Announcements

We are pleased to announce the winners of the two poster awards sponsored by Entropy (ISSN: 1099-4300) from MaxEnt 2022—the 41st International Conference on Bayesian and Maximum Entropy Methods in Science and Engineering, which took place in Paris (France) from 18 to 22 July 2022.

1st prize
“Efficient representations of spatially variant point spread functions in Bayesian imaging algorithms”
by Vincent Eberle, Philipp Frank, Julia Stadler, Silvan Streit, Torsten Enßlin

Bayesian imaging algorithms are becoming increasingly important in, e.g., astronomy, medicine, and biology. Given that many of these algorithms compute iterative solutions to high-dimensional inverse problems, the efficiency and accuracy of the instrument response representation are of high importance for the imaging process. For this reason, point spread functions, which make up a large fraction of the response functions of telescopes and microscopes, are usually assumed to be spatially invariant in a given field of view and can thus be represented by convolution. For many instruments, this assumption does not hold and degrades the accuracy of the instrument representation. We discuss the application of butterfly transforms, which are linear neural network structures whose size scales with the number of data points subquadratically. Butterfly transforms are efficient by design since they are inspired by the structure of the Cooley–Tukey Fast Fourier transform algorithm. We combine them into butterfly networks in several ways, compare the different architectures with respect to their performance, and identify a representation that is suitable for the efficient representation of a synthetic spatially variant point spread function with up to a 1% error.

2nd prize
“Modelling of aortic dissection with Beta random fields and uncertainty propagation with a Bayesian variational auto-encoder”
by Sascha Ranftl, Malte Rolf-Pissarczyk, GloriaWolkerstorfer, Antonio Pepe, Jan Egger, Gerhard A. Holzapfel, Wolfgang von der Linden

In this work, we create a stochastic constitutive model for arterial tissue mechanics and utilize deep learning surrogates in order to facilitate the ensuing propagation of uncertainties to the Cauchy stress fields resulting from tissue response to a mechanical load. In particular, "aortic dissection" is a dangerous disease that is linked to the stochastic and spatially heterogeneous degradation of the elastin fibers in aortic tissue. Here, this degradation is modeled as a "Beta" random field, i.e., a random field for which every marginal follows a Beta distribution, through a suitable combination of auxiliary Gaussian random fields. Based on this, the Cauchy stress fields in the tissue are computed using a finite element method in response to a mechanical load. Due to the stochasticity of the constitutive model in the input parameters, it is necessary to propagate these uncertainties to the computed mechanical Cauchy stress fields in order to make the simulations interpretable. The prohibitive computational effort of this latter step makes uncertainty propagation with direct sampling infeasible, instead requiring a surrogate model to be learned from a small number of samples from the finite element simulation. The structure of the input data, i.e., "Beta" random field realizations of the tissue's fibers degradation, and the output data, i.e., resulting mechanical Cauchy stress fields, define a problem similar to image-to-image (I2I) regression. This I2I problem structure suggests a convolutional neural network as a surrogate that is well-suited for learning the relationship between the spatial correlations. Here, we chose a Bayesian Variational Auto-Encoder (B-VAE) architecture. After training with Stein Variational Gradient Descent, the B-VAE can subsequently predict approximate Cauchy stress field samples from "Beta" random field samples several orders of magnitude faster, and with non-parametric Variational Inference, it can estimate the PDF of the predicted mechanical Cauchy stress fields. The study is presented within the framework of a rigorous Bayesian analysis. The results quantify the precision of such biomechanical simulations, and biologically relevant implications such as tissue rupture probabilities can be quantified.

Reference: Ranftl, S., Rolf-Pissarczyk, M., Wolkerstorfer, G., Pepe, A., Egger, J., von der Linden, W, & Holzapfel, G.A. (2022). “Stochastic Modeling of Inhomogeneities in the Aortic Wall and Uncertainty Quantification using a Bayesian Encoder-Decoder Surrogate”. ArXiv: abs/2202.10244

In order to acknowledge our reviewers, who so generously dedicate their time to reviewing papers and demonstrate diligence, professionalism, and timeliness when reviewing manuscripts, MDPI journals regularly offer outstanding reviewer awards to scholars who participate in the peer-review process.

We are proud to recognize this year’s winners in the “Physical Sciences” category for their outstanding contributions among extensive competition by presenting them with an Outstanding Reviewer Award.

We would like to take this opportunity to congratulate all of the winners on their achievement. MDPI will continue to provide support and recognition to the academic community.

