Quantum Physics
Classical and Quantum Simulation of All-to-All Quantum Dynamics in Logarithmic Space
Maximilian Lutz, Rahul Trivedi and J. Ignacio Cirac
We study both the classical and the
quantum complexity of the problem of estimating disorder-averaged quench dynamics for all-to-all
spin Hamiltonians such as
quantum Hopfield, Sherrington–Kirkpatrick (SK) or Dicke-type models. Disorder averaging restores permutation invariance in this setting, so states of $N$
spins can be stored in $\mathcal O(\log N)$
qubits. While logarithmic-space
quantum computations are known to be simulatable classically in
polynomial time or in polylogarithmic space, whether a single
algorithm can achieve both is open, raising the possibility of simultaneous
quantum advantage. To this end, we give a
quantum algorithm for permutation-invariant $k$-local dynamics without disorder using
polynomial time and $\mathcal O(\log N)$
quantum and classical space. We show that any classical
algorithm matching these resources would imply $\mathsf{BQL}\subseteq \mathsf{SC}$. For short times, however, we provide such
algorithms, including for SK models. For Hopfield models, we discuss how dilating the disorder to ancilla
qubits reduces the problem to the disorder-free case on an enlarged system, thus extending both classical and
quantum results to them. We give some evidence that their long-time dynamics are non-trivial. They thus emerge as a candidate for a simultaneous time–space advantage in
quantum simulation.
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Astrophysics of Galaxies
The assembly history of NGC 1365 through chemical archaeology
Lisa J. Kewley, Kathryn Grasha, Alex Garcia et al. (+8 more)
Galaxies build through infalling gas and
galaxy mergers. Tracking the dynamical history of a
galaxy from a single snapshot in time is notoriously difficult. We show that the dynamical history of a
galaxy can be tracked using oxygen abundances as archeological tracers. We derive the gas-phase oxygen abundances for 4546 spaxels across the face-on spiral
galaxy NGC~1365 at a spatial resolution of 175 pc, providing one of the most detailed chemical fossil records of a spiral
galaxy outside our Milky Way. We apply IllustrisTNG cosmological simulations to analyse the chemical abundance distribution in a theoretical model for NGC~1365. In the model, the main disk oxygen abundance gradient formed earliest, 11.9-12.5 billion years ago via mergers with multiple
dwarf galaxies. A steep inner bar gradient formed slowly over the last 12 billion years through enrichment from
star formation triggered by the infall of gas into the
nuclear regions. An extended ionized gas disk with flat oxygen abundances was assembled more recently (5.9-8.6 billion years ago) through a minor merger. This work indicates that cosmological simulations and ultra-high spatial resolution oxygen abundances together can provide an archaeological probe of the
star formation and merger histories of spiral
galaxies.
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All authors Lisa J. Kewley, Kathryn Grasha, Alex Garcia, Paul Torrey, Jeff Rich, Z. S. Hemler, Qian-hui Chen, Peixin Zhu, Mark Seibert, Lars Hernquist, Barry Madore
Quantum Physics
Quantum Černý complexity of binary words
Pui Hang Lee, Pui-Yee Lee and Bjørn Kjos-Hanssen
We introduce the
quantum Černý complexity $\mathrm{qc}(w)$ of a binary word $w$: the least dimension $d$ for which there exist
quantum channels $A_0,A_1$ on $d\times d$ density
matrices and a start state $\rho_0$ such that $w$ is the unique shortest word whose associated channel is constant on the reachable set. We show that $2\le\mathrm{qc}(w)\le\lceil\sqrt{|w|+1}\,\rceil$ for every nonempty $w$, a quadratic saving over the classical analogue, and that constant words are extremal: $\mathrm{qc}(0^m)=\lceil\sqrt{m+1}\,\rceil$. In contrast, $\mathrm{qc}(01^n0)=2$ for every $n\ge 1$, realized by a single
qubit whose rotation angle acts as a counter; consequently there is no
quantum analogue of the Černý function, and $\mathrm{qc}$ is strongly anti-correlated with intuitive notions of descriptive complexity. We further study the variant $\mathrm{qcp}$ in which the synchronization target is required to be a pure state. We prove that in dimension $2$ no word of length at least $2$ can be a unique shortest synchronizing word with pure target, and we exhibit an explicit qutrit instance, combining a coherent rotation with a measure-and-funnel channel, achieving $\mathrm{qcp}(01^n0)=3$ with target a computational basis state and with synchronization holding universally over all input states. Thus purity of the reset state costs exactly one dimension on this family. We also observe that $\mathrm{qc}$ is computable, by reduction to the first-order theory of the reals.
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Biological Physics
Computational Insights into Mechanostability and Dissociation Dynamics of the Dengue Virus Envelope Protein Ectodomain Dimer Across pH and Temperature Gradients
Georcki Ropón-Palacios, Luís G. F. Crespi, Jakub Rydzewski et al. (+2 more)
Dengue virus (DENV) is an enveloped flavivirus of major public health importance. Its envelope (E)
protein mediates viral entry through homodimer dissociation and subsequent membrane fusion, making it one of the principal targets for antiviral strategies. To investigate the molecular determinants of this process, we performed steered molecular dynamics (SMD) simulations of the E
protein ectodomain (ecE) dimer from DENV-2 and DENV-3 under variable pH and temperature conditions. Force-extension analyses revealed a highly stable interface for both serotypes, with rupture forces exceeding 1000 pN. pH and temperature had modest effects on overall mechanical resistance. However, DENV-3 displayed a distinct sensitivity to thermal stress compared to DENV-2. We identified a robust, asymmetric dissociation pathway across all conditions, characterized by a metastable intermediate state involving partial dimer opening and exposure of the fusion loop (FL). This intermediate exposes an immunodominant epitope and persists under physiological conditions, suggesting it as a viable target for therapeutic intervention. The primary contributions to the interfacial interaction network were found to arise from van der Waals interactions, followed by hydrogen bonds, salt bridges, and pi-cation interactions. DENV-3 exhibited a slightly greater contribution from polar interactions involving domains EDI, EDII, and EDIII. Furthermore, pairwise occupancy analysis identified pH-sensitive contacts that are disrupted under acidic conditions, particularly in DENV-3, providing mechanistic insight into the early stages of ecE dissociation. Together, these findings provide structural insights into the dissociation mechanism, identifying key metastable states and pH-sensitive interactions that could be exploited to develop antivirals that stabilize the dimer and prevent viral fusion.
