Quantum rotors with regular frustration and the quantum Lifshitz point

Dutta, A. ; Bhattacharjee, J. K. ; Chakrabarti, B. K. (1998) Quantum rotors with regular frustration and the quantum Lifshitz point The European Physical Journal B - Condensed Matter and Complex Systems, 3 (1). pp. 97-103. ISSN 1434-6028

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Official URL: http://www.springerlink.com/content/6cdlh7yce1l7hk...

Related URL: http://dx.doi.org/10.1007/s100510050287

Abstract

We have discussed the zero-temperature quantum phase transition in n-component quantum rotor Hamiltonian in the presence of regular frustration in the interaction. The phase diagram consists of ferromagnetic, helical and quantum paramagnetic phase, where the ferro-para and the helical-para phase boundary meets at a multicritical point called a (d,m) quantum Lifshitz point where (d,m) indicates that the m of the d spatial dimensions incorporate frustration. We have studied the Hamiltonian in the vicinity of the quantum Lifshitz point in the spherical limit and also studied the renormalisation group flow behaviour using standard momentum space renormalisation technique (for finite n). In the spherical limit ()one finds that the helical phase does not exist in the presence of any nonvanishing quantum fluctuation for m=d though the quantum Lifshitz point exists for all d < 1+m/2, and the upper critical dimensionality is given by d u=3+m/2. The scaling behaviour in the neighbourhood of a quantum Lifshitz point in d dimensions is consistent with the behaviour near the classical Lifshitz point in (d+z) dimensions. The dynamical exponent of the quantum Hamiltonian z is unity in the case of anisotropic Lifshitz point (d<m) whereas z=2 in the case of isotropic Lifshitz point (d=m). We have evaluated all the exponents using the renormalisation flow equations along-with the scaling relations near the quantum Lifshitz point. We have also obtained the exponents in the spherical limit (). It has also been shown that the exponents in the spherical model are all related to those of the corresponding Gaussian model by Fisher renormalisation.

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