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At least 109 records · Page 6

Seebeck effect studies in the charge density wave state of organic conductor α-(BEDT–TTF) 2 KHg(SCN) 4

Angular, magnetic field and temperature dependence of the interlayer Seebeck effect of the multiband organic conductor $\alpha -{(\mathrm{BEDT}-\mathrm{TTF})}_{2}\mathrm{KHg}{(\mathrm{SCN})}_{4}$ is experimentally studied at temperatures down to 0.55 K and fields up to 31 T in a wide range of angles. The background magnetic field and angular component of the Seebeck effect as well as the magnetic quantum oscillations that originate from the closed Fermi surface orbits are analyzed. The background interlayer Seebeck effect components show that above certain tilt angle of the magnetic field and above the kink field there is another CDW state in $\alpha -{(\mathrm{BEDT}-\mathrm{TTF})}_{2}\mathrm{KHg}{(\mathrm{SCN})}_{4}$, between previously known CDW0 and CDWx states, in agreement with magnetoresistance and magnetization studies in this material. Our observations show that this state possesses some of the properties of the CDW0 state. The Fermi surface in the third CDW state is still reconstructed but less imperfectly nested as expected as this state develops above the kink field. The temperature dependence of the interlayer Seebeck effect reveals that this state is developed at temperatures below 3 K and at field orientations around the second AMRO maximum. In addition, for the first time, a detailed T - θ phase diagram of $\alpha -{(\mathrm{BEDT}-\mathrm{TTF})}_{2}\mathrm{KHg}{(\mathrm{SCN})}_{4}$ based purely on Seebeck effect measurements is presented. We find that other states and transitions, beside the CDW states, also exist in a given temperature and angular range that have not been previously reported. These observations change the whole picture about the transport processes in the organic conductor $\alpha -{(\mathrm{BEDT}-\mathrm{TTF})}_{2}\mathrm{KHg}{(\mathrm{SCN})}_{4}$ and allow to better understand the complex nature of the CDW order in this and similar compounds.

Physics↗

Ultrafast enhancement of electron-phonon coupling via dynamic quantum well states

Abstract The density of states at the Fermi surface controls many material properties by influencing the low-energy interactions of conductive electrons. Typically, external tuning knobs generate only small perturbations to the density of states in crystals, since their band structure depends strongly on the lattice potential. In contrast, quantum well states are contingent on a localized potential extrinsic to the crystal lattice and can be easily modified leading to changes in the density of states at the Fermi level. Here, we are able to control the quantum well potential on the surface of Bi 2 Se 3 with light, driving a density of states singularity below E F at ultrafast timescales, thereby triggering a reversible Lifshitz transition. We reveal a substantial ultrafast enhancement of the electron-phonon coupling with repercussions on the relaxation dynamics in the system. We argue that the relaxation dynamics are governed largely by the interplay of the dynamic density of states of the quantum wells with c -axis scattering from the $${A}_{{{{{{{{\rm{1g}}}}}}}}}^{2}$$ A 1g 2 optical phonon mode. These results demonstrate a powerful way to enhance electron-boson interaction on ultrafast timescales providing new avenues for controlling material properties and driving novel quantum phases of matter.

Ciocys, Samuel T.↗

Attention-based quantum tomography

Abstract With rapid progress across platforms for quantum systems, the problem of many-body quantum state reconstruction for noisy quantum states becomes an important challenge. There has been a growing interest in approaching the problem of quantum state reconstruction using generative neural network models. Here we propose the ‘attention-based quantum tomography’ (AQT), a quantum state reconstruction using an attention mechanism-based generative network that learns the mixed state density matrix of a noisy quantum state. AQT is based on the model proposed in ‘Attention is all you need’ by Vaswani et al (2017 NIPS ) that is designed to learn long-range correlations in natural language sentences and thereby outperform previous natural language processing (NLP) models. We demonstrate not only that AQT outperforms earlier neural-network-based quantum state reconstruction on identical tasks but that AQT can accurately reconstruct the density matrix associated with a noisy quantum state experimentally realized in an IBMQ quantum computer. We speculate the success of the AQT stems from its ability to model quantum entanglement across the entire quantum system much as the attention model for NLP captures the correlations among words in a sentence.

97 MATHEMATICS AND COMPUTING↗