The discovery of superconductivity in LaFeAsO introduced ferropnictides as a new class of superconducting compounds with critical temperatures second only to those of the cuprates. Although the presence of iron makes the ferropnictides radically different from the cuprates, antiferromagnetism in the parent compounds suggests that superconductivity and magnetism are interrelated in both of them. However, the character of magnetic interactions and spin fluctuations in ferropnictides is not reasonably described by conventional models of magnetism. Here we show that the most puzzling features can be naturally reconciled within a rather simple effective spin model with a biquadratic interaction, which is consistent with electronic structure calculations. By going beyond the Heisenberg model, our description explains numerous experimental observations, including the peculiarities of the spin-wave spectrum, thin domain walls and crossover from a first- to second-order phase transition under doping. The model also offers insight into the occurrence of the nematic phase above the antiferromagnetic phase transition.
\\\",[],False,\\\"[\\\"\\\"Aleksander L. Wysocki\\\"\\\", \\\"\\\"Kirill D. Belashchenko\\\"\\\", \\\"\\\"Vladimir P. Antropov\\\"\\\"]\\\",\\\"Wysocki, A., Belashchenko, K. & Antropov, V. Consistent model of magnetism in ferropnictides. Nature Phys7, 485–489 (2011).\\\",338,0,116,aplusplus,10.1038/nphys1933,https://doi.org/10.1038/nphys1933,,6,nphys,nature physics,1299369600,2011-03-06,,https://www.nature.com/articles/nphys1933,7\\narticle,Floquet topological insulator in semiconductor quantum wells,\\\"Topological phases of matter have captured our imagination over the past few years, with tantalizing properties such as robust edge modes and exotic non-Abelian excitations, and potential applications ranging from semiconductor spintronics to topological quantum computation. Despite recent advancements in the field, our ability to control topological transitions remains limited, and usually requires changing material or structural properties. We show, using Floquet theory, that a topological state can be induced in a semiconductor quantum well, initially in the trivial phase. This can be achieved by irradiation with microwave frequencies, without changing the well structure, closing the gap and crossing the phase transition. We show that the quasi-energy spectrum exhibits a single pair of helical edge states. We discuss the necessary experimental parameters for our proposal. This proposal provides an example and a proof of principle of a new non-equilibrium topological state, the Floquet topological insulator, introduced in this paper.
\\\",[],False,\\\"[\\\"\\\"Netanel H. Lindner\\\"\\\", \\\"\\\"Gil Refael\\\"\\\", \\\"\\\"Victor Galitski\\\"\\\"]\\\",\\\"Lindner, N., Refael, G. & Galitski, V. Floquet topological insulator in semiconductor quantum wells. Nature Phys7, 490–495 (2011).\\\",4828,7,945,aplusplus,10.1038/nphys1926,https://doi.org/10.1038/nphys1926,,6,nphys,nature physics,1299974400,2011-03-13,,https://www.nature.com/articles/nphys1926,7\\narticle,Time-resolved measurement of spin-transfer-driven ferromagnetic resonance and spin torque in magnetic tunnel junctions,\\\"The bias dependence of the torque that a spin-polarized current exerts on ferromagnetic elements is important for understanding fundamental spin physics in magnetic devices and for applications. Several experimental techniques have been introduced in recent years in attempts to measure spin-transfer torque in magnetic tunnel junctions. However, these techniques have provided only indirect measures of the torque and their results regarding bias dependence are qualitatively and quantitatively inconsistent. Here we demonstrate that spin torque in magnetic tunnel junctions can be measured directly by using time-domain techniques to detect resonant magnetic precession in response to an oscillating spin torque. The technique is accurate in the high-bias regime relevant for applications, and because it detects directly small-angle linear-response magnetic dynamics caused by spin torque it is relatively immune to artefacts affecting competing techniques. At high bias we find that the spin-torque vector differs markedly from the simple lowest-order Taylor series approximations commonly assumed.
