- Comp-phys-alps-users - lists.phys.ethz.ch

Passive Radar: Revolutionizing Surveillance Through Silent Detection Technology
by wadekar.sagar087＠gmail.com 02 Nov '26

02 Nov '26

In modern defense and surveillance systems, radar technology plays an essential role in detecting, tracking, and monitoring objects across different environments. Among emerging detection technologies, Passive Radar is gaining attention for its ability to identify moving targets without transmitting its own radio signals. Unlike conventional radar systems, which actively emit electromagnetic waves and analyze their reflections, passive radar uses existing signals from sources such as television broadcasts, radio transmissions, and cellular networks. The fundamental working principle of Passive Radar involves receiving signals transmitted by external sources and analyzing how these signals interact with surrounding objects. When an aircraft, vehicle, or other moving target reflects these signals, the radar receiver detects variations in the reflected waves. By comparing direct signals with reflected signals, the system can estimate the target's location, movement, and speed. This approach eliminates the need for a dedicated radar transmitter. One of the major characteristics of this technology is its low probability of detection. Since passive radar does not actively transmit signals, it is more difficult for adversaries to identify its operational presence through conventional electronic surveillance methods. This makes it relevant for military surveillance, airspace monitoring, border security, and maritime observation. The technology also presents certain operational challenges. Its performance depends on the availability and quality of external signal sources, receiver sensitivity, signal processing capabilities, and surrounding environmental conditions. Complex terrain, interference, and changing transmission patterns can influence detection accuracy. As defense organizations increasingly explore advanced surveillance capabilities, Passive Radar represents an alternative approach to conventional radar infrastructure. Its ability to utilize existing electromagnetic signals highlights the growing importance of innovative, energy-efficient, and less detectable technologies in modern situational awareness and security operations. https://www.marketresearchfuture.com/reports/passive-radar-market-36776

1 0

problem: entanglement spectrum, pyalps, optim_mps
by Kaisa(凯志) Yin(尹) 10 Jul '25

10 Jul '25

Dear All, I'm trying to use `pyalps-optim_mps` to figure out the entanglement spectrum of the AFM Heisenberg Chain. But I'm stuck. I tried setting `model['entanglement_spectra'] = '32'` in the `model_params`, but there's just no reaction at all. Can anyone tell me what I'm doing wrong and how to fix it?

2 1

problem: entanglement spectrum, pyalps, optim_mps
by Kaisa(凯志) Yin(尹) 08 May '25

08 May '25

Dear All, I'm trying to use `pyalps-optim_mps` to figure out the entanglement spectrum of the AFM Heisenberg Chain. But I'm stuck. I tried setting `model['entanglement_spectra'] = '32'` in the `model_params`, but there's just no reaction at all. Can anyone tell me what I'm doing wrong and how to fix it?

1 0

[pyALPS]help!!
by kz_y_fzzsd＠outlook.com 08 May '25

08 May '25

Dear All, I'm trying to use `pyalps-optim_mps` to figure out the entanglement spectrum of the AFM Heisenberg Chain. But I'm stuck. I tried setting `model['entanglement_spectra'] = '32'` in the `model_params`, but there's just no reaction at all. Can anyone tell me what I'm doing wrong and how to fix it?

1 0

[pyALPS]help!!
by kz_y_fzzsd＠outlook.com 08 May '25

08 May '25

Dear All, I'm trying to use `pyalps-optim_mps` to figure out the entanglement spectrum of the AFM Heisenberg Chain. But I'm stuck. I tried setting `model['entanglement_spectra'] = '32'` in the `model_params`, but there's just no reaction at all. Can anyone tell me what I'm doing wrong and how to fix it?

