arXiv subjects

Yang Qi

Publications and source records attributed to Yang Qi.

At least 37 records · Page 2Linked to original sources

arXiv2025

Universal Magnetocaloric Effect near Quantum Critical Point of Magnon Bose-Einstein Condensation

Bose-Einstein condensation (BEC), a macroscopic quantum phenomenon arising from phase coherence and bosonic statistics, has been realized in quantum magnets. Here, we report the observation of a universal magnetocaloric effect (MCE) near a BEC quantum critical point (QCP) in copper sulfate crystal ($CuSO_4 \cdot 5H_2O$). By conducting magnetocaloric and nuclear magnetic resonance measurements, we uncover a field-driven BEC QCP, evidenced by the universal scaling law $T_c \propto (B_c - B)^{2/3}$ and the perfect data collapse of the magnetic Grüneisen ratio. Thermal excitation triggers a dimensional crossover to a 1D quantum-critical regime, where the MCE scaling strictly matches the universality class of 1D Fermi gases. Notably, the quantum-critical MCE enables cooling down to 12.8 mK without helium-3, with very fast thermal relaxation rate that is critical for high cooling power. This work demonstrates the universal MCE in magnon BEC systems, using a common copper sulfate compound as a paradigmatic example, and paves the way for next-generation sub-Kelvin cooling.

cond-mat.str-el↗

arXiv2025

Classification of Average Crystalline Topological Superconductors through a Generalized Real-Space Construction

We investigate a novel class of topological superconducting phases protected by exact fermion-parity symmetry and average crystalline symmetries. These phases belong to the broader class of average crystalline symmetry-protected topological (ACSPT) states and include numerous examples of intrinsic ACSPTs -- topological phases that arise only in the presence of disorder or decoherence. Unlike conventional symmetry-protected topological (SPT) phases, which require exact symmetry protection, average SPT (ASPT) phases remain robust as long as the symmetry is restored on average across disorder realizations or mixed-state ensembles. To classify these phases, we extend the real-space block state construction framework to account for average crystalline symmetries. In this generalized setting, lower-dimensional cells are decorated with ASPT phases, and the obstruction-free conditions are reformulated to incorporate the constraints imposed by average symmetry at block intersections. This provides a physically transparent and systematic method for classifying ASPTs with spatial symmetries that are only preserved statistically. We further validate our classification using a generalized spectral sequence analysis, which serves as an independent consistency check. Our results demonstrate that many crystalline topological superconductors remain well defined under realistic imperfections, and they uncover a rich landscape of intrinsically average-symmetry-protected phases that have no analog in clean systems.

cond-mat.str-el↗

arXiv2025

Parity violation as enforced symmetry breaking in 3D fermionic topological order

Symmetry can be intrinsically broken in topological phases due to inherent incompatibilities, a phenomenon known as enforced symmetry breaking (ESB) in the framework of topological order. In our previous work, we developed a systematic framework to understand ESB within 2D invertible topological order. Meanwhile, the origin of parity violation in the Standard Model remains one of the most profound mysteries in physics, with no clear explanation to date. In this study, we explore the ESB of parity symmetry by three-dimensional fermionic topological order (fTO), offering potential insights into the origins of parity violation. As the simplest example, here we consider an fTO related to the intrinsic interacting fermionic SPT phase protected by $Z_2^f\times Z_2\times Z_8$ symmetry in three dimensions. We show that time-reversal symmetry (TRS) with ${T}^2=1$ on physical fermions is incompatible with such fTO; then, through the so-called crystalline equivalence principle, we show that the parity symmetry is also incompatible with it. In comparison, conventional TRS with ${T}^2={P}_f$ remains compatible to this fTO. We also discuss a general framework to study the ESB phenomenon for 3D fTO.