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All authors Georcki Ropón-Palacios, Luís G. F. Crespi, Jakub Rydzewski, Walter Rocchia, Alexandre S. de Araujo
Strongly Correlated Electrons
adapol: Adaptive pole-fitting for quantum many-body physics
Zhen Huang, Chia-Nan Yeh, Lin Lin et al. (+3 more)
We describe adapol, a Python package for fitting Matsubara Green's functions, self-energies, and hybridization functions by a compact sum of simple poles with real pole locations and
matrix-valued residues. This pole-fitting step arises in many contexts, including hybridization fitting for
quantum impurity solvers based on exact diagonalization, perturbation theory, and tensor networks, the compression of existing pole expansions such as the discrete Lehmann representation, diagrammatic methods based on discrete pole representations, and the analytic continuation of Matsubara Green's functions. adapol uses a modified version of the AAA rational approximation
algorithm to estimate pole locations, and non-convex optimization to refine them. This procedure yields accurate and compact fits in a black-box and noise-robust manner. adapol provides a simple, self-contained interface with extensive documentation and examples, as well as an interface to the TRIQS package.
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All authors Zhen Huang, Chia-Nan Yeh, Lin Lin, Nils Wentzell, Jason Kaye, Hugo U. R. Strand
Quantum Physics
QuLoC: Photonic Quantum-Assisted Low-Rank LLM Compression
Xiao-Hui Ni, Yu-Han Yao, Yu-Ze Zhu et al. (+4 more)
As LLMs grow in size, compression becomes increasingly important for efficient deployment. SVD-based low-rank compression reduces parameter counts but can degrade downstream performance. To improve performance after compression, we introduce QuLoC, a photonic
quantum-assisted LLM compression
algorithm that uses
quantum circuit outputs to gate the retained low-rank components during training. Model performance is recovered through local functional reconstruction followed by end-to-end knowledge
distillation. After training, the gating coefficients are absorbed into the low-rank factors, allowing the compressed model to run on classical hardware without executing
quantum circuits during inference. Experiments on Qwen3.5-4B show that QuLoC achieves a 9.73% relative improvement in average accuracy over state-of-the-art baselines across multiple downstream tasks, demonstrating its effectiveness. We further evaluate QuLoC on LLaMA-7B at different parameter compression ratios. It achieves comparable or higher average downstream accuracy than state-of-the-art baselines, supporting its applicability to a larger model across different compression settings. These results motivate further exploration of photonic
quantum-assisted compression for larger models and more complex agentic tasks.
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All authors Xiao-Hui Ni, Yu-Han Yao, Yu-Ze Zhu, Hang Song, Xiang Zhao, Lin Yang, Xian-Min Jin
Quantum Physics
Fast Cliffords When Your Quantum Memory Is Full
Marten Folkertsma, Ian Mertz, Sergii Strelchuk et al. (+1 more)
Additional
qubits can reduce the depth of a
quantum circuit by providing workspace for parallel computation, but standard constructions assume that this workspace is initialized in a known state. In this work we study catalytic implementations, i.e. asking whether dirty
qubits can instead be used provided that their joint state including any
entanglement with other registers is restored exactly at the end of the computation. We show that every $n$-
qubit Clifford
circuit has a catalytic implementation of depth $O(\log n)$ using $O(n^2/\log^2 n)$ catalytic
qubits and no clean
qubits, matching the asymptotic depth achievable when clean workspace is available. We extend this approach to diagonal elements of any fixed level $C_k$ of the Clifford hierarchy, which admit catalytic implementations of depth $O(\log(n+1))$ with $O(n^k/\log(n))$ gates and $O(n^k/\log^2(n))$ catalytic
qubits, as well as to semi-Clifford Gates.
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All authors Marten Folkertsma, Ian Mertz, Sergii Strelchuk, Sathyawageeswar Subramanian
Soft Condensed Matter
Fluctuation-induced ionic friction at solid-electrolyte interfaces
Damien Toquer, Baptiste Coquinot, Nikita Kavokine et al. (+1 more)
In this article, we explore how transport at a solid–electrolyte interface is affected by the internal fluctuations of the solid and quantify the role of solid excitations on ionic friction. Combining molecular dynamics simulations with theoretical modeling, we show that the presence of ions enhances the dynamical response of the electrolyte compared to pure water. This leads to an ionic contribution to the fluctuation-induced interfacial friction. We show that collective ionic modes dominate the dissipation, such that ionic friction arises from many-body effects rather than from individual drag forces. Furthermore, high-frequency molecular modes are found to be ion-specific, suggesting possible routes toward spectral separation of ions, with implications for desalination, filtration, and energy conversion.