Entropy:

• Jim W. Kay, University of Glasgow, UK;
• Christophe Chesneau, University of Caen, France;
• Esteban Tlelo-Cuautle, Instituto Nacional de Astrofísica, Óptica y Electrónica (INAOE), Mexico;
• Dennis Dieks, Utrecht University, The Netherlands;
• Claudio Cremaschini, Silesian University in Opava, Czech Republic.

Photonics:

• Carlos A. F. Marques, University of Aveiro, Portugal;
• Tatiana Latychevskaia, Paul Scherrer Institute, Switzerland.

Universe:

• Amit Kashi, Ariel University, Israel;
• Dominik Elsaesser, Technical University of Dortmund, Germany;
• Isaac Tutusaus, Instituto de Ciencias del Espacio, Spain;
• Jose A.R. Cembranos, Universidad Complutense de Madrid, Spain;
• Kazuharu Bamba, Fukushima University, Japan;
• Przemyslaw Malkiewicz, National Centre for Nuclear Research, Poland;
• Szymon Piotr Harabasz, Technical University of Darmstadt, Germany;
• Theocharis Kosmas, University of Ioannina, Greece;
• Viktor Toth, Perimeter Institute for Theoretical Physics, Canada;
• Vitor De Souza, Universidade de São Paulodisabled, Brazil.

We are proud to recognize the winners of MDPI’s 2021 Travel Awards in the “Physical Sciences” category for their outstanding presentations and to present them with the prize.

MDPI journals regularly offer travel awards to encourage talented junior scientists to present their latest research at academic conferences in specific fields, which helps to increase their influence.

The winners mentioned below were carefully selected by the journal editors based on an outline of their research and the work to be presented at an academic conference.

We would like to warmly congratulate the winners of this year’s Travel Awards and wish them the greatest success with their future research endeavors. MDPI will continue to enhance communication among scientists.

Galaxies:

• Mahdis Ghodrati, Yangzhou University, China;
• Sandra Etoka, University of Manchester, UK.

Instruments:

• Adriana Dias, University of London, UK.

Photonics:

• Aleksandrs Leitis, École Polytechnique Fédérale de Lausanne, Switzerland;
• Elena Losero, École Polytechnique Fédérale de Lausanne, Switzerland;
• Zhifeng Zhang, University of Pennsylvania, USA.

The purpose of our Best Paper Awards is to promote and recognize the most impactful contributions published within MDPI journals.

The editors of each journal carefully selected reviews and research papers through a rigorous judging process based on criteria such as the scientific merit, overall impact, and the quality of presentation of the papers published in the journal last year.

We are honored to present the winners in the “Physical Sciences” category, who were selected amongst extensive competition, and congratulate the authors for their outstanding scientific publications.

MDPI will continue to provide support and recognition to the academic community.

Entropy:

• “Classical (Local and Contextual) Probability Model for Bohm–Bell Type Experiments: No-Signaling as Independence of Random Variables”
  By Andrei Khrennikov and Alexander Alodjants
  Entropy 2019, 21(2), 157; doi 10.3390/e21020157
• “Nonlinear Information Bottleneck”
  By Artemy Kolchinsky, Brendan D. Tracey and David H. Wolpert
  Entropy 2019, 21(12), 1181; doi 10.3390/e21121181
• “Dynamic Maximum Entropy Reduction”
  By Václav Klika, Michal Pavelka, Petr Vágner and Miroslav Grmela
  Entropy 2019, 21(7), 715; doi 10.3390/e21070715
• “Topological Information Data Analysis”
  By Pierre Baudot, Monica Tapia, Daniel Bennequin and Jean-Marc Goaillard
  Entropy 2019, 21(9), 869; doi 10.3390/e21090869

Universe:

• “Nonsingular Black Holes in ƒ (R) Theories”
  By Gonzalo J. Olmo and Diego Rubiera-Garcia
  Universe 2015, 1(2), 173-185; doi 10.3390/universe1020173
• “Is It No Longer Necessary to Test Cosmologies with Type Ia Supernovae?”
  By Ram Gopal Vishwakarma and Jayant V. Narlikar
  Universe 2018, 4(6), 73; doi 10.3390/universe4060073
• “A Universe that Does Not Know the Time”
  By João Magueijo and Lee Smolin
  Universe 2019, 5(3), 84 ; doi 10.3390/universe5030084
• “Seeing Black Holes: From the Computer to the Telescope”
  By Jean-Pierre Luminet
  Universe 2018, 4(8), 86; doi 10.3390/universe4080086

We are pleased to announce the winners of the two poster awards sponsored by Entropy (ISSN: 1099-4300) from Quantum Information and Probability: from Foundations to Engineering (QIP22), which took place in Växö (Sweden) from 14 to 18 June 2022.

