A Riemann-Hilbert formulation for the finite temperature Hubbard model

Inspired by recent results in the context of AdS/CFT integrability, we reconsider the Thermodynamic Bethe Ansatz equations describing the 1D fermionic Hubbard model at finite temperature. We prove that the infinite set of TBA equations are equivalent to a simple nonlinear Riemann-Hilbert problem for a finite number of unknown functions. The latter can be transformed into a set of three coupled nonlinear integral equations defined over a finite support, which can be easily solved numerically. We discuss the emergence of an exact Bethe Ansatz and the link between the TBA approach and the results by J\"uttner, Kl\"umper and Suzuki based on the Quantum Transfer Matrix method. We also comment on the analytic continuation mechanism leading to excited states and on the mirror equations describing the finite-size Hubbard model with twisted boundary conditions.Comment: 43 pages, 13 figures. v2: References added, typos corrected, minor changes to the text. v3: JHEP published version; typos corrected, references added and text improved in Section

CDVSec: Privacy-Preserving Biometrical User Authentication in the Cloud with CDVS Descriptors

We explore the use of CDVS-compressed SIFT descriptors for user authentication via fingerprint matching over the cloud. Previous research has shown that SIFT descriptors are suitable for fingerprint matching, however they do not guarantee user-privacy nor they enable efficient storage and matching. The MPEG CDVS standard is devised to extract compressed SIFT descriptors from natural images and compare them in the compressed domain. CDVS descriptors can potentially prevent recovering the original fingerprints from the compressed descriptor, strengthening user privacy. Also, CDVS descriptors do enable efficient storage and matching, a key factor with bandwidth-constrained mobile devices. We acquire a database of raw fingerprint images and we experiment with different acquisition, compression and matching schemes. Experiments show that CDVS descriptors yield a large number of repeatable, highly distinctive, keypoints from fingerprint images. Proper control over the encoding and matching algorithms shows low false acceptance rates and high true acceptance rates. Finally, we demonstrate the use of CDVS descriptors for cloud-based user authentication experimenting with a mobile client and a remote verification server over a realistic testbed