Papers

Quantum-state complexity diagnostics provide valuable insight into many-body dynamics, information scrambling, and quantum computation. Here, we investigate the real-time dynamics of quantum complexity in $1+1$-dimensional Abelian U(1) and non-Abelian SU(2) lattice gauge theories (LGTs), focusing on the disorder-free localization (DFL) regime. Using stabilizer Rényi entropy, participation Rényi entropy, and fermionic non-Gaussianity as measures of complexity, we observe, for both theories, two main behaviors as a function of the gauge coupling: at intermediate values, a power-law relaxation towards saturation, consistent with observations in many-body localization, and, at sufficiently large values, an ultraslow double-logarithmic growth, which we substantiate with a configuration-space bound verified by exact counting. Our results not only provide deeper insight into the dynamics of DFL but also highlight the role of gauge invariance in constraining quantum resources and are relevant to recent quantum simulations of LGTs.

We show that the hierarchy of quantum correlations produced in deep-inelastic scattering (DIS) can serve as a novel probe of the proton's nonperturbative structure. Specifically, we show that quantum entanglement, discord, steering, and magic provide nontrivial and complementary sensitivities to the nucleon's parton distribution functions (PDFs), particularly those encoding the transverse-spin polarization of the interacting quark. This connection leads to a unique probe of the proton's parton-level tensor charges with implications for beyond Standard Model (BSM) physics searches. We propose how quantum information measures can be utilized for precision studies of hadron structure at DIS experiments like the upcoming Electron-Ion Collider (EIC).

We construct an anomalous Floquet topological phase on a negatively curved hyperbolic lattice. The model is a tight-binding Hamiltonian with a periodically repeated four-color edge-hopping sequence and a sublattice-staggered onsite potential step. The topological regime is reached near the limit in which a single hopping step transfers amplitude completely across an active edge, while the trivial regime is reached near the point where two full hops occur along an active edge during a single hopping step, returning the amplitude to its starting site. In finite open patches, the topological regime is characterized by bulk quasienergy gaps at $0$ and $\pi$ that are populated by in-gap states, in contrast to a trivial regime where these gaps remain empty. Using compact periodic lattices, we map the bulk $0$ and $\pi$ quasienergy gaps and identify the gapped regions connected to the trivial and anomalous open-boundary spectra. We diagnose the in-gap states as chiral boundary modes by their real-space dynamics. Finally, we introduce a small-boundary spectral-flow diagnostic based on punctured periodic hyperbolic lattices, which avoids the ambiguity associated with the extensive outer boundary of finite hyperbolic patches. This puncture-based diagnostic should be useful for studying other topological hyperbolic systems.

A standard laser beam has photon degeneracy, or coherence, $\mathfrak{C}$, of at most $8\mu^2$, where $\mu$ is the number of photons in the laser itself. Even quantum-engineered lasers, if required to produce a beam with the standard statistical properties, have limited coherence, scaling as $\mu^4$. Moreover, such lasers (still unrealised) require very unconventional gain and output-coupling mechanisms. Here, we propose a different path to increasing $\mathfrak{C}$: cascaded linear amplifiers, with conventional couplings. By dropping the requirement on the beam's properties, this approach can, in theory, achieve $\mathfrak{C}$ scaling exponentially in $\mu$. Here $\mu$ is the total source excitation number, across all the amplifiers. Two amplifiers suffice to surpass the standard $\mu^2$ scaling.

Harnessing finite-time nonadiabatic transitions that are conventionally associated with quantum inner friction for useful work extraction remains an open experimental challenge. Here we address this issue by introducing and experimentally realizing an innovative measurement-feedback quantum information engine model in the trapped 40Ca+ ion system, in which the projective measurement replaces the hot reservoir as a nonthermal energy source and the feedback control conditionally steers the system through either unitary compression-expansion strokes or thermalization. We experimentally show that the repeated feedback cycle converges to a stable operating regime with a resolved energetic balance, and, by controlling the measurement angle and stroke duration, measurement-induced coherence and the finite-time nonadiabatic contribution can enhance work extraction and raise the efficiency above the corresponding Otto benchmark. The experimental results further show that, over finite ranges of stroke durations, the efficiency and intrinsic cycle power can increase simultaneously. Our experiment establishes a route toward information-to-work quantum engines that convert finite-time irreversibility into performance-enhancing resources.