\\\",[],False,\\\"[\\\"\\\"Chen Wang\\\"\\\", \\\"\\\"Yong-Tao Cui\\\"\\\", \\\"\\\"Jordan A. Katine\\\"\\\", \\\"\\\"Robert A. Buhrman\\\"\\\", \\\"\\\"Daniel C. Ralph\\\"\\\"]\\\",\\\"Wang, C., Cui, YT., Katine, J. et al. Time-resolved measurement of spin-transfer-driven ferromagnetic resonance and spin torque in magnetic tunnel junctions. Nature Phys7, 496–501 (2011).\\\",529,6,91,aplusplus,10.1038/nphys1928,https://doi.org/10.1038/nphys1928,,6,nphys,nature physics,1298764800,2011-02-27,,https://www.nature.com/articles/nphys1928,7\\narticle,Controlling the quantum stereodynamics of ultracold bimolecular reactions,\\\"Molecular collisions in the quantum regime represent a new opportunity to explore chemical reactions. Recently, atom-exchangereactions were observed in a trapped ultracold gas of KRb molecules. In an external electric field, these polar molecules can easily be oriented and the exothermic and barrierless bimolecular reactions, KRb+KRb→K2+Rb2, occur at a rate that rises steeply with increasing dipole moment. Here we demonstrate the suppression of the bimolecular chemical reaction rate by nearly two orders of magnitude when we use an optical lattice trap to confine the fermionic polar molecules in a quasi-two-dimensional, pancake-like geometry, with the dipoles oriented along the tight confinement direction. With the combination of sufficiently tight confinement and Fermi statistics of the molecules, two polar molecules can approach each other only in a ‘side-by-side’ collision under repulsive dipole–dipole interactions. The suppression of chemical reactions is a prerequisite for the realization of new molecule-based quantum systems.
\\\",[],False,\\\"[\\\"\\\"M. H. G. de Miranda\\\"\\\", \\\"\\\"A. Chotia\\\"\\\", \\\"\\\"B. Neyenhuis\\\"\\\", \\\"\\\"D. Wang\\\"\\\", \\\"\\\"G. Qu\\\\u00e9m\\\\u00e9ner\\\"\\\", \\\"\\\"S. Ospelkaus\\\"\\\", \\\"\\\"J. L. Bohn\\\"\\\", \\\"\\\"J. Ye\\\"\\\", \\\"\\\"D. S. Jin\\\"\\\"]\\\",\\\"de Miranda, M., Chotia, A., Neyenhuis, B. et al. Controlling the quantum stereodynamics of ultracold bimolecular reactions. Nature Phys7, 502–507 (2011).\\\",838,0,333,aplusplus,10.1038/nphys1939,https://doi.org/10.1038/nphys1939,,6,nphys,nature physics,1300579200,2011-03-20,,https://www.nature.com/articles/nphys1939,7\\narticle,Random walks with barriers,\\\"Restrictions to molecular motion by barriers (membranes) are ubiquitous in porous media, composite materials and biological tissues. A major challenge is to characterize the microstructure of a material or an organism non-destructively using a bulk transport measurement. Here we demonstrate how the long-range structural correlations introduced by permeable membranes give rise to distinct features of transport. We consider Brownian motion restricted by randomly placed and oriented membranes (d−1-dimensional planes in d dimensions) and focus on the disorder-averaged diffusion propagator using a scattering approach. The renormalization group solution reveals a scaling behaviour of the diffusion coefficient for large times, with a characteristically slow inverse square root time dependence for any d. Its origin lies in the strong structural fluctuations introduced by the spatially extended random restrictions, representing a new universality class of the structural disorder. Our results agree well with Monte Carlo simulations in two dimensions. They can be used to identify permeable barriers as restrictions to transport, and to quantify their permeability and surface area.
