Mastodawn

📰 "Accurate, full-dimensional computations of thousands of complex vibrational eigenstates with tree tensor network states"
https://arxiv.org/abs/2605.00998 #Physics.Chem-Ph #Physics.Comp-Ph #Quant-Ph #Matrix #Force

Accurate, full-dimensional computations of thousands of complex vibrational eigenstates with tree tensor network states

Tree tensor network states (TTNSs) combined with the density matrix renormalization group (DMRG) are emerging as powerful tools for vibrational and vibronic structure simulations in molecules with strong coupling and fluxionality. In this Perspective, we discuss how TTNS methods enable accurate, full-dimensional computations of thousands of eigenstates for molecular systems ranging from quartic-force-field benchmarks to molecules with strong vibronic coupling and protonated water clusters as large as the 33-dimensional Eigen ion, H$_3$O$^+$$\cdot$(H$_2$O)$_3$. We emphasize the close connection and interoperability between DMRG-based TTNS methods and the multilayer multiconfiguration time-dependent Hartree method (ML-MCTDH), which share the same underlying ansatz. We also highlight practical challenges of predictive simulations, including robust error estimation, convergence of observables such as infrared intensities, and optimization of tensor network tree structures. Finally, we outline recent advances toward direct targeting of excited states and discuss opportunities for broader applications in molecular spectroscopy and quantum dynamics.

arXiv.org

G-Prophet 2d ago

Sleepless night, but worth it. A new data ingestion optimization just went live, cutting our signal processing latency by 12ms. A small win, but these compound. For our models, fresher data means a potentially clearer signal. The hunt for efficiency is relentless.

https://gprophet.com

#AI #Quant #DataEngineering #MLOps #Fintech

G-Prophet - Financial Data Analysis Platform

Professional AI-assisted financial data analysis and market research platform for informed investment decisions

G-Prophet

Rxiv mechanobio 3d ago

📰 "Nonreciprocity-enriched steady phases in open quantum systems"
https://arxiv.org/abs/2605.00101 #Cond-Mat.Quant-Gas #Cond-Mat.Str-El #Physics.Optics #Quant-Ph #Dynamics #Matrix

Nonreciprocity-enriched steady phases in open quantum systems

Nonreciprocity can profoundly alter the spectra and dynamics of open quantum systems, yet its impact on the long-time steady-state phases of matter has remained largely unexplored. Here we show that the interplay of nonreciprocity, symmetry defects, and spatial boundaries can generate phases beyond the standard spontaneous-symmetry-breaking paradigm. We demonstrate this mechanism by showing that sufficiently strong nonreciprocity turns boundaries into sources and drains of symmetry defects, while simultaneously endowing these defects with chiral dynamics in the bulk. As a result, the conventional uniform symmetry-broken state gives way to a domain-wall traveling-wave phase, in which symmetry defects form a persistent chiral wave. We showcase this mechanism in a bosonic model with $Z_{2}$ symmetry, where periodic boundary conditions support only the conventional symmetric and symmetry-broken phases, whereas open boundary conditions allow the traveling-wave phase. We further show that even in the absence of symmetry breaking, the steady state can exhibit anomalous chiral relaxation: owing to the non-Hermitian skin effect in the stability matrix, local fluctuations are chirally amplified as they approach a boundary, where they eventually decay. Combining mean-field theory with truncated Wigner simulations, we characterize these phases, analyze the order parameter and Goldstone-mode fluctuations of the traveling-wave phase, and confirm its existence in three spatial dimensions.

arXiv.org

G-Prophet 4d ago

A +50% model upside prediction often gets clicks, but a +5% prediction can be far more valuable. Why?

Confidence.

A high-confidence, well-calibrated signal, even for a smaller move, provides a stronger basis for research than a low-confidence moonshot. The latter is often just noise. Our work focuses heavily on calibrating our models' confidence scores, not just chasing headline numbers. The real research challenge isn't the magnitude, but the model's certainty.

#AI #Quant #ML #Investing #Dat

G-Prophet 4d ago

Weekly model dev log: We tested a wild hypothesis – could global atmospheric pressure data serve as a proxy for mass psychological sentiment, influencing market behavior?

The result: Null. Absolutely no correlation found. A spectacular failure, but a useful one.

It's a humbling reminder that most novel datasets are just noise. The path to finding alpha is paved with null hypotheses. Back to the drawing board for new sentiment sources.

#AI #Quant #MachineLearning #DataScience #Finance #MastoDe

Rxiv mechanobio 6d ago

📰 "Towards Accelerated SCF Workflows with Equivariant Density-Matrix Learning and Analytic Refinement"
https://arxiv.org/abs/2604.27256 #Physics.Comp-Ph #Physics.Chem-Ph #Quant-Ph #Matrix #Forces #Cs.Ai #Cs.Lg

Towards Accelerated SCF Workflows with Equivariant Density-Matrix Learning and Analytic Refinement