Lifted product (LP) codes form an important class of quantum error correcting codes with favorable code parameters. We introduce a systematic construction of LP code families based on group extensions and graph lifts. The construction increases the code size while preserving the local structure of the Tanner graph, and relates code parameters, logical operators, and fault-tolerant logical-operation gadgets within the families through chain and cochain maps. As a first application, we obtain LP codes with better code parameters than previously reported ones. We then demonstrate that code-surgery gadgets can be transferred across the selected finite lifts through chain maps and, in several cases, implemented with lower space overhead. We also develop parallel product surgery for lifted clustered cyclic codes. Finally, we propose lifting as a systematic first step toward defining thermodynamic families for algebraically defined qLDPC codes without an underlying Euclidean lattice. For several base codes and selected lifts, coherent information exhibits finite-size crossings, while our results also indicate that additional conditions are needed to determine a unique family.

Preparation of optimal measurement states is a key requirement in quantum metrology utilizing squeezed states. We discuss a geometric framework that transforms an initially misaligned squeezed input into a measurement-optimal state in SU(2)-symmetric systems. Within this framework, the orientation of the squeezing ellipse constitutes an additional geometric degree of freedom and evolves as the mean state follows a controlled trajectory on the unit sphere. The resulting rotation of the ellipse is determined by the geometry of the path and, for the relevant class of transformations, depends on the solid angle enclosed by the trajectory, establishing a connection with the geometric phase. The discussed framework is applicable to different physical platforms. As a particular example, we consider polarization-squeezed light and outline a possible implementation using a continuously varying birefringent element.

We study the problem of learning an unknown Markovian open-system generator from access to its physical time evolution. This generator, called a Lindbladian, contains Hamiltonian and dissipative coefficients indexed by an exponentially large family of possible Pauli terms. We propose an efficient algorithm that learns arbitrary Lindbladians from time evolution under minimal assumptions. For a Lindbladian of dynamical strength at most $\Lambda$, the algorithm estimates every coefficient to error $\epsilon$ using $\widetilde O(\Lambda^2/\epsilon^2)$ experiments and $\widetilde O(\Lambda/\epsilon^2)$ total evolution time, together with polynomial classical running time. The algorithm consists of two nonadaptive, ancilla-free, and control-free stages: 1. The support-learning stage outputs a candidate support of size $\mathrm{poly}(\Lambda/\eta)$ that contains every Hamiltonian and dissipative coordinate of magnitude at least $\eta$, using $\widetilde O(\Lambda^2/\eta^2)$ experiments with preparations of product Pauli eigenstates and single-qubit Pauli measurements. 2.The coefficient-learning stage estimates all coefficients in any candidate support of size $M$ to error $\epsilon$, using $\widetilde O(\Lambda^2\log M/\epsilon^{2})$ experiments with preparations of random stabilizer states and measurements in random Clifford bases. Composing the two stages identifies and estimates every coefficient of an arbitrary Lindbladian in polynomial time. The experiment-count and total-evolution-time scalings match the lower bounds up to logarithmic factors, so the algorithm is nearly optimal for learning arbitrary Lindbladians.

High-rate quantum low-density parity-check (qLDPC) codes encode many logical qubits with low physical-qubit overhead, but realizing efficient fault-tolerant computation on such dense encodings remains a major challenge. Generic, code-agnostic techniques such as code surgery and gate teleportation apply broadly, but are difficult to make modular, low-overhead, and fully certifiable on complex high-rate codes whose structure is left unexploited. Here we overcome these obstacles by co-designing the code together with its logical instruction set for a broad family of canonical lifted-product (LP) codes with cyclic symmetry. We show that these codes admit a canonical logical basis, in which conjugate logical operators are organized into rows and columns of cyclic orbits inherited directly from the underlying classical codes, analogous to the structure that makes hypergraph-product codes so tractable. This canonical basis enables universal logical processing using magic-state input and a constant number of reusable seed surgery gadgets—only two (resp. four) for a $[[1122,148,\leq 20]]$ (resp. $[[4350,1224,\leq 20]]$) LP code. A fixed extractor smaller than half the data block also enables arbitrarily high-weight logical Pauli-product measurements (PPMs) while preserving the code's cyclic symmetry. These codes also enable rigorously fault-tolerant parallel logic, including PPMs across all logical qubits and magic-state injection from many surface codes into a full LP block. For example, a $[[468,36,20]]$ (resp. $[[952,112,17]]$) code supports simultaneous measurements of arbitrary logically disjoint Pauli products with an ancilla overhead of roughly three (resp. four) times the data block size. These results advance the frontier of fault-tolerant quantum computation on ultra-high-rate quantum architectures.