cond-mat.str-el↗

arXiv2025

Giant Magnetocaloric Effect in Spin Supersolid Candidate Na$_2$BaCo(PO$_4$)$_2$

Supersolid, an exotic quantum state of matter that consists of particles forming an incompressible solid structure while simultaneously showing superfluidity of zero viscosity [1], is one of the long-standing pursuits in fundamental research [2, 3]. Although the initial report of $^4$He supersolid turned out to be an artifact [4], this intriguing quantum matter has inspired enthusiastic investigations into ultracold quantum gases [5-8]. Nevertheless, the realization of supersolidity in condensed matter remains elusive. Here we find evidence for a quantum magnetic analogue of supersolid -- the spin supersolid -- in the recently synthesized triangular-lattice antiferromagnet Na$_2$BaCo(PO$_4$)$_2$ [9]. Notably, a giant magnetocaloric effect related to the spin supersolidity is observed in the demagnetization cooling process, manifesting itself as two prominent valley-like regimes, with the lowest temperature attaining below 100 mK. Not only is there an experimentally determined series of critical fields but the demagnetization cooling profile also shows excellent agreement with the theoretical simulations with an easy-axis Heisenberg model. Neutron diffractions also successfully locate the proposed spin supersolid phases by revealing the coexistence of three-sublattice spin solid order and interlayer incommensurability indicative of the spin superfluidity. Thus, our results indicate a strong entropic effect of the spin supersolid phase in a frustrated quantum magnet and open up a viable and promising avenue for applications in sub-Kelvin refrigeration, especially in the context of persistent concerns about helium shortages [10, 11].

cond-mat.str-el↗

arXiv2025

Statistical Limits in Random Tensors with Multiple Correlated Spikes

We use tools from random matrix theory to study the multi-spiked tensor model, i.e., a rank-$r$ deformation of a symmetric random Gaussian tensor. In particular, thanks to the nature of local optimization methods used to find the maximum likelihood estimator of this model, we propose to study the phase transition phenomenon for finding critical points of the corresponding optimization problem, i.e., those points defined by the Karush-Kuhn-Tucker (KKT) conditions. Moreover, we characterize the limiting alignments between the estimated signals corresponding to a critical point of the likelihood and the ground truth signals. With the help of these results, we propose a new estimator of the rank-$r$ tensor weights by solving a system of polynomial equations, which is asymptotically unbiased contrary the maximum likelihood estimator.

math.ST↗

arXiv2025

Point-group symmetry enriched topological orders

We study the classification of two-dimensional (2D) topological orders enriched by point-group symmetries, by generalizing the folding appraoch which was previously developed for mirror-symmetry-enriched topological orders. We fold the 2D plane hosting the topological order into the foundamental domain of the group group, which is a sector with an angle $2π/n$ for the cyclic point group $C_n$ and a sector with an angle $π/n$ for the dihedral point group $D_{2n}$, and the point-group symmetries becomes onsite unitary symmetries on the sector. The enrichment of the point-group symmetries is then fully encoded at the boundary of the sector and the apex of the section, which forms a junction between the two boundaries. The mirror-symmetry enrichment encoded on the boundaries is analyzed by the classification theory of symmetric gapped boundaries, and the point-group-symmetry enrichment encoded on the junction is analyzed by a framework for classifying symmetric gapped junctions between boundaries which we develop in this work. We show that at the junction, there are two potential obstructions, which we refer to as an $H^1$ obstruction and an $H^2$ obstruction, respectively. When the obstruction vanishes, the junction, and therefore the point-group-symmetry-enriched topological orders, are classified by an $H^0$ cohomology class and an $H^1$ cohomology class, which can be understood as an additional Abelian anyon and a symmetry charge attached to the rotation center, respectively. These results are consistent with the classification of onsite-symmetry-enriched topological orders, where the $H^1$ and $H^2$ obstructions and the junction corresponds to the $H^3$ and $H^4$ obstructions for onsite symmetries, respectively.

cond-mat.str-el↗

arXiv2025

Fidelity Strange Correlators for Average Symmetry-Protected Topological Phases

Topological phases in open quantum systems have become an exciting area of research, driven by the rising importance of noisy intermediate-scale quantum platforms. The concept of Average Symmetry-Protected Topological (ASPT) phases extends symmetry-protected topological phases to quantum systems affected by disorder or decoherence. To identify nontrivial ASPT states, we introduce a "fidelity strange correlator" (FSC), which operates directly on a single bulk density matrix without boundaries. For nontrivial ASPT phases in one and two dimensions, we show that the FSC reveals long-range or power-law behavior. In several two-dimensional examples, we establish a link between the FSC and certain non-local correlation functions in statistical loop models with quantum corrections, enabling us to derive exact scaling exponents for the FSC. In addition, we discuss methods to measure the FSC using classical shadow tomography. Our work lays the groundwork for identifying these intriguing topological phases of matter in open quantum systems, both numerically and experimentally.

