SearcharxivSearch

arXiv · 2211.00333

Derivation of a $\PT$-Symmetric Sine-Gordon Model from a Nonequilibrium Spin-Boson System via Keldysh Functional Integrals

Abstract

We present a microscopic derivation from a nonequilibrium spin-boson model to a $\PT$-symmetric non-Hermitian sine-Gordon (SG) effective theory, via the Keldysh functional-integral formalism, a Lang-Firsov polaron transformation, bosonization, and a Grassmann coherent-state spin trace.The spin trace yields the generic reduced vertex $g_r\cos(\lambda\Phi_1)+ig_i\sin(\lambda\Phi_1)$, where the imaginary part originates from the nonequilibrium Keldysh distribution asymmetry $\delta n(\omega)=n_+(\omega)-n_-(\omega)$. We provide an explicit dictionary between the spin-boson microscopic parameters and the NH-SG couplings: $K=v_f/\tilde{J}_\parallel^2$ (Luttinger parameter from $J_\parallel$), $g_r\propto J_\perp^2/\Gamma$ (from the transverse coupling and impurity width), and $\mathcal{I}=g_i/g_r\propto\mu/v_f$ (bias ratio, an exact RG invariant).One-loop Wilson momentum-shell RG on the NH-SG action gives the closed equations $\diff K/\diff l=-g_r^2(1-\mathcal{I}^2)K^2$ and $\diff g_r/\diff l=(2-K)g_r$, identical to those of Ashida \textit{et al.}\ for the $\PT$-symmetric SG; the present work supplies the microscopic initial conditions from the spin-boson Keldysh reduction. The BKT separatrix $K=2$ (Toulouse line), the EP fixed manifold $\mathcal{I}=1$ ($\mu=\mu_c$), and the mass gap $m\sim\Lambda e^{-c/\sqrt{K_0-2}}$ all follow from this closed system.In the non-relativistic soliton sector near the EP, the effective coupling $\tilde{g}=g_r\sqrt{1-\mathcal{I}^2}$ reduces the S-matrix to the Lieb-Liniger rational form and the Bethe ansatz becomes exact for that auxiliary gas.Within this sector we derive $n$-string bound states with$E_n^{\rm bind}=-n(n^2-1)\tilde{g}^2/12$, identify the EP as the many-body bound-state threshold, and construct the Jordan-partner state from the $\epsilon$-regularised dimer.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Vinayak M. Kulkarni. 2022-11-01. Derivation of a $\PT$-Symmetric Sine-Gordon Model from a Nonequilibrium Spin-Boson System via Keldysh Functional Integrals. https://arxiv.org/abs/2211.00333

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

Probing the Error-Mitigation Threshold with Matrix Product States

Quantum error mitigation relies on accurate noise characterization, but mismatches between the actual and characterized noise can be amplified and drive a sharp threshold between successful and failed mitigation. In random circuits, this threshold maps onto a random-field Ising transition, but previous exact numerics were limited to small one-dimensional and all-to-all systems, leaving explicit two-dimensional architectures unresolved. We develop a fixed-bond-dimension matrix-product-state method for the replicated transfer dynamics that extends threshold calculations beyond exact propagation while retaining the finite-size signatures of the transition. At system sizes beyond previous exact studies, we recover the predicted absence of a threshold for quenched disorder in 1D, obtain a sharper annealed all-to-all critical point, and resolve architecture-dependent finite-depth thresholds in 2D square and heavy-hex circuits. These results establish replicated tensor-network dynamics as a practical tool for probing error-mitigation thresholds in large and higher-dimensional noisy circuits.

quant-ph

Low-cost algorithm-to-execution framework for surface-code quantum computing

The execution of useful quantum algorithms on fault-tolerant processors requires more than a mapping from logical gates to encoded operations: the spatial organization, non-Clifford resource supply, and execution schedule must also be determined while keeping physical overhead within practical limits. Although the theoretical hierarchy from logical circuits to fault-tolerant operations is well established, these implementation choices are often specified and optimized separately. Here we develop a low-cost algorithm-to-execution framework for surface-code quantum computing. From hierarchical algorithm descriptions, it constructs dependency-preserving logical schedules and an executable workload capturing logical interactions, operation parallelism, and time-resolved non-Clifford demand, thereby linking logical computation to surface-code organization, resource-state preparation, and fault-tolerant execution in a traceable workflow. We apply the framework to twenty benchmark circuits across seven algorithm families and a hierarchically composed application-scale elliptic-curve discrete-logarithm workload. Physical costs vary substantially even for circuits with similar logical resource counts. Under our direct-rotation calibration, non-Clifford implementation selection reduces space-time volume by up to 241.5 times versus an all-synthesis baseline for the QAOA amplitude-amplification workload. Circuit-specific surface-code layouts reduce routed-latency estimates for all twenty benchmarks; thirteen also reduce space-time volume because communication savings outweigh added spatial overhead. These results show that low-cost fault-tolerant execution depends on computation scheduling and organization, not aggregate logical resource counts alone.

quant-ph

Sample-optimal learning of stabilizer states

It is well-known that learning a pure $n$-qubit stabilizer state $|\psi\rangle$ both requires, and can be accomplished with, access to a number of copies of $|\psi\rangle$ linear in $n$. However, the precise constant coefficient of this scaling does not appear to have been determined. Here we prove that $L_\delta(n)$, the smallest number of copies from which a quantum procedure can identify any stabilizer state with failure probability at most $0<\delta<1/8$, satisfies $n+\lceil\log_2(1/\delta)\rceil-3\leq L_\delta(n)\leq n+\left\lceil\log_2(1/\delta)\right\rceil+4$. We present a polynomial-time quantum learning algorithm that saturates this bound, achieving a constant factor improvement in sample-complexity over previously known approaches. As an immediate corollary, we obtain via the Choi-Jamiolkowski isomorphism an algorithm for learning an unknown $n$-qubit Clifford unitary from $2n+\left\lceil\log_2(1/\delta)\right\rceil+4$ queries, the $n$-dependence of which we show to be optimal. Our proof technique, which involves Fourier analysis on the abelian group $\mathbb{Z}_4^n \times \mathbb{F}_2^{n(n-1)/2}$, seems to be qualitatively different to previous approaches to stabilizer state learning, and may be of some independent interest; in particular, it admits natural generalisations to further problems in quantum learning theory.

quant-ph