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All authors Damien Toquer, Baptiste Coquinot, Nikita Kavokine, Lydéric Bocquet
Atmospheric and Oceanic Physics
Less is more: error-distance scaling relation for data-efficient kilometer-scale downscaling of extreme heat
Ahmed Marey, Henry Lu, Abhishek Gaur et al. (+6 more)
Extreme heat is where urban adaptation needs kilometer-scale data the most, but the simulations training a downscaler can cost more than they save, and how much is needed has not been identified. We measured it with CASPER, a U-Net with a structure-preserving loss downscaling 32 km reanalysis to 1 km temperature, humidity and wind, across 24 configurations of one to eight months. Held-out error grows linearly with climatological distance to the training data, RMSE = 0.83 + 2.95 d, explaining 90% of its variance against 7% for volume and predicting unseen months in advance. On held-out extreme summer weeks CASPER preserves the fine-scale structure and cross-variable physics that matched-budget baselines degrade, and matches station observations during documented heat waves to within 1.8 K. Transfer to a new region degrades geographically; 11 days of local simulation cuts Vancouver's held-out error from 3.8 to 1.3 K. Training periods should span the target
climate: the same accuracy for four times less simulation, putting kilometer-scale downscaling of extreme heat within reach of groups without large computing facilities.
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All authors Ahmed Marey, Henry Lu, Abhishek Gaur, Sherif Goubran, Malek Aloui, Theodore Potsis, David Rolnick, Alex Hernandez-Garcia, Liangzhu Leon Wang
Superconductivity
Electronic Reconstruction across the Tilt-Free Transition in La$_3$Ni$_2$O$_7$
Mengjie Kong, Gergely Németh, Yingpeng Yu et al. (+5 more)
The emergence of high-$T_c$ superconductivity in pressurized La$_3$Ni$_2$O$_7$ is intimately linked to a structural transition that suppresses the tilts of the NiO$_6$ octahedra, yet its impact on the electronic structure remains poorly understood. Here, we probe the electronic response across this tilt-free transition at $T_{st}\simeq 544$ K using broadband infrared-to-visible reflectivity at ambient pressure, covering
photon energies from 15 meV to 3.2 eV. We observe a pronounced redistribution of spectral weight over an exceptionally broad energy range, with spectral weight transferred from excitations between 1 and 3 eV toward low-energy excitations below 1 eV. Most strikingly, two low-energy interband excitations progressively converge and merge upon entering the tilt-free phase, revealing a substantial reconstruction of the finite-energy electronic structure. These changes point to a reconstruction of the
bilayer Ni $3d_{z^2}$-derived electronic states, whose interlayer coupling is central to proposed mechanisms of superconductivity in La$_3$Ni$_2$O$_7$. Our results establish the tilt-free transition as a direct route to reorganizing the electronic degrees of freedom implicated in high-$T_c$ superconductivity and provide an ambient-pressure reference for the electronic structure of the superconducting state.
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All authors Mengjie Kong, Gergely Németh, Yingpeng Yu, Bosen Wang, Jianping Sun, Jinguang Cheng, Ferenc Borondics, Bastien Michon
Chemical Physics
Smite: A quasiclassical trajectory (QCT) program for bimolecular collisions and unimolecular dynamics on ab-initio, and machine-learned potential energy surfaces
Péter Szabó, Jenne van Veerdeghem, Jérôme Loreau et al. (+2 more)
We present Smite, a Python toolkit for quasiclassical trajectory (QCT) simulations of reactive and inelastic bimolecular collisions, unimolecular dynamics, and molecular collisions with finite surface models. A central feature is the explicit control of reactant preparation: harmonic normal modes admit fixed
quantum numbers, prescribed energies, thermal
quantum populations, or ground-state Wigner sampling; rotation is prepared at fixed angular-momentum magnitude or from thermal distributions appropriate to diatomic and polyatomic rotors. Rotating-Morse sampling provides a coupled anharmonic treatment of diatomic vibration and rotation, while saved molecular-dynamics phase points provide an alternative source of initial conditions. The same
nuclear propagators operate with on-the-fly electronic-structure calculations or user-supplied analytical and machine-learned potential energy surfaces. Additional modules provide constrained rigid-fragment dynamics, thermostat-based preparation, photoionization initial conditions with energy and
recoil constraints, and fewest-switches surface hopping (FSSH) on multiple PESs with approximate
curvature-derived couplings. Geometry optimization, transition-state searches, crossing-point optimization, intrinsic-reaction-coordinate following, and thermochemistry use the same energy and derivative interfaces. Analysis tools connect trajectories to product energy partitioning, stereodynamical correlations, time-resolved vibrational signatures, and independent-atom x-ray scattering.
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All authors Péter Szabó, Jenne van Veerdeghem, Jérôme Loreau, Jean-François Müller, Jeremy N. Harvey
Atmospheric and Oceanic Physics
reGRAF: a global MPAS reforecast data set with convection-allowing refinements over the US and Europe
Thomas M Hamill, Akshay Subramaniam, Montgomery Flora et al. (+8 more)
NVIDIA and The Weather Company (TWC) have generated a data set of reforecasts from TWC's GRAF (Global high-Resolution Atmospheric
Forecasting) model, a version of the National Center for Atmospheric Research (NCAR) Model for Predictions Across Scales (\href{https://ncar.ucar.edu/what-we-offer/models/model-prediction-across-scales-mpas}{\underline{MPAS}}). GRAF is global, but the configuration for this reforecast had a mesh refinement to \textasciitilde4 km over the US, Caribbean Basin, and Europe, and 15 km elsewhere. This model was designed to run much of the computation on graphical processing units (GPUs), with this development assisted by NVIDIA. The 1836 reforecast cases (\textasciitilde5 years) were generated from ECMWF reanalyses (ERA5) for selected initial condition dates spanning more than 20 years, 2004–2024. These dates of the chosen initial conditions were mostly selected based on high-impact weather in the contiguous US (CONUS) and Caribbean. Sampling in this way, the reforecast spanned a wider range of interesting, high-impact weather scenarios than had we performed five contiguous years of once-daily reforecasts. The reforecast still provides many samples in non-precipitating regions with more ordinary weather. GRAF reforecasts were mostly run to $+$27 h lead time, assuming a 3-h
spin-up followed by a full diurnal cycle. Data were saved in zarr format on the native model vertical coordinate. Most fields were archived at 15-min intervals, though several precipitation variables were saved at 5-min cadence. Data are made publicly available to all through Amazon Web Services' Open-Data Initiative at https://registry.opendata.aws/graf-reforecast.
