Magnetic-field-induced transition in BaVS3

The metal-insulator transition (MIT) of BaVS3 is suppressed under pressure and above the critical pressure of p~2GPa the metallic phase is stabilized. We present the results of detailed magnetoresistivity measurements carried out at pressures near the critical value, in magnetic fields up to B=12T. We found that slightly below the critical pressure the structural tetramerization -- which drives the MIT -- is combined with the onset of magnetic correlations. If the zero-field transition temperature is suppressed to a sufficiently low value (T_MI<15K), the system can be driven into the metallic state by application of magnetic field. The main effect is not the reduction of T_MI with increasing B, but rather the broadening of the transition due to the applied magnetic field. We tentatively ascribe this phenomenon to the influence on the magnetic structure coupled to the bond-order of the tetramers.Comment: 5 pages, 5 figure

Isentropic Curves at Magnetic Phase Transitions

Experiments on cold atom systems in which a lattice potential is ramped up on a confined cloud have raised intriguing questions about how the temperature varies along isentropic curves, and how these curves intersect features in the phase diagram. In this paper, we study the isentropic curves of two models of magnetic phase transitions- the classical Blume-Capel Model (BCM) and the Fermi Hubbard Model (FHM). Both Mean Field Theory (MFT) and Monte Carlo (MC) methods are used. The isentropic curves of the BCM generally run parallel to the phase boundary in the Ising regime of low vacancy density, but intersect the phase boundary when the magnetic transition is mainly driven by a proliferation of vacancies. Adiabatic heating occurs in moving away from the phase boundary. The isentropes of the half-filled FHM have a relatively simple structure, running parallel to the temperature axis in the paramagnetic phase, and then curving upwards as the antiferromagnetic transition occurs. However, in the doped case, where two magnetic phase boundaries are crossed, the isentrope topology is considerably more complex

The electronic structure and the phases of BaVS3

BaVS3 is a moderately correlated d-electron system with a rich phase diagram. To construct the corresponding minimal electronic model, one has to decide which d-states are occupied, and to which extent. The ARPES experiment presented here shows that the behavior of BaVS3 is governed by the coexistence of wide-band (A_1g) and narrow-band (twofold degenerate E) d-electrons. We sketch a lattice fermion model which may serve as a minimal model of BaVS3. This serves foremost for the understanding of the metal-insulator in pure BaVS3 and its absence in some related compounds. The nature of the low temperature magnetic order differs for several systems which may be described in terms of the same electron model. We describe several recent experiments which give information about magnetic order at high pressures. In particular, we discuss field-induced insulator-to-metal transition at slightly subcritical pressures, and an evidence for magnetic order in the high-pressure metallic phase. The phase diagram of Sr-doped BaVS3 is also discussed. The complexity of the phases of BaVS3 arises from the fact that it is simultaneously unstable against several kinds of instabilities.Comment: Presented at the International Conference on Magnetism 2006 (Kyoto), 6 pages, 9 figure

Experimental Electronic Structure and Interband Nesting in BaVS_3

The correlated 3d sulphide BaVS_3 is a most interesting compound because of the apparent coexistence of one-dimensional and three-dimensional properties. Our experiments explain this puzzle and shed new light on its electronic structure. High-resolution angle-resolved photoemission measurements in a 4eV wide range below the Fermi level explored the coexistence of weakly correlated a_1g wide-band and strongly correlated e_g narrow-band d-electrons that is responsible for the complicated behavior of this material. The most relevant result is the evidence for a_1g--e_g inter-band nesting condition.Comment: 4 pages, 3 figure

MusCaps: generating captions for music audio

Content-based music information retrieval has seen rapid progress with the adoption of deep learning. Current approaches to high-level music description typically make use of classification models, such as in auto tagging or genre and mood classification. In this work, we propose to address music description via audio captioning, defined as the task of generating a natural language description of music audio content in a human-like manner. To this end, we present the first music audio captioning model, MusCaps, consisting of an encoder-decoder with temporal attention. Our method combines convolutional and recurrent neural network architectures to jointly process audio-text inputs through a multimodal encoder and leverages pre-training on audio data to obtain representations that effectively capture and summarise musical features in the input. Evaluation of the generated captions through automatic metrics shows that our method outperforms a baseline designed for non-music audio captioning. Through an ablation study, we unveil that this performance boost can be mainly attributed to pre-training of the audio encoder, while other design choices – modality fusion, decoding strategy and the use of attention -- contribute only marginally. Our model represents a shift away from classification-based music description and combines tasks requiring both auditory and linguistic understanding to bridge the semantic gap in music information retrieval

