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master's thesis
Tensor network algorithm for solving quantum physics on high-performance computing clusters
2023. urn:nbn:hr:166:271117
Barač, Rocco
University of Split
Faculty of Science
Department of Physics

Cite this document

Barač, R. (2023). Tensor network algorithm for solving quantum physics on high-performance computing clusters (Master's thesis). Split: University of Split, Faculty of Science. Retrieved from https://urn.nsk.hr/urn:nbn:hr:166:271117

Barač, Rocco. "Tensor network algorithm for solving quantum physics on high-performance computing clusters." Master's thesis, University of Split, Faculty of Science, 2023. https://urn.nsk.hr/urn:nbn:hr:166:271117

Barač, Rocco. "Tensor network algorithm for solving quantum physics on high-performance computing clusters." Master's thesis, University of Split, Faculty of Science, 2023. https://urn.nsk.hr/urn:nbn:hr:166:271117

Barač, R. (2023). 'Tensor network algorithm for solving quantum physics on high-performance computing clusters', Master's thesis, University of Split, Faculty of Science, accessed 21 April 2024, https://urn.nsk.hr/urn:nbn:hr:166:271117

Barač R. Tensor network algorithm for solving quantum physics on high-performance computing clusters [Master's thesis]. Split: University of Split, Faculty of Science; 2023 [cited 2024 April 21] Available at: https://urn.nsk.hr/urn:nbn:hr:166:271117

R. Barač, "Tensor network algorithm for solving quantum physics on high-performance computing clusters", Master's thesis, University of Split, Faculty of Science, Split, 2023. Available at: https://urn.nsk.hr/urn:nbn:hr:166:271117

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Metadata
TitleTensor network algorithm for solving quantum physics on high-performance computing clusters
Title (croatian)Algoritam tenzorskih mreža za rješavanje problema u kvantnoj fizici na računalnim klasterima visokih performansi
AuthorRocco Barač
MentorLeandra Vranješ Markić (mentor)
MentorSimone Montangero https://orcid.org/0000-0002-8882-2169 (pomoć pri izradi, neposredni voditelj)
Committee memberLeandra Vranješ Markić (predsjednik povjerenstva)
Committee memberPetar Stipanović (član povjerenstva)
Committee memberJosipa Šćurla (član povjerenstva)
GranterUniversity of Split
Faculty of Science
(Department of Physics)
Split
Defense date and country2023-10-25, Croatia
Scientific / art field,
discipline and subdiscipline		NATURAL SCIENCES
Physics
Abstract
With the second quantum revolution currently ongoing, the ability to precisely predict the behavior of many-body quantum systems via computer simulations remains of utmost importance. Tensor networks provide a unique way to simulate these systems classically. This thesis shows how a serial tree tensor network algorithm can be adapted to operate across multiple computer threads, making it possible to manipulate these networks faster on high-performance computing clusters. We show how the idea of the algorithm works on a 2-qubit example by finding the ground state energy in a 1D quantum Ising model lattice. Future improvements should make it possible to manipulate large tree tensor networks based on the algorithms of this thesis and accurately solve many-body quantum physics problems, both in statics and dynamics.
Abstract (croatian)
U sklopu druge kvantne revolucije koja je trenutačno u tijeku, sposobnost preciznog predviđanja ponašanja višečestičnih kvantnih sustava putem računalnih simulacija ostaje od najveće važnosti. Tenzorske mreže pružaju jedinstven način za klasičnu simulaciju takvih sustava. Ovaj rad pokazuje kako se serijski algoritam stablastih tenzorskih mreža može prilagoditi za paralelni rad na više procesorskih jezgara, omogućavajući brže manipuliranje stablastih tenzorskih mreža na računalnim klasterima visokih performansi. Pokazujemo kako ideja algoritma radi na primjeru s 2 qubita pronalazeći energiju osnovnog stanja u 1D kvantnom Isingovom modelu. Buduća poboljšanja trebala bi omogućiti manipuliranje stablastim tenzorskim mrežama temeljenim na algoritmima ovog rada te točno rješavati probleme višečestične kvantne fizike, kako u statici tako i u dinamici.
Keywords
Keywords (croatian)
Languageenglish
URN:NBNurn:nbn:hr:166:271117
Study programmeTitle: Physics; specializations in: major in teaching, major in Astrophysics, major in Biophysics, major in Enviromental physics, major in Computational physics, major in Astrophysics and physics of elemental particles
Course: major in Astrophysics and physics of elemental particles
Study programme type: university
Study level: graduate
Academic / professional title: magistar/magistra fizike (magistar/magistra fizike)
Type of resourceText
File originBorn digital
Access conditionsOpen access
Terms of useLicence In copyright icon
Created on2023-10-26 09:23:55