1st prize
"Delayed Choice and Bohmian Trajectories Investigated with Entangled Photons in a Double Slit"
by Jan Dziewior

Bohmian mechanics, a hidden-variable interpretation of quantum mechanics, ascribes reality to the positions and momenta of quantum particles at the cost of a non-local ontology. Thus, contrary to standard quantum mechanics, it allows one to conceive of definite particle trajectories while being fully compatible with the standard theory in all empirical predictions. Nevertheless, the plausibility of the Bohmian picture was called into question by a double-slit Gedankenexperiment conducted by Englert et al. [1], which initiated a lively controversy. While most of the proponents of Bohmian mechanics agreed with the predictions of Englert et al., their conclusions have been criticized. Here, the experimental realization of this Gedankenexperiment is presented. The conditions for the occurrence of so-called “surrealistic” trajectories are realized by using a pair of entangled photons, where one of the photons is sent into an optical double-slit interferometer. The average trajectories are recorded using a method inspired by weak measurements [2,3]. By avoiding the measurement of the second photon as long as the trajectories of the first one are measured, it is possible to realize a delayed choice scenario, fully illustrating the contrasting inferences of standard and Bohmian quantum mechanics.

[1] Englert, B., Scully, M., Sussmann G., Walther, H., Surrealistic Bohm Trajectories, Zeitschrift fur Naturforschung A, 47 1175-1186 (1992).
[2] Wiseman, H. M., Grounding Bohmian mechanics in weak values and bayesianism, New J. Phys. 9 165 (2007).
[3] Mahler, D. et al., Experimental nonlocal and surreal Bohmian trajectories, Science Advances, 2 2 (2016).

2nd prize
“Inconsistency of linear dynamics and Born's rule”
by Lotte Mertens

Modern experiments conducted using nanoscale devices come ever closer to bridging the divide between the quantum and classical realms, bringing experimental tests of objective collapse theories that propose alterations to Schrödinger’s equation within reach. Such objective collapse theories aim to explain the emergence of classical dynamics in the thermodynamic limit and hence resolve the inconsistency that exists within the axioms of quantum mechanics when assuming measurements can be described by quantum mechanics as well. Here, we show that requiring the emergence of Born’s rule for relative frequencies of measurement outcomes without imposing them as part of any axiom implies that such objective collapse theories cannot be linear. Previous suggestions regarding the proof of the emergence of Born’s rule in classes of problems that include linear objective collapse theories are analyzed and shown to include hidden assumptions.

We are pleased to invite you to read papers from the “Editor’s Choice Articles” in 2021. We have carefully curated a list of high-quality articles from the Section “Thermodynamics” below:

• “Medium Entropy Reduction and Instability in Stochastic Systems with Distributed Delay”
  by Loos, S.A.M. et al.
  Entropy 2021, 23(6), 696; https://doi.org/10.3390/e23060696
  Available online: https://www.mdpi.com/1099-4300/23/6/696

• “Stirling Refrigerating Machine Modeling Using Schmidt and Finite Physical Dimensions Thermodynamic Models: A Comparison with Experiments”
  by Dobre, C. et al.
  Entropy 2021, 23(3), 368; https://doi.org/10.3390/e23030368
  Available online: https://www.mdpi.com/1099-4300/23/3/368

• “Josephson Currents and Gap Enhancement in Graph Arrays of Superconductive Islands”
  by Lucci, M. et al.
  Entropy 2021, 23(7), 811; https://doi.org/10.3390/e23070811
  Available online: https://www.mdpi.com/1099-4300/23/7/811

• “The Carnot Cycle, Reversibility and Entropy”
  by Sands, D.
  Entropy 2021, 23(7), 810; https://doi.org/10.3390/e23070810
  Available online: https://www.mdpi.com/1099-4300/23/7/810

• “Information Thermodynamics and Reducibility of Large Gene Networks”
  by Sarkar, S. et al.
  Entropy 2021, 23(1), 63; https://doi.org/10.3390/e23010063
  Available online: https://www.mdpi.com/1099-4300/23/1/63

• “A Thermodynamic Approach to Measuring Entropy in a Few-Electron Nanodevice”
  by Pyurbeeva, E. et al.
  Entropy 2021, 23(6), 640; https://doi.org/10.3390/e23060640
  Available online: https://www.mdpi.com/1099-4300/23/6/640 

We would like to take this opportunity to thank all the research groups that submitted these exceptional papers for their contributions to Entropy (ISSN: 1099-4300). We would appreciate it if you would circulate this document among your colleagues or through your network.