Orbitally Driven Spin Pairing in the 3D Non-Magnetic Mott Insulator BaVS3: Evidence from Single Crystal Studies

Static electrical and magnetic properties of single crystal BaVS_3 were measured over the structural (T_S=240K), metal-insulator (T_MI=69K), and suspected orbital ordering (T_X=30K) transitions. The resistivity is almost isotropic both in the metallic and insulating states. An anomaly in the magnetic anisotropy at T_X signals a phase transition to an ordered low-T state. The results are interpreted in terms of orbital ordering and spin pairing within the lowest crystal field quasi-doublet. The disordered insulator at T_X<T<T_MI is described as a classical liquid of non-magnetic pairs.Comment: 4 pages, 5 figures, revtex, epsf, and multicol style. Problem with figures fixed. To appear in Phys. Rev. B Rap. Com

Contrastive audio-language learning for music

As one of the most intuitive interfaces known to humans, natural language has the potential to mediate many tasks that involve human-computer interaction, especially in application-focused fields like Music Information Retrieval. In this work, we explore cross-modal learning in an attempt to bridge audio and language in the music domain. To this end, we propose MusCALL, a framework for Music Contrastive Audio-Language Learning. Our approach consists of a dual-encoder architecture that learns the alignment between pairs of music audio and descriptive sentences, producing multimodal embeddings that can be used for text-to-audio and audio-to-text retrieval out-of-the-box. Thanks to this property, MusCALL can be transferred to virtually any task that can be cast as text-based retrieval. Our experiments show that our method performs significantly better than the baselines at retrieving audio that matches a textual description and, conversely, text that matches an audio query. We also demonstrate that the multimodal alignment capability of our model can be successfully extended to the zero-shot transfer scenario for genre classification and auto-tagging on two public datasets

The effect of cluster thinning, cluster tipping, cluster shredding and defoliation at the flowering on the vegetative and generative vine performance from Kékfrankos Cv.

The cluster thinning is a method of the yield regulation.With the removal one part of the clusters, the yield pro leaf area will be lower, hereby the grape and wine quality will be improved. The regulation of the yield can lead to further advantages: the ratio of the vegetative and generative performance of the vines will improve, the condition of the plants will better, the number of the physiological diseases can be reduced and the growth of the shoots and roots can be promoted. The grape growers make the cluster thinning almost exclusive by creating one cluster shoots. Usually the upper clusters are removed, because the sugar content of these second or third clusters will be lower. The cluster thinning is an easy task, can be done without special skills. It is an effective method improving wine quality, but its use can lead to other problems. The grapes try to compensate the removed clusters. Therefore the clusters will be bigger and thicker, but more sensitive to bunch rot. Moreover the treatment is expensive, because it needs manual work. It is worth to get acquainted and try the new yield regulation methods, which can help to avoid the occurring problems. Our aim is to show the results of our experiment, which was carried out in Eger, examining the red grape cultivar Kékfrankos. During our 4 years long experiment we compared the effects of cluster thinning, cluster shredding, cluster tipping and defoliation at the flowering, on the vegetative and generative vine performance

Two-dimensional gapless spin liquids in frustrated SU(N) quantum magnets

A class of the symmetrically frustrated SU(N) models is constructed for quantum magnets based on the generators of SU(N) group. The total Hamiltonian lacks SU(N) symmtry. A mean field theory in the quasi-particle representation is developed for spin liquid states. Numerical solutions in two dimension indicate that the ground states are gapless and the quasi-particles are Dirac particles. The mechanism may be helpful in exploring the spin liquid phases in the spin-1 bilinear-biquadratic model and the spin-orbital model in higher dimensions.Comment: 9 pages, 3 figures, to appear in New Journal of Physic

Learning music audio representations via weak language supervision

Audio representations for music information retrieval are typically learned via supervised learning in a task-specific fashion. Although effective at producing state-of-the-art results, this scheme lacks flexibility with respect to the range of applications a model can have and requires extensively annotated datasets. In this work, we pose the question of whether it may be possible to exploit weakly aligned text as the only supervisory signal to learn general-purpose music audio representations. To address this question, we design a multimodal architecture for music and language pre-training (MuLaP) optimised via a set of proxy tasks. Weak supervision is provided in the form of noisy natural language descriptions conveying the overall musical content of the track. After pre-training, we transfer the audio backbone of the model to a set of music audio classification and regression tasks. We demonstrate the usefulness of our approach by comparing the performance of audio representations produced by the same audio backbone with different training strategies and show that our pre-training method consistently achieves comparable or higher scores on all tasks and datasets considered. Our experiments also confirm that MuLaP effectively leverages audio-caption pairs to learn representations that are competitive with audio-only and cross-modal self-supervised methods in the literature