Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 6 of 6 for “"hybrid quantum-classical algorithms"”.
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The Trainability and Expressivity of Quantum Machine Learning Models
… more evidence that precise control of many-body quantum systems yields a method of computation more powerful than what is achievable using conventional models of computation. This culminated in recent years with experimental demonstrations on quantum devices of computational tasks on the verge of …
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Quantum computing for biophysical and optimization problems
The remarkable progress of quantum technologies over recent years has driven significant efforts toward developing algorithms with applications to a wide range of research fields. Beyond fully quantum algorithms — whose efficacy remains constrained by technological limitations — hybrid …
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On Near-Term Quantum Computation: Theoretical Aspects of Variational Quantum Algorithms and Quantum Computational Supremacy
In recent years, programmable quantum devices have reached sizes and complexities which put them outside the regime of simulation on modern supercomputers. However, since their computational power is not well understood, it’s not obvious what to do with them! Of course, there are several ideas, and …
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Accelerating Learning of Quantum Systems using Prior Information
Towards realizing practically useful quantum devices, the sizes of quantum devices are being scaled up. An imminent challenge to scalability is ensuring resource requirements of learning tasks that occur as part of device characterization and execution of quantum algorithms also scale favorably. …
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Using Device Physics and Error Mitigation to Improve the Performance of Quantum Computers
Quantum computers have seen rapid development over the last two decades. Despite this, they are not yet scalable or fault-tolerant (i.e. we cannot address arbitrarily many error-corrected qubits). Therefore, improvements that include consideration of the underlying physics are paramount. To do …
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Investigating Topological Quantum Matter: Machine Learning Topological Phases, Topological Quantum Codes, Interplay of Disorder and Topology via Transport Phenomena and Phase Transitions
Future quantum technologies must meet three inter-locking demands: (i) faithful yet compact representations of strongly–entangled quantum matter, (ii) scalable error-mitigation protocols that tame spatially correlated noise, and (iii) near-term algorithms that coax useful optimisation and learning …