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All authors Thomas M Hamill, Akshay Subramaniam, Montgomery Flora, Raghu Raj Prasanna Kumar, Karthik Kashinath, Carl Ponder, Tao Ge, Sepideh Khajehie, John Wong, Brett Wilt, Peter Neilley
Plasma Physics
FIREWALL: A surrogate model for the rapid assessment of tokamak wall loading and melting by runaway electrons
Victor Johan Svensson, Tommaso Rizzi, Svetlana Ratynskaia et al. (+4 more)
Runaway electron (RE) beams generated during tokamak disruptions can deposit highly localized heat loads on
plasma-facing components, posing a serious risk of melting and damage. Monte Carlo particle transport simulations coupled with three-dimensional thermomechanical response modeling can quantify this damage but are too computationally demanding for device-scale assessments and extensive scenario scans. We present FIREWALL (Fast Integrated Runaway Electron WALL loads), a surrogate model that combines a database of Geant4 volumetric energy-deposition profiles with a one-dimensional heat-
diffusion solver for each wall element. FIREWALL retains the energy and incident angle distributions of impacting REs and predicts the spatiotemporal temperature
evolution of detailed three-dimensional wall geometries up to the melting threshold. FIREWALL thus provides a fast physics-based framework for translating global RE simulations into global wall melting predictions, enabling large-scale screening of disruption scenarios while directing high-fidelity costly workflows to the limited wall regions where they are actually required.
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All authors Victor Johan Svensson, Tommaso Rizzi, Svetlana Ratynskaia, Hannes Bergström, Luca Venerando Greco, Matthias Hoelzl, Panagiotis Tolias
Atomic Physics
Nuclear moments, charge radii, and magnetization distribution parameters of Ag isotopes from laser spectroscopy and ab initio electronic-structure calculations
Leonid V. Skripnikov, Bram van den Borne, Michail Athanasakis-Kaklamanakis et al. (+2 more)
The
nuclear electromagnetic moments and mean-square charge radii of several silver (Ag) isotopes deduced from recent
laser spectroscopy studies in the mass region $A=$ 96-121 are determined using high-accuracy electronic structure calculations performed in this work. We report hyperfine structure and isotope-shift atomic factors calculated with the relativistic coupled cluster approach, including single, double, triple, and perturbative quadruple excitations, CCSDT(Q). Following a systematic theoretical uncertainty analysis, we show that at the precision now achieved (sub-percent uncertainties in some cases),
quantum electrodynamic effects become significant. We also show that the isotope-dependent effect in the hyperfine structure due to the non-point-like
nuclear magnetization distribution can be extracted with negligible dependence on the assumed
nuclear magnetization model at the present level of precision. This also yields a
nuclear magnetic dipole moment that is corrected for the hyperfine anomaly induced by the Bohr-Weisskopf effect. In terms of the
nuclear electric quadrupole moments, the uncertainty in the electric-field gradient used to extract the quadrupole moments from
laser spectroscopy has also been reduced by one to two orders of magnitude relative to values used in previous studies. Finally, the
nuclear charge radii of Ag isotopes are extracted using field- and mass-shift factors from our coupled cluster calculations, and the difference in mean-square charge radii between $^{107,109}$Ag agrees with the value deduced from muonic X-ray spectroscopy.
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All authors Leonid V. Skripnikov, Bram van den Borne, Michail Athanasakis-Kaklamanakis, Gleb Penyazkov, Ruben P. de Groote
Quantum Physics
Optimal Resource Scaling for Early Fault Tolerant Iterative Quantum Phase Estimation under Cost Error Tradeoffs
Mrudula A Mahindrakar and Avhishek Chatterjee
The iterative
quantum phase estimation
algorithm (IPEA) is better suited for NISQ and early fault-tolerant hardware compared to the original
algorithm, which requires the inverse
quantum Fourier transform. However, current error mitigation and correction implementations lead to imperfect
unitaries, causing erroneous phase feedback in IPEA. To improve the reliability of phase bits is to repeat the k^th iteration for the 2^k-th power of the
unitary $N_k^*$ times, followed by a majority decision. However, due to variations in their
circuit complexities, different iterations incur varying resource costs ($w_k$) and different per-shot error probabilities ($q_k$). Given tight resource constraints, we ask what the optimal number $\{N_k^*: 1\le k \le L\}$ of shots per bit is: $$\arg \max_{\{N_k\}} \mathbb{P}(\text{all } L \text{ bits correct}) \text{ s.t.} \sum_{k=1}^L w_k N_k \le W$$ We obtain closed-form expressions for $N^*_k$ under the conditions: $W \gg \sum_k w_k $(enough for at least one shot per iteration), $w_k$ increases with $k$, $q_k$ are small enough and $L$ is large. We do so by analyzing tractable upper and lower surrogate problems derived via tight concentration and anti-concentration bounds and showing that their solutions converge when $q_k\ll 1$. We observe that when $W\gg \sum_k w_k \ln\! \left(\sum_k w_k\right)$, the optimal $N_k^*$ is proportional to $\frac{\ln\! \left(\sum_k w_k\right)}{c_k}$ and does not depend on individual $w_k$, where $c_k=-\ln\left(2\sqrt{\left(1-\frac{q_k}{2} \right) \frac{q_k}{2}}\right) \propto \ln\frac{1}{q_k}$. However, when $\sum_k w_k \ll W\ll\sum_k w_k \ln\! \left(\sum_k w_k\right)$, the allocation is also (additively) influenced by $\frac{1}{c_k}\ln\frac{1}{w_k}$ for larger values of $k$, i.e., higher powers of
unitary. These results lead to simple rules of thumb for resource allocation that may benefit the design of practical systems.
