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<p><span style="font-size: medium;"><strong>Estimados:</strong></span></p>
<p><span style="font-size: medium;"><strong></strong><strong>Agradecemos la difusión del anuncio del <span class="il">seminario</span> del C<strong>iclo de Coloquios y <span class="il">Seminarios</span> </strong></strong></span></p>
<p><span style="font-size: medium;"><strong><strong>que se organizan en el Instituto de Física La Plata</strong>/ <strong>Departamento de Física. </strong></strong></span></p>
<p><span style="font-size: medium;"><strong><strong>Se adjunta material para difundir en carteleras.</strong></strong></span></p>
<p><span style="font-size: medium;"><strong><br /></strong></span></p>
<p><span style="font-size: medium;"><strong>Saludos, </strong></span></p>
<p><span style="font-size: medium;"><strong></strong><strong>Atte.</strong></span></p>
<p><span style="font-size: medium;"><strong></strong><strong>Administración IFLP</strong></span></p>
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<p align="center"><span style="font-family: arial, helvetica, sans-serif; font-size: large;"><strong><span style="text-decoration: underline;">SEMINARIOS DEL IFLP y DEL DEPARTAMENTO</span></strong></span></p>
<p align="center"><span style="font-family: arial, helvetica, sans-serif; font-size: large;"><strong><span style="text-decoration: underline;">MARTES 21</span></strong><strong><span style="text-decoration: underline;"> de JUNIO a las 11hs</span></strong><strong><span style="text-decoration: underline;"></span></strong></span></p>
<p align="center"><span style="font-family: arial, helvetica, sans-serif; font-size: large;"><strong><span style="text-decoration: underline;">AULA CHICA</span></strong></span></p>
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<p style="text-align: center;"><span style="font-family: arial, helvetica, sans-serif; font-size: medium;"><span style="font-size: large;"><strong><span style="text-decoration: underline;">TÍTULO:</span></strong><strong> </strong><strong>Quantum Pattern Recognition</strong></span><strong><span style="text-decoration: underline;"></span></strong></span></p>
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<pre><span style="font-family: arial, helvetica, sans-serif; font-size: medium;"><strong><span style="text-decoration: underline;">EXPONEN</span></strong><strong>:</strong><strong> </strong></span><strong style="font-family: arial, helvetica, sans-serif; font-size: medium;">Giuseppe Sergioli, Hector Freytes, Federico Holik, Martin Bosyk /University of Cagliari - University of La Plata</strong></pre>
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<p style="text-align: justify;"><span style="font-family: arial, helvetica, sans-serif; font-size: small;"><strong><span style="text-decoration: underline;">R</span></strong></span><span style="font-family: arial, helvetica, sans-serif;"><strong><span style="text-decoration: underline;">esumen:</span></strong></span></p>
<p style="text-align: justify;"><span style="font-family: arial, helvetica, sans-serif;"><strong><span style="text-decoration: underline;"></span></strong></span><span style="font-family: arial, helvetica, sans-serif;"> We introduce a new framework for describing pattern recognition tasks by means of the mathematical language of density matrices.</span></p>
<p style="text-align: justify;"><span style="font-family: arial, helvetica, sans-serif;">In recent years, many efforts to apply the quantum formalism to non-microscopic contexts have been made and, in this direction, important contributions in the areas of pattern recognition and image understanding have been provided. Even if these results seem to suggest some possible computational advantages of an approach of this sort, an extensive and universally recognized treatment of the topic is still missing.</span></p>
<p style="text-align: justify;"><span style="font-family: arial, helvetica, sans-serif;">The natural motivations which have led to use quantum states for the purpose of representing patterns are</span></p>
<p style="text-align: justify;"><span style="font-family: arial, helvetica, sans-serif;">i) the possibility to exploit quantum algorithms to boost the computational intensive parts of the classification process,</span></p>
<p style="text-align: justify;"><span style="font-family: arial, helvetica, sans-serif;">ii) the possibility of using quantum-inspired algorithms for solving classical problems more effectively.</span></p>
<p style="text-align: justify;"><span style="font-family: arial, helvetica, sans-serif;">In our work, firstly we provide a one-to-one correspondence between patterns, expressed as n-dimensional feature vectors (according to the standard pattern recognition approach), and pure density operators (i.e. points in the n-dimensional Bloch hypersphere) called "density patterns". By using this correspondence, we give a representation of the well-known Nearest Mean classifier (NMC) in terms of quantum objects by defining an "ad hoc" Normalized Trace Distance (which coincides with the Euclidean distance between patterns in the real space).</span></p>
<p style="text-align: justify;"><span style="font-family: arial, helvetica, sans-serif;">Consequently, we have found a quantum version of the discriminant function by means of Pauli components, represented as a plane which intersects the Bloch sphere.</span></p>
<p style="text-align: justify;"><span style="font-family: arial, helvetica, sans-serif;">This first result suggests future potential developments, which consist in finding a quantum algorithm able to implement the normalized trace distance between density patterns with a consequent significative reduction of the computational complexity of the process.</span></p>
<p style="text-align: justify;"><span style="font-family: arial, helvetica, sans-serif;">But the main result we show consists in introducing a purely quantum classifier (QC), which has not any kind of classical counterpart, through a new definition of "quantum centroid". The convenience of using this quantum centroid lies in the fact that it seems to be more informative than the classical one because it takes into account also information about the distribution of the patterns.</span></p>
<p style="text-align: justify;"><span style="font-family: arial, helvetica, sans-serif;">As a consequence, the main implementative result consists in showing how this quantum classifier performs a significative reduction of the error and an improvement of the accuracy and precision of the algorithm with respect to the NMC (and also to other commonly used classifiers) on a classical computer.</span></p>
<p style="text-align: justify;"><span style="font-family: arial, helvetica, sans-serif;">The behaviors of QC and NMC on different datasets will be shown and compared.</span></p>
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