The unclonable bit question asks whether quantum encryption can prevent an adversary from producing two systems that both reveal the plaintext once the key is disclosed. We introduce and study Pauli Encodings, a simple class of one-bit encryption schemes whose ciphertexts are normalized eigenspace projectors of Pauli strings. For every Pauli Encoding with K Pauli strings, we prove a universal lower bound $1/2+1/(2\sqrt{K})$ on the optimal monogamy-of-entanglement winning probability, together with sharper bounds for several structured families. We then establish two limitations of natural approaches to unclonable security. First, if the Pauli strings are restricted to strings of X and Z of length n, the encoding is not secure. Second, we identify a universal 3/4 obstruction showing that arguments based only on pairwise guessing marginals cannot establish unclonable-indistinguishable security. When the Pauli strings all pairwise anticommute, the protocol becomes the one studied in [Quantum 10, 2157 (2026)]. We exploit the symmetry of this protocol to solve the third level of the natural semidefinite programming relaxation obtaining an asymptotic upper bound of approximately 0.5556 on the winning probability. Finally, we prove strong unclonable-indistinguishable security against bounded-local-dimension adversaries and strong indistinguishability security for several efficient Pauli families. First-level NPA computations provide additional numerical evidence towards the strong unclonable-indistinguishable security.

Fault-tolerant protocols often consist largely of stabilizer subcircuits, yet the non-Clifford operations required for universality make exact sampling costly. We present SymFT, a high-throughput simulator for Clifford-dominated circuits with Pauli rotations, stochastic Pauli noise, mid-circuit Pauli measurements, and measurement-record-controlled Pauli feedback. It combines two ideas. First, symbolic Clifford–Pauli frame factorization reduces branch-probability sampling to Pauli rotations and measurement projectors, with noise and feedback represented by symbolic signs. Since the residual Clifford and Pauli frames are unitary, they do not affect branch probabilities and need not be applied in every shot. Second, adaptive stabilizer-coordinate planning uses a shared stabilizer–destabilizer tableau to define the basis and stores only the active non-stabilizer degrees of freedom in a dynamically sized dense active-state vector. It resolves basis changes once and emits direct multi-coordinate sampling instructions, thereby avoiding per-shot tableau updates and localization-induced Clifford transformations of the dense vector. Across the tested pure-Clifford and near-Clifford circuits, SymFT achieves state-of-the-art sampling performance. On a single CPU core, it achieves a $2.51\text{--}2.56\times$ speedup over Stim for surface-code circuits and a $1.86\text{--}3.51\times$ speedup over Clifft for magic-state cultivation and distillation circuits. For the tested cultivation circuits, its GPU sampling throughput also exceeds that of our previous simulator, SOFT, by more than two orders of magnitude.

In this article, we present an explicit family of invertible $n\times n$ matrices over $\mathbb Z_2$ whose CNOT and row complexity is at least $4n-\text{o}(n)$; equivalently, reducing these matrices to the identity requires at least $4n-\text{o}(n)$ elementary row operations. Moreover, the same complexity lower bound holds in the stronger computational model where the CNOT gates are replaced by arbitrary local linear logic gates, namely arbitrary invertible linear transformations acting on pairs of coordinates. Let $G_n$ denote the permutation group generated by local logic gates acting on the set of binary strings of length $n$. We prove that $G_n$ is naturally isomorphic to the group of all invertible affine transformations of the vector space $\mathbb Z_2^n$, thus reducing the problem of estimating the quantum complexity of permutations in $G_n$ to the row reduction complexity of invertible matrices over $\mathbb Z_2$. As an application, we show that the permutations associated with our explicit matrices have quantum complexity at least $4n-\text{o}(n)$.