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Cosmology and Nongalactic Astrophysics
Improved Constraints on Cosmic Microwave Background Circular Polarization with CLASS
Thomas Essinger-Hileman, Caleigh Ryan, Yunyang Li et al. (+25 more)
We present improved constraints on circular polarization in the
cosmic microwave background (CMB) from the Cosmology Large Angular Scale Surveyor (CLASS) experiment using data at 90, 150, and 220 GHz to complement previous results based on 40 GHz data alone. We extend constraints on circular polarization from the atmosphere to all CLASS frequencies and compare with a model of the atmospheric circular polarization spectrum. The inclusion of data at all CLASS frequencies improves upper limits on circular polarization, Stokes $V$, in the CMB by a factor of $\sim 5$ at the largest angular scales ($10 < \ell < 30$) and extends the constraints to smaller angular scales, $\ell = 700$. In combination with Planck temperature data, we provide the first limits on the temperature-circular-polarization ($TV$) power spectrum to date. Both circular polarization ($VV$) and $TV$ power spectra are consistent with zero, and CLASS places upper limits of $5.4 \times 10^{-3}$ $\mu$K$_{\text{CMB}}^2$ on $VV$ at large angular scale ($10 < \ell < 30$) and $5.8 \times 10^{-1}$ $\mu$K$_{\text{CMB}}^2$ on $TV$ at 95% confidence at $30 < \ell < 50$.
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All authors Thomas Essinger-Hileman, Caleigh Ryan, Yunyang Li, Matthew A. Petroff, John W. Appel, Charles L. Bennett, Ricardo Bustos, Carol Yan Yan Chan, David T. Chuss, Joseph Cleary, Sumit Dahal, Rahul Datta, Jullianna Denes Couto, Kevin L. Denis, Joseph R. Eimer, Joseph E. Golec, Kyle R. Helson, Jeffrey Iuliano, Tobias A. Marriage, Jeffrey J. McMahon, Ivan Padilla, Carolina Morales Perez, Karwan Rostem, Rui Shi, Deniz A. N. Valle, Duncan J. Watts, Janet L. Weiland, Edward J. Wollack
Quantum Physics
Quantum Advantage of Permutation-Invariant Functions in Communication Complexity
Yunqi Huang and Zekun Ye
We study how
symmetry affects
quantum advantage in two-party communication complexity. For any partial function $f$ on length-$n$ strings over a fixed alphabet of size $q$, invariant under simultaneous coordinate permutations, we prove $R^{\mathrm{pub}}(f)=O_q(t\log(2+n/t))$, where $t=\min\{n,Q^{\ast}(f)^2\}$, $R^{\mathrm{pub}}$ denotes public-coin randomized communication complexity, and $Q^{\ast}$ denotes
entanglement-assisted
quantum communication complexity. This bound is tight for set disjointness and extends the binary-alphabet result of Guan et al. with a smaller logarithmic overhead. The exponent of the logarithmic factor cannot be reduced by any fixed positive amount: for every fixed $\varepsilon\in(0,1)$, there are binary permutation-invariant partial functions with
quantum communication complexity $O_\varepsilon(\log\log n)$ and randomized communication complexity $\Omega_\varepsilon((\log n)^{1-\varepsilon})$. We also characterize
quantum communication complexity by a combinatorial parameter up to a logarithmic factor. Growing alphabets and graph
symmetries admit exponential separations. For every fixed $\varepsilon\in(0,1)$, we exhibit permutation-invariant partial functions on length-$n$ strings over an $n$-symbol alphabet with
quantum communication complexity $O_\varepsilon(\log n)$ and randomized communication complexity $\Omega_\varepsilon(n^{1-\varepsilon})$. For graph-invariant partial functions on $v$-vertex graphs, we obtain $O_\varepsilon(\log v)$
quantum versus $\Omega_\varepsilon(v^{2-\varepsilon})$ randomized communication complexity. All separation protocols require no prior
entanglement.
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Soft Condensed Matter
Liquid crystalline order and its impact on shape evolution of fluid lipid membranes
Ingo Nitschke, Maik Porrmann and Axel Voigt
Dynamic approaches to minimize the classical
curvature-elasticity free energy for a fluid lipid membrane, are extended towards a Surface Beris–Edwards–Helfrich model. This extension explicitly treats the
liquid crystal structure of the membrane, which results from the lipid molecules, that are, on average, oriented normal to the surface. Locally varying
liquid crystal order leads to local variations in bending
rigidities and surface viscosity and thus influences the shape
evolution. This provides a multiscale coupling between the local membrane mechanics on the level of the lipids and the mesoscopic length and time scales of biological functions. The model is derived using the Lagrange–d'Alembert principle. We provide a numerical
algorithm to solve the equations in the one-constant approximation and demonstrate the impact on the emerging
equilibrium shapes, which not only depend on the specified conserved surface area and enclosed volume, as for the classical
curvature-elasticity free energy, but also the elastic parameter. Exploring the dynamic
evolution shows a tight coupling of tangential flow, shape
evolution and
liquid crystalline order. We further point to extensions towards lipid phase separation and asymmetric lipid
bilayers.
