We give a positive answer to the constant-error formulation of the Aaronson–Kuperberg unitary synthesis problem. For every n, a quantum oracle circuit generated in polynomial time from n alone can approximate the channel of every n-qubit unitary to full diamond-norm error at most 1/2, after a suitable Boolean oracle is chosen. Using the fixed gates H,T,T^\dagger,\mathrm{CNOT}, the circuit has polynomially many qubits, elementary gates, and oracle calls, and its oracle queries have polynomial length. The oracle may depend on the target unitary; the theorem does not give an efficient classical procedure for constructing it.
We give a positive answer to the constant-error formulation of the Aaronson–Kuperberg unitary synthesis problem. For every n, a quantum oracle circuit generated in polynomial time from n alone can approximate the channel of every n-qubit unitary to full diamond-norm error at most 1/2, after a suitable Boolean oracle is chosen. Using the fixed gates H,T,T^\dagger,\mathrm{CNOT}, the circuit has polynomially many qubits, elementary gates, and oracle calls, and its oracle queries have polynomial length. The oracle may depend on the target unitary; the theorem does not give an efficient classical procedure for constructing it.
The unitary synthesis problem (Aaronson-Kuperberg, CCC 2007) asks whether every n-qubit unitary U is computable by efficient quantum circuits relative to some classical oracle f=fU depending on U. Recently, Lombardi-Ma-Wright (STOC 2024) proved that Haar-random unitaries cannot be efficiently synthesized by algorithms that make 1 query (or poly(n) parallel queries) to an arbitrary classical oracle. In this work, we prove several results about the hardness (and easiness!) of variants of unitary synthesis. Our results include: (1) 1-query vs. 2-query unitary synthesis: we prove 1-query lower bounds for synthesizing random permutation unitaries P∣x⟩=∣π(x)⟩, as well as random alternating-basis phase unitaries F2⋅H⊗n⋅F1. This gives 1-query lower bounds for "explicit" families of unitaries that have efficient (even 2-query) synthesis algorithms. (2) Upper bound for complex phase unitaries: we also consider complex phase unitaries ∣x⟩↦αx∣x⟩, which have a clean 2-query synthesis algorithm with no obvious 1-query algorithm. In this case, we prove an upper bound: there are 1-query algorithms (relative to binary phase oracles) that constant-approximate these unitaries in diamond distance. In order to prove our lower bounds, we introduce and analyze two new cryptographic games: the oracle state search game and the oracle Choi state game. Compared to prior work, our framework is mathematically simple, more flexible in what it can prove, and more accurately captures the hardness of synthesizing unitaries that are not "fully random". Finally, we also use the search game to prove a new hardness-of-approximation result for quantum programs (synthesizing unitaries relative to quantum advice) for phase unitaries, giving a sharper separation between 1-query unitary synthesis and quantum programs.
The Unitary Synthesis Problem (Aaronson-Kuperberg 2007) asks whether any n-qubit unitary U can be implemented by an efficient quantum algorithm A augmented with an oracle that computes an arbitrary Boolean function f. In other words, can the task of implementing any unitary be efficiently reduced to the task of implementing any Boolean function? In this work, we prove a one-query lower bound for unitary synthesis. We show that there exist unitaries U such that no quantum polynomial-time oracle algorithm Af can implement U, even approximately, if it only makes one (quantum) query to f. Our approach also has implications for quantum cryptography: we prove (relative to a random oracle) the existence of quantum cryptographic primitives that remain secure against all one-query adversaries Af. Since such one-query algorithms can decide any language, solve any classical search problem, and even prepare any quantum state, our result suggests that implementing random unitaries and breaking quantum cryptography may be harder than all of these tasks. To prove this result, we formulate unitary synthesis as an efficient challenger-adversary game, which enables proving lower bounds by analyzing the maximum success probability of an adversary Af. Our main technical insight is to identify a natural spectral relaxation of the one-query optimization problem, which we bound using tools from random matrix theory. We view our framework as a potential avenue to rule out polynomial-query unitary synthesis, and we state conjectures in this direction.
It is well-known that every n-qubit unitary can be implemented by a 2O(n)-depth quantum circuit using single- and two-qubit gates. It has been open whether exponential depth is *necessary* for general unitaries, even when allowing an unlimited number of ancilla qubits. Here we show, perhaps surprisingly, that all unitaries can be implemented exactly by a circuit of one- and two-qubit gates of depth poly(n) with 2O(n) ancilla qubits. In other words, every n-qubit unitary can be parallelized to polynomial depth. In fact, our depth bound is *linear* in n, which is the best possible, and an exponential improvement on the previous best bound of 2n/2 due to Rosenthal [TQC 2022, Quantum 2026]. Moreover, if we allow unbounded fan-out gates, these circuits can be further reduced to *constant* depth. Our construction takes advantage of a novel relationship connecting the unitary synthesis problem of Aaronson and Kuperberg to locally-decodable codes and private information retrieval from complexity theory and cryptography, and has a natural interpretation in bosonic quantum computation.
A major open problem in quantum complexity is the question of unitary synthesis---namely, is it possible to efficiently implement any unitary, given the ability to evaluate any classical function in superposition? Inspired by a recent work by Brakerski and Yuen (CRYPTO 2026), we propose an ``average-case'' unitary synthesis problem, which asks whether it is possible to efficiently implement a Haar random unitary given access to a random Boolean function. We then demonstrate a superpolynomial query lower bound, establishing that unitary synthesis in this model is impossible.
Along with our main result, we settle in the negative a question Brakerski and Yuen pose, of whether scalable pseudorandom unitaries (PRUs) can be implemented in the ROM-PRU model. In particular, we show that in the ROM-PRU model, no Ω(N1+γ) unitary design on n qubits, where N=2n, can be efficiently achieved for any γ>0. On the other hand, we construct an O(N)-design in poly(n) queries in the same model, surpassing the previously best known results which constructed O(N)-designs.
We show that if quantum commitments exist, then either there is no polynomial-time solution to the unitary synthesis problem, or BPP=NEXP. Thus, showing unconditionally that quantum commitments exist would require answering at least one of two longstanding open questions in complexity theory. We prove our main result as a consequence of a more general lemma, which shows that every unitary in unitaryPSPACE either cannot be synthesized efficiently relative to any classical oracle, or can be synthesized efficiently with an oracle for NEXP search problems. Our lemma has other noteworthy consequences, including that certain oracle separations involving unitaryPSPACE would imply breakthrough classical lower bounds such as NC=NP.
Along the way, we propose new definitions for the unitary complexity classes unitaryP and unitaryPSPACE. Our changes address the biggest conceptual issues with definitions suggested in prior work, and lead to elegant proofs. We study both implementations that erase garbage and implementations that allow it, because we cannot rule out the possibility that the two definitions differ. Nevertheless, we show that both definitions can be viewed as special cases of each other. We also showcase many other ways in which our definitions are robust. For example, we show that unitaryPSPACE has an equivalent characterization as the set of unitary transformations whose entries can be computed to arbitrary precision in polynomial space. Consequently, we deduce that unitaryPSPACE can generically erase garbage, a result that provably fails relative to unitary oracles.