cond-mat.str-el↗

arXiv2025

Multi-Center Study on Deep Learning-Assisted Detection and Classification of Fetal Central Nervous System Anomalies Using Ultrasound Imaging

Prenatal ultrasound evaluates fetal growth and detects congenital abnormalities during pregnancy, but the examination of ultrasound images by radiologists requires expertise and sophisticated equipment, which would otherwise fail to improve the rate of identifying specific types of fetal central nervous system (CNS) abnormalities and result in unnecessary patient examinations. We construct a deep learning model to improve the overall accuracy of the diagnosis of fetal cranial anomalies to aid prenatal diagnosis. In our collected multi-center dataset of fetal craniocerebral anomalies covering four typical anomalies of the fetal central nervous system (CNS): anencephaly, encephalocele (including meningocele), holoprosencephaly, and rachischisis, patient-level prediction accuracy reaches 94.5%, with an AUROC value of 99.3%. In the subgroup analyzes, our model is applicable to the entire gestational period, with good identification of fetal anomaly types for any gestational period. Heatmaps superimposed on the ultrasound images not only provide a visual interpretation for the algorithm but also provide an intuitive visual aid to the physician by highlighting key areas that need to be reviewed, helping the physician to quickly identify and validate key areas. Finally, the retrospective reader study demonstrates that by combining the automatic prediction of the DL system with the professional judgment of the radiologist, the diagnostic accuracy and efficiency can be effectively improved and the misdiagnosis rate can be reduced, which has an important clinical application prospect.

eess.IV↗

arXiv2024

Optimal signal transmission and timescale diversity in a model of human brain operating near criticality

Cortical neurons exhibit a hierarchy of timescales across brain regions in response to input stimuli, which is thought to be crucial for information processing of different temporal scales. Modeling studies suggest that both intra-regional circuit dynamics as well as cross-regional connectome may contribute to this timescale diversity. Equally important to diverse timescales is the ability to transmit sensory signals reliably across the whole brain. Therefore, the brain must be able to generate diverse timescales while simultaneously minimizing signal attenuation. To understand the dynamical mechanism behind these phenomena, we develop a second-order mean field model of the human brain by applying moment closure and coarse-graining to a digital twin brain model endowed with whole brain structural connectome. Cross-regional coupling strength is found to induced a phase transition from asynchronous activity to synchronous oscillation. By analyzing the input-response properties of the model, we reveal criticality as a unifying mechanism for enabling simultaneously optimal signal transmission and timescales diversity. We show how structural connectome and criticality jointly shape intrinsic timescale hierarchy across the brain.

q-bio.NC↗

arXiv2024

Phase Diagram, $d$-Wave Superconductivity, and Pseudogap of the $t$-$t'$-$J$ Model at Finite Temperature

Recently, robust $d$-wave superconductive (SC) order has been unveiled in the ground state of the 2D $t$-$t'$-$J$ model -- with both nearest-neighbor ($t$) and next-nearest-neighbor ($t'$) hoppings -- by density matrix renormalization group studies. However, there is currently a debate on whether the $d$-wave SC holds up strong on both $t'/t>0$ and $t'/t<0$ cases for the $t$-$t'$-$J$ model, which correspond to the electron- and hole-doped sides of the cuprate phase diagram, respectively. Here we exploit state-of-the-art thermal tensor network approach to accurately obtain the phase diagram of the $t$-$t'$-$J$ model on cylinders with widths up to $W=6$ and down to low temperature as $T/J \simeq 0.06$, pushing the boundaries of contemporary finite-$T$ calculations. For $t'/t>0$, we find a dome-like SC regime with a diverging $d$-wave pairing susceptibility, $χ_\textrm{SC} \propto 1/T^α$ below a characteristic temperature $T_c^*$. Near optimal doping, $T_c^*$ reaches its highest value of about $0.15 J$. Above $T_c^*$ yet below a higher crossover temperature $T^*$, the magnetic susceptibility becomes suppressed, which can be related to the onset of pseudogap (PG) behaviors. On the other hand, for $t'/t<0$ we find the pairing correlations are much weaker, although there exhibits a node-antinode structure in the PG regime as observed in the hole-doped cuprates. The thermal tensor network calculations of the $t$-$t'$-$J$ model underscore both the similarities and differences in the finite-temperature phase diagram between the fundamental model and cuprates, yielding unique insights into their intricate behaviors.