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Chemical Physics
Smart Machine Learning for Solving the Full Electron-Nuclear Schrödinger Equation with a Quantum-Chemically Inspired Wavefunction Ansatz
Yaolong Zhang, Bin Jiang and Hua Guo
Directly solving the full electron-
nuclear Schrödinger equation remains one of the grand challenges in
quantum mechanics. Here, we propose a
quantum-chemically motivated orbital-based neural network wavefunction ansatz with explicit many-body electron-electron correlation terms, with parameters depending on the entire electron-
nuclear configuration, enabling an accurate description of strongly correlated and/or multi-reference electronic structures by a single Slater-determinant across a broad
nuclear configuration space. To train this wavefunction, we further develop an efficient hybrid optimization strategy that combines the variational Monte Carlo technique with local-energy constraints, mitigating the intrinsic sampling bias of the former and considerably reducing the statistical error. These advances are embedded in a unified neural network framework, Schrödinger, enabling the determination of globally accurate potential energy surfaces with a single training for systems ranging from strongly correlated diatomic molecules, triatomic reactions containing conical intersections, to polyatomic multi-reference molecules. This work offers a practical machine-learning tool for solving the electron-
nuclear Schrödinger equation and capturing full
quantum effects beyond the Born-Oppenheimer approximation.
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Quantum Gases
Collective excitations of driven-dissipative quantum fluids of light
Alberto Bramati and Iacopo Carusotto
In this work we give an overview on a couple of decades of theoretical and experimental research on the many-body physics of driven-dissipative
quantum fluids of light in optical cavities. These systems consist of a large number of
photons enclosed in a cavity device where spatial confinement induces a finite
photon mass and the Kerr optical nonlinearity of the cavity material mediates finite
photon-
photon interactions. Differently from standard Bose gases of material particles like
liquid Helium or ultracold atomic gases,
photons are inevitably subject to radiative and/or non-radiative losses, which must be compensated by some pumping mechanism. As a result, the properties of the steady state are not imposed by a thermal
equilibrium condition, but are determined by a dynamical interplay of pumping and losses. Among the many collective phenomena that are observed in these systems, we focus here on the collective excitations around the steady state and we characterize the impact of the driven-dissipative nature of the gas on their properties, in particular on their dispersion relation. Different pumping configurations give very different behaviors: a specific discussion is provided for the most important configurations used in the experiments. Observable consequences of the various forms of the dispersion -gapped, gapless, sonic, band-sticking, diffusive Goldstone- are illustrated with a special eye towards their consequences on the superfluidity properties. We conclude the article with a presentation of a few research avenues that we personally find most exciting for the next years, namely the osbervable consequences of the concurrently superfluid and solid nature of supersolid states of light and the collective dynamics of
quantum correlated states of strongly interacting
photon gases in the presence of strong nonlinearities, in particular Mott
insulator states.
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Strongly Correlated Electrons
Probing Collective and Individual Kondo Screening: Multi-Stage, Multi-Channel Kondo Effects in a $C_3$-Symmetric Four-Impurity Model
Danqing Hu, Jiangfan Wang, Zixiang Hu et al. (+1 more)
Collective screening has been proposed to underlie the basic physics of multi-
impurity and
lattice Kondo systems. But how to establish this picture and distinguish it from individual (local) Kondo screening remains a grand challenge. The recently developed auxiliary-bath numerical renormalization group (AUNRG) method provides a key step towards resolving this issue. Its application to the $C_3$-symmetric three-
impurity Kondo (3IK) model with a shared electron bath reveals fully screened
Fermi liquid ground states arising from collective screening of cluster
spin degrees of freedom at small Kondo coupling $J_{\rm K}$ and individual (local) screening of local
impurities at large $J_{\rm K}$. Here we design a four-
impurity Kondo (4IK) model where the probe
impurity couples only to the original three Kondo
impurities to detect the nature of the screened states. We show that the collective and individual Kondo screenings give rise to emergent multi-stage, two-channel Kondo effect and unstable three-channel Kondo effect, respectively. This suggests a special helicity structure of the screened states and confirms the idea of collective screening in multi-
impurity Kondo systems. Our work also demonstrates that the same auxiliary-bath construction can be readily extended to models with additional
impurities to explore novel many-body
quantum states with emergent cluster degrees of freedom.
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All authors Danqing Hu, Jiangfan Wang, Zixiang Hu, Yi-feng Yang
Quantum Physics
Verification Complexity and Extension of Classical Shadows
Georgios Karaiskos, Asad Raza, Dorian Rudolph et al. (+2 more)
Classical shadows are an influential framework for compressing copies of a given
quantum state $\rho$ into classical data $S$, enabling many properties of $\rho$ to be predicted from relatively few copies. In this work, we study two natural questions involving shadows: (1) Given $S$, when can one efficiently verify that $S$ came from a genuine $n$-
qubit state? This is called the Classical Shadow Validity (CSV) problem, introduced by Karaiskos, Rudolph, Meyer, Eisert, and Gharibian [ICALP 2026]. (2) Given $S$ that allows one to capture 2-local properties of $\rho$, can one fake or spoof a shadow $S'$ which predicts 3-local properties of some state? For (1), we show CSV is efficiently solvable for permutation-invariant shadows, QMA-hard for real, fermionic, and bosonic shadows, and both coNP-hard and QMA-hard when the observable family consists of all $n$-
qubit Pauli strings. A result of independent interest along the way is a new upper bound qc-$\Sigma_2$ $\subseteq$ $\mathrm{P}^{\mathrm{PP}}$, where qc-$\Sigma_2$ is a
quantum analogue of the second level of the
polynomial hierarchy in which the first proof is
quantum. For (2), we show intractability: Given the 2-local marginals $S$ of a
quantum state $\rho$, estimating the 3-local marginals of $\rho$ is intractable unless QCMA $\subseteq$ BPP, even if the state $\rho$ is the unique state consistent with $S$.
