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Jens Oppliger

Publications and source records attributed to Jens Oppliger.

7 recordsLinked to original sources

Direct High-Magnetic-Field Coupling to Stripe Order in a Cuprate Superconductor

Superconductivity in cuprates emerges out of a complex normal state that hosts density waves, pseudogap physics, and strange metal properties. Here, we access this normal state by synchronizing free-electron laser x-rays with high-magnetic-field pulses up to 44 T. We observe a linear increase in charge order amplitude and correlation length that persists far above the vortex melting transition. This behavior is incompatible with standard phase competition between charge order and superconductivity. By means of conventional hard x-ray diffraction and magnetostriction, we show that applied fields also enhance monoclinic lattice distortions. However, this magnetoelastic response is weaker and an epiphenomenon of the stripe order enhancement. Combined with recent observations of field-linear spin freezing, our results point to a direct coupling between magnetic field and the spin component of stripe order in the high-field normal state -- a mechanism independent of superconductivity suppression that has so far remained hidden from scattering probes.

cond-mat.str-el

Reversible nanoscale patterning of WTe$_2$ with a scanning tunneling microscope

Manipulating the lattice structure of ferroelectric quantum materials enables their use in low-power electronic devices, including field-effect transistors. WTe$_2$ is a Weyl-semimetal candidate and ferroelectric, both properties arising from the reduced crystal symmetry of its T$_\mathrm{d}$ ground state. The T$_\mathrm{d}$ crystal phase results from a Peierls distortion of the 1T parent structure and an interlayer shift. While experiments in WTe$_2$ have established ferroelectric switching and transient control of the predicted topological phase via ultrafast excitations, persistent electronic changes on the nanometer scale remain elusive. Here, we demonstrate that current pulses applied via scanning tunneling microscopy can both write and erase persistent nanometer-scale patterns on the surface of WTe$_2$. These patterns consist of apparent picometer in-plane and out-of-plane atomic displacements, accompanied by changes to the local density of states. The out-of-plane displacements further modulate the Peierls-like distortion present in WTe$_2$, while the in-plane displacements are indicative of ferroelectric switching. The induced patterns can be repositioned and erased, suggesting a nanoscale handle on the ferroelectric properties of WTe$_2$.

cond-mat.mtrl-sci

Weak-signal extraction enabled by deep-neural-network denoising of diffraction data

Removal or cancellation of noise has wide-spread applications for imaging and acoustics. In every-day-life applications, denoising may even include generative aspects, which are unfaithful to the ground truth. For scientific use, however, denoising must reproduce the ground truth accurately. Here, we show how data can be denoised via a deep convolutional neural network such that weak signals appear with quantitative accuracy. In particular, we study X-ray diffraction on crystalline materials. We demonstrate that weak signals stemming from charge ordering, insignificant in the noisy data, become visible and accurate in the denoised data. This success is enabled by supervised training of a deep neural network with pairs of measured low- and high-noise data. We demonstrate that using artificial noise does not yield such quantitatively accurate results. Our approach thus illustrates a practical strategy for noise filtering that can be applied to challenging acquisition problems.

eess.IV

A Sacrificial Magnet Concept for Field Dependent Surface Science Studies

We demonstrate a straightforward approach to integrating a magnetic field into a low-temperature scanning tunneling microscope (STM) by adhering an NdFeB permanent magnet to a magnetizable sample plate. To render our magnet concept compatible with high-temperature sample cleaning procedures, we make the irreversible demagnetization of the magnet a central part of our preparation cycle. After sacrificing the magnet by heating it above its Curie temperature, we use a transfer tool to attach a new magnet in-situ prior to transferring the sample into the STM. We characterize the magnetic field created by the magnet using the Abrikosov vortex lattice of superconducting NbSe2. Excellent agreement between the distance dependent magnetic fields from experiments and simulations allows us to predict the magnitude and orientation of magnetic flux at any location with respect to the magnet and the sample plate. Our concept is an accessible solution for field-dependent surface science studies that require fields in the range of up to 400 mT and otherwise detrimental heating procedures.

physics.app-ph

Adaptive Sparse Sampling for Quasiparticle Interference Imaging

Quasiparticle interference imaging (QPI) offers insight into the band structure of quantum materials from the Fourier transform of local density of states (LDOS) maps. Their acquisition with a scanning tunneling microscope is traditionally tedious due to the large number of required measurements that may take several days to complete. The recent demonstration of sparse sampling for QPI imaging showed how the effective measurement time could be fundamentally reduced by only sampling a small and random subset of the total LDOS. However, the amount of required sub-sampling to faithfully recover the QPI image remained a recurring question. Here we introduce an adaptive sparse sampling (ASS) approach in which we gradually accumulate sparsely sampled LDOS measurements until a desired quality level is achieved via compressive sensing recovery. The iteratively measured random subset of the LDOS can be interleaved with regular topographic images that are used for image registry and drift correction. These reference topographies also allow to resume interrupted measurements to further improve the QPI quality. Our ASS approach is a convenient extension to quasiparticle interference imaging that should remove further hesitation in the implementation of sparse sampling mapping schemes.

cond-mat.other

Fast spectroscopic mapping of two-dimensional quantum materials

Spectroscopic mapping refers to the massive recording of spectra whilst varying an additional degree of freedom, such as: magnetic field, location, temperature, or charge carrier concentration. As this involves two serial tasks, spectroscopic mapping can become excruciatingly slow. We demonstrate exponentially faster mapping through our combination of sparse sampling and parallel spectroscopy. We exemplify our concept using quasiparticle interference imaging of Au(111) and Bi2Sr2CaCu2O8 (Bi2212), as two well-known model systems. Our method is accessible, straightforward to implement with existing scanning tunneling microscopes, and can be easily extended to enhance gate or field-mapping spectroscopy. In view of a possible four orders of magnitude speed advantage, it is setting the stage to fundamentally promote the discovery of novel quantum materials.

cond-mat.mtrl-sci

Sparse Sampling for Fast Quasiparticle Interference Mapping

Scanning tunneling microscopy (STM) is a notoriously slow technique; Data-recording is serial which renders complex measurement tasks, such as quasiparticle interference (QPI) mapping, impractical. However, QPI would provide insight into band-structure details of quantum materials which can be inaccessible to angle-resolved photoemission spectroscopy. Here we use compressed sensing (CS) to fundamentally speed-up QPI mapping. We reliably recover the QPI information from a fraction of the usual local density of state measurements. The requirement of CS is naturally fulfilled for QPI, since CS relies on sparsity in a vector domain, here given by few nonzero coefficients in Fourier space. We exemplify CS on a simulated Cu(111) surface using random sampling of constant and varying probability density. We further simplify the motion of the STM tip through an open traveling salesman's problem for greater efficiency. We expect that the implications of our CS approach will be transformative for the exploration of 2D quantum materials.

cond-mat.other