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Anton Andreev

Publications and source records attributed to Anton Andreev.

At least 19 recordsLinked to original sources

I-V characteristics of SNS junctions with a multivalley normal region

In multivalley conductors the inter-valley relaxation time $τ_v$ and the inelastic relaxation time $τ_{in}$ may be significantly longer than the intra-valley momentum relaxation time $τ$. We show that this separation of time scales has dramatic effects on the I-V characteristics of SNS junctions with a multivalley normal region. We generalize the Larkin-Ovchinnikov equations describing superconducting kinetics to the case of multivalley superconductors. We use this generalization to obtain a kinetic description of multivalley SNS junctions. We find that at constant voltage bias $V$, the current $I(V)$ is nonmonotonic; it exhibits two peaks of similar magnitude $I_\text{max,1} \sim I_\text{max,2}$ at $V_1 \sim \hbar(eτ_{in})^{-1}$ and $V_2\sim \hbar(eτ_v)^{-1}$, which may greatly exceed the critical current $I_c(T)$. At constant current bias $I$ we find that in a wide interval, $I_c(T) < I \lesssim I_{\text{jump}}$, the nonlinear resistance of the junction is controlled by the long relaxation times and may be several orders of magnitude smaller than the normal state resistance.

cond-mat.supr-con

A New Generation of Brain-Computer Interface Based on Riemannian Geometry

Based on the cumulated experience over the past 25 years in the field of Brain-Computer Interface (BCI) we can now envision a new generation of BCI. Such BCIs will not require training; instead they will be smartly initialized using remote massive databases and will adapt to the user fast and effectively in the first minute of use. They will be reliable, robust and will maintain good performances within and across sessions. A general classification framework based on recent advances in Riemannian geometry and possessing these characteristics is presented. It applies equally well to BCI based on event-related potentials (ERP), sensorimotor (mu) rhythms and steady-state evoked potential (SSEP). The framework is very simple, both algorithmically and computationally. Due to its simplicity, its ability to learn rapidly (with little training data) and its good across-subject and across-session generalization, this strategy a very good candidate for building a new generation of BCIs, thus we hereby propose it as a benchmark method for the field.

cs.HC

Low-temperature dissipative conductivity of superconductors with paramagnetic impurities

In s-wave superconductors with a small concentration of magnetic impurities, the only electronic excitations that remain available at low temperatures are the excitations of the system of localized spins. We discuss a new mechanism of interaction between electromagnetic waves and the localized spins in disordered superconductors. A supercurrent induces randomly distributed spin density of the itinerant electrons, which couples to the impurity spins by exchange interaction. Acceleration of the Cooper pair condensate by the external AC electric field of frequency $ω$ creates a strong, time-dependent exchange field acting on the localized spins, which is inversely proportional to $ω$. As a result, the low-frequency dissipative part of the conductivity saturates to a nonzero value. We use the fluctuation-dissipation theorem to evaluate the spectrum of equilibrium current fluctuations associated with the fluctuation in the spin subsystem. We also predict that in the presence of a DC magnetic field parallel to the superconducting film, the system of spins exhibits a large positive magnetoconductance.

cond-mat.supr-con

Axion electrodynamics and giant magnetic birefringence in Weyl excitonic insulators

We study the electromagnetic (EM) response of the excitonic insulator phase of a time-reversal (TR) invariant Weyl semimetal (WSM). At low temperatures, the system develops two exciton condensates. The condensates are related to each other by TR symmetry and weakly coupled by a Josephson tunneling term. The latter leads to the formation of the Leggett mode [Number-phase fluctuations in two-band superconductors, Prog. Theor. Phys. 36, 901 (1966).] with a small gap. Our main finding is that the Leggett mode couples to the EM fields as a massive dynamical axion. This is a consequence of the chiral anomaly and the chiral magnetic effect in the parent WSM. Because of the small axion mass, its coupling to EM fields results in a giant anisotropic polarizability and birefringence in the presence of a static magnetic field. The photon-axion hybridization produces a polariton resonance near the axion gap.