1 0

reading ALPS results in xml
by Francesco Parisen Toldin 05 Sep '23

05 Sep '23

Dear all, (hopefully this mailing list is not dead...) I am facing a problem in visualizing the results of ALPS simulation done some years ago (~2019), in the xml format. I have the file param.task1.out.xml containing the output, and the ALPS.xsl file. Still, the browser (firefox 117.0) does not render the xml file correctly (I just see some "raw" contents, no formatting). Inspecting the xml files, I found in the header: <SIMULATION xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:noNamespaceSchemaLocation="http://xml.comp-phys.org/2002/10/ALPS.xsd"> The site xml.comp-phys.org is down, so I suppose that this is the reason of the problem. Searching on the internet archive, I was not able to find ALPS.xsd: the internet archive has a snapshot of xml.comp-phys.org, and has stored several xsd files, but not the ALPS.xsd. Where can I find this file? Do I need additional xsd files to display the xml output? Or is there a replacement I can use? Best, Francesco Parisen Toldin

1 0

problem in CT-QMC : MPI
by fateme heydari nasab 16 Nov '22

16 Nov '22

Dear ALPS team, I have recently installed alps to use CT_QMC. Running tutorial1.py in the alps/tutorials/hybridization-01-python results $ alpspython tutorial1.py Traceback (most recent call last): File "tutorial1.py", line 49, in <module> import pyalps.mpi as mpi # MPI library (required) File "/home/fheydari/MPS/lib/pyalps/mpi.py", line 39, in <module> from boost.mpi import * ImportError: No module named boost.mpi $ mpirun -np 2 alpspython tutorial1.py /opt/intel/composer_xe_2013.2.146/mpirt/bin/intel64/mpirun: 96: .: Can't open /opt/intel/composer_xe_2013.2.146/mpirt/bin/intel64/mpivars.sh While i have installed mpi: $ which mpirun /opt/intel/composer_xe_2013.2.146/mpirt/bin/intel64/mpirun As I know from the Documentation – Hybridization Expansion CT-QMC solver version 3.0b1 Emanuel Gull, Hartmut Hafermann, and Philipp Werner MPI is required. Would you please help me to resolve this issue? Best regards, Fatemeh -- Fateme Heydari-Nasab, Ph.D. University of Sistan and Baluchestan University Blvd, Zahedan, Iran PoBox: 98155-987 Tel: +98-54-31136391 https://www.usb.ac.ir/astaff/fheydari Email: fheydari(a)phys.usb.ac.ir fatiheydaree(a)gmail.com

1 0

problems in ALPS installation
by fateme heydari nasab 10 Aug '22

10 Aug '22

Dear All I'm new in ALPS, and want install it on ubuntu 21.04, but there are some problems in the installation procedure. Would you please help me to solve this problem and install ALPS correctly?! This is the complete error I have gotten: In file included from /home/fheydari/alps/src/alps/alea/histogrameval.h:36, from /home/fheydari/alps/src/alps/alea/observablefactory.C:38: /home/fheydari/alps/src/alps/alea/histogram.h: In member function ‘alps::HistogramObservable<T>::const_iterator alps::HistogramObservable<T>::rbegin() const’: /home/fheydari/alps/src/alps/alea/histogram.h:88:59: error: could not convert ‘((const alps::HistogramObservable<T>*)this)->alps::HistogramObservable<T>::histogram_.std::vector<unsigned int>::rbegin()’ from ‘std::vector<unsigned int>::reverse_iterator’ {aka ‘std::reverse_iterator<__gnu_cxx::__normal_iterator<unsigned int*, std::vector<unsigned int> > >’} to ‘alps::HistogramObservable<T>::const_iterator’ {aka ‘std::vector<unsigned int>::const_iterator’} 88 | const_iterator rbegin() const { return histogram_.rbegin();} | ~~~~~~~~~~~~~~~~~^~ | | | std::vector<unsigned int>::reverse_iterator {aka std::reverse_iterator<__gnu_cxx::__normal_iterator<unsigned int*, std::vector<unsigned int> > >} /home/fheydari/alps/src/alps/alea/histogram.h: In member function ‘alps::HistogramObservable<T>::const_iterator alps::HistogramObservable<T>::rend() const’: /home/fheydari/alps/src/alps/alea/histogram.h:90:55: error: could not convert ‘((const alps::HistogramObservable<T>*)this)->alps::HistogramObservable<T>::histogram_.std::vector<unsigned int>::rend()’ from ‘std::vector<unsigned int>::reverse_iterator’ {aka ‘std::reverse_iterator<__gnu_cxx::__normal_iterator<unsigned int*, std::vector<unsigned int> > >’} to ‘alps::HistogramObservable<T>::const_iterator’ {aka ‘std::vector<unsigned int>::const_iterator’} 90 | const_iterator rend() const { return histogram_.rend();} | ~~~~~~~~~~~~~~~^~ | | | std::vector<unsigned int>::reverse_iterator {aka std::reverse_iterator<__gnu_cxx::__normal_iterator<unsigned int*, std::vector<unsigned int> > >} make[2]: *** [src/alps/CMakeFiles/alps.dir/build.make:173: src/alps/CMakeFiles/alps.dir/alea/observablefactory.C.o] Error 1 make[1]: *** [CMakeFiles/Makefile2:2758: src/alps/CMakeFiles/alps.dir/all] Error 2 make: *** [Makefile:182: all] Error 2 Sincerely yours, Fateme -- Fateme Heydari-Nasab, Ph.D. University of Sistan and Baluchestan University Blvd, Zahedan, Iran PoBox: 98155-987 Tel: +98-54-31136391 https://www.usb.ac.ir/astaff/fheydari Email: fheydari(a)phys.usb.ac.ir fatiheydaree(a)gmail.com