cond-mat.str-el↗

arXiv2024

Anomalies in mirror symmetry enriched topological orders

Two-dimensional mirror symmetry enriched topological (SET) orders can be studied using the folding approach: it can be folded along the mirror axis and turned into a bilayer system on which the mirror symmetry acts as a $\mathbb Z_2$ layer-exchange symmetry. How mirror symmetry enriches the topological order is then encoded at the mirror axis, which is a gapped boundary of the folded bilayer system. Based on anyon-condensation theory, we classify possible $\mathbb Z_2$-symmetric gapped boundaries of the folded system. In particular, we derive an $H^2$ obstruction function, which corresponds to an $H^3$ obstruction for topological orders enriched by the time-reversal symmetry instead of mirror symmetry. We demonstrate that states with a nontrivial $H^2$ obstruction function can be constructed on the surface of a three-dimensional mirror SET order.

cond-mat.str-el↗

arXiv2024

Universal collective Larmor-Silin mode emerging in magnetized correlated Dirac fermions

Employing large-scale quantum Monte Carlo simulations, we find that in the magnetized interacting Dirac fermion model there emerges a universal collective Larmor-Silin spin wave mode in the transverse dynamical spin susceptibility. Such mode purely originates from the interaction among Dirac fermions and distinguishes itself from the usual particle-hole continuum with finite lifetime and clear dispersion, both at small and large momenta in a large portion of the Brillouin zone. Our unbiased numerical results offer the dynamic signature of this collective excitation in interacting Dirac fermion systems, and provide experimental guidance for inelastic neutron scattering, electron spin resonance, and other spectroscopic approaches in the investigation of such universal collective modes in quantum Moire materials, topological insulators, and quantum spin liquid materials under magnetic field, with quintessential interaction nature beyond the commonly assumed noninteracting Dirac fermion or spinon approximations.

cond-mat.str-el↗

arXiv2024

Magnetocaloric Effect of Topological Excitations in Kitaev Magnets

Traditional magnetic sub-Kelvin cooling relies on the nearly free local moments in hydrate paramagnetic salts, whose utility is hampered by the dilute magnetic ions and low thermal conductivity. Here we propose to use instead fractional excitations inherent to quantum spin liquids (QSLs) as an alternative, which are sensitive to external fields and can induce a very distinctive magnetocaloric effect. With state-of-the-art tensor-network approach, we compute low-temperature properties of Kitaev honeycomb model. For the ferromagnetic case, strong demagnetization cooling effect is observed due to the nearly free $Z_2$ vortices via spin fractionalization, described by a paramagnetic equation of state with a renormalized Curie constant. For the antiferromagnetic Kitaev case, we uncover an intermediate-field gapless QSL phase with very large spin entropy, possibly due to the emergence of spinon Fermi surface. Potential realization of topological excitation cooling in Kitaev materials is also discussed, which may offer a promising pathway to circumvent existing limitations in the paramagnetic hydrates.

cond-mat.str-el↗

arXiv2024

Hidden orders and phase transitions for the fully packed quantum loop model on the triangular lattice

Quantum loop and dimer models are prototypical correlated systems with local constraints, which are not only intimately connected to lattice gauge theories and topological orders but are also widely applicable to the broad research areas of quantum materials and quantum simulation. Employing our sweeping cluster quantum Monte Carlo algorithm, we reveal the complete phase diagram of the triangular-lattice fully packed quantum loop model. Apart from the known lattice nematic (LN) solid and the even $\mathbb{Z}_2$ quantum spin liquid (QSL) phases, we discover a hidden vison plaquette (VP) phase, which had been overlooked and misinterpreted as a QSL for more than a decade. Moreover, the VP-to-QSL continuous transition belongs to the $(2+1)$D cubic* universality class, which offers a lattice realization of the (fractionalized) cubic fixed point that had long been considered as irrelevant towards the O($3$) symmetry until corrected recently by conformal bootstrap calculations. Our results are therefore of relevance to recent developments in both experiments and theory, and facilitate further investigations of hidden phases and transitions.

cond-mat.str-el↗

arXiv2024

Construction and classification of crystalline topological superconductor and insulators in three-dimensional interacting fermion systems

