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arXiv:2508.13215

A 1.5-Query Lower Bound for the Unitary Synthesis Problem

Eric Huang

Published Aug 17, 2025• 0 citations
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Abstract

We prove a new lower bound for the unitary synthesis problem in the so-called 1.5-query setting. Our analysis establishes that any attempt to implement arbitrary n-qubit unitaries via limited oracle access requires resources that exceed the fractional query threshold. This result extends the one-query lower bound of Lombardi, Ma, and Wright (2023) to the fractional query regime, and introduces a conservative and chaining-based approach to handle intermediate query complexities. As a consequence, we derive cryptographic implications, showing that pseudorandom quantum states remain secure against adversaries restricted to 1.5 queries. Our work provides both conceptual clarification of fractional-query complexity and practical insights into the design of quantum cryptographic protocols.

DOI
10.48550/arxiv.2508.13215

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We prove a new lower bound for the unitary synthesis problem in the so-called 1.5-query setting. Our analysis establishes that any attempt to implement arbitrary n-qubit unitaries via limited oracle access requires resources that exceed the fractional query threshold. This result extends the one-query lower bound of Lombardi, Ma, and Wright (2023) to the fractional query regime, and introduces a conservative and chaining-based approach to handle intermediate query complexities. As a consequence, we derive cryptographic implications, showing that pseudorandom quantum states remain secure against adversaries restricted to 1.5 queries. Our work provides both conceptual clarification of fractional-query complexity and practical insights into the design of quantum cryptographic protocols.
The unitary synthesis problem (Aaronson-Kuperberg, CCC 2007) asks whether every nnn-qubit unitary UUU is computable by efficient quantum circuits relative to some classical oracle f=fUf = f_Uf=fU​ depending on UUU. Recently, Lombardi-Ma-Wright (STOC 2024) proved that Haar-random unitaries cannot be efficiently synthesized by algorithms that make 1 query (or poly(n)(n)(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)⟩P\lvert x\rangle = \lvert π(x)\rangleP∣x⟩=∣π(x)⟩, as well as random alternating-basis phase unitaries F2⋅H⊗n⋅F1F_2 \cdot H^{\otimes n} \cdot F_1F2​⋅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⟩\lvert x\rangle\mapsto α_x \lvert x\rangle∣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.
We prove near-optimal lower bounds for preprocessing attacks on quantum cryptography in the random oracle model. Specifically, we show that a TTT-query adversary with SSS qubits of non-uniform advice can recover a random key kkk from the nnn-qubit binary phase state ∣ψk⟩∝∑xR(k,x)∣x⟩|ψ_k\rangle \propto \sum_{x} R(k,x) |x\rangle∣ψk​⟩∝∑x​R(k,x)∣x⟩ with probability at most O(T2+STN)O(\frac{T^2 + \sqrt{ST}}{N})O(NT2+ST​​) for N=2nN=2^nN=2n. In contrast, the best known bound for post-quantum one-way functions is O(T2+STN)O(\frac{T^2 + ST}{N})O(NT2+ST​), with a trivial attack at S=NS = NS=N. This demonstrates a new advantage of quantum cryptography over classical cryptography: nnn qubits of communication suffice for security against preprocessing attacks with space up to N2N^2N2 rather than NNN. Our methodology is simple: express the optimal preprocessing attack as the operator norm of a random matrix, and bound this value in expectation over the random oracle via the trace-moment method. These trace moments have a natural interpretation using compressed oracles [Zhandry, Crypto 2019], which we then analyze. This can be viewed as a simplification and generalization of the approach of Liu [Eurocrypt 2023] for proving the security of post-quantum cryptography against preprocessing attacks. We also prove the following results: (1) We tighten Liu's analysis of post-quantum PRGs in QROM, achieving a distinguishing advantage bound of O(T2N+STN)O(\frac{T^2}N + \sqrt{\frac{ST}N})O(NT2​+NST​​). (2) For unitary synthesis, we extend the one-query lower bound of Lombardi-Ma-Wright [STOC 2024] to hold against adversaries that can make one arbitrary function query along with polynomially many (adaptive) queries to the random oracle, either before or after the function query. This also interprets the original LMW24 result in terms of compressed oracles. (3) Finally, we prove a tight O(SN)O(\frac{\sqrt{S}}N)O(NS​​) bound for the pseudorandomness of random binary phase states against space SSS distinguishers.
Given oracle access to an unknown unitary U=eiHU=e^{iH}U=eiH , the fractional query problem asks how many queries are required to implement a noninteger power Ut=eitHU^t=e^{itH}Ut=eitH, 0<t<10<t<10<t<1, when the spectrum is separated from the branch cut by a gap δδδ. Quantum singular value transformation gives an upper bound of O ⁣(1δlog⁡1ε)O\!\left(\frac{1}δ\log\frac{1}{\varepsilon}\right)O(δ1​logε1​) queries for approximation error ε\varepsilonε. We prove a matching lower bound for arbitrary query algorithms. Our argument reduces any NNN-query circuit to the approximation of eitθe^{itθ}eitθ by a trigonometric polynomial with degree bounded by O(N)O(N)O(N), together with Remez inequality. This allows us to establish the lower bound of Ωτ ⁣(1δlog⁡1ε)Ω_τ\!\left(\frac{1}δ\log\frac{1}{\varepsilon}\right)Ωτ​(δ1​logε1​). Consequently, the optimal query complexity for fractional query problem is Θτ ⁣(1δlog⁡1ε)Θ_τ\!\left(\frac{1}δ\log\frac{1}{\varepsilon}\right)Θτ​(δ1​logε1​), showing that the known QSVT construction is asymptotically optimal. We also give an alternative lower bound proof based on constructing a linear functional that annihilates the approximant space, yielding a Ωτ ⁣(log⁡1ε)Ω_τ\!\left(\log\frac{1}{\varepsilon}\right)Ωτ​(logε1​) bound uniform to δδδ.
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)Ω(N^{1+γ})Ω(N1+γ) unitary design on nnn qubits, where N=2nN=2^nN=2n, can be efficiently achieved for any γ>0γ> 0γ>0. On the other hand, we construct an O(N)O(N)O(N)-design in poly(n)\text{poly}(n)poly(n) queries in the same model, surpassing the previously best known results which constructed O(N)O(\sqrt{N})O(N​)-designs.
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.
We show that if quantum commitments exist, then either there is no polynomial-time solution to the unitary synthesis problem, or BPP≠NEXP\mathsf{BPP} \neq \mathsf{NEXP}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\mathsf{unitaryPSPACE}unitaryPSPACE either cannot be synthesized efficiently relative to any classical oracle, or can be synthesized efficiently with an oracle for NEXP\mathsf{NEXP}NEXP search problems. Our lemma has other noteworthy consequences, including that certain oracle separations involving unitaryPSPACE\mathsf{unitaryPSPACE}unitaryPSPACE would imply breakthrough classical lower bounds such as NC≠NP\mathsf{NC} \neq \mathsf{NP}NC=NP. Along the way, we propose new definitions for the unitary complexity classes unitaryP\mathsf{unitaryP}unitaryP and unitaryPSPACE\mathsf{unitaryPSPACE}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\mathsf{unitaryPSPACE}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\mathsf{unitaryPSPACE}unitaryPSPACE can generically erase garbage, a result that provably fails relative to unitary oracles.