cond-mat.mes-hall

Isotopic Fingerprints of Proton-mediated Dielectric Relaxation in Solid and Liquid Water

We report cross-validated measurements of the isotope effect on dielectric relaxation for four isotopologues of ice and water, including the 1-10^5 Hz region, in which only sporadic and inconsistent measurements were previously available. In ice, the relaxation rates exhibit an activated temperature dependence with an isotope-independent activation energy. Across 248-273 K, the H_2O/D_2O relaxation rate ratio remains constant at 2.0 \pm 0.1. This scaling agrees with Kramers' theory in the high-friction limit if the moving mass is the proton or deuteron, indicating that dielectric relaxation is governed by a classic proton transfer over an energy barrier rather than molecular reorientation.

physics.chem-ph

The Riemannian Means Field Classifier for EEG-Based BCI Data

A substantial amount of research has demonstrated the robustness and accuracy of the Riemannian minimum distance to mean (MDM) classifier for all kinds of EEG-based brain--computer interfaces (BCIs). This classifier is simple, fully deterministic, robust to noise, computationally efficient, and prone to transfer learning. Its training is very simple, requiring just the computation of a geometric mean of a symmetric positive-definite (SPD) matrix per class. We propose an improvement of the MDM involving a number of power means of SPD matrices instead of the sole geometric mean. By the analysis of 20 public databases, 10 for the motor-imagery BCI paradigm and 10 for the P300 BCI paradigm, comprising 587 individuals in total, we show that the proposed classifier clearly outperforms the MDM, approaching the state-of-the art in terms of performance while retaining the simplicity and the deterministic behavior. In order to promote reproducible research, our code will be released as open source.

cs.HC

Reconstruction of surface electron spectrum and cyclotron motion in the CDW phase of Weyl semimetals

Charge density wave (CDW) instability drastically affects the surface electron spectrum of a Weyl semimetal. We show that in the CDW phase, the Fermi arcs reconnect into either closed Fermi loops or Frieze patterns traversing the reconstructed surface mini-Brillouin zone. For the closed reconnection topology, the application of an out-of-plane magnetic field leads to a cyclotron motion of the surface electrons. We determine the cyclotron frequency as a function of the electron energy and the magnitude of the CDW gap $Δ$ for various orientations of the Fermi arcs. For weak coupling, the period of cyclotron motion is dominated by the time of traversal of the arc reconnection regions and is inversely proportional to $Δ$.

cond-mat.mes-hall

Revealing the conduction band and pseudovector potential in 2D moiré semiconductors

Stacking monolayer semiconductors results in moiré patterns that host many correlated and topological electronic phenomena, but measurements of the basic electronic structure underpinning these phenomena are scarce. Here, we investigate the properties of the conduction band in moiré heterobilayers using submicron angle-resolved photoemission spectroscopy with electrostatic gating, focusing on the example of WS2/WSe2. We find that at all twist angles the conduction band edge is the K-point valley of the WS2, with a band gap of 1.58 +- 0.03 eV. By resolving the conduction band dispersion, we observe an unexpectedly small effective mass of 0.15 +- 0.02 m_e. In addition, we observe replicas of the conduction band displaced by reciprocal lattice vectors of the moiré superlattice. We present arguments and evidence that the replicas are due to modification of the conduction band states by the moiré potential rather than to final-state diffraction. Interestingly, the replicas display an intensity pattern with reduced, 3-fold symmetry, which we show implicates the pseudo vector potential associated with in-plane strain in moiré band formation.

cond-mat.mes-hall

Towards an architectural framework for intelligent virtual agents using probabilistic programming

