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Visar resultat 1 - 5 av 63 avhandlingar som matchar ovanstående sökkriterier.

1. 1. Reducing Memory Traffic with Approximate Compression

   Författare :Albin Eldstål-Ahrens; Chalmers tekniska högskola; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Memory Compression; Memory Systems; Compression; Computer Architecture; Lossy Compression; Approximate Computing;

   Sammanfattning : Memory bandwidth is a critical resource in modern systems and has an increasing demand. The large number of on-chip cores and specialized accelerators improves the potential processing throughput but also calls for higher data rates. In addition, new emerging data-intensive applications further increase memory traffic. LÄS MER

3. 2. Large-scale simulation-based experiments with stochastic models using machine learning-assisted approaches : Applications in systems biology using Markov jump processes

   Författare :Fredrik Wrede; Andreas Hellander; Ramon Grima; Uppsala universitet; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; bioinformatics; systems biology; stochastic simulation; model exploration; approximate parameter inference; machine learning; distributed computing; Beräkningsvetenskap; Scientific Computing;

   Sammanfattning : Discrete and stochastic models in systems biology, such as biochemical reaction networks, can be modeled as Markov jump processes. The chemical master equation describes how the probability distribution of a biochemical system's states evolves. Unfortunately, solutions to the chemical master equation only exist for trivial problems. LÄS MER

4. 3. The quantum approximate optimization algorithm: optimization problems and implementations

   Författare :Pontus Vikstål; Chalmers tekniska högskola; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; Quantum approximate optimization algorithm; quantum computing; error mitigation; cat qubits;

   Sammanfattning : This thesis explores the Quantum Approximate Optimization Algorithm (QAOA), a hybrid classical-quantum algorithm designed to solve combinatorial optimization problems. The goal of this algorithm is to iteratively optimize a variational state to approximate the ground state of a cost Hamiltonian that encodes a combinatorial optimization problem. LÄS MER

5. 4. Applying quantum approximate optimization to the heterogeneous vehicle routing problem

   Författare :David Fitzek; Chalmers tekniska högskola; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; combinatorial optimization; variational quantum algorithm; Quantum computing; quantum approximate optimization algorithm; vehicle routing;

   Sammanfattning : Quantum computing offers new heuristics for combinatorial problems. With small- and intermediate-scale quantum devices becoming available, it is possible to implement and test these heuristics on small-size problems. LÄS MER

7. 5. Application of the quantum approximate optimization algorithm to combinatorial optimization problems

   Författare :Pontus Vikstål; Chalmers tekniska högskola; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; combinatorial optimization; quantum computing; Quantum approximate optimization algorithm;

   Sammanfattning : This licentiate thesis is an extended introduction to the accompanying papers, which encompass a study of the quantum approximate optimization algorithm (QAOA). It is a hybrid quantum-classical algorithm for solving combinatorial optimization problems and is a promising algorithm to run on near term quantum devices. LÄS MER