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arXiv:2607.10550

Coherent Quantum Schrodinger Bridge: Two-Boundary Optimal Control for Quantum Algorithm Design

Masayuki Ohzeki

quant-phSubmitted Jul 12, 2026• Announced Jul 14, 2026• 0 citations
arXivHTMLPDF

Abstract

Quantum algorithms are intrinsically two-boundary processes: an input state is prepared, and an output state or subspace is selected as the computational answer. We formulate this observation as a coherent Quantum Schrödinger Bridge (QSB), a pure-state Hamiltonian counterpart of Schrödinger bridge theory in which the endpoint constraint is imposed on state vectors and the transport cost is the quadratic control action. In this setting Aharonov's two-state vector becomes the natural optimal-control pair: a forward state from the input and a backward state from the target. Pontryagin's principle then yields a universal optimal Hamiltonian whose weak value is purely imaginary in the geodesic gauge. Thus weak values are not an auxiliary interpretation; they are the local response functions that quantify the drift of the pre-selected state toward the post-selected boundary. Applying this framework to unstructured search, periodicity finding, and matrix arithmetic, we reconstruct Grover's algorithm, the quantum Fourier transform underlying Shor's algorithm, and quantum singular value transformation (QSVT). The usual circuit components -- oracles, diffusion reflections, controlled phases, and signal-processing rotations -- emerge as Lie-algebraic syntheses of the optimal weak-value drift. This perspective unifies distinct algorithmic paradigms into a single geometric principle: algorithm design is the problem of choosing computational boundary conditions and realizing the corresponding optimal flow.

AI Summary

The paper asks whether quantum algorithm primitives can be organized as minimum-energy unitary transport between prescribed input and output states. It defines a coherent, pure-state “Quantum Schrödinger Bridge” by minimizing $J[H]=\frac12\int_0^T\mathrm{Tr}(H(t)^2)\,dt$, with the target specified up to global phase. Using Pontryagin’s principle, it derives the candidate Hamiltonian $H^*=\frac{i}{2}(|\chi\rangle\langle\psi|-|\psi\rangle\langle\chi|)$, where forward and adjoint states evolve under the same Hamiltonian. It shows that this generator is time-independent and connects it to imaginary weak values through the response identity $\partial_g\log P_A(g)|_{g=0}=2\operatorname{Im}A_w$. Boundary-projector commutators provide a proposed route from the continuous generator to circuit operations. Three applications reinterpret existing primitives. For Grover search, the construction identifies the two-dimensional rotation direction generated by oracle and diffusion reflections, with input–target overlap $1/\sqrt N$. For the QFT, it proposes deriving controlled-phase interactions from Fourier-basis boundary phases. For QSVT, it assigns a rotation angle $\arccos p(\sigma)$ to each singular-value subspace and invokes existing QSP/QSVT synthesis theorems to connect admissible polynomial profiles to phase sequences. No new query-complexity bound or phase-synthesis algorithm is provided. The scope is explicitly restricted to coherent pure-state control, not stochastic, channel, or mixed-state Schrödinger bridges. Direct implementation of the resulting generators is generally unavailable. Unknown target boundaries, including ground states sought by variational algorithms, remain outside the exact construction; intermediate-boundary methods are proposed as future work.

Likely largely AI-generatedOverclaimsUnclear noveltyStrong assumptionsPossible error

Central claim may not hold: The prescribed terminal alignment of the adjoint and target, together with their identical unitary dynamics, forces the proposed optimal Hamiltonian to generate only phase evolution rather than nontrivial state transport. The displayed optimal weak-value formula omits the adjoint norm, whose scale affects the Hamiltonian and cannot generally be discarded for a prescribed transfer time. Application II's claimed exact QFT Hamiltonian is diagonal and therefore cannot map computational-basis states to Fourier superpositions. Application II's assertion that product-state endpoints imply additive optimal cost and decoupled generators fails under the paper's unrestricted global Frobenius-cost optimization.

Written by gpt-6.1-sol from the paper's full text. Automated: it can be wrong.