The physics of quantum chaos and diffusive transport is typically studied in settings with microscopic disorder or many-body interactions. In this Letter, we demonstrate that these phenomena can arise purely from geometric randomness. By studying non-interacting quantum particles on random locally tree-like layered graphs with uniform couplings, we show that the geometric randomness and effective graph dimensionality dictates the presence of chaotic dynamics or lack thereof. These graphs can be considered as structurally disordered generalisations of regular square lattices or ladders, or equivalently as multi-component one-dimensional chains with random links between the components. We find that an extensive layer size yields robust quantum chaos, level repulsion, and diffusive transport. Conversely, in the quasi-one-dimensional limit, we find the coexistence of extensive number of localised and delocalised states – this leads to suppressed level repulsion accompanied by the latter driving ballistic transport. These results establish geometric randomness as a fundamental and independent mechanism for generating and tuning quantum chaos.

Cloud-accessible quantum computing has made hardware comparison not only a physics benchmark but also a practical purchasing decision. Cost-aware comparison of quantum computers remains underexplored and is difficult to do under the heterogeneous billing models offered by various cloud-based quantum computing providers. This paper makes two main contributions to enable price-aware comparison of quantum computers. First, this work presents a cross-provider measurement study of quantum circuit execution fidelity spanning 14 cloud QPU access-path entries (12 distinct physical QPUs) across four cloud access paths: Amazon Web Services (AWS) cloud, IBM Quantum Runtime (IBM) cloud, IQM Resonance (IQM) cloud, and Oxford Quantum Circuits (OQC) cloud. Second, this work proposes and analyzes a cost-aware score, Quantum Fidelity-per-Cost (QFC), which combines Kullback–Leibler (KL) divergence from an ideal output distribution, shot count, and monetary cost into one possible metric under a documented billing model. The main empirical observation from this work is that cost-aware ranking can differ from purely fidelity-based evaluation of quantum computers, and that users may select different quantum computing backends when they consider price in their selection, as opposed to selection based on fidelity alone. This work shows that the ranking is stable under reweighting of the metric, and that a device's billing model, not its hardware, governs how its score scales with shot count. Reported QFC values change as new machines come online or as providers revise their prices.

As quantum computing matures, it is critical to benchmark its real-world problem solving performance against competitive classical methods, such as tensor networks. In this work, we leverage the Density Matrix Renormalization Group (DMRG) algorithm to compute ground state energies of the Lipkin Meshkov Glick (LMG) model as a comparative benchmark against popular noisy intermediate-scale (NISQ) algorithms like the Variational Quantum Eigensolver (VQE) and Sample-Based Quantum Diagonalization (SQD) method. By running DMRG on the NERSC Perlmutter supercomputer, we provide one of the largest LMG ground state energy datasets in literature, containing accurate ground state energies for systems up to 1400 particles. We compare these results with VQE and SQD implementations on an IBM Eagle quantum computer for comparison. VQE achieved results within 1 percent error for 6 particles, while exceeding that threshold for all other values while SQD extended that range to 17 particles, suggesting that in a noisy intermediate scale quantum era, subspace-based approaches may strike the best balance between accuracy, circuit depth, and noise resilience.

Unconditional uncloneable encryption of a single bit with efficient encryption and decryption is now possible. However, whether the extension to messages of arbitrary length achieves statistical security remains to be known. Using the fact that the encoding bases for the single-bit scheme known to be secure consist of a subset of the Clifford unitaries, we show that this scheme can be upgraded to achieve unconditional uncloneable encryption for messages of arbitrary length, with encoding time polynomial in the message length and security parameter. This establishes that one-time uncloneable encryption of arbitrary messages enjoys statistical security.

We demonstrate a quantum-classical workflow for ab initio molecular dynamics (AIMD) in which quantum measurements from a chemistry-inspired LUCJ ansatz are post-processed using Sample-based Quantum Diagonalization (SQD) to recover determinant subspaces and deliver energies and analytical nuclear gradients for dynamics. As an exact benchmark, we use full configuration interaction (FCI) in the STO-3G basis, enabling a direct assessment of the accuracy of SQD. In gas-phase benchmarks, SQD reproduces FCI energies and gradients to within 1 kcal mol$^{-1}$ of the FCI reference and yields stable AIMD trajectories. In explicit-solvent QM/MM simulations, SQD retains this agreement, matching FCI energy fluctuations and RMS gradient profiles and reproducing solute-solvent structure as quantified by radial distribution functions. Overall, these benchmarks establish LUCJ+SQD as a practical route for integrating current quantum hardware into QM/MM molecular dynamics and provide an early demonstration of condensed-phase QM/MM dynamics driven by a quantum electronic-structure engine.

