Publisher Copyright: AuthorWe provide evidence that commonly held intuitions when designing quantum circuits can be misleading. In particular, we show that 1) reducing the T-count can increase the total depth; 2) it may be beneficial to trade controlled NOTs for measurements in noisy intermediate-scale quantum (NISQ) circuits; 2) measurement-based uncomputation of relative phase Toffoli ancillae can make up to 30% of a circuit's depth; and 4) area and volume cost metrics can misreport the resource analysis. Our findings assume that qubits are and will remain a very scarce resource. The results are applicable for both NISQ and quantum error-corrected protected circuits. Our method uses multiple ways of decomposing Toffoli gates into Clifford...
We present a technique to derive depth lower bounds for quantum circuits. The technique is based on ...
Thesis: Ph. D., Massachusetts Institute of Technology, Department of Electrical Engineering and Comp...
The task of learning a probability distribution from samples is ubiquitous across the natural scienc...
In some quantum algorithms, arithmetic operations are of utmost importance for resource estimation. ...
In this work, we propose a generalization of the current most widely used quantum computing hardware...
We present a post-compilation quantum circuit optimization technique that takes into account the var...
Numerous scientific developments in this NISQ-era (Noisy Intermediate Scale Quantum) have raised the...
The quantum Fourier transform (QFT) is one of the most important quantum operations for numerous qua...
The impressive progress in quantum hardware of the last years has raised the interest of the quantum...
The quantum approximate optimization algorithm (QAOA) is an approach for near-term quantum computers...
Quantum computers offer the potential to extend our abilities to tackle computational problems in fi...
Quantum computers offer the potential to extend our abilities to tackle computational problems in fi...
Quantum computers offer the potential to extend our abilities to tackle computational problems in fi...
As the width and depth of quantum circuits implemented by state-of-the-art quantum processors rapidl...
In quantum computing the decoherence time of the qubits determines the computation time available, a...
We present a technique to derive depth lower bounds for quantum circuits. The technique is based on ...
Thesis: Ph. D., Massachusetts Institute of Technology, Department of Electrical Engineering and Comp...
The task of learning a probability distribution from samples is ubiquitous across the natural scienc...
In some quantum algorithms, arithmetic operations are of utmost importance for resource estimation. ...
In this work, we propose a generalization of the current most widely used quantum computing hardware...
We present a post-compilation quantum circuit optimization technique that takes into account the var...
Numerous scientific developments in this NISQ-era (Noisy Intermediate Scale Quantum) have raised the...
The quantum Fourier transform (QFT) is one of the most important quantum operations for numerous qua...
The impressive progress in quantum hardware of the last years has raised the interest of the quantum...
The quantum approximate optimization algorithm (QAOA) is an approach for near-term quantum computers...
Quantum computers offer the potential to extend our abilities to tackle computational problems in fi...
Quantum computers offer the potential to extend our abilities to tackle computational problems in fi...
Quantum computers offer the potential to extend our abilities to tackle computational problems in fi...
As the width and depth of quantum circuits implemented by state-of-the-art quantum processors rapidl...
In quantum computing the decoherence time of the qubits determines the computation time available, a...
We present a technique to derive depth lower bounds for quantum circuits. The technique is based on ...
Thesis: Ph. D., Massachusetts Institute of Technology, Department of Electrical Engineering and Comp...
The task of learning a probability distribution from samples is ubiquitous across the natural scienc...