On Exact Space-Depth Trade-Offs in Multi-Controlled Toffoli Decomposition
Suman Dutta, Siyi Wang, Anubhab Baksi, Anupam Chattopadhyay, Subhamoy, Maitra

TL;DR
This paper analyzes the trade-offs between Toffoli depth and ancilla qubits in multi-controlled Toffoli gate decompositions within Clifford+T frameworks, providing formulas, limitations, and optimal bounds for quantum circuit optimization.
Contribution
It explicitly quantifies the space-depth trade-offs, introduces improved techniques for reducing Toffoli depth, and establishes fundamental lower bounds in Clifford+T decompositions.
Findings
Toffoli depth cannot be exactly $oxed{ ext{log}_2 n}$ using conditionally clean ancilla.
T-Depth lower bound is $oxed{ ext{log}_2 n}$, achieved by a binary tree structure.
Various decomposition methods for Toffoli gates are explored for trade-off implications.
Abstract
In this paper, we consider the optimized implementation of Multi Controlled Toffoli (MCT) using the Clifford T gate sets. While there are several recent works in this direction, here we explicitly quantify the trade-off (with concrete formulae) between the Toffoli depth (this means the depth using the classical 2-controlled Toffoli) of the -controlled Toffoli (hereform we will tell -MCT) and the number of clean ancilla qubits. Additionally, we achieve a reduced Toffoli depth (and consequently, T-depth), which is an extension of the technique introduced by Khattar et al. (2024). In terms of a negative result, we first show that using such conditionally clean ancilla techniques, Toffoli depth can never achieve exactly , though it remains of the same order. This highlights the limitation of the techniques exploiting conditionally clean ancilla [Nie et al., 2024,…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsComputational Geometry and Mesh Generation · Digital Image Processing Techniques · Advanced Numerical Analysis Techniques
