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arXiv:2512.16309

Prefix Sums via Kronecker Products

Aleksandros Sobczyk, Anastasios Zouzias

quant-phcs.DSSubmitted Dec 18, 2025• Announced Dec 19, 2025• 0 citations
v1 · Dec 18, 2025v2 · Dec 23, 2025
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Abstract

In this work, we revisit prefix sums through the lens of linear algebra. We describe an identity that decomposes triangular all-ones matrices as a sum of two Kronecker products, and apply it to design recursive prefix sum algorithms and circuits. Notably, the proposed family of circuits is the first one that achieves the following three properties simultaneously: (i) zero-deficiency, (ii) constant fan-out per-level, and (iii) depth that is asymptotically strictly smaller than $2\log(n)$ for input length n. As an application, we show how to use these circuits to design quantum adders with $1.893\log(n) + O(1)$ Toffoli depth, $O(n)$ Toffoli gates, and $O(n)$ additional qubits, improving the Toffoli depth and/or Toffoli size of existing constructions.

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In this work, we revisit prefix sums through the lens of linear algebra. We describe an identity that decomposes triangular all-ones matrices as a sum of two Kronecker products, and apply it to design recursive prefix sum algorithms and circuits. Notably, the proposed family of circuits is the first one that achieves the following three properties simultaneously: (i) zero-deficiency, (ii) constant fan-out per-level, and (iii) depth that is asymptotically strictly smaller than 2log⁡(n)2\log(n)2log(n) for input length n. As an application, we show how to use these circuits to design quantum adders with 1.893log⁡(n)+O(1)1.893\log(n) + O(1)1.893log(n)+O(1) Toffoli depth, O(n)O(n)O(n) Toffoli gates, and O(n)O(n)O(n) additional qubits, improving the Toffoli depth and/or Toffoli size of existing constructions.
In 2004, Cuccaro et al found a quantum-quantum adder with O(n)O(n)O(n) gate cost and O(1)O(1)O(1) ancilla qubits. Since then, it's been an open question whether classical-quantum adders can achieve the same asymptotic complexity. These costs are particularly relevant to modular arithmetic circuits, which often offset by the classically known modulus. In this paper, I construct an adder that uses 3 clean ancillae and 4n±O(1)4n \pm O(1)4n±O(1) Toffoli gates to add a classical offset into a quantum register. I also present an adder with a Toffoli cost of 3n±O(1)3n \pm O(1)3n±O(1) that uses 2 clean ancillae and n−2n-2n−2 dirty ancillae. I further show that applying the presented adders conditioned on a control qubit requires no additional workspace or Toffolis.
We construct an exact nnn-bit quantum adder with O(n)O(n)O(n) gates and O(log⁡n)O(\log n)O(logn) depth that requires no ancillary qubits. The circuit uses only XXX, CNOT, and Toffoli gates under all-to-all connectivity and is classically reversible. Our construction accelerates the controlled ladder underlying addition. Grouping the data into blocks and use existing control qubits as conditional workspace gives a recursive construction with O(nlog⁡log⁡n)O(n\log\log n)O(nloglogn) gates and O(log⁡n)O(\log n)O(logn) depth. We then coordinate inter-block propagation via two short-path forest operations to cut the per-block workspace requirement, yielding a nonrecursive implementation with O(n)O(n)O(n) gates. Both the gate count and circuit depth are asymptotically optimal.
Quantum computing (Q-computing) is a revolutionary technology that applies quantum mechanics (QM) to implement calculations significantly quicker than traditional computers. Q-computing employs Q-bits (qubits) rather than classical bits, which can take on a superposition state, making it possible to represent both 0 and 1 at once. This distinctive property allows qubits to perform multiple calculations simultaneously, making Q computers exponentially more powerful as more qubits are added, compared to the linear scaling of classical computers. However, challenges such as qubit instability and error rates remain significant obstacles to fully realizing this potential. A vital aspect of this technology is the development of Q arithmetic circuits, which act as the foundational blocks for efficiently executing Q algorithms. Q half-adder and full-adder circuits are integral to performing fundamental arithmetic operations within Q computers. In contrast to classical adders, Q adders rely on Q gates such as Controlled NOT (CNOT) and Toffoli gates. These gates exploit Q phenomena like entanglement and superposition, allowing for more efficient computations. The Q half-adder consists of two qubits and adds two single bits, producing a carry