitter, and provide estimates of the measuring time and efficiency of the measurement for relevant experimental parameters.Comment: 13 pages, 12 figure

Operon information improves gene expression estimation for cDNA microarrays

BACKGROUND: In prokaryotic genomes, genes are organized in operons, and the genes within an operon tend to have similar levels of expression. Because of co-transcription of genes within an operon, borrowing information from other genes within the same operon can improve the estimation of relative transcript levels; the estimation of relative levels of transcript abundances is one of the most challenging tasks in experimental genomics due to the high noise level in microarray data. Therefore, techniques that can improve such estimations, and moreover are based on sound biological premises, are expected to benefit the field of microarray data analysis RESULTS: In this paper, we propose a hierarchical Bayesian model, which relies on borrowing information from other genes within the same operon, to improve the estimation of gene expression levels and, hence, the detection of differentially expressed genes. The simulation studies and the analysis of experiential data demonstrated that the proposed method outperformed other techniques that are routinely used to estimate transcript levels and detect differentially expressed genes, including the sample mean and SAM t statistics. The improvement became more significant as the noise level in microarray data increases. CONCLUSION: By borrowing information about transcriptional activity of genes within classified operons, we improved the estimation of gene expression levels and the detection of differentially expressed genes

One-Component Order Parameter in URu2_2Si2_2 Uncovered by Resonant Ultrasound Spectroscopy and Machine Learning

The unusual correlated state that emerges in URu$_2$Si$_2$ below T$_{HO}$ = 17.5 K is known as "hidden order" because even basic characteristics of the order parameter, such as its dimensionality (whether it has one component or two), are "hidden". We use resonant ultrasound spectroscopy to measure the symmetry-resolved elastic anomalies across T$_{HO}$. We observe no anomalies in the shear elastic moduli, providing strong thermodynamic evidence for a one-component order parameter. We develop a machine learning framework that reaches this conclusion directly from the raw data, even in a crystal that is too small for traditional resonant ultrasound. Our result rules out a broad class of theories of hidden order based on two-component order parameters, and constrains the nature of the fluctuations from which unconventional superconductivity emerges at lower temperature. Our machine learning framework is a powerful new tool for classifying the ubiquitous competing orders in correlated electron systems

Universal linear relations between susceptibility and Tc in cuprates

We developed an experimental method for measuring the intrinsic susceptibility \chi of powder of cuprate superconductors in the zero field limit using a DC-magnetometer. The method is tested with lead spheres. Using this method we determine \chi for a number of cuprate families as a function of doping. A universal linear (and not proportionality) relation between Tc and \chi is found. We suggest possible explanations for this phenomenon.Comment: Accepted for publication in PR