2 3

alps.comp-phys.org is down?
by Synge Todo 14 Jul '22

14 Jul '22

Dear All, I have found that the ALPS website http://alps.comp-phys.org/ has not been working for the past few days. Does anyone know about the situation? Best, Synge

3 2

ALPS for Schwinger boson mean field theory?
by Stein Kåre Lundeberg Fosstveit 15 Mar '22

15 Mar '22

Hi! Too long, didn't read; Is there any way ALPS can be used to self-consistently determine the mean field parameters in a Schwinger boson mean field framework? I am currently writing my masters' thesis in condensed matter physics, focusing on the possible identification of quantum spin liquids in magnetically frustrated systems. The model I am currently studying is the Kane-Mele-Hubbard model on the honeycomb lattice, which is studied in "Phys. Rev. B 85, 195126", with an additional Dzyaloshinskii-Moriya interaction (DMI) term. I treat my system in the same way as is done in the paper, employing a Schwinger boson mean field theory to obtain the mean field ground state energy from the spin Hamiltonian. The ground state energy contains both the original parameters in the Hamiltonian and some mean field parameters introduced in the mean field approximation. Having obtained the ground state, the next step is to self-consistently determine the mean field parameters numerically and construct the resulting phase diagram, which should resemble Fig. 2 in "Phys. Rev. B 85, 195126" when the DMI is set to zero. I am having some trouble determining the mean field parameters in an accurate way. The approach I have used so far is consistent with what is usually done in literature: We minimize the mean field ground state energy (assuming T=0) with respect to the mean field parameters and solve the resulting self-consistency equations for a number of initial parameter guesses, accepting as the solution that which gives the lowest value for the ground state energy. Even if the lattice is composed of 20 to 40 sites in each spatial direction, the run-time of the computation varies between 2-8 hours, and the results are inconsistent. Going to the more accurate continuum limit, where the self-consistency equations become integrals over the Brillouin zone, the run-time is so high that the approach is unreasonable. This integral approach has, however, proven successful in one dimension for a simpler initial Hamiltonian. The question I am asking is therefore if there is an implementation in ALPS that can be used to determine these mean field parameters. I am perhaps worried that the problem I'm working on is a bit too "narrow" to be covered by ALPS, which seem to me to have excellent approaches to the more general Hamiltonians that one often starts out with (e.g. the original Kane-Mele-Hubbard model, Eq. (1) in"Phys. Rev. B 85, 195126"). If anyone has any ideas or pointers, I would be most grateful. I apologize for the longevity of the mail and thank you in advance. Best regards, Stein Kåre L. Fosstveit

2 2