#quantumtomography
New tomography method enables polynomial-sample reconstruction of mixed quantum states with extensive entanglement and magic by exploiting hidden block structure, surpassing prior methods limited to restricted state classes.

#QuantumTomography #QuantumInformation #Research
Efficient Tomography of Highly Entangled Mixed Quantum States
arxiv.org
September 24, 2026 at 4:22 AM
Two Fully Funded PhD Positions in Quantum Information and Thermodynamics, Department of Condensed Matter Physics, Charles University, Prague, Czech Republic

#QuantumInformation #QuantumTomography #QuantumThermodynamics

www.quantiki.org/position/two...
Two fully funded PhD Positions in Quantum Information and Thermodynamics at Charles University, Prague | Quantiki
www.quantiki.org
January 23, 2025 at 8:37 AM
Two Postdoc positions in quantum information and thermodynamics, Department of Condensed Matter Physics, Charles University, Prague, Czech Republic

#QuantumInformation #QuantumTomography #QuantumThermodynamics

www.quantiki.org/position/two...
Two Postdoc positions in Quantum Information and Thermodynamics in Prague | Quantiki
www.quantiki.org
January 23, 2025 at 4:03 PM
Framework for reconstructing finite-dimensional Floquet monodromy matrices from observable measurements, separating universal spectral structure from observable-dependent dressing through algebraic and realization-theoretic methods.

#FloquetSystems #QuantumTomography #Research
Algebraic Tomography of Non-Hermitian Floquet Quantum Systems
arxiv.org
May 26, 2026 at 5:11 PM
Normalizing flows enable efficient reconstruction of quantum states with improved accuracy for non-classical systems. QST-Flow achieves better results than traditional methods while handling noisy real-world measurements.

#QuantumTomography #MachineLearning #QuantumComputing
QST-Flow: Machine Learning Framework for Scalable Quantum State Tomography
iq.fp2.dev
August 1, 2026 at 1:05 PM
Novel CGAN approach using differentiable Cholesky layers overcomes computational scaling bottleneck in quantum tomography, enabling high-fidelity state and process reconstruction for NISQ devices without iterative optimization.

#QuantumML #QuantumTomography #Research
Physics-Constrained Generative Learning for Quantum State and Process Tomography
arxiv.org
August 31, 2026 at 3:15 AM
Quantum network tomography requires probe path constraints beyond measurement completeness. Novel FIM analysis reveals that topology and monitor placement critically determine link parameter identifiability.

#QuantumNetworking #QuantumTomography #Research
Identifiability in Quantum State, Process, and Network Tomography via Fisher Information Matrix
iq.fp2.dev
September 16, 2026 at 1:07 PM
Novel algorithms achieve near-optimal complexity for learning k-sparse quantum states: Õ(k/ε) samples and Õ(kn/ε) time for pure states, with extension to mixed states via purification.

#QuantumAlgorithms #QuantumTomography #Research
Optimal Algorithms for Sparse Quantum State Tomography
arxiv.org
September 15, 2026 at 9:28 AM
Physicists develop a quantum tomography technique proving entanglement in mixed-spin hadrons can be certified from incomplete experimental data, enabling direct studies of how quantum spin correlations evolve during QCD hadronization.

#QuantumEntanglement #QuantumTomography #Research
Quantum Tomography of Mixed-Spin Hadronic Systems
arxiv.org
September 11, 2026 at 4:24 AM
Researchers proved optimal sample complexity for learning low-rank quantum states, demonstrating that jointly measuring t samples improves over single-sample tomography by factor √t, with matching algorithmic and information-theoretic bounds.

#QuantumTomography #QuantumAlgorithms #Research
Sample-Optimal Quantum State Tomography via Bounded-Sample Joint Measurements
arxiv.org
September 10, 2026 at 9:08 AM
Resolves open question in quantum state tomography by proving tight lower bounds for protocols where each measurement acts on k copies, removing earlier restrictions and determining optimal copy complexity.

#QuantumInformationTheory #QuantumTomography #Research
Tight Lower Bounds for Quantum State Tomography with Limited Entanglement
iq.fp2.dev
September 9, 2026 at 5:34 AM
New algorithms learn tensor network quantum states efficiently using graph parameters like cutwidth and tree-cutwidth. Bounds sample and computational complexity of state tomography, with applications to quantum simulation and verification.

#QuantumAlgorithms #TensorNetworks #QuantumTomography
Parameterised Graph Theory for Tensor Networks: Entanglement Rerouting and Quantum State Tomography
iq.fp2.dev
September 4, 2026 at 7:02 AM
Study reveals the unextended Petz recovery map fails at quantum state tomography, but an extended version using candidate state ensembles recovers Bayesian tomography structure, bridging quantum retrodiction and inference theory.