If you would like to learn more about the contributions published in the “Editor’s Choice Articles”, please click on the following link: https://www.mdpi.com/journal/entropy/editors_choice.

It is our pleasure to invite you to read the selected papers from the “Editor’s Choice Articles” in 2021. The papers from the Section “Statistical Physics” are listed below:

• “Causality and Information Transfer Between the Solar Wind and the Magnetosphere–Ionosphere System”
  by Manshour, P. et al.
  Entropy 2021, 23(4), 390; https://doi.org/10.3390/e23040390
  Available online: https://www.mdpi.com/1099-4300/23/4/390

• “Coupling between Blood Pressure and Subarachnoid Space Width Oscillations during Slow Breathing”
  by Gruszecka, A. et al.
  Entropy 2021, 23(1), 113; https://doi.org/10.3390/e23010113
  Available online: https://www.mdpi.com/1099-4300/23/1/113

• “Dynamics of Ion Channels via Non-Hermitian Quantum Mechanics”
  by Gulden, T. et al.
  Entropy 2021, 23(1), 125; https://doi.org/10.3390/e23010125
  Available online: https://www.mdpi.com/1099-4300/23/1/125

• “Gradient Profile Estimation Using Exponential Cubic Spline Smoothing in a Bayesian Framework”
  by De Silva, K. et al.
  Entropy 2021, 23(6), 674; https://doi.org/10.3390/e23060674
  Available online: https://www.mdpi.com/1099-4300/23/6/674

• “Spectral Properties of Effective Dynamics from Conditional Expectations”
  by Nüske, F. et al.
  Entropy 2021, 23(2), 134; https://doi.org/10.3390/e23020134
  Available online: https://www.mdpi.com/1099-4300/23/2/134

• “Ground-State Properties and Phase Separation of Binary Mixtures in Mesoscopic Ring Lattices”
  by Penna, V. et al.
  Entropy 2021, 23(7), 821; https://doi.org/10.3390/e23070821
  Available online: https://www.mdpi.com/1099-4300/23/7/821

• “A Semi-Deterministic Random Walk with Resetting”
  by Villarroel, J. et al.
  Entropy 2021, 23(7), 825; https://doi.org/10.3390/e23070825
  Available online: https://www.mdpi.com/1099-4300/23/7/825

We would like to take this opportunity to thank all the research groups that submitted these exceptional papers for their contributions to Entropy (ISSN: 1099-4300). We would greatly appreciate it if you could circulate this document among your colleagues or through your network.

If you would like to learn more about the contributions published in the “Editor’s Choice Articles”, please click on the following link: https://www.mdpi.com/journal/entropy/editors_choice.

It is our pleasure to invite you to read the selected papers from the “Editor’s Choice Articles” in 2021. The papers from the Section “Signal and Data Analysis” are listed below:

• “Deep Task-Based Quantization”
  by Shlezinger, N. et al.
  Entropy 2021, 23(1), 104; https://doi.org/10.3390/e23010104
  Available online: https://www.mdpi.com/1099-4300/23/1/104

• “Phase Transitions in Transfer Learning for High-Dimensional Perceptrons”
  by Dhifallah, O. et al.
  Entropy 2021, 23(4), 400; https://doi.org/10.3390/e23040400
  Available online: https://www.mdpi.com/1099-4300/23/4/400

• “Novel Features for Binary Time Series Based on Branch Length Similarity Entropy”
  by Lee, S.-H. et al.
  Entropy 2021, 23(4), 480; https://doi.org/10.3390/e23040480
  Available online: https://www.mdpi.com/1099-4300/23/4/480

• “Field Theoretical Approach for Signal Detection in Nearly Continuous Positive Spectra II: Tensorial Data”
  by Lahoche, V. et al.
  Entropy 2021, 23(7), 795; https://doi.org/10.3390/e23070795
  Available online: https://www.mdpi.com/1099-4300/23/7/795  

We would like to take this opportunity to thank all the research groups that submitted these exceptional papers for their contributions to Entropy (ISSN: 1099-4300). We would greatly appreciate it if you could circulate this document among your colleagues or through your network.

If you would like to learn more about the contributions published in the “Editor’s Choice Articles”, please click on the following link: https://www.mdpi.com/journal/entropy/editors_choice.