We develop a hybrid qubit–qumode algorithm for nonlinear ordinary differential equations of the form $\dot{\mathbf{x}}=\mathbf{f}(\mathbf{x})$ with drift of polynomial degree~$L$. Following the Fokker–Planck route of Tennie and Magri, the algorithm propagates the state density and returns the deterministic trajectory as the peak of that density in the small-noise limit. The discretised generator is carried into a parametrised family of Schrödinger equations by the warped-phase transformation of Jin, Liu, and Yu, and the Fourier-mode parameter of that family is placed on a single continuous-variable qumode. Our central structural result is that the Hermitian parts $H_{1}$ and $H_{2}$ of the discretised generator admit a bipartite Pauli decomposition that sorts the non-zero Pauli strings into $\mathcal{O}(\log N)$ mutually commuting families and factorises each family into a diagonal of degree at most $L$ tensored with a fixed rank-two bond operator. The factorisation renders each family exponential an exact product of $\mathcal{O}(n^{L})$ monomial-controlled momentum displacements, with no intra-family Trotter error. On a $d$-dimensional grid of $N=2^{n}$ points per axis the circuit costs $\mathcal{O}(d^{L+1}n^{L+2})$ gates per Trotter step. No sparse-access oracle and no block encoding is invoked: every gate is fixed in closed form by the polynomial coefficients of the drift. We also prove a bound on the numerical abscissa $\lambda_{\max}(H_{1})$ that fixes the recovery domain of the warped-phase transform and the post-selection cost. A classical simulation on two nonlinear benchmarks confirms the structural theorems, the shifted recovery, and the accuracy-per-resource advantage of the continuous-variable coupling over a discretised mode register.

At high temperature, quantum Gibbs states retain several classical features of the maximally mixed state: the absence of entanglement, the absence of magic, analyticity of the partition function, correlation decay, and algorithmic tractability. We prove new and sharp bounds showing that these features persist down to finite temperatures independent of system size, but fail at distinct inverse-temperature scales, forming a hierarchy of classical-to-quantum transitions. Our results hold for long-range Pauli interactions with bounded strength at every site. Despite such all-to-all interactions, we show that the death of entanglement occurs at constant temperature, resolving an open question of Rouze, Franca and Alhambra (STOC'25). We give a polynomial-time classical algorithm that prepares Gibbs states up to the death of entanglement transition. Notably, this is asymptotically colder than temperatures at which quantum Gibbs samplers are known to mix quickly, as well as the original separability temperature of Bakshi et al. (FOCS'24), which we improve to be tight up to constants. At asymptotically even colder temperatures, we show that the Gibbs state remains in the thermodynamic infinite-temperature phase. We give polynomial-time classical algorithms for estimating thermal expectations up to the phase transition (despite both entanglement and magic), and as a corollary resolve a correlation decay conjecture of Harrow, Mehraban and Soleimanifar (STOC'20).

We give a quantum signal processing (QSP) algorithm for the overlap fermion Hamiltonian which preserves the Ginsparg-Wilson relation up to a controllable error $\epsilon_e$. Quantum simulations of Dirac fermions with exact chiral symmetry are thus nearly free: applying the overlap Hamiltonian costs only a factor logarithmic in $\epsilon_e$ more than the Wilson-Dirac Hamiltonian. Comparing to domain-wall fermions, a mild overhead is found in circuit complexity while reducing qubit costs. We show how QSP effectively constructs an extra dimension when simulating the overlap operator, illustrating that the scaling of quantum algorithms reflects the deeper physics of overlap fermions arising at the boundary of domain-wall fermions.

We prove that every ironed two-qubit gadget whose KAK-derived parameter satisfies $a=5/9$ has, on the complete graph $K_n$ with $n\geqslant 5$, the same second-moment spectral gap as the iSWAP gadget. The central step is a representation-theoretic localisation theorem: the largest strictly negative eigenvalue of the associated $\mathfrak S_n$-invariant operator always occurs in the highest-spin $\mathrm{SU}(2)$ summand. A local positive-semidefinite decomposition separates every spin sector except the two highest. This settles a conjecture of Kong, Li, and Liu.