\\\",[],False,\\\"[\\\"\\\"Dmitry S. Novikov\\\"\\\", \\\"\\\"Els Fieremans\\\"\\\", \\\"\\\"Jens H. Jensen\\\"\\\", \\\"\\\"Joseph A. Helpern\\\"\\\"]\\\",\\\"Novikov, D., Fieremans, E., Jensen, J. et al. Random walks with barriers. Nature Phys7, 508–514 (2011).\\\",546,0,128,aplusplus,10.1038/nphys1936,https://doi.org/10.1038/nphys1936,,6,nphys,nature physics,1299369600,2011-03-06,,https://www.nature.com/articles/nphys1936,7\\n\\n\\npatient_id,specimen_id,status,specimen_type_display,specimen_datetime,organism_code,organism_display_name,organism_id,drug_id,drug_display_name,rsi_code\\n99999999999,CCC2,,MRSA Screen,2017-02-14,NA,No growth,2300967,NA,NA,NA\\n99999999999,CCC1,,Blood Culture,2017-02-13,NA,No growth,2365356,NA,NA,NA\\n99999999999,BBB8,,MRSA Screen,2016-01-12,NA,No growth,2284807,NA,NA,NA\\n99999999999,BBB7,,Faeces,2016-05-27,NA,No growth,2392702,NA,NA,NA\\n99999999999,BBB6,,Urine,2015-04-11,NA,No growth,1960554,NA,NA,NA\\n99999999999,BBB5,,Blood Culture,2015-07-08,NA,No growth,2110922,NA,NA,NA\\n99999999999,BBB4,,MRSA Screen,2015-07-08,NA,No growth,2015253,NA,NA,NA\\n99999999999,BBB3,,MRSA Screen,2015-05-15,NA,No growth,1996884,NA,NA,NA\\n99999999999,BBB2,,MRSA Screen,2015-03-05,NA,No growth,1994380,NA,NA,NA\\n99999999999,BBB1,,Urine,2015-03-25,NA,No growth,1770706,NA,NA,NA\\n99999999999,AAA2,,Urine,2015-07-02,ECOL,Escherichia coli,1761696,Amp,Ampicillin,R\\n99999999999,AAA2,,Urine,2015-07-02,ECOL,Escherichia coli,1761696,Aug,Co-amoxiclav,R\\n99999999999,AAA2,,Urine,2015-07-02,ECOL,Escherichia coli,1761696,Caz,Ceftazidime,S\\n99999999999,AAA2,,Urine,2015-07-02,ECOL,Escherichia coli,1761696,Cet,Cefotaxime,S\\n99999999999,AAA2,,Urine,2015-07-02,ECOL,Escherichia coli,1761696,Cip,Ciprofloxacin,R\\n99999999999,AAA2,,Urine,2015-07-02,ECOL,Escherichia coli,1761696,Clx,Cefalexin,S\\n99999999999,AAA2,,Urine,2015-07-02,ECOL,Escherichia coli,1761696,Cxm,Cefuroxime,S\\n99999999999,AAA2,,Urine,2015-07-02,ECOL,Escherichia coli,1761696,Ert,Ertapenem,S\\n99999999999,AAA2,,Urine,2015-07-02,ECOL,Escherichia coli,1761696,Fos,Fosfomycin,S\\n99999999999,AAA2,,Urine,2015-07-02,ECOL,Escherichia coli,1761696,Gen,Gentamicin,S\\n99999999999,AAA2,,Urine,2015-07-02,ECOL,Escherichia coli,1761696,Mer,Meropenem,S\\n99999999999,AAA2,,Urine,2015-07-02,ECOL,Escherichia coli,1761696,Nit,Nitrofurantoin,S\\n99999999999,AAA2,,Urine,2015-07-02,ECOL,Escherichia coli,1761696,Taz,Piperacillin + Tazobactam,R\\n99999999999,AAA2,,Urine,2015-07-02,ECOL,Escherichia coli,1761696,Tri,Trimethoprim,R\\n99999999999,AAA1,,Urine,2014-08-03,ECOL,Escherichia coli,1519213,Amp,Ampicillin,R\\n99999999999,AAA1,,Urine,2014-08-03,ECOL,Escherichia coli,1519213,Aug,Co-amoxiclav,S\\n99999999999,AAA1,,Urine,2014-08-03,ECOL,Escherichia coli,1519213,Caz,Ceftazidime,S\\n99999999999,AAA1,,Urine,2014-08-03,ECOL,Escherichia coli,1519213,Cet,Cefotaxime,S\\n99999999999,AAA1,,Urine,2014-08-03,ECOL,Escherichia coli,1519213,Cip,Ciprofloxacin,R\\n99999999999,AAA1,,Urine,2014-08-03,ECOL,Escherichia coli,1519213,Clx,Cefalexin,S\\n99999999999,AAA1,,Urine,2014-08-03,ECOL,Escherichia coli,1519213,Cxm,Cefuroxime,S\\n99999999999,AAA1,,Urine,2014-08-03,ECOL,Escherichia coli,1519213,Ert,Ertapenem,S\\n99999999999,AAA1,,Urine,2014-08-03,ECOL,Escherichia coli,1519213,Fos,Fosfomycin,S\\n99999999999,AAA1,,Urine,2014-08-03,ECOL,Escherichia coli,1519213,Gen,Gentamicin,S\\n99999999999,AAA1,,Urine,2014-08-03,ECOL,Escherichia coli,1519213,Mer,Meropenem,S\\n99999999999,AAA1,,Urine,2014-08-03,ECOL,Escherichia coli,1519213,Nit,Nitrofurantoin,S\\n99999999999,AAA1,,Urine,2014-08-03,ECOL,Escherichia coli,1519213,Taz,Piperacillin + Tazobactam,S\\n99999999999,AAA1,,Urine,2014-08-03,ECOL,Escherichia coli,1519213,Tri,Trimethoprim,R\",\"difficulty\":\"hard\",\"domain\":\"Long Structured Data Understanding\",\"length\":\"medium\",\"question\":\"Which model is best suited for identifying genes related to neuron migration, and what type of dataset was this model trained on?\",\"sub_domain\":\"Table QA\"}","display_format":"text","language":"","answer_status":"published","assets":[],"source_url":"https://huggingface.co/datasets/zai-org/LongBench-v2","history":"initial import","indexing_mode":"noindex","subproblems":[],"grids":[]}