The natural existence of crystalline symmetry in real materials manifests the importance of understanding crystalline symmetry-protected topological (SPT) phases, especially for interacting systems. In this paper, we systematically construct and classify all the crystalline topological superconductors and insulators in three-dimensional (3D) interacting fermion systems using the novel concept of topological crystal. The corresponding higher-order topological surface theory can also be systematically studied via higher-order bulk-boundary correspondence. In particular, we discover an intriguing fact that almost all topological crystals with nontrivial 2D block states are intrinsically interacting topological phases that cannot be realized in any free-fermion systems. Moreover, the crystalline equivalence principle for 3D interacting fermionic systems is also verified, with an additional subtle "twist" on the spin of fermions.

cond-mat.str-el↗

arXiv2024

Cubic* criticality emerging from a quantum loop model on triangular lattice

Quantum loop and dimer models are archetypal examples of correlated systems with local constraints. Obtaining generic solutions for these models is difficult due to the lack of controlled methods to solve them in the thermodynamic limit. Nevertheless, these solutions are of immediate relevance to both statistical and quantum field theories, as well as the rapidly growing experiments in Rydberg atom arrays and quantum moiré materials, where the interplay between correlation and local constraints gives rise to a plethora of novel phenomena. In a recent work [X. Ran, Z. Yan, Y.-C. Wang, et al, arXiv:2205.04472 (2022)], it was found through sweeping cluster quantum Monte Carlo (QMC) simulations and field theory analysis that the triangular lattice quantum loop model (QLM) hosts a rich ground state phase diagram with lattice nematic, vison plaquette (VP) crystals, and the $\mathbb{Z}_2$ quantum spin liquid (QSL) close to the Rokhsar-Kivelson point. Here, we focus on the continuous quantum critical point separating the VP and QSL phases and demonstrate via both static and dynamic probes in QMC simulations that this transition is of the (2+1)D cubic* universality. In this transition, the fractionalized visons in QSL condense to give rise to the crystalline VP phase, while leaving their trace in the anomalously large anomalous dimension exponent and pronounced continua in the dimer and vison spectra compared with those at the conventional cubic or O(3) quantum critical points.

cond-mat.str-el↗

arXiv2024

Evidence for distortion-induced local electric polarization in $α$-RuCl$_3$

The spin-orbit assisted Mott insulator $α$-RuCl$_3$ is a prime candidate for material realization of the Kitaev quantum spin liquid. While little attention has been paid to charge degrees of freedom, charge effects, such as electric polarization, may arise in this system. Here, we report distortion-induced local electric polarization in $α$-RuCl$_3$ as evidenced by single-crystal X-ray diffraction, second harmonic generation (SHG) and dielectric measurements. The SHG signal appears at room temperature and develops substantially in the Kitaev paramagnetic state when short-range spin correlations come into play. Despite sizable pyroelectric currents in the Kitaev paramagnetic state, the absence of hysteresis in electric field-dependent polariza-tion (P-E) points to the short-range nature of electric polarization. This localized electric polarization is likely the result of distortion-induced charge dimerization, achieved through virtual hopping-induced charge redistribution. In addition, the electric polarization is boosted by short-range spin correlations via spin-phonon coupling in the Kitaev paramagnetic state. Our results emphasize the importance of charge degrees of freedom in $α$-RuCl$_3$, which establish a novel platform to investi-gate charge effects in Kitaev materials.

cond-mat.str-el↗

arXiv2024

Toward stochastic neural computing

The highly irregular spiking activity of cortical neurons and behavioral variability suggest that the brain could operate in a fundamentally probabilistic way. Mimicking how the brain implements and learns probabilistic computation could be a key to developing machine intelligence that can think more like humans. In this work, we propose a theory of stochastic neural computing (SNC) in which streams of noisy inputs are transformed and processed through populations of nonlinearly coupled spiking neurons. To account for the propagation of correlated neural variability, we derive from first principles a moment embedding for spiking neural network (SNN). This leads to a new class of deep learning model called the moment neural network (MNN) which naturally generalizes rate-based neural networks to second order. As the MNN faithfully captures the stationary statistics of spiking neural activity, it can serve as a powerful proxy for training SNN with zero free parameters. Through joint manipulation of mean firing rate and noise correlations in a task-driven way, the model is able to learn inference tasks while simultaneously minimizing prediction uncertainty, resulting in enhanced inference speed. We further demonstrate the application of our method to Intel's Loihi neuromorphic hardware. The proposed theory of SNC may open up new opportunities for developing machine intelligence capable of computing uncertainty and for designing unconventional computing architectures.

cs.NE↗