We present \textsc{dm-PhiSNet}, a physically constrained \textsc{PhiSNet}-based equivariant model that predicts one-electron reduced density matrices (1-RDMs) directly from molecular geometries in an atomic-orbital (AO) basis for accelerated self-consistent field (SCF) workflows. Training follows a two-stage schedule with progressively introduced physically motivated objectives, and the resulting predictions are refined by a lightweight analytic block. This block enforces electron-number conservation, drives the 1-RDM toward generalized idempotency in the AO metric, and regularizes the occupation spectrum of the Löwdin-orthogonalized density. Across six closed-shell systems -- H$_2$O, CH$_4$, NH$_3$, HF, ethanol, and NO$_3^-$ -- the refined 1-RDMs provide SCF initial guesses that substantially reduce iteration steps by 49--81\% relative to standard initializations. Beyond SCF acceleration, the learned 1-RDMs yield accurate one-shot total energies and Hellmann--Feynman atomic forces without force supervision, indicating that the model captures chemically meaningful electronic structure. These results demonstrate that combining equivariant learning with analytic constraint enforcement provides a simple, general route to solver-ready density-matrix initializations and accelerated SCF workflows.

arXiv.org

Rxiv mechanobio Apr 29

📰 "Randomised measurements of a disorder-induced entanglement transition in a neutral atom quantum processor"
https://arxiv.org/abs/2604.24854 #Cond-Mat.Stat-Mech #Physics.Atom-Ph #Quant-Ph #Dynamics #Matrix

Randomised measurements of a disorder-induced entanglement transition in a neutral atom quantum processor

The development and spread of entanglement in complex quantum systems is central to exploring many-body phenomena out of equilibrium. Measuring entanglement dynamics can shed light on information scrambling and thermalisation, namely on transitions from many-body quantum chaos to localisation in disordered, interacting systems. In quantum computing systems, entanglement entropy and other nonlinear functions of the density matrix have been recently measured, in particular by using the randomised measurement toolbox. However, it is difficult to implement the required arbitrary unitary rotations on specific subsystems without universal local control. Here we devise and demonstrate the measurement of entanglement entropy in a programmable analogue quantum simulator using a randomised measurement protocol that leverages local energy tuning together with a global field to bypass the need for local gate control. We implement this on a commercially available neutral-atom quantum simulator, QuEra's Aquila, and use it to show how programmable disorder in the local Hamiltonian parameters leads to a transition from chaotic to localised entanglement dynamics. Given current decoherence times, we clearly resolve disorder-specific, time-dependent entanglement spreading in small systems. Our work extends the utility of programmable analogue quantum simulators, and opens further opportunities for wider randomised measurement toolboxes in a range of other analogue systems.

arXiv.org

richardgolian Apr 26

Since 2022 I tracked the market manually in a spreadsheet.
No explicit predictions → nothing to test.
So I used AI to build a system that makes predictions and grades itself.
The record starts today.
#AI #Investing #Quant #StockMarket #MachineLearning

Rxiv cytoskeleton Apr 22

📰 "Engineering quantum optical responses of microtubules through tryptophan-network simulations and ultraviolet spectroscopy"
https://arxiv.org/abs/2604.18604
#Physics.Bio-Ph #Microtubule #Quant-Ph

Engineering quantum optical responses of microtubules through tryptophan-network simulations and ultraviolet spectroscopy

Microtubules host dense ultraviolet-absorbing aromatic networks, suggesting an opportunity to engineer their optical response for biotechnology. Here we assess the feasibility of tuning microtubule fluorescence by combining an excitonic radiative-coupling model with molecular-dynamics-derived microtubule-like assemblies and steady-state absorbance and fluorescence measurements in microplate geometries. Simulations quantify how positional and orientational fluctuations reshape radiative rates and quantum yield, and predict how perturbing the tryptophan network by removing a specific site, adding an extra tryptophan at candidate binding pockets, or using mixed modification fractions can modulate emission. Experiments on porcine tubulin dimers and taxol-stabilized microtubules support these trends: polymerization enhances microtubule quantum yield at 280 nm and yields bounded changes at 295 nm due to scattering, while added L-tryptophan reproducibly quenches microtubules at both wavelengths. Together, theory and experiment provide evidence for chemically addressable tuning of microtubule quantum yield and motivate design rules for engineered microtubule photonics.

arXiv.org

Rxiv mechanobio Apr 22

📰 "Engineering quantum optical responses of microtubules through tryptophan-network simulations and ultraviolet spectroscopy"
https://arxiv.org/abs/2604.18604 #Physics.Bio-Ph #Microtubule #Dynamics #Quant-Ph

Engineering quantum optical responses of microtubules through tryptophan-network simulations and ultraviolet spectroscopy

Microtubules host dense ultraviolet-absorbing aromatic networks, suggesting an opportunity to engineer their optical response for biotechnology. Here we assess the feasibility of tuning microtubule fluorescence by combining an excitonic radiative-coupling model with molecular-dynamics-derived microtubule-like assemblies and steady-state absorbance and fluorescence measurements in microplate geometries. Simulations quantify how positional and orientational fluctuations reshape radiative rates and quantum yield, and predict how perturbing the tryptophan network by removing a specific site, adding an extra tryptophan at candidate binding pockets, or using mixed modification fractions can modulate emission. Experiments on porcine tubulin dimers and taxol-stabilized microtubules support these trends: polymerization enhances microtubule quantum yield at 280 nm and yields bounded changes at 295 nm due to scattering, while added L-tryptophan reproducibly quenches microtubules at both wavelengths. Together, theory and experiment provide evidence for chemically addressable tuning of microtubule quantum yield and motivate design rules for engineered microtubule photonics.

arXiv.org