It is our pleasure to invite you to read the selected papers from the “Editor’s Choice Articles” in 2021. The papers from the Section “Quantum Information” are listed below:

• “Switching and Swapping of Quantum Information: Entropy and Entanglement Level”
  by Sawerwain, M. et al.
  Entropy 2021, 23(6), 717; https://doi.org/10.3390/e23060717
  Available online: https://www.mdpi.com/1099-4300/23/6/717

• “Beyond Causal Explanation: Einstein’s Principle Not Reichenbach’s”
  by Silberstein, M. et al.
  Entropy 2021, 23(1), 114; https://doi.org/10.3390/e23010114
  Available online: https://www.mdpi.com/1099-4300/23/1/114

• “The Phase Space Model of Nonrelativistic Quantum Mechanics”
  by Tosiek, J. et al.
  Entropy 2021, 23(5), 581; https://doi.org/10.3390/e23050581
  Available online: https://www.mdpi.com/1099-4300/23/5/581

• “The Principle of Covariance and the Hamiltonian Formulation of General Relativity”
  by Tessarotto, M. et al.
  Entropy 2021, 23(2), 215; https://doi.org/10.3390/e23020215
  Available online: https://www.mdpi.com/1099-4300/23/2/215

• “On the Classical Capacity of General Quantum Gaussian Measurement”
  by Holevo, A.
  Entropy 2021, 23(3), 377; https://doi.org/10.3390/e23030377
  Available online: https://www.mdpi.com/1099-4300/23/3/377

• “Advances in Atomtronics”
  by Pepino, R.A.
  Entropy 2021, 23(5), 534; https://doi.org/10.3390/e23050534
  Available online: https://www.mdpi.com/1099-4300/23/5/534

• “Entanglement and Non-Locality in Quantum Protocols with Identical Particles”
  by Benatti, F. et al.
  Entropy 2021, 23(4), 479; https://doi.org/10.3390/e23040479
  Available online: https://www.mdpi.com/1099-4300/23/4/479

• “Lapsing Quickly into Fatalism: Bell on Backward Causation”
  by Norsen, T. et al.
  Entropy 2021, 23(2), 251; https://doi.org/10.3390/e23020251
  Available online: https://www.mdpi.com/1099-4300/23/2/251

• “Quantum Speed Limit and Divisibility of the Dynamical Map”
  by Teittinen, J. et al.
  Entropy 2021, 23(3), 331; https://doi.org/10.3390/e23030331
  Available online: https://www.mdpi.com/1099-4300/23/3/331

• “Federated Quantum Machine Learning”
  by Chen, S. Y.-C. et al.
  Entropy 2021, 23(4), 460; https://doi.org/10.3390/e23040460
  Available online: https://www.mdpi.com/1099-4300/23/4/460

• “Unveiling Operator Growth Using Spin Correlation Functions”
  by Carrega, M. et al.
  Entropy 2021, 23(5), 587; https://doi.org/10.3390/e23050587
  Available online: https://www.mdpi.com/1099-4300/23/5/587  

We would like to take this opportunity to thank all the research groups that submitted these exceptional papers for their contributions to Entropy (ISSN: 1099-4300). We would greatly appreciate it if you could circulate this document among your colleagues or through your network.

If you would like to learn more about the contributions published in the “Editor’s Choice Articles”, please click on the following link: https://www.mdpi.com/journal/entropy/editors_choice.

It is our pleasure to invite you to read the selected papers from the “Editor’s Choice Articles” in 2021. The papers from the Section “Non-equilibrium Phenomena” are listed below:

• “Characterization of a Two-Photon Quantum Battery: Initial Conditions, Stability and Work Extraction”
  by Delmonte, A. et al.
  Entropy 2021, 23(5), 612; https://doi.org/10.3390/e23050612
  Available online: https://www.mdpi.com/1099-4300/23/5/612

• “Stochastic Thermodynamics of a Piezoelectric Energy Harvester Model”
  by Costanzo, L. et al.
  Entropy 2021, 23(6), 677; https://doi.org/10.3390/e23060677
  Available online: https://www.mdpi.com/1099-4300/23/6/677  

We would like to take this opportunity to thank all the research groups that submitted these exceptional papers for their contributions to Entropy (ISSN: 1099-4300). We would greatly appreciate it if you could circulate this document among your colleagues or through your network.

If you would like to learn more about the contributions published in the “Editor’s Choice Articles”, please click on the following link: https://www.mdpi.com/journal/entropy/editors_choice.