We present a new framework called KorraAI for conceiving and building embodied conversational agents (ECAs). Our framework models ECAs' behavior considering contextual information, for example, about environment and interaction time, and uncertain information provided by the human interaction partner. Moreover, agents built with KorraAI can show proactive behavior, as they can initiate interactions with human partners. For these purposes, KorraAI exploits probabilistic programming. Probabilistic models in KorraAI are used to model its behavior and interactions with the user. They enable adaptation to the user's preferences and a certain degree of indeterminism in the ECAs to achieve more natural behavior. Human-like internal states, such as moods, preferences, and emotions (e.g., surprise), can be modeled in KorraAI with distributions and Bayesian networks. These models can evolve over time, even without interaction with the user. ECA models are implemented as plugins and share a common interface. This enables ECA designers to focus more on the character they are modeling and less on the technical details, as well as to store and exchange ECA models. Several applications of KorraAI ECAs are possible, such as virtual sales agents, customer service agents, virtual companions, entertainers, or tutors.

cs.AI

First steps towards quantum machine learning applied to the classification of event-related potentials

Low information transfer rate is a major bottleneck for brain-computer interfaces based on non-invasive electroencephalography (EEG) for clinical applications. This led to the development of more robust and accurate classifiers. In this study, we investigate the performance of quantum-enhanced support vector classifier (QSVC). Training (predicting) balanced accuracy of QSVC was 83.17 (50.25) %. This result shows that the classifier was able to learn from EEG data, but that more research is required to obtain higher predicting accuracy. This could be achieved by a better configuration of the classifier, such as increasing the number of shots.

cs.HC

Elucidating contact electrification mechanism of water

The open water surface is known to be charged. Yet, the magnitude of the charge and the physical mechanism of the charging remain unclear, causing heated debates across the scientific community. Here we directly measure the charge Q of microdrops ejected from hydrophilic and hydrophobic capillaries and show that the water surface can take both positive or negative charge values depending on pH and the capillary type. Our experiments, theory, and simulations provide evidence that a junction of two aqueous interfaces with a different ion adsorption energy (e.g., liquid-solid and liquid-air interfaces) develops a pH-dependent contact potential difference Δϕ up to 52 mV. The longitudinal charge transfer between the interfaces stimulated by Δϕ determines the charge of the open water surface. The suggested static electrification mechanism provides far-reaching insights into the origin of electrical potentials in biological and electrochemical energy systems.

cond-mat.soft

A comparison of mobile VR display running on an ordinary smartphone with standard PC display for P300-BCI stimulus presentation

A brain-computer interface (BCI) based on electroencephalography (EEG) is a promising technology for enhancing virtual reality (VR) applications-in particular, for gaming. We focus on the so-called P300-BCI, a stable and accurate BCI paradigm relying on the recognition of a positive event-related potential (ERP) occurring in the EEG about 300 ms post-stimulation. We implemented a basic version of such a BCI displayed on an ordinary and affordable smartphone-based head-mounted VR device: that is, a mobile and passive VR system (with no electronic components beyond the smartphone). The mobile phone performed the stimuli presentation, EEG synchronization (tagging) and feedback display. We compared the ERPs and the accuracy of the BCI on the VR device with a traditional BCI running on a personal computer (PC). We also evaluated the impact of subjective factors on the accuracy. The study was within-subjects, with 21 participants and one session in each modality. No significant difference in BCI accuracy was found between the PC and VR systems, although the P200 ERP was significantly wider and larger in the VR system as compared to the PC system.

cs.HC

Engineering study on the use of Head-Mounted display for Brain- Computer Interface

In this article, we explore the availability of head-mounted display (HMD) devices which can be coupled in a seamless way with P300-based brain-computer interfaces (BCI) using electroencephalography (EEG). The P300 is an event-related potential appearing about 300ms after the onset of a stimulation. The recognition of this potential on the ongoing EEG requires the knowledge of the exact onset of the stimuli. In other words, the stimulations presented in the HMD must be perfectly synced with the acquisition of the EEG signal. This is done through a process called tagging. The tagging must be performed in a reliable and robust way so as to guarantee the recognition of the P300 and thus the performance of the BCI. An HMD device should also be able to render images fast enough to allow an accurate perception of the stimulations, and equally to not perturb the acquisition of the EEG signal. In addition, an affordable HMD device is needed for both research and entertainment purposes. In this study, we selected and tested two HMD configurations.