Fault-tolerant quantum computing requires system-level coordination of logical primitives. Here, we establish a logical compilation framework for the color code, grounded in its topological structure and supporting universal logical operations. Based on its anyon-condensation and domain-wall structure, we introduce a spacetime block-diagram representation capturing logical patches and operations and derive the rules governing block assembly. A correspondence with ZX diagrams further identifies the logical semantics of this representation and enables transformations that preserve the represented computation. Moreover, we develop a code-derived compilation strategy that converts ZX representations of logical computations into valid color-code spacetime layouts. In this strategy, edge-decorated ZX diagrams tailor the logical representation to the color code under the block-assembly constraints, and fusion-region-aware routing exploits semantic equivalence during geometric embedding. We automate the complete logical compilation process and demonstrate successful compilation across a broad range of algorithms. Our work advances color-code architecture from individual primitives to the automated synthesis of logical computations, marking a significant step toward its full-stack quantum computing.

Wave equations provide a natural testbed for near-term quantum simulation of partial differential equations, but hardware demonstrations have remained limited in spatial dimension, equation class, system size, and physically meaningful output. We develop and benchmark structure-preserving, Fourier-based quantum circuits for the one- and two dimensional acoustic wave equations and Dirac dynamics with variable mass on the Quantinuum H2-2 trapped-ion processor. The experiments include one-dimensional grids with up to \(1024\) points and \(32\times32\) two-dimensional grids, corresponding to an encoded state-space dimension of up to \(4096\). Rather than reconstructing the full fields, we estimate subdomain kinetic energies directly from measurement samples. Across all tested acoustic and Dirac dynamics problems, the H2-2 results track the classical kinetic-energy dynamics with mean absolute errors between \(5.9\times10^{-3}\) and \(2.4\times10^{-2}\). At fixed retained bandwidth, the compiled gate counts grow approximately quadratically with the number of grid qubits; the acoustic circuit sizes are essentially independent of evolution time, whereas the cost also grows with the number of product-formula steps. These results provide hardware-level evidence that accurate observable dynamics can remain resolvable for structured wave problems with thousands of encoded degrees of freedom on a present-day trapped-ion processor.

Broadband squeezed light functioning as a Markovian reservoir can exponentially enhance light-matter interactions, benefiting quantum technologies. However, conventional single-cavity sources face a trade-off between squeezing depth and spectral bandwidth. We propose a scalable scheme for generating broadband squeezed vacuum using a cascade of parametric microring resonators coupled to a common bus waveguide. By analyzing the output, we identify the specific conditions that yield a broad, flat-topped squeezing spectrum, even under realistic intracavity pump attenuation. We demonstrate that this architecture is robust against fabrication imperfections, including inhomogeneous resonator frequencies and component failures. We show that the flat-topped spectrum converges to the Markovian limit significantly faster than a single-cavity Lorentzian profile. An array of as few as $N=5$ coupled resonators with an intrinsic loss ratio of $\kappa_I/\kappa = 0.1$ reduces the required bandwidth to a quarter of that needed by a single cavity to achieve same squeezing. This rapid convergence relaxes the low-$Q$ and high-gain constraints of single broadband cavities, distributing the squeezing process across moderately pumped resonators to provide a practical route for engineering squeezed reservoirs on mature integrated photonic platforms.

In the original Hayden–Preskill recovery, the post-injection scrambler and initial state are not related. We extend this setup in two ways: by using a SWAP gate so that the scrambler and initial state are related, and by considering recovery at finite temperature. For this modified protocol, we show that the information is successfully recovered in the sense that the postselection probability is non-negligible and the conditional fidelity is large. We find that both the postselection probability and the conditional fidelity are proportional to temperature, reflecting the reduced entanglement of the initial state at lower temperatures. We also derive their late-time analytic estimates under the assumption of uniform operator spreading and show that they agree well with the numerical results. This demonstrates that strong scrambling is important for successful information recovery. Implementing the protocol on an IBM superconducting processor using a binary sparse SYK Hamiltonian with $N = 8$ Majoranas, we observe that the data retain the qualitative recovery dynamics and that a SWAP-based error-mitigation scheme improves both the postselection probability and the conditional fidelity.