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All authors Georgios Karaiskos, Asad Raza, Dorian Rudolph, Dax Enshan Koh, Sevag Gharibian
Quantum Physics
A Complete and Natural Rule Set for Multi-Qudit Clifford Circuits in All Odd Prime Dimensions
Xiaoning Bian, Sarah Meng Li, Neil J. Ross et al. (+2 more)
We present a complete set of $16$ rewrite rules for multi-qudit Clifford
circuits in all odd
prime dimensions. Completeness means that any two Clifford
circuits representing the same linear map can be rewritten into each other using these rules. Each rule involves at most three qudits and admits an intuitive interpretation. To establish completeness, we first work at the
symplectic level, using the isomorphism between the
symplectic group $\mathrm{Sp}(2n,\mathbb{Z}_p)$ and the quotient of the Clifford group by the Pauli group. We construct a
circuit normal form that captures the stabiliser tableau of a Clifford operator and is unique up to Pauli correction. Using this normal form, we derive a complete set of
symplectic relations, which we then lift to Clifford relations by incorporating Pauli corrections. We also formally verify completeness in the Agda proof assistant.
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All authors Xiaoning Bian, Sarah Meng Li, Neil J. Ross, John van de Wetering, Yuming Zhao
Quantum Physics
Harnessing problem structure for end-to-end quantum speed-ups
Qifan Jiang, Xiao-Ming Zhang, Debin Xiang et al. (+3 more)
Quantum algorithms can offer substantial computational speed-ups, yet these advantages may disappear once the cost of structure-agnostic classical data encoding is taken into account. Real-world problem instances, however, often possess rich internal structure. This raises a fundamental question: can such structure be harnessed to make
quantum speed-ups survive end-to-end cost accounting? Here we show that it can. We introduce a general framework for structure-aware
quantum data encoding that compiles compact recursive descriptions of problem structure into efficient state-preparation
circuits, translating structural information directly into reduced encoding complexity. For the uncapacitated facility-location problem, structure-agnostic encoding admits a classical dequantization that eliminates the quadratic
quantum speed-up, whereas exploiting the underlying problem structure restores this advantage even when state-preparation costs are included. More broadly, the same framework prepares structured
quantum states for combinatorial optimization that capture non-trivial relations among constraints, including group balance, conflicts and synergistic rewards, extending previously reported super-
polynomial quantum advantages to broader classes of objectives. These results establish exploitable problem structure as a computational resource for
quantum algorithms and provide a systematic route towards realizing
quantum advantage in data-intensive problems.
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All authors Qifan Jiang, Xiao-Ming Zhang, Debin Xiang, Xiao Yuan, Liqiang Lu, Jianwei Yin
Superconductivity
A Different Perspective on Superconductivity in Crystalline Graphene: Exploiting Energetics
Ke Wang, Shicong Song and K. Levin
A central mystery of crystalline
graphene is why superconductivity is so widespread yet often confined to strange slivers near boundaries between distinct isospin-ordered metals. In this paper, we apply a “two-parent” energetic framework which we show can explain this unusual form of superconductivity without specifying the details of the necessarily present pairing attraction. First-order transitions are crucial here: when two normal isospin-ordered states are degenerate in free energy, even a small net superconducting energy gain may stabilize an
equilibrium superconductor. We demonstrate how this is possible even though the small energy gain from pairing is reduced by the expense of reconstructing the normal metal, which is needed to achieve superconducting compatibility. The first order degeneracy also gives superconductivity a choice between two normal state parents, favoring the state with the largest net free energy gain.
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Quantum Physics
Logarithmic-Depth Fermion Sampling: Anticoncentration and Average-Case Hardness
Natansh Mathur and Iordanis Kerenidis
Sampling problems give some of the clearest conditional separations between
quantum and classical computation. In
Fermion Sampling, passive linear optics acts on a non-Gaussian magic input. Globally Haar-random transformations give anticoncentration and high-precision average-case hardness, but require linear depth and quadratically many gates. A natural open question is whether linear depth is necessary? We show that logarithmic depth suffices for both guarantees in the same ensemble. For fresh uniform matchings with independent Haar two-mode gates, the collision reaches the passive-Haar scale at a sharp threshold of $\log n/\log(9/4)\approx0.855\log_2 n$ layers, with an explicit limiting transition profile and a matching lower bound from two-particle correlations. The mechanism is input-dependent: the magic input suppresses the extensive weight of the slowest relaxation mode, leaving the next to set the scale. An occupation-basis input retains large collision even under full Haar randomness. At a larger logarithmic depth, we prove, in the real-RAM model, average-case $\#\mathsf{P}$-hardness of estimating output probabilities to additive error $2^{-O(n\log^2 n)}$ on any fixed fraction of instances above $3/4$. We construct hard instances in four native layers, embed them in typical schedules, and interpolate along Cayley paths using a rational linear-program decoder. A finite $192$-gate alphabet preserves the collision law exactly. Both guarantees use logarithmic native fermionic depth between arbitrary mode pairs and $O(n\log n)$ gates, replacing the global-Haar construction's quadratic budget. The accuracy proved is finer than the $1/N$ scale, where $N=\binom{n}{n/2}$, required by sampling-to-counting; hardness of sampling within constant total-variation distance remains open.