cs.HC

Building Brain Invaders: EEG data of an experimental validation

We describe the experimental procedures for a dataset that we have made publicly available at https://doi.org/10.5281/zenodo.2649006 in mat and csv formats. This dataset contains electroencephalographic (EEG) recordings of 25 subjects testing the Brain Invaders (Congedo, 2011), a visual P300 Brain-Computer Interface inspired by the famous vintage video game Space Invaders (Taito, Tokyo, Japan). The visual P300 is an event-related potential elicited by a visual stimulation, peaking 240-600 ms after stimulus onset. EEG data were recorded by 16 electrodes in an experiment that took place in the GIPSA-lab, Grenoble, France, in 2012 (Van Veen, 2013 and Congedo, 2013). Python code for manipulating the data is available at https://github.com/plcrodrigues/py.BI.EEG.2012-GIPSA. The ID of this dataset is BI.EEG.2012-GIPSA.

cs.HC

Brain Invaders Adaptive versus Non-Adaptive P300 Brain-Computer Interface dataset

We describe the experimental procedures for a dataset that we have made publicly available at https://doi.org/10.5281/zenodo.1494163 in mat and csv formats. This dataset contains electroencephalographic (EEG) recordings of 24 subjects doing a visual P300 Brain-Computer Interface experiment on PC. The visual P300 is an event-related potential elicited by visual stimulation, peaking 240-600 ms after stimulus onset. The experiment was designed in order to compare the use of a P300-based brain-computer interface on a PC with and without adaptive calibration using Riemannian geometry. The brain-computer interface is based on electroencephalography (EEG). EEG data were recorded thanks to 16 electrodes. Data were recorded during an experiment taking place in the GIPSA-lab, Grenoble, France, in 2013 (Congedo, 2013). Python code for manipulating the data is available at https://github.com/plcrodrigues/py.BI.EEG.2013-GIPSA. The ID of this dataset is BI.EEG.2013-GIPSA.

cs.HC

Analysis of tagging latency when comparing event-related potentials

Event-related potentials (ERPs) are very small voltage produced by the brain in response to external stimulation. In order to detect and evaluate an ERP in an ongoing electroencephalogram (EEG), it is necessary to tag the EEG with the exact onset time of the stimulus. We define the latency as the delay between the time the tagging command is sent and the detection of the stimulus on the screen. Failing to control sequencing in the tagging pipeline causes problems when interpreting latency, in particular when comparing ERPs generated from stimuli displayed by different systems. In this work, we present number of technical aspects which can influence latency such as the refresh rate of the screen or the display of a stimulus at different screen location. A few propositions are suggested to estimate and correct this latency.

cs.HC

Evidence for a strain tuned topological phase transition in ZrTe5

A phase transition between topologically distinct insulating phases involves closing and reopening of the bandgap. Close to this topological phase transition, the bulk energy spectrum is characterized by a massive Dirac dispersion, where the mass plays the role of bandgap. Here we report the observation of a non-monotonic strain dependence of resistivity and negative longitudinal magnetoresistance in ZrTe5, which is known to host massive Dirac Fermions in the bulk. This non-monotonic strain dependence is consistent with the closing and reopening of the bandgap at the Brillouin-zone center, indicative of a topological phase transition. This observation suggests that the topological state of ZrTe5 is highly sensitive to uniaxial stress. Our study presents a promising platform for continuous in-situ control of nontrivial topological properties of materials.

cond-mat.str-el

Manifestations of electron interactions in photogalvanic effect in chiral nanotubes

Carbon nanotubes provide one of the most accessible experimental realizations of one dimensional electron systems. In the experimentally relevant regime of low doping the Luttinger liquid formed by electrons may be approximated by a Wigner crystal. The crystal-like electronic order suggests that nanotubes exhibit effects similar to the Mössbauer effect where the momentum of an emitted photon is absorbed by the whole crystal. We show that the circular photovoltaic effect in chiral nanotubes is of the same nature. We obtain the frequency dependence of the photovoltage and characterize its singularities in a broad frequency range where the electron correlations are essential. Our predictions provide a basis for using the photogalvanic effect as a new experimental probe of electron correlations in nanotubes.

cond-mat.mes-hall