Single T centers in silicon have emerged as promising optically active spins for quantum networking applications. One of the major obstacles to advancing the system is their broad optical linewidth due to spectral diffusion, which is two orders of magnitude larger than their cavity-enhanced radiative linewidth. We tackle this issue by utilizing above-band optical excitation delivered via a laser scanning microscope to device-coupled single T centers, achieving up to 70% optical linewidth reduction. We attribute the linewidth narrowing effect to the filling of nearby charge traps by photo-generated free carriers. We analyze charge stabilization dynamics by exploiting pulsed above-band excitation and develop a rate equation model to describe the dynamics and to explain the observed linewidth narrowing and center shift. This work provides an effective pathway to control and reduce the optical linewidth for single T centers, clearing one of the major roadblocks to advance the single T center spin platform for quantum information and networking applications.

We show that global optimal control can drastically suppress the impact of decoherence in globally driven superconducting quantum computing architectures, taking as a prototype a recently proposed quasi-two-dimensional ladder geometry. Using a tensor-network-based approach, we quantify how amplitude-damping and dephasing channels degrade the flow of quantum information along the ladder and the fidelity of one- and two-qubit gate operations. We then demonstrate that shaping the global drive compresses the gate sequences by an order of magnitude in time, restoring high gate fidelities. We stress that this mitigation is far from trivial: in a globally driven processor, dissipation acts on every physical qubit—including those outside the logical register that sustain the surrounding ordered phases—so its impact cannot be suppressed by protecting an isolated subsystem, and is instead overcome purely through the temporal shaping of the global drive.

We investigate quantum steering and nonlocal correlations between two electrons in a two-dimensional electron gas (2DEG) as functions of Rashba spin-orbit interaction (RSOI) strength and inter-electron separation. We focus particularly on the Bi/Ag(111) system characterized by its strong RSOI ($\alpha_0 = 3.05\times10^{-11}$ eV~m), and we explore the influence of tuning intensity of RSOI and inter-electron distance on the dynamics of Bell nonlocality, uncertainty-induced nonlocality and steering. We find that, although increasing $\alpha_R$ initially suppresses quantum correlations, all three metrics exhibit a non-monotonic recovery as functions of $\alpha_R$, peaking near an optimal coupling strength $\alpha_R = 4.32\times10^{-11}$~eV~m across the range of inter-electron separations considered. This finding establishes RSOI as a critical control parameter for stabilizing quantum properties in two-dimensional electron gases against the decay of quantum correlations with inter-electron separation, and shows that the suppression and recovery of quantum resources within the Bi/Ag(111) system can be controlled by adjusting the inter-electron distance and carefully tuning the RSOI strength.

Fourier-based methods are among the most widely used techniques for pricing European options when the characteristic function of the underlying asset process is available. Their applicability to increasingly fine discretizations, however, is limited by the rapidly growing memory requirements of classical Fourier transforms, which become a computational bottleneck for large-scale pricing problems. In this work, we overcome this limitation by reformulating the Carr-Madan pricing framework using tensor networks. Specifically, we employ the Superfast Fourier Transform (SFFT), a compressed Tensor Train representation of the Quantum Fourier Transform (QFT), and apply it directly to tensorized option pricing without ever explicitly constructing exponentially large vectors or Fourier operators. This formulation also enables a direct comparison between the classical tensor network algorithm and its quantum counterpart through QFT-based option pricing on quantum simulators and quantum hardware. Numerical experiments for European call options demonstrate that the proposed SFFT method maintains pricing accuracy while substantially reducing memory requirements and achieving subexponential computational scaling compared with conventional FFT-based pricing. The accompanying quantum simulations and hardware executions enable a direct comparison between the classical tensor network formulation and its QFT-based quantum counterpart, showing that both approaches avoid the exponential scaling of conventional Fourier implementations and provide complementary perspectives on large-scale option pricing. Together, these results establish a unified framework connecting classical Fourier pricing, tensor network algorithms, and quantum computing approaches, demonstrating how tensorized Fourier methods can provide scalable alternatives for high-dimensional financial computations.

We extend the regime of convergence of Carleman-embedded quantum algorithms that solve the Vlasov-Poisson equations from kinetic plasma physics. We establish convergence, using both analytical and numerical lower bounds, for physically reasonable collision frequencies using a Fourier-Hermite expansion of the shifted phase-space distribution function. We also show that for a large class of basis functions, the convergence of the Carleman-embedded Vlasov-Poisson system requires increasing collision frequency strength with velocity resolution. The complexity of the quantum algorithm depends strongly on whether we seek time-averaged or -resolved outputs.