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Quantum Physics
Finding gflow on unlabelled open graphs
Miriam Backens, Victor Gasse, Piotr Mitosek et al. (+1 more)
The one-way model of measurement-based
quantum computing implements computations via successive adaptive single-
qubit measurements on a resource graph state. This model has practical applications, particularly in photonics, and it is also useful as a theoretical tool e.g. for optimisation. Gflow is a necessary and sufficient condition for implementing certain one-way computations deterministically (in a suitable sense); it is also used in efficient translations from the one-way model to
quantum circuits. For a computation on $n$
qubits, a gflow can be found in $\mathcal{O}(n^3)$ time. Here, we consider an incompletely specified computation given by an unlabelled open graph: the graph state as well as the input and output
qubits are known, but the measurements have not yet been fixed. We give an
algorithm that identifies a measurement labelling and a compatible gflow, and runs in $\mathcal{O}(n^3)$, strictly generalising the previous approach. The new
algorithm can also handle restrictions on the order of the measurements and returns only solutions compatible with these constraints. We additionally prove that if an open graph has equal numbers of inputs and outputs, it has at most one labelling compatible with gflow; and show how to identify additional inputs for an open graph that does not yet have the maximal number, without breaking an existing gflow.
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All authors Miriam Backens, Victor Gasse, Piotr Mitosek, Robert Raussendorf
Mathematical Physics · Cross-listed from math.PR
Limit Theorems for Disordered Quantum Trajectories
Yeor Hafouta and Lubashan Pathirana
We study discrete-time
quantum trajectories of a finite-dimensional system in a disordered environment, where the instrument applied at each step is determined by an invertible measure-preserving dynamical system. For general
quantum instruments on a standard Borel outcome space, we construct the quenched probability law on sequences of measurement outcomes for a fixed realization of the disorder and a given initial state. Under a quenched Doeblin condition with a uniform deterministic minorization constant and an environment-dependent minorizing probability measure, we establish the existence and uniqueness of an equivariant family of random posterior laws and identify its barycenter as the unique dynamically stationary state for the associated non-selective channel cocycle. If the environment is ergodic, we prove a pathwise ergodic
theorem valid for every measurable choice of initial state: for almost every realization of the disorder, time averages of posterior states converge almost surely under the corresponding quenched law to the disorder average of the unique dynamically stationary state. For an ergodic environment, we establish quenched variance asymptotics and, when the asymptotic variance is positive, a central limit
theorem and standardized Berry–Esseen bounds for additive functionals generated by bounded measurable real-valued functions of the environment and posterior state. These results hold for every measurable initial state and almost every disorder realization. We then show that the stationary annealed joint process of instruments and posterior states inherits the $\alpha$-mixing of the instrument process, up to an exponentially decaying term. Finally, we provide classes of examples involving perfect and imperfect measurements, including models with continuous or finite outcome spaces, that satisfy the standing Doeblin condition.
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Quantum Physics
Classical Shadows with Selective GHZ Measurements
Nicolas Faroß, Marc Wanner, Pingal Pratyush Nath et al. (+3 more)
Classical shadows allow the prediction of many
quantum-state properties from measurement data, but their efficiency strongly depends on the underlying measurement ensemble. We introduce selective GHZ measurement (SGM) shadows, which perform Greenberger-Horne-Zeilinger (GHZ)-basis measurements on randomly selected subsets of
qubits and computational-basis measurements on their complement. The corresponding
quantum circuits are practically feasible, with their number of CNOT gates scaling linearly with the number of
qubits. This is in stark contrast to global Clifford
circuits, which are generally difficult to implement. Varying the subset distribution allows tuning the SGM shadow protocol for different classes of observables with prescribed X/Y support, allowing us to outperform local Pauli as well as global Clifford shadows in certain scenarios. We determine the exact shadow channel and its inverse for arbitrary subset distributions and prove an explicit bound on the shadow norm using methods from discrete
Fourier analysis and Markov
semigroup theory. For natural choices of subset distributions, this gives a
polynomial scaling for observables with fixed X/Y-locality. Numerical simulations of up to 50
qubits support the predicted improvements for nonlocal observables and long-range systems, and demonstrate the practical benefits of our protocol's generality by showing how the subset distributions can be tailored to settings such as fermionic modes under the Jordan-Wigner transformation.
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All authors Nicolas Faroß, Marc Wanner, Pingal Pratyush Nath, Akshay Gaikwad, Anton Frisk Kockum, Devdatt Dubhashi
Quantum Physics
Accelerating Quantum Dense-Output Simulation through Locality
Songqinghao Yang, Chang Liu, Junkai Wang et al. (+2 more)
Estimating time-accumulated observables, or dense outputs, is central to extracting classical information from
quantum simulations. Whereas most
quantum-simulation
algorithms aim to reproduce a final state or a single-time expectation value, many applications require the integrated signal $J_H(O)=\int_0^T \langle \psi(t)|O(t)|\psi(t)\rangle\,dt$. Previous
Hamiltonian-simulation-based dense-output
algorithms have query costs that depend on the norm of the full
Hamiltonian, which can grow with system size. However, one can naturally optimize the simulation
algorithm when the system structure is known. Consequently, we develop a locality-based truncation framework for the dense-output problem on
lattice Hamiltonians. By truncating the
Hamiltonian and tightening the resulting error with Lieb-Robinson bounds, we show that a local simulation can recover the dense output. We bound the
quantum simulation error from spatial truncation and translate it into local-simulation query bounds. Our analysis includes free and interacting systems for both
fermions and
bosons, as well as open
quantum systems governed by Lindbladians. The improvement from our truncation
algorithm varies from constant to unbounded as the system size grows. We also give example applications and conduct relevant numerical experiments to support our findings.
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All authors Songqinghao Yang, Chang Liu, Junkai Wang, Jingxuan Zhang, Jin-Peng Liu