#QuantumTomography #QuantumRetrodiction #Research
Tomographic Limits of the Petz Recovery Map
arxiv.org
August 24, 2026 at 2:55 AM
Researchers disproved a key conjecture about fractional colorings in quantum shadow tomography, proving fractional chromatic numbers scale worse than O(ε⁻²)—with implications for quantum measurement efficiency protocols.

#QuantumTomography #QuantumInformation #Research
Counterexamples to the Fractional Coloring Conjecture for Triply Efficient Shadow Tomography
iq.fp2.dev
August 21, 2026 at 4:30 AM
Novel interferometric method enables complete characterization of quantum operations on high-dimensional photonic states without detecting the transformed photon, using path identity principle.

#QuantumTomography #PhotonicQudits #Research
High-Dimensional Quantum Process Tomography Without Photon Detection
arxiv.org
August 4, 2026 at 4:45 AM
Protocol reduces tomography measurements from exponential to linear scaling, enabling efficient characterization of fermionic quantum systems. Validated on SYK model and free-fermion chains across phase transitions.

#QuantumTomography #QuantumSimulation #News
Linear-Scaling Quantum State Tomography for Fermionic Many-Body Systems
quantumzeitgeist.com
July 31, 2026 at 11:23 AM
Extends phase retrieval theory from pure quantum states to mixed states of bounded rank, establishing stability characterizations for quantum superoperators and measurements with applications to quantum tomography.

#QuantumInformation #QuantumTomography #Research
Phase Retrievability of Superoperators and Measurements in Quantum Information Theory
arxiv.org
July 30, 2026 at 5:05 AM
Develops quantum-tomographic methods to distinguish CP violation in top-quark pair production from decay-level effects using angular distributions as spin analyzers, providing systematic separation strategy for fundamental symmetry studies.

#TopQuarks #CPViolation #QuantumTomography
Quantum Tomography Framework for Separating CP Violation Sources in Top-Antitop Production and Decay
arxiv.org
July 29, 2026 at 8:19 AM
Developed scalable tomography protocol for fermionic quantum systems achieving linear measurement complexity instead of exponential. Reconstructs quantum states from particle-number and momentum distributions accessible in ultracold-atom experiments.

#QuantumTomography #QuantumSimulation #Research
Permutationally Invariant Quantum State Tomography for Fermions
arxiv.org
July 28, 2026 at 2:22 AM
SSP-QST enables rank-adaptive reconstruction of photonic quantum states without priors, achieving 8× photon efficiency gain and highest fidelity across probe ranks via Weyl-theoretic spectral thresholding—ideal for real-time feedback sensing.

#PhotonicQuantum #QuantumSensing #QuantumTomography
Spectral Subspace Purification for Photonic Quantum State Tomography
arxiv.org
July 27, 2026 at 7:46 AM
Developed a scalable quantum state tomography algorithm using rank-adaptive matrix-free density operator representation, achieving superior accuracy-runtime-memory tradeoffs without forming dense matrices.

#QuantumAlgorithms #QuantumTomography #Scalability
Rank-Adaptive Matrix-Free Quantum State Tomography
arxiv.org
July 23, 2026 at 8:50 AM
New framework reveals when quantum state reconstruction from finite measurements is statistically stable. Shows informational completeness is necessary but not sufficient—measurement frame bounds determine true reconstructibility.

#QuantumEstimation #QuantumTomography #Research
Measurement Frames and σ-Regularized Estimation for Continuous-Variable Quantum Systems
arxiv.org
July 22, 2026 at 3:41 AM
Proven: quantum memory provides provable query-complexity advantage in learning quantum channels. Coherent protocols achieve O(D²/ε²) scaling vs O(D³/ε²) for best classical adaptive methods, establishing strict quantum memory separation.

#QuantumMemory #QuantumTomography #Research
Quantum Memory Advantage for Quantum Process Tomography
iq.fp2.dev
July 16, 2026 at 3:55 AM
Resolved: the sample complexity of learning Gaussian quantum states. Both bosonic and fermionic m-mode systems require O(m²) copies, proving non-Gaussian operations fundamentally outperform Gaussian-only measurement strategies for tomography.

#QuantumTomography #QuantumLearning #Research
Optimal Tomography of Bosonic and Fermionic Gaussian States
arxiv.org
July 14, 2026 at 6:34 AM
Novel tomography approach enables efficient characterization of noisy quantum channels, outperforming existing methods while requiring fewer resources. Particularly valuable for NISQ device users interpreting computational results beyond vendor specifications.

#QuantumTomography #NISQ #Research
Procrustes Tomography: Efficient Quantum Channel Characterization
arxiv.org
July 10, 2026 at 6:34 AM