and sum output. It utilizes the CNOT gate to compute the sum and the Toffoli gate (controlled-controlled-NOT [CCNOT]) to compute the carry. The Q full-adder builds on this, adding three qubits to produce a sum and a carry output, further increasing computational capacity. Through the entanglement of qubits, these circuits allow for more parallelism and speed compared to classical adders. Q carry-look-ahead adders (QCLAs) and Q ripple-carry adders (QRCAs) are used to perform more complex arithmetic operations based on these half-adder and full-adder structures. Q arithmetic circuits have broad applications, boosting secure key generation in cryptography, speeding up matrix operations for faster model training in machine learning, and enabling more precise, efficient image transformations in Q image processing, benefiting fields like medical imaging and computer vision.
Classical circuits with unbounded fan-in can compute any Boolean function in constant depth when their size is unrestricted. We ask whether removing the restrictions on circuit size and ancillary qubits also allows quantum circuits built from arbitrary single-qubit gates and generalised Toffoli gates to implement every unitary in constant depth. We give exact constant-depth constructions for arbitrary permutations of computational basis states, diagonal unitaries and the preparation of arbitrary pure states. These connect quantum state preparation to reversible classical computation and the preparation of probability distributions. With fanout in the gate set, they use exponentially many gates and ancillary qubits and return all ancillary qubits to zero. Replacing fanout by an exact circuit over the original gate set preserves constant depth, although the size bounds can become doubly exponential. The implementation of arbitrary unitaries in constant depth remains open. We give equivalent formulations in terms of copying the vectors of a specified orthonormal basis, extracting their labels and implementing restricted families of unitaries. We also reduce arbitrary unitary implementation to that of traceless unitary involutions using one additional clean qubit. With adaptive measurements, gate teleportation gives depth proportional to the level of a gate in the Clifford hierarchy. Towards arbitrary unitary implementation in constant depth, we use port-based teleportation: for input dimension ddd and M≥d2−1M\geq d^2-1M≥d2−1 ports, we construct a unitary circuit of depth O(d)O(\sqrt d)O(d​), independent of MMM and including resource preparation and port selection, with entanglement fidelity at least (1−(d2−1)/(2M))2(1-(d^2-1)/(2M))^2(1−(d2−1)/(2M))2. Thus, at fixed ddd, the approximation can be made arbitrarily accurate without increasing depth. Whether the dependence on ddd can also be removed remains open.
This paper presents a method for constructing quantum circuits for schoolbook multiplication using controlled add-subtract circuits, asymptotically halving the Toffoli count compared to traditional controlled-adder-based constructions. Controlled n-qubit add-subtract circuits, which perform an addition when the control qubit is one and a subtraction when it is zero, require only n-1 Toffoli gates, instead of the 2n-1 needed for controlled adders. Despite the existence of multiplication circuits with better asymptotic scaling, schoolbook multiplication yields the lowest Toffoli counts for small register sizes, making it advantageous in practical applications. For example, the presented approach reduces the Toffoli count by up to around 30% in circuits for breaking 256-bit elliptic curve keys compared to circuits with standard schoolbook multipliers.
We present quantum circuits for comparison and increment operations that achieve an asymptotically optimal gate count of Θ(n)Θ(n)Θ(n) and depth of Θ(log⁡n)Θ(\log n)Θ(logn) over the Clifford+Toffoli gate set, while using a provably minimal number of qubits. We extend these results to classical-quantum comparators, yielding an improved classical-quantum adder with an optimal qubit count. Given the ubiquity of these operations as algorithmic building blocks, our constructions translate directly into reduced circuit complexity for many quantum algorithms. As a notable example, they can be used to improve a space-efficient circuit for Shor's factoring algorithm, reducing circuit depth from O(n3)\mathcal{O}(n^3)O(n3) to O(n2log⁡2n)\mathcal{O}(n^2 \log^2 n)O(n2log2n) without increasing either the qubit count or the asymptotic gate complexity. Underpinning these results is a general theorem demonstrating how to trade ancilla qubits for control qubits with low overhead in both depth and gate count, providing a broadly applicable tool for quantum circuit design.