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7 pages

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Quantum algorithms are intrinsically two-boundary processes: an input state is prepared, and an output state or subspace is selected as the computational answer. We formulate this observation as a coherent Quantum Schrödinger Bridge (QSB), a pure-state Hamiltonian counterpart of Schrödinger bridge theory in which the endpoint constraint is imposed on state vectors and the transport cost is the quadratic control action. In this setting Aharonov's two-state vector becomes the natural optimal-control pair: a forward state from the input and a backward state from the target. Pontryagin's principle then yields a universal optimal Hamiltonian whose weak value is purely imaginary in the geodesic gauge. Thus weak values are not an auxiliary interpretation; they are the local response functions that quantify the drift of the pre-selected state toward the post-selected boundary. Applying this framework to unstructured search, periodicity finding, and matrix arithmetic, we reconstruct Grover's algorithm, the quantum Fourier transform underlying Shor's algorithm, and quantum singular value transformation (QSVT). The usual circuit components -- oracles, diffusion reflections, controlled phases, and signal-processing rotations -- emerge as Lie-algebraic syntheses of the optimal weak-value drift. This perspective unifies distinct algorithmic paradigms into a single geometric principle: algorithm design is the problem of choosing computational boundary conditions and realizing the corresponding optimal flow.
The paper asks whether quantum algorithm primitives can be organized as minimum-energy unitary transport between prescribed input and output states. It defines a coherent, pure-state “Quantum Schrödinger Bridge” by minimizing J[H]=12∫0TTr(H(t)2) dtJ[H]=\frac12\int_0^T\mathrm{Tr}(H(t)^2)\,dtJ[H]=21​∫0T​Tr(H(t)2)dt, with the target specified up to global phase.
Using Pontryagin’s principle, it derives the candidate Hamiltonian H∗=i2(∣χ⟩⟨ψ∣−∣ψ⟩⟨χ∣)H^*=\frac{i}{2}(|\chi\rangle\langle\psi|-|\psi\rangle\langle\chi|)H∗=2i​(∣χ⟩⟨ψ∣−∣ψ⟩⟨χ∣), where forward and adjoint states evolve under the same Hamiltonian. It shows that this generator is time-independent and connects it to imaginary weak values through the response identity ∂glog⁡PA(g)∣g=0=2Im⁡Aw\partial_g\log P_A(g)|_{g=0}=2\operatorname{Im}A_w∂g​logPA​(g)∣g=0​=2ImAw​. Boundary-projector commutators provide a proposed route from the continuous generator to circuit operations.
Three applications reinterpret existing primitives. For Grover search, the construction identifies the two-dimensional rotation direction generated by oracle and diffusion reflections, with input–target overlap 1/N1/\sqrt N1/N​. For the QFT, it proposes deriving controlled-phase interactions from Fourier-basis boundary phases. For QSVT, it assigns a rotation angle arccos⁡p(σ)\arccos p(\sigma)arccosp(σ) to each singular-value subspace and invokes existing QSP/QSVT synthesis theorems to connect admissible polynomial profiles to phase sequences. No new query-complexity bound or phase-synthesis algorithm is provided.
The scope is explicitly restricted to coherent pure-state control, not stochastic, channel, or mixed-state Schrödinger bridges. Direct implementation of the resulting generators is generally unavailable. Unknown target boundaries, including ground states sought by variational algorithms, remain outside the exact construction; intermediate-boundary methods are proposed as future work.
Modern quantum algorithms are increasingly formulated as coherent procedures for implementing polynomial transformations of operators and singular values. This perspective provides a powerful and unifying language for quantum algorithm design, connecting a wide range of distinct problems through five closely related key tools: block-encoding, qubitization, QSP, QSVT and GQSP. Block-encoding embeds non-unitary matrices into larger unitaries; qubitization converts block-encodings into structured operators; QSP, QSVT and GQSP enable polynomial transformations with near-optimal query complexity. Together, these techniques form a general toolkit for transforming matrix functions into implementable quantum circuits. This paper develops these techniques from first principles as a unified framework for constructing quantum algorithms. We apply this framework to representative applications to highlight design principles and demonstrate how distinct algorithms can be constructed from a unified sequence of operator transformations. A central contribution is a systematic decision workflow for selecting the appropriate approach according to the operator structure and the desired transformation polynomial. This perspective clarifies when direct GQSP or through qubitization, or Laurent expansion, or QSVT is most appropriate. We organize algorithmic design into an end-to-end pipeline: identifying the target matrix function, constructing an appropriate block-encoding, determining the relevant spectral domain, designing a polynomial or Laurent-polynomial approximation, synthesizing the phase factors, and translating the transformation into an executable quantum circuit. By applying this unified framework to example applications, we showcase a practical methodology for reasoning, designing, and implementing quantum algorithms based on polynomial transformations.
Schrödinger bridges and entropic optimal transport are usually formulated as stochastic interpolation problems between initial and final probability distributions. In their computational form, the bridge potentials are obtained by Sinkhorn or iterative proportional fitting, and are often regarded as auxiliary scaling functions. We show that for continuously monitored quantum systems, these potentials acquire a direct measurement-theoretic meaning. The mathematical structure of conditional quantum trajectory theory induces a Fokker--Planck equation on quantum state space. Conditioning this diffusion on a terminal distribution or a terminal measurement effect produces a Doob/Sinkhorn potential whose directional derivative along a unitary control vector field is the imaginary part of a generalized weak value. The same construction connects the Schrödinger-bridge viewpoint to the optimal-path framework for continuously monitored trajectories: the backward bridge potential plays the role of an effect-like costate, and its weak-value directional derivative gives the local control signal. By specifying the desired endpoint distribution, the induced drift produced by the Schrödinger bridge solution is the control solution that minimizes the quadratic cost feedback law, guiding the distribution to its desired endpoint. We quantify the control score of the available control Hamiltonian as a logarithmic directional derivative of the bridge potential, or an imaginary weak value. Three explicit examples identify weak measurement as a natural entropic regularization mechanism for quantum state transport and gives a route from Sinkhorn scaling to quantum feedback and Hamiltonian control synthesis for practical optimal control.
Grover's algorithm is one of the most famous algorithms which explicitly demonstrates how the quantum nature can be utilized to accelerate the searching process. In this work, Grover's quantum search problem is mapped to a time-optimal control problem. Resorting to Pontryagin's minimum principle, we find that the time-optimal solution has the bang-singular-bang structure. This structure can be derived naturally, without integrating the differential equations, using the geometric control technique where Hamiltonians in Schr\"odinger's equation are represented as vector fields. In view of optimal control, Grover's algorithm uses the bang-bang protocol to approximate the optimal protocol with a minimized number of bang-to-bang switchings to reduce the query complexity. Our work provides a concrete example of how Pontryagin's minimum principle is connected to quantum computation, and offers insight into how a quantum algorithm can be designed.
The problem of quantum state preparation is one of the main challenges in achieving the quantum advantage. Furthermore, classically, for multi-level problems, our ability to solve the corresponding quantum optimal control problems is rather limited. The ability of the latter to feed into the former may result in significant progress in quantum computing. To address this challenge, we propose a formulation of quantum optimal control that makes use of artificial boundary conditions for the Schrödinger equation in combination with spectral methods. The resulting formulations are well suited for investigating periodic potentials and lend themselves to direct numerical treatment using conventional methods for bounded domains.
Quantum functional programming has been developed through two distinct paradigms in the last few years: Quantum Signal Processing (QSP)-based methods, including the Quantum Singular Value Transformation (QSVT), and methods based on higher-order quantum transformations, such as the Universal Hamiltonian Eigenvalue Transformation (UHET). While UHET performs functional transformations of Hamiltonian dynamics, its relationship to QSP-based techniques has remained unclear despite evident structural similarities. In this work, we resolve this gap by establishing a connection between UHET and QSP-based frameworks; specifically, we show that UHET can be interpreted as a (randomised) linearisation of Generalised QSP (GQSP). Building on this result, we introduce a linearised variant of (Hamiltonian-based) QSVT, which we call Universal Hamiltonian Singular Value Transformation (UHSVT), that enables the efficient transformation of the singular values of any arbitrary matrix AAA encoded in a block of a Hamiltonian, whose dynamics is accessible as a black box, by any sufficiently differentiable complex-valued function fff. Our algorithm requires the sole condition that fff vanishes at the origin, in contrast to previous QSVT-based approaches that assumed either a lower bound on the singular values of AAA or the ability to perform XXX-rotation gates on the induced two-dimensional 'qubitised' subspace.