PORTALE DELLA DIDATTICA

PORTALE DELLA DIDATTICA

PORTALE DELLA DIDATTICA

Elenco notifiche



Introduction to Random Matrices: Theory and Practice (didattica di eccellenza)

01TYWKG

A.A. 2018/19

Course Language

Inglese

Degree programme(s)

Doctorate Research in Fisica - Torino

Course structure
Teaching Hours
Lezioni 20
Lecturers
Teacher Status SSD h.Les h.Ex h.Lab h.Tut Years teaching
Dall'Asta Luca   Professore Associato PHYS-02/A 2 0 0 0 1
Co-lectures
Espandi

Context
SSD CFU Activities Area context
*** N/A ***    
2018/19
PERIOD: MAY - JUNE Dott. Pierpaolo VIVO - King's College of London
PERIOD: MAY - JUNE Dott. Pierpaolo VIVO - King's College of London
Introduction to Random Matrices: Theory and Practice (~22 hours). 1. Simple classification of random matrix models. Gaussian and Wishart ensembles. Warmup calculations: semicircle and Marcenko-Pastur laws via resolvent method. (~3 hours) 2. Level spacing statistics: Poisson vs Wigner-Dyson. (~2 hours) 3. Coulomb gas method. Singular integral equation for the spectral density. (~2 hours) 4. Orthogonal polynomial technique and numerical checks. (~3 hours) 5. Largest eigenvalue of a random matrix. Comparison with Extreme Value Statistics for i.i.d. random variables. Tracy-Widom distribution and third-order phase transitions. (~3 hours) 6. The Replica method. Edwards-Jones formalism. Applications to full and sparse matrices (random graphs). (~4 hours) 7. Cavity method for single instances. Spectral density and extreme eigenpairs. (~3 hours) 8. Free probability. Sum of random matrices. Blue’s function. (~2 hours)
Introduction to Random Matrices: Theory and Practice (~22 hours). 1. Simple classification of random matrix models. Gaussian and Wishart ensembles. Warmup calculations: semicircle and Marcenko-Pastur laws via resolvent method. (~3 hours) 2. Level spacing statistics: Poisson vs Wigner-Dyson. (~2 hours) 3. Coulomb gas method. Singular integral equation for the spectral density. (~2 hours) 4. Orthogonal polynomial technique and numerical checks. (~3 hours) 5. Largest eigenvalue of a random matrix. Comparison with Extreme Value Statistics for i.i.d. random variables. Tracy-Widom distribution and third-order phase transitions. (~3 hours) 6. The Replica method. Edwards-Jones formalism. Applications to full and sparse matrices (random graphs). (~4 hours) 7. Cavity method for single instances. Spectral density and extreme eigenpairs. (~3 hours) 8. Free probability. Sum of random matrices. Blue’s function. (~2 hours)
Modalità di esame:
Exam:
...
Gli studenti e le studentesse con disabilità o con Disturbi Specifici di Apprendimento (DSA), oltre alla segnalazione tramite procedura informatizzata, sono invitati a comunicare anche direttamente al/la docente titolare dell'insegnamento, con un preavviso non inferiore ad una settimana dall'avvio della sessione d'esame, gli strumenti compensativi concordati con l'Unità Special Needs, al fine di permettere al/la docente la declinazione più idonea in riferimento alla specifica tipologia di esame.
Exam:
In addition to the message sent by the online system, students with disabilities or Specific Learning Disorders (SLD) are invited to directly inform the professor in charge of the course about the special arrangements for the exam that have been agreed with the Special Needs Unit. The professor has to be informed at least one week before the beginning of the examination session in order to provide students with the most suitable arrangements